Lebenswissenschaften und Ethik
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In the field of computer- and robot-assisted minimally invasive surgery, enormous progress has been made in recent years based on the recognition of surgical instruments in endoscopic images and videos. In particular, the determination of the position and type of instruments is of great interest. Current work involves both spatial and temporal information, with the idea that predicting the movement of surgical tools over time may improve the quality of the final segmentations. The provision of publicly available datasets has recently encouraged the development of new methods, mainly based on deep learning. In this review, we identify and characterize datasets used for method development and evaluation and quantify their frequency of use in the literature. We further present an overview of the current state of research regarding the segmentation and tracking of minimally invasive surgical instruments in endoscopic images and videos. The paper focuses on methods that work purely visually, without markers of any kind attached to the instruments, considering both single-frame semantic and instance segmentation approaches, as well as those that incorporate temporal information. The publications analyzed were identified through the platforms Google Scholar, Web of Science, and PubMed. The search terms used were “instrument segmentation”, “instrument tracking”, “surgical tool segmentation”, and “surgical tool tracking”, resulting in a total of 741 articles published between 01/2015 and 07/2023, of which 123 were included using systematic selection criteria. A discussion of the reviewed literature is provided, highlighting existing shortcomings and emphasizing the available potential for future developments.
The human nose serves as the primary gateway for air entering the respiratory system and plays a vital role in breathing. Nasal breathing difficulties are a significant health concern, leading to substantial healthcare costs for patients. Understanding nasal airflow dynamics is crucial for comprehending respiratory mechanisms. This article presents a detailed study using tomo-Particle Image Velocimetry (PIV) to investigate nasal airflow dynamics while addressing its accuracy. Embedded in the OpenNose project, the work described aims to provide a validation basis for different numerical approaches to upper airway flow. The study includes the manufacturing of a transparent silicone model based on a clinical CT scan, refractive index matching to minimize optical distortions, and precise flow rate adjustments based on physiological breathing cycles. This method allows for spatial high-resolution investigations in different regions of interest within the nasopharynx during various phases of the breathing cycle. The results demonstrate the accuracy of the investigations, enabling detailed analysis of flow structures and gradients. This spatial high-resolution tomo-PIV approach provides valuable insights into the complex flow phenomena occurring during the physiological breathing cycle in the nasopharynx. The study's findings contribute to advancements in non-free-of-sight experimental flow investigation of complex cavities under nearly realistic conditions. Furthermore, reliable and accurate experimental data is crucial for properly validating numerical approaches that compute this patient-specific flow for clinical purposes.
Preliminary considerations on the form-finding of a tensegrity joint to be used in dynamic orthoses
(2024)
Small and medium-sized enterprises (SMEs) increasingly need to manage nformation technology (IT) effectively in order to remain competitive. However, compared to larger organizations, SMEs often face challenges in terms of resources and employer attractiveness, and regularly do not have the need to employ a Chief Information Officer (CIO) on a full-time basis. To address this issue, a growing number of global experts have begun to provide CIO services on a part-time basis for multiple clients simultaneously. This approach allows SMEs to tap into the expertise of experienced IT leaders at a fraction of the cost and without committing to long-term arrangements. While these professionals, known as “Fractional CIOs”, have proven their value in the field, there has been a lack of academic research on this emerging trend. Therefore, we carried out a comprehensive research project between 2020 and 2023, involving 62 Fractional CIOs from 10 countries. The research produced a definition, different types of engagements, and success factors for Fractional CIOs and their engagements. This paper summarizes these findings for a wider audience of academics and practitioners.
Utility of Smartphone-based Three-dimensional Surface Imaging for Digital Facial Anthropometry
(2024)
Background
The utilization of three-dimensional (3D) surface imaging for facial anthropometry is a significant asset for patients undergoing maxillofacial surgery. Notably, there have been recent advancements in smartphone technology that enable 3D surface imaging.
In this study, anthropometric assessments of the face were performed using a smartphone and a sophisticated 3D surface imaging system.
Methods
30 healthy volunteers (15 females and 15 males) were included in the study. An iPhone 14 Pro (Apple Inc., USA) using the application 3D Scanner App (Laan Consulting Corp., USA) and the Vectra M5 (Canfield Scientific, USA) were employed to create 3D surface models. For each participant, 19 anthropometric measurements were conducted on the 3D surface models. Subsequently, the anthropometric measurements generated by the two approaches were compared. The statistical techniques employed included the paired t-test, paired Wilcoxon signed-rank test, Bland–Altman analysis, and calculation of the intraclass correlation coefficient (ICC).
Results
All measurements showed excellent agreement between smartphone-based and Vectra M5-based measurements (ICC between 0.85 and 0.97). Statistical analysis revealed no statistically significant differences in the central tendencies for 17 of the 19 linear measurements. Despite the excellent agreement found, Bland–Altman analysis revealed that the 95% limits of agreement between the two methods exceeded ±3 mm for the majority of measurements.
Conclusion
Digital facial anthropometry using smartphones can serve as a valuable supplementary tool for surgeons, enhancing their communication with patients. However, the proposed data suggest that digital facial anthropometry using smartphones may not yet be suitable for certain diagnostic purposes that require high accuracy.
Training data for Neural Networks is often scarce in the medical domain, which often results in models that struggle to generalize and consequently showpoor performance on unseen datasets. Generally, adding augmentation methods to the training pipeline considerably enhances a model’s performance. Using the dataset of the Foot Ulcer Segmentation Challenge, we analyze two additional augmentation methods in the domain of chronic foot wounds - local warping of wound edges along with projection and blurring of shapes inside wounds. Our experiments show that improvements in the Dice similarity coefficient and Normalized Surface Distance metrics depend on a sensible selection of those augmentation methods.
Background:
With the prevalence of burnout among surgeons posing a significant threat to healthcare outcomes, the mental toughness of medical professionals has come to the fore. Mental toughness is pivotal for surgical performance and patient safety, yet research into its dynamics within a global and multi-specialty context remains scarce. This study aims to elucidate the factors contributing to mental toughness among surgeons and to understand how it correlates with surgical outcomes and personal well-being.
Methods:
Utilizing a cross-sectional design, this study surveyed 104 surgeons from English and German-speaking countries using the Mental Toughness Questionnaire (MTQ-18) along with additional queries about their surgical practice and general life satisfaction. Descriptive and inferential statistical analyses were applied to investigate the variations in mental toughness across different surgical domains and its correlation with professional and personal factors.
Results:
The study found a statistically significant higher level of mental toughness in micro-surgeons compared to macro-surgeons and a positive correlation between mental toughness and surgeons' intent to continue their careers. A strong association was also observed between general life satisfaction and mental toughness. No significant correlations were found between the application of psychological skills and mental toughness.
Conclusion:
Mental toughness varies significantly among surgeons from different specialties and is influenced by professional dedication and personal life satisfaction. These findings suggest the need for targeted interventions to foster mental toughness in the surgical community, potentially enhancing surgical performance and reducing burnout. Future research should continue to explore these correlations, with an emphasis on longitudinal data and the development of resilience-building programs.
Background
This study evaluated the effect of an artificial intelligence (AI)-based clinical decision support system on the performance and diagnostic confidence of endoscopists in their assessment of Barrett’s esophagus (BE).
Methods
96 standardized endoscopy videos were assessed by 22 endoscopists with varying degrees of BE experience from 12 centers. Assessment was randomized into two video sets: group A (review first without AI and second with AI) and group B (review first with AI and second without AI). Endoscopists were required to evaluate each video for the presence of Barrett’s esophagus-related neoplasia (BERN) and then decide on a spot for a targeted biopsy. After the second assessment, they were allowed to change their clinical decision and confidence level.
Results
AI had a stand-alone sensitivity, specificity, and accuracy of 92.2%, 68.9%, and 81.3%, respectively. Without AI, BE experts had an overall sensitivity, specificity, and accuracy of 83.3%, 58.1%, and 71.5%, respectively. With AI, BE nonexperts showed a significant improvement in sensitivity and specificity when videos were assessed a second time with AI (sensitivity 69.8% [95%CI 65.2%–74.2%] to 78.0% [95%CI 74.0%–82.0%]; specificity 67.3% [95%CI 62.5%–72.2%] to 72.7% [95%CI 68.2%–77.3%]). In addition, the diagnostic confidence of BE nonexperts improved significantly with AI.
Conclusion
BE nonexperts benefitted significantly from additional AI. BE experts and nonexperts remained significantly below the stand-alone performance of AI, suggesting that there may be other factors influencing endoscopists’ decisions to follow or discard AI advice.
Aims
Recent evidence suggests the possibility of intraprocedural phase recognition in surgical operations as well as endoscopic interventions such as peroral endoscopic myotomy and endoscopic submucosal dissection (ESD) by AI-algorithms. The intricate measurement of intraprocedural phase distribution may deepen the understanding of the procedure. Furthermore, real-time quality assessment as well as automation of reporting may become possible. Therefore, we aimed to develop an AI-algorithm for intraprocedural phase recognition during ESD.
Methods
A training dataset of 364385 single images from 9 full-length ESD videos was compiled. Each frame was classified into one procedural phase. Phases included scope manipulation, marking, injection, application of electrical current and bleeding. Allocation of each frame was only possible to one category. This training dataset was used to train a Video Swin transformer to recognize the phases. Temporal information was included via logarithmic frame sampling. Validation was performed using two separate ESD videos with 29801 single frames.
Results
The validation yielded sensitivities of 97.81%, 97.83%, 95.53%, 85.01% and 87.55% for scope manipulation, marking, injection, electric application and bleeding, respectively. Specificities of 77.78%, 90.91%, 95.91%, 93.65% and 84.76% were measured for the same parameters.
Conclusions
The developed algorithm was able to classify full-length ESD videos on a frame-by-frame basis into the predefined classes with high sensitivities and specificities. Future research will aim at the development of quality metrics based on single-operator phase distribution.
Even though artificial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their accountability and transparency level must be improved to transfer this success into clinical practice. The reliability of machine learning decisions must be explained and interpreted, especially for supporting the medical diagnosis.For this task, the deep learning techniques’ black-box nature must somehow be lightened up to clarify its promising results. Hence, we aim to investigate the impact of the ResNet-50 deep convolutional design for Barrett’s esophagus and adenocarcinoma classification. For such a task, and aiming at proposing a two-step learning technique, the output of each convolutional layer that composes the ResNet-50 architecture was trained and classified for further definition of layers that would provide more impact in the architecture. We showed that local information and high-dimensional features are essential to improve the classification for our task. Besides, we observed a significant improvement when the most discriminative layers expressed more impact in the training and classification of ResNet-50 for Barrett’s esophagus and adenocarcinoma classification, demonstrating that both human knowledge and computational processing may influence the correct learning of such a problem.
Aims
Artificial Intelligence (AI) systems in gastrointestinal endoscopy are narrow because they are trained to solve only one specific task. Unlike Narrow-AI, general AI systems may be able to solve multiple and unrelated tasks. We aimed to understand whether an AI system trained to detect, characterize, and segment early Barrett’s neoplasia (Barrett’s AI) is only capable of detecting this pathology or can also detect and segment other diseases like early squamous cell cancer (SCC).
Methods
120 white light (WL) and narrow-band endoscopic images (NBI) from 60 patients (1 WL and 1 NBI image per patient) were extracted from the endoscopic database of the University Hospital Augsburg. Images were annotated by three expert endoscopists with extensive experience in the diagnosis and endoscopic resection of early esophageal neoplasias. An AI system based on DeepLabV3+architecture dedicated to early Barrett’s neoplasia was tested on these images. The AI system was neither trained with SCC images nor had it seen the test images prior to evaluation. The overlap between the three expert annotations („expert-agreement“) was the ground truth for evaluating AI performance.
Results
Barrett’s AI detected early SCC with a mean intersection over reference (IoR) of 92% when at least 1 pixel of the AI prediction overlapped with the expert-agreement. When the threshold was increased to 5%, 10%, and 20% overlap with the expert-agreement, the IoR was 88%, 85% and 82%, respectively. The mean Intersection Over Union (IoU) – a metric according to segmentation quality between the AI prediction and the expert-agreement – was 0.45. The mean expert IoU as a measure of agreement between the three experts was 0.60.
Conclusions
In the context of this pilot study, the predictions of SCC by a Barrett’s dedicated AI showed some overlap to the expert-agreement. Therefore, features learned from Barrett’s cancer-related training might be helpful also for SCC prediction. Our results allow different possible explanations. On the one hand, some Barrett’s cancer features generalize toward the related task of assessing early SCC. On the other hand, the Barrett’s AI is less specific to Barrett’s cancer than a general predictor of pathological tissue. However, we expect to enhance the detection quality significantly by extending the training to SCC-specific data. The insight of this study opens the way towards a transfer learning approach for more efficient training of AI to solve tasks in other domains.
Aims
While AI has been successfully implemented in detecting and characterizing colonic polyps, its role in therapeutic endoscopy remains to be elucidated. Especially third space endoscopy procedures like ESD and peroral endoscopic myotomy (POEM) pose a technical challenge and the risk of operator-dependent complications like intraprocedural bleeding and perforation. Therefore, we aimed at developing an AI-algorithm for intraprocedural real time vessel detection during ESD and POEM.
Methods
A training dataset consisting of 5470 annotated still images from 59 full-length videos (47 ESD, 12 POEM) and 179681 unlabeled images was used to train a DeepLabV3+neural network with the ECMT semi-supervised learning method. Evaluation for vessel detection rate (VDR) and time (VDT) of 19 endoscopists with and without AI-support was performed using a testing dataset of 101 standardized video clips with 200 predefined blood vessels. Endoscopists were stratified into trainees and experts in third space endoscopy.
Results
The AI algorithm had a mean VDR of 93.5% and a median VDT of 0.32 seconds. AI support was associated with a statistically significant increase in VDR from 54.9% to 73.0% and from 59.0% to 74.1% for trainees and experts, respectively. VDT significantly decreased from 7.21 sec to 5.09 sec for trainees and from 6.10 sec to 5.38 sec for experts in the AI-support group. False positive (FP) readings occurred in 4.5% of frames. FP structures were detected significantly shorter than true positives (0.71 sec vs. 5.99 sec).
Conclusions
AI improved VDR and VDT of trainees and experts in third space endoscopy and may reduce performance variability during training. Further research is needed to evaluate the clinical impact of this new technology.
Aims
Endoscopic retrograde cholangiopancreaticography (ERCP) is the gold standard in the diagnosis as well as treatment of diseases of the pancreatobiliary tract. However, it is technically complex and has a relatively high complication rate. In particular, cannulation of the papillary ostium remains challenging. The aim of this study is to examine whether a deep-learning algorithm can be used to detect the major duodenal papilla and in particular the papillary ostium reliably and could therefore be a valuable tool for inexperienced endoscopists, particularly in training situation.
Methods
We analyzed a total of 654 retrospectively collected images of 85 patients. Both the major duodenal papilla and the ostium were then segmented. Afterwards, a neural network was trained using a deep-learning algorithm. A 5-fold cross-validation was performed. Subsequently, we ran the algorithm on 5 prospectively collected videos of ERCPs.
Results
5-fold cross-validation on the 654 labeled data resulted in an F1 value of 0.8007, a sensitivity of 0.8409 and a specificity of 0.9757 for the class papilla, and an F1 value of 0.5724, a sensitivity of 0.5456 and a specificity of 0.9966 for the class ostium. Regardless of the class, the average F1 value (class papilla and class ostium) was 0.6866, the sensitivity 0.6933 and the specificity 0.9861. In 100% of cases the AI-detected localization of the papillary ostium in the prospectively collected videos corresponded to the localization of the cannulation performed by the endoscopist.
Conclusions
In the present study, the neural network was able to identify the major duodenal papilla with a high sensitivity and high specificity. In detecting the papillary ostium, the sensitivity was notably lower. However, when used on videos, the AI was able to identify the location of the subsequent cannulation with 100% accuracy. In the future, the neural network will be trained with more data. Thus, a suitable tool for ERCP could be established, especially in the training situation.
Limitations in computer-assisted diagnosis include lack of labeled data and inability to model the relation between what experts see and what computers learn. Even though artificial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their accountability and transparency level must be improved to transfer this success into clinical practice. The reliability of machine learning decisions must be explained and interpreted, especially for supporting the medical diagnosis. While deep learning techniques are broad so that unseen information might help learn patterns of interest, human insights to describe objects of interest help in decision-making. This paper proposes a novel approach, DeepCraftFuse, to address the challenge of combining information provided by deep networks with visual-based features to significantly enhance the correct identification of cancerous tissues in patients affected with Barrett’s esophagus (BE). We demonstrate that DeepCraftFuse outperforms state-of-the-art techniques on private and public datasets, reaching results of around 95% when distinguishing patients affected by BE that is either positive or negative to esophageal cancer.
Background:
Pediatricians are important sources of information for parents regarding their children's health. During the COVID-19 pandemic, pediatricians faced a variety of challenges regarding information uptake and transfer to patients, practice organization and consultations for families. This qualitative study aimed at shedding light on German pediatricians’ experiences of providing outpatient care during the first year of the pandemic.
Methods:
We conducted 19 semi-structured, in-depth interviews with pediatricians in Germany from July 2020 to February 2021. All interviews were audio recorded, transcribed, pseudonymized, coded, and subjected to content analysis.
Results:
Pediatricians felt able to keep up to date regarding COVID-19 regulations. However, staying informed was time consuming and onerous. Informing the patients was perceived as strenuous, especially when political decisions had not been officially communicated to pediatricians or if the recommendations were not supported by the professional judgment of the interviewees. Some felt that they were not taken seriously or adequately involved in political decisions. Parents were reported to consider pediatric practices as sources of information also for non-medical inquiries. Answering these questions was time consuming for the practice personnel and involved non-billable hours. Practices had to adapt their set-up and organization immediately to the new circumstances of the pandemic, which proved costly and laborious as well. Some changes in the organization of routine care, such as the separation of appointments for patients with acute infection from preventive appointments, were perceived as positive and effective by some study participants. Telephone and online consultations were established at the beginning of the pandemic and considered helpful for some situations, whereas for others these methods were deemed insufficient (e.g. for examinations of sick children). All pediatricians reported reduced utilization mainly due to a decline in acute infections. However, preventive medical check-ups and immunization appointments were reported to be mostly attended.
Conclusion:
Positive experiences of reorganizing pediatric practice should be disseminated as “best practices” in order to improve future pediatric health services. Further research could show how some of these positive experiences in reorganizing care during the pandemic are to be maintained by pediatricians in the future.
Background:
People with aphasia (PWA) often suffer from reduced participation and quality of life. Nevertheless, there are currently only a few specific interventions that respond to this problem. Participation and quality of life could be increased by interacting with peers who have similar experiences. Digital social networks could stimulate an autonomous interaction. However, digital social networks need to be adapted to the specific needs of PWA. Therefore, a participatory, agile process involving the target group should be chosen to develop such a olution, i.e., an app. The research project consists of a total of three phases. In the first phase—app development—the app was developed and programmed including the target group. In the second phase—app testing—the usability and user-friendliness of the app were evaluated with four PWA. In the third phase—feasibility and preliminary effcacy—that will be described in the article, the impact of the app on PWA will be evaluated.
Aims:
The overarching aim of our study is to provide preliminary effcacy of the intervention. Digital social interaction with other PWA can lead to increased social integration. In addition to digital interaction, personal encounters between PWA should be encouraged. As a result, we expect an improvement in quality of life of PWA. Additionally, we focus on identification of the most appropriate measurements to discover changes associated with the intervention.
Methods:
The evaluation, which is described in this paper, takes place in a pre-test - post-test design with a total of n = 48 PWA. Participants will be recruited in regional clusters to facilitate face-to-face meetings. Half of the participants will be assigned to the delayed intervention group and the other half to the immediate intervention group. Participants in the delayed intervention group will go through a 3-month waiting period before using the app, while the participants of the immediate intervention group will start using the app for 3 months right away. Inclusion criteria are the presence of chronic aphasia (at least 6 months) and possession of a smartphone with internet access. Questionnaires on quality of life (SAQOL-39, GHQ-12), depression (GDS, DISCs), communicative participation (CPIB), and social support (F-SozU) will be conducted at inclusion (t0), after 3 months of app use (t1), and after another 3 months for follow-up (t2). Participants in the delayed intervention group will be assessed twice before the intervention, before the 3-month waiting period (t0a) and after the waiting period (t0b). In addition to the quantitative measures, interviews will take place with 6 to 8 selected participants after 3 months of app use. Responses will be analysed using Thematic Analysis.
Discussion:
The app will be the first social network tool that is systematically developed with PWA. Initial indications from the first phases are that the app can be used by PWA, so that the evaluation of this app version can take place in the third phase. Results of this study can provide an initial indication of whether social network support is a suitable intervention. Findings will help provide information on the feasibility of digital connectivity for PWA. Preliminary findings on its impact on the participation and quality of life of PWA could be made available.
Older adults in long-term care homes are at high risk of experiencing
reduced quality of life (QoL) and depression. Technology-assisted biography work can have a positive impact on QoL and mood, but there is little research on its use with this target group. The purpose of this paper is to examine the effect of tablet-based biography work conducted by volunteers on the QoL of residents and volunteers. A pretest-posttest control group design with an intervention period of 3 months and a 3-month follow-up was used. Results show a significant increase in participation for volunteers and residents after
the intervention, which is stable for residents until follow-up. Volunteers also show significant improvement in mental QoL immediately after the intervention. There were no significant effects for life satisfaction, self-esteem, or depression. No significant changes were found for the control group. Digitally conducted tablet-based biography work appears to have effects on QoL-associated outcomes.
The elite sport movement for athletes with hearing impairments, namely Deaflympics, differs from the Paralympic and Olympic sport movements because it exhibits a variety of distinct sociocultural and organisational characteristics. Yet, mental training with Deaflympic athletes receives little to no attention from the scientific community. Little is known about sport psychology consultants’ (SPCs) work with Deaflympic athletes. In this study, we explored SPCs’ exposure to so called Deaf sport as well as their experiences, attitudes, and assumptions regarding the utility of psychological skills training (PST) with Deaflympic athletes. A self-constructed questionnaire with closed and semi-open questions was completed by 93 (58.8% female) SPCs in European German-speaking countries. Analyses revealed SPCs had limited exposure to Deaflympic sport but indicated readiness to work with Deaflympic athletes. SPCs shared no reasons as to why PST skills and techniques would not be effective with Deaflympic athletes. However, SPCs regarded communication challenges as a major obstacle. We conclude that the integration of elite Deaf sport in SPCs’ training programmes is vital, considering SPCs’ lack of exposure and experience with Deaflympic athletes as well as their communication insecurities. In addition, further empirical research on PST effectiveness in Deaflympics athletes should provide the foundation for evidence-based utility of applied sport psychology in Deaflympic sport.
Osteoporosis is a common disease of old age. However, in many cases, it can be very well prevented and counteracted with physical activity, especially high-impact exercises. Wearables have the potential to provide data that can help with continuous monitoring of patients during therapy phases or preventive exercise programs in everyday life. This study aimed to determine the accuracy and reliability of measured acceleration data at different body positions compared to accelerations at the pelvis during different jumping exercises. Accelerations at the hips have been investigated in previous studies with regard to osteoporosis prevention. Data were collected using an IMU-based motion capture system (Xsens) consisting of 17 sensors. Forty-nine subjects were included in this study. The analysis shows the correlation between impacts and the corresponding drop height, which are dependent on the respective exercise. Very high correlations (0.83–0.94) were found between accelerations at the pelvis and the other measured segments at the upper body. The foot sensors provided very weak correlations (0.20–0.27). Accelerations measured at the pelvis during jumping exercises can be tracked very well on the upper body and upper extremities, including locations where smart devices are typically worn, which gives possibilities for remote and continuous monitoring of programs.
Three-dimensional Medical Printing and Associated Legal Issues in Plastic Surgery: A Scoping Review
(2023)
Three-dimensional printing (3DP) represents an emerging field of surgery. 3DP can facilitate the plastic surgeon’s workflow, including preoperative planning, intraoperative assistance, and postoperative follow-up. The broad clinical application spectrum stands in contrast to the paucity of research on the legal framework of 3DP. This imbalance poses a potential risk for medical malpractice lawsuits. To address this knowledge gap, we aimed to summarize the current body of legal literature on medical 3DP in the US legal system. By combining the promising clinical use of 3DP with its current legal regulations, plastic surgeons can enhance patient safety and outcomes.
In Vitro Analysis of Human Cartilage Infiltrated by Hydrogels and Hydrogel-Encapsulated Chondrocytes
(2023)
Osteoarthritis (OA) is a degenerative joint disease causing loss of articular cartilage and structural damage in all joint tissues. Given the limited regenerative capacity of articular cartilage, methods to support the native structural properties of articular cartilage are highly anticipated. The aim of this study was to infiltrate zwitterionic monomer solutions into human OA-cartilage explants to replace lost proteoglycans. The study included polymerization and deposition of methacryloyloxyethyl-phosphorylcholine- and a novel sulfobetaine-methacrylate-based monomer solution within ex vivo human OA-cartilage explants and the encapsulation of isolated chondrocytes within hydrogels and the corresponding effects on chondrocyte viability. The results demonstrated that zwitterionic cartilage–hydrogel networks are formed by infiltration. In general, cytotoxic effects of the monomer solutions were observed, as was a time-dependent infiltration behavior into the tissue accompanied by increasing cell death and penetration depth. The successful deposition of zwitterionic hydrogels within OA cartilage identifies the infiltration method as a potential future therapeutic option for the repair/replacement of OA-cartilage extracellular suprastructure. Due to the toxic effects of the monomer solutions, the focus should be on sealing the OA-cartilage surface, instead of complete infiltration. An alternative treatment option for focal cartilage defects could be the usage of monomer solutions, especially the novel generated sulfobetaine-methacrylate-based monomer solution, as bionic for cell-based 3D bioprintable hydrogels.
Although adopting Low Code Development Platforms (LCDPs) promises significant efficiency and effectiveness improvements for application development, its adoption still needs further empirical research. This paper uses a combinatorial approach to research LCDP adoption and presents the results of a multiple mini case study with 36 cases on LCDP adoption. A combination of the Socio-Technical Systems theory and the Technology-Organisational-Environment model is used as a theoretical lens. In this paper, we show that LCDP adoption is a multifaceted phenomenon and identify three archetypes for LCDP adoption (i.e., IT Resource Shortage Mitigators, Application Development Democratisers, and Synergy Realisers) and one archetype for LCDP non-adoption (i.e., Intricacy Adversaries). Each archetype can be interpreted as an individual path towards LCDP (non-)adoption. Based on these archetypes, we derive seven starting points for practitioners to adopt LCDPs in work systems. Moreover, by using the theoretical lenses, the paper shows that for an LCDP adoption to occur, an optimisation of the social and technical sub-systems is required.
Im Rahmen des Projektes AUT-1A wurden 123 Arbeitgeber*innen mittels Fragebogen zu ihren Erfahrungen mit der Beschäftigung von autistischen Mitarbeiter*innen befragt. Ziel war es, die beschäftigungsfördernden und -hindernden Faktoren herauszuarbeiten. Die Studie deutet darauf hin, dass sich die berufliche Qualifizierung in den Berufsbildungswerken positiv auf die nachhaltige Beschäftigung von Menschen mit Autismus-Spektrum-Diagnose (ASD) auswirkt, die Unterstützungsleistungen für Betriebe aber noch nicht hinreichend sind. Auch konnte eine mangelnde Aufklärung in Bezug auf eine autismusfreundliche Umgebungsgestaltung sowie eine mangelnde Aufklärung über die Diagnose Autismus der direkten Kolleg*innen herausgearbeitet werden.
In the treatment of hand injuries in the context of orthopedic care, movable wrist hand orthoses are used in numerous instances. Early motion therapy is in most cases advantageous for adequate, rapid and successful long-term healing of the hand. Conventional dynamic wrist hand orthoses can only be used for movement therapy to a limited extent since they represent the wrist as a simple rotating joint and neglect the complexity of the hand movement possibilities. In this paper, a preliminary concept for dynamic wrist hand orthoses based on prestressed compliant structures is presented. The distinctive feature of this concept lies in the enabling of multiaxial motion capabilities of the human hand without applying conventional joints. According to the concept the wrist region is surrounded by a prestressed compliant structure. Besides the derivation and description of the concept, a first three-dimensional computer-aided design is shown. Additionally, the necessary steps in the development of such a novel dynamic wrist orthosis are discussed.
In the treatment of hand injuries in the context of orthopedic care, movable hand orthoses are used in many cases. Early motion therapy is in most cases advantageous for adequate, rapid, and successful long-term healing of the hand. Conventional mobile hand orthoses can only be used for movement therapy to a limited extent since they represent the wrist as a simple rotating joint and neglect the complexity of the movement possibilities of the hand. In this paper, a novel concept for movable hand orthoses based on prestressed compliant structures is presented. The advantage with this concept is that it replicates the multiaxial motion capabilities without the need for conventional joints. Besides the derivation and description of the concept, a first three-dimensional CAD design is shown. Additionally, the next planned steps in the development of such a novel dynamic hand orthosis are described.
The study is based on a German single-topic population survey on vaccination willingness against COVID-19 (VWC) by the authors (2020, n = 2014). The single-topic survey allowed us to test several competing explanations for VWC, as discussed in the literature. The VWC in the sample was 67.3%. Logistic regression was used to identify factors affecting VWC. Being at high risk from COVID-19 and having received flu vaccination have a positive impact on VWC. Perceived VWC of friends has a strong positive effect on respondents’ VWC. Bivariate relationships of gender, age, and level of education with VWC were no longer significant in a multivariate analysis. Trust in alternative medicine and belief in conspiracy theories have a negative effect on VWC.
This paper investigates DevOps adoption, emphasizing its cultural dimensions in the context of the information systems domain. Utilizing a robust systematic literature review methodology, we discerned nine salient success factors and delineated three stage models instrumental for a smooth transition into DevOps-centric projects. Despite the increasing breadth of research in the DevOps area, the absence of a consolidated definition remains a challenge, underscoring the importance of a unified interpretative framework. This research notably extends the current body of knowledge by focusing on the cultural dynamics of DevOps adoption. As a result, it offers a refined lens through which both practitioners involved in the adoption process and academic researchers can comprehend the nuances and implications of cultural shifts in the evolving landscape of DevOps within information systems.
BACKGROUND
Surgeons have historically used age as a preoperative predictor of postoperative outcomes. Sarcopenia, the loss of skeletal muscle mass due to disease or biological age, has been proposed as a more accurate risk predictor. The prognostic value of sarcopenia assessment in surgical patients remains poorly understood. Therefore, we aimed to synthesize the available literature and investigate the impact of sarcopenia on peri- and postoperative outcomes across all surgical specialties.
METHODS
We systematically assessed the prognostic value of sarcopenia on postoperative outcomes by conducting a systematic review and meta-analysis according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching the PubMed/MEDLINE and EMBASE databases from inception to 1st October 2022. Our primary outcomes were complication occurrence, mortality, length of operation and hospital stay, discharge to home, and postdischarge survival rate at one, three, and five years. Subgroup analysis was performed by stratifying complications according to the Clavien-Dindo classification system. Sensitivity analysis was performed by focusing on studies with an oncological, cardiovascular, emergency, or transplant surgery population, and on those of higher quality or prospective study design.
RESULTS
A total of 294 studies comprising 97,643 patients, of which 33,070 had sarcopenia, were included in our analysis. Sarcopenia was associated with significantly poorer postoperative outcomes including greater mortality, complication occurrence, length of hospital stay, and lower rates of discharge to home (all P<0.00001). A significantly lower survival rate in patients with sarcopenia was noted at one, three, and five years (all P<0.00001) after surgery. Subgroup analysis confirmed higher rates of complications and mortality in oncological (both P<0.00001), cardiovascular (both P<0.00001), and emergency (P=0.03 and P=0.04, respectively) patients with sarcopenia. In the transplant surgery cohort, mortality was significantly higher in patients with sarcopenia (P<0.00001). Among all patients undergoing surgery for inflammatory bowel disease, the frequency of complications was significantly increased among sarcopenic patients (P=0.007). Sensitivity analysis based on higher-quality studies and prospective studies showed that sarcopenia remained a significant predictor of mortality and complication occurrence (all P<0.00001).
CONCLUSION
Sarcopenia is a significant predictor of poorer outcomes in surgical patients. Preoperative assessment of sarcopenia can help surgeons to identify patients at risk, critically balance eligibility, and refine perioperative management. Large-scale studies are required to further validate the importance of sarcopenia as a prognostic indicator of perioperative risk, especially in surgical sub-specialties.
To avoid dislocation of the shoulder joint after reverse total shoulder arthroplasty, it is important to achieve sufficient shoulder stability when placing the implant components during surgery. One parameter for assessing shoulder stability can be shoulder stiffness. The aim of this research was to develop a temporary reverse shoulder implant prototype that would allow intraoperative measurement of shoulder stiffness while varying the position of the implant components. Joint angle and torque measurement techniques were developed to determine shoulder stiffness. Hall sensors were used to measure the joint angles by converting the magnetic flux densities into angles. The accuracy of the joint angle measurements was tested using a test bench. Torques were determined by using thin-film pressure sensors. Various mechanical mechanisms for variable positioning of the implant components were integrated into the prototype. The results of the joint angle measurements showed measurement errors of less than 5° in a deflection range of ±15° adduction/abduction combined with ±45° flexion/extension. The proposed design provides a first approach for intra-operative assessment of shoulder stiffness. The findings can be used as a technological basis for further developments.
The utilization of virtual reality (VR) technology has shown promise in various therapeutic applications, particularly in exposure therapy
for reducing fear of certain situations objects or activities, e.g. fear of height, or negative evaluation of others in social situations. VR has been shown to yield positive outcomes in follow-up studies, and provides a safe and ecological therapeutic environment for therapists and their patients. This paper presents a collaborative
effort to develop a VR speech therapy system which simulates a virtual audience for users to practice their public speaking skills. We describe a novel web-based graphica user interface that enables
therapists to manage the therapy session using a simple timeline. Lastly, we present the results from a qualitative study with therapists and teachers with functional dysphonia, which highlight the potential of such an application to support and augment the therapists’ work and the remaining challenges regarding the design of natural interactions, agent behaviours and scenario customisation for patients.
Background and aims
Celiac disease with its endoscopic manifestation of villous atrophy is underdiagnosed worldwide. The application of artificial intelligence (AI) for the macroscopic detection of villous atrophy at routine esophagogastroduodenoscopy may improve diagnostic performance.
Methods
A dataset of 858 endoscopic images of 182 patients with villous atrophy and 846 images from 323 patients with normal duodenal mucosa was collected and used to train a ResNet 18 deep learning model to detect villous atrophy. An external data set was used to test the algorithm, in addition to six fellows and four board certified gastroenterologists. Fellows could consult the AI algorithm’s result during the test. From their consultation distribution, a stratification of test images into “easy” and “difficult” was performed and used for classified performance measurement.
Results
External validation of the AI algorithm yielded values of 90 %, 76 %, and 84 % for sensitivity, specificity, and accuracy, respectively. Fellows scored values of 63 %, 72 % and 67 %, while the corresponding values in experts were 72 %, 69 % and 71 %, respectively. AI consultation significantly improved all trainee performance statistics. While fellows and experts showed significantly lower performance for “difficult” images, the performance of the AI algorithm was stable.
Conclusion
In this study, an AI algorithm outperformed endoscopy fellows and experts in the detection of villous atrophy on endoscopic still images. AI decision support significantly improved the performance of non-expert endoscopists. The stable performance on “difficult” images suggests a further positive add-on effect in challenging cases.
We investigate contrastive learning in a multi-task learning setting classifying and segmenting early Barrett’s cancer. How can contrastive learning be applied in a domain with few classes and low inter-class and inter-sample variance, potentially enabling image retrieval or image attribution? We introduce a data sampling strategy that mines per-lesion data for positive samples and keeps a queue of the recent projections as negative samples. We propose a masking strategy for the NT-Xent loss that keeps the negative set pure and removes samples from the same lesion. We show cohesion and uniqueness improvements of the proposed method in feature space. The introduction of the auxiliary objective does not affect the performance but adds the ability to indicate similarity between lesions. Therefore, the approach could enable downstream auto-documentation tasks on homogeneous medical image data.
This study investigates the impact of eye movement modeling examples in Software Engineering education. Software Engineering is a highly visual domain. The daily tasks of a software engineer (e.g., formulating requirements, creating UML diagrams, or conducting a code review) require in many cases the use of certain visual strategies. Although these strategies can be found for experts, it has been observed in different eye tracking studies that students have difficulties in learning and applying them. To familiarize students with these visual strategies and to provide them with a better understanding for the cognitive processes involved, a total of seven eye movement modeling examples was created. The seven eye movement modeling examples cover relevant parts of an introductory Software Engineering lecture; they are focused on typical situations in which visual strategies are applied. The results of a questionnaire-based evaluation shows that students consider the eye movement modeling examples as useful, feel supported in their learning process, and would like to see more use of them in the Software Engineering lecture. Furthermore, the students suggested that eye movement modeling examples should also be used in other lectures.
Early motion therapy plays an important role for effective long-term healing of joint injuries. In many cases, conventional dynamic orthoses fail to address the intricate movement possibilities of the underlying joints, limited by their simplistic joint representations, often represented by revolute joints, enabling rotations by only one axis. In this paper, a two-dimensional compliant tensegrity joint for use in biomedical applications is investigated. It consists of two compressed members and five compliant tensioned members. Relative movement possibilities are realized by the intrinsic compliance of the structure. In the development of these systems, the first step is the determination of the static stable equilibrium. This analysis is conducted in this paper by considering the potential energy approach or by using the geometric nonlinear finite element method. The mechanical behavior of the structure is assessed with a specific emphasis on its mechanical compliance. The primary objective of this study is the investigation of the influence of structural parameters on the overall stiffness and movability of the structure. The results underscore the significant effect of member parameters on the stiffness and movability of the compliant tensegrity joint, particularly under varying load magnitudes. These findings provide insights for optimizing the joint’s performance, contributing to its potential application in advanced orthotic and exoskeleton devices.
Surgical Smoke is generated during the cauterization of tissue with high-frequency (HF) devices and consists of 95% water vapor and 5% cellular debris. When the coagulation tweezers, which are supplied with HF voltage by the HF device, touch tissue, the electric circuit is closed, and smoke is generated by the heat. In-vivo investigations are performed during tracheotomies where surgical smoke is produced during coagulation of tissue. Furthermore, in-vitro parametric studies to investigate the particle number and size distribution and the spatial distribution of surgical smoke with laser light sheet technique are conducted. With higher power of the HF device, the particles generated are larger in size and the total number of particles generated is also higher. Adding artificial saliva to the tissue shows even higher particle counts. The study by laser light sheet also confirms this. The resulting characteristic size distribution, which may include viruses and bacterial components, confirms considering the risk arising from surgical smoke. Furthermore, the experiments will provide the database for further numerical investigations.
BACKGROUND: Thrombosis remains a critical complication during venovenous extracorporeal membrane oxygenation (VV ECMO). The involvement of neutrophil extracellular traps (NETs) in thrombogenesis has to be discussed. The aim was to verify NETs in the form of cell-free DNA (cfDNA) in the plasma of patients during ECMO.
METHODS: A fluorescent DNA-binding dye (QuantifFluor®, Promega) was used to detect cell-free DNA in plasma samples. cfDNA concentrations from volunteers (n = 21) and patients (n = 9) were compared and correlated with clinical/technical data before/during support, ECMO end and time of a system exchange.
RESULTS: Before ECMO, patients with a median (IQR) age of 59 (51/63) years, SOFA score of 11 (10/15), and ECMO run time of 9.0 (7.0/19.5) days presented significantly higher levels of cfDNA compared to volunteers (6.4 (5.8/7.9) ng/μL vs. 5.9 (5.4/6.3) ng/μL; p = 0.044). Within 2 days after ECMO start, cfDNA, inflammatory, and hemolysis parameters remained unchanged, while platelets decreased (p = 0.005). After ECMO removal at the end of therapy, cfDNA, inflammation, and coagulation data (except antithrombin III) remained unchanged. The renewal of a system resulted in known alterations in fibrinogen, d-dimers, and platelets, while cfDNA remained unchanged.
CONCLUSION: Detection of cfDNA in plasma of ECMO patients was not an indicator of acute and circuit-induced thrombogenesis.
Digital nerve lesions result in a loss of tactile sensation reflected by an anesthetic area (AA) at the radial or ulnar aspect of the respective digit. Yet, available tools to monitor the recovery of tactile sense have been criticized for their lack of validity. However, the precise quantification of AA dynamics by three-dimensional (3-D) imaging could serve as an accurate surrogate to monitor recovery following digital nerve repair.
For validation, AAs were marked on digits of healthy volunteers to simulate the AA of an impaired cutaneous innervation. Three dimensional models were composed from raw images that had been acquired with a 3-D camera (Vectra H2) to precisely quantify relative AA for each digit (3-D models, n= 80). Operator properties varied regarding individual experience in 3-D imaging and image processing. Additionally, the concept was applied in a clinical case study.
Images taken by experienced photographers were rated better quality (p< 0.001) and needed less processing time (p= 0.020). Quantification of the relative AA was neither altered significantly by experience levels of the photographer (p= 0.425) nor the image assembler (p= 0.749).
The proposed concept allows precise and reliable surface quantification of digits and can be performed consistently without relevant distortion by lack of examiner experience. Routine 3-D imaging of the AA has the great potential to provide visual evidence of various returning states of sensation and to convert sensory nerve recovery into a metric variable with high responsiveness to temporal progress.
BACKGROUND:
Tracheobronchial mucus plays a crucial role in pulmonary function by providing protection against inhaled pathogens. Due to its composition of water, mucins, and other biomolecules, it has a complex viscoelastic rheological behavior. This interplay of both viscous and elastic properties has not been fully described yet. In this study, we characterize the rheology of human mucus using oscillatory and transient tests. Based on the transient tests, we describe the material behavior of mucus under stress and strain loading by mathematical models.
METHODS:
Mucus samples were collected from clinically used endotracheal tubes. For rheological characterization, oscillatory amplitude-sweep and frequency-sweep tests, and transient creep-recovery and stress-relaxation tests were performed. The results of the transient test were approximated using the Burgers model, the Weibull distribution, and the six-element Maxwell model. The three-dimensional microstructure of the tracheobronchial mucus was visualized using scanning electron microscope imaging.
RESULTS:
Amplitude-sweep tests showed storage moduli ranging from 0.1 Pa to 10000 Pa and a median critical strain of 4 %. In frequency-sweep tests, storage and loss moduli increased with frequency, with the median of the storage modulus ranging from 10 Pa to 30 Pa, and the median of the loss modulus from 5 Pa to 14 Pa. The Burgers model approximates the viscoelastic behavior of tracheobronchial mucus during a constant load of stress appropriately (R2 of 0.99), and the Weibull distribution is suitable to predict the recovery of the sample after the removal of this stress (R2 of 0.99). The approximation of the stress-relaxation test data by a six-element Maxwell model shows a larger fit error (R2 of 0.91).
CONCLUSIONS:
This study provides a detailed description of all process steps of characterizing the rheology of tracheobronchial mucus, including sample collection, microstructure visualization, and rheological investigation. Based on this characterization, we provide mathematical models of the rheological behavior of tracheobronchial mucus. These can now be used to simulate mucus flow in the respiratory system through numerical approaches.
High Spatial Resolution Tomo-PIV of the Trachea Focussing on the Physiological Breathing Cycle
(2023)
Investigations of complex patient-specific flow in the nasopharynx requires high resolution numerical calculations validated by reliable experiments. When building the validation base and the benchmark of computational fluid dynamics, an experimental setup of the nasal airways was developed. The applied optical measurement technique of tomo-PIV supplies information on the governing flow field in three dimensions.
This paper presents tomo-PIV measurements of the highly complex patient-specific geometry of the human trachea. A computertomographic scan of a person’s head builds the basis of the experimental silicone model of the nasal airways. An optimised approach for precise refractive index matching avoids optical distortions even in highly complex non-free-of-sight 3D geometries. A linear-motor-driven pump generates breathing scenarios, based on measured breathing cycles. Adjusting of the CCD cameras‘ double-frame-rate PIV-Δt enables the detailed analysis of flow structures during different cycle phases. Merging regions of interest enables high spatial resolution acquisition of the flow field.
It is generally known that project-based learning is a very important part of engineering education to connect theoretical knowledge with practical work. Students learn to apply their knowledge to real-world challenges as it is the case in their later professional life. If students are not used to project work or the scientific topic is new and relatively complex, they may be overwhelmed. The consequence is that students achieve poor results, are frustrated, and therefore learning success is low. Semi-structured projects are introduced that combine the advantages of structured experiments with projects. The project work is structured into several parts with detailed descriptions of the tasks. In the end, students get similar results to doing a free project, but the success rate is higher due to higher guidance. Therefore, these semi-structured projects are seen to be an appropriate method to guide students to learn how to do project work. The feedback from most students is very positive. Some students with no previous lab experience complained about the project work and wished for more guidance to become familiar with lab work. In sum, the student feedback is encouraging to develop semi-structured projects further.
Aims
VA is an endoscopic finding of celiac disease (CD), which can easily be missed if pretest probability is low. In this study, we aimed to develop an artificial intelligence (AI) algorithm for the detection of villous atrophy on endoscopic images.
Methods
858 images from 182 patients with VA and 846 images from 323 patients with normal duodenal mucosa were used for training and internal validation of an AI algorithm (ResNet18). A separate dataset was used for external validation, as well as determination of detection performance of experts, trainees and trainees with AI support. According to the AI consultation distribution, images were stratified into “easy” and “difficult”.
Results
Internal validation showed 82%, 85% and 84% for sensitivity, specificity and accuracy. External validation showed 90%, 76% and 84%. The algorithm was significantly more sensitive and accurate than trainees, trainees with AI support and experts in endoscopy. AI support in trainees was associated with significantly improved performance. While all endoscopists showed significantly lower detection for “difficult” images, AI performance remained stable.
Conclusions
The algorithm outperformed trainees and experts in sensitivity and accuracy for VA detection. The significant improvement with AI support suggests a potential clinical benefit. Stable performance of the algorithm in “easy” and “difficult” test images may indicate an advantage in macroscopically challenging cases.
We present the Regensburg Breast Shape Model (RBSM)—a 3D statistical shape model of the female breast built from 110 breast scans acquired in a standing position, and the first publicly available. Together with the model, a fully automated, pairwise surface registration pipeline used to establish dense correspondence among 3D breast scans is introduced. Our method is computationally efficient and requires only four landmarks to guide the registration process. A major challenge when modeling female breasts from surface-only 3D breast scans is the non-separability of breast and thorax. In order to weaken the strong coupling between breast and surrounding areas, we propose to minimize the variance outside the breast region as much as possible. To achieve this goal, a novel concept called breast probability masks (BPMs) is introduced. A BPM assigns probabilities to each point of a 3D breast scan, telling how likely it is that a particular point belongs to the breast area. During registration, we use BPMs to align the template to the target as accurately as possible inside the breast region and only roughly outside. This simple yet effective strategy significantly reduces the unwanted variance outside the breast region, leading to better statistical shape models in which breast shapes are quite well decoupled from the thorax. The RBSM is thus able to produce a variety of different breast shapes as independently as possible from the shape of the thorax. Our systematic experimental evaluation reveals a generalization ability of 0.17 mm and a specificity of 2.8 mm. To underline the expressiveness of the proposed model, we finally demonstrate in two showcase applications how the RBSM can be used for surgical outcome simulation and the prediction of a missing breast from the remaining one. Our model is available at https://www.rbsm.re-mic.de/.
Theoretical considerations on a 2D compliant tensegrity joint in context of a biomedical application
(2023)
In this paper, a two-dimensional compliant tensegrity joint was investigated for potential biomedical applications such as orthotics or exoskeletons. The structure consists of two compressed members connected by five compliant tensioned members. The concept is based on the tensegrity principle, which allows the realization of dynamic orthoses without conventional hinge joints. Another advantage is the adaptability to the individual needs of the patient through a suitable design of the structure and the careful selection of the characteristics of the elements. Using geometric nonlinear analysis, the mechanical behavior of the structure was investigated, focusing on mechanical compliance. The main objective was to determine the influence of the initial length and stiffness of the tensioned members and the influence of the magnitude of external forces on the overall stiffness of the movable member of the structure. The results highlight the significant impact of member parameters on the structure's stiffness and movability under varying load magnitudes. The research laid the foundation for future development of dynamic orthoses based on this structure.
Following a ban on many materials containing bisphenol-A, new bisphenol-free Boron silicates have been found as substitutes. The purpose of this study is to describe the mechanical properties of these bisphenol-free magnetoactive borosilicate polymers containing hard magnetic particles. Samples of 0%, 33% and 66% by wt. were loaded for compression using a universal testing machine. The maximum forces occurring for different travel speeds were compared before and after post-magnetization treatments. The post-magnetization included 2 stages. In addition, the change in mechanical properties within 24 hours after the post-magnetization process was investigated. Furthermore, the influence of speed and particle content were investigated. In general, there is a correlation between the required compressive force and, the level of post-magnetization stress, the increase in travel speed and particle content in the boron silicate. Comparison of the non-post-magnetized and post-magnetized samples using two-tailed t-tests shows that the p-values for all weight fraction changes in NdPrFeB particles and travel speeds are less than 0.001. Also, a comparison between tests in which the traverse speed was varied also showed significant changes in the resulting compression forces. The same is valid for changes in the weight ratio of the NdPrFeB particles in the samples. For post-magnetized samples, no significant difference can be observed in the first 24 hours following magnetization. In summary, the material presents viscoelastic, plastic force-displacement behavior, which can be well recognized by its bi-linear curve shape.
The investigation shows that borosilicate polymers based on NdPrFeB can have their mechanical behavior modified and controlled by post-magnetization processes. This opens new possibilities for many future applications.
Aims
Evaluation of the add-on effect an artificial intelligence (AI) based clinical decision support system has on the performance of endoscopists with different degrees of expertise in the field of Barrett's esophagus (BE) and Barrett's esophagus-related neoplasia (BERN).
Methods
The support system is based on a multi-task deep learning model trained to solve a segmentation and several classification tasks. The training approach represents an extension of the ECMT semi-supervised learning algorithm. The complete system evaluates a decision tree between estimated motion, classification, segmentation, and temporal constraints, to decide when and how the prediction is highlighted to the observer. In our current study, ninety-six video cases of patients with BE and BERN were prospectively collected and assessed by Barrett's specialists and non-specialists. All video cases were evaluated twice – with and without AI assistance. The order of appearance, either with or without AI support, was assigned randomly. Participants were asked to detect and characterize regions of dysplasia or early neoplasia within the video sequences.
Results
Standalone sensitivity, specificity, and accuracy of the AI system were 92.16%, 68.89%, and 81.25%, respectively. Mean sensitivity, specificity, and accuracy of expert endoscopists without AI support were 83,33%, 58,20%, and 71,48 %, respectively. Gastroenterologists without Barrett's expertise but with AI support had a comparable performance with a mean sensitivity, specificity, and accuracy of 76,63%, 65,35%, and 71,36%, respectively.
Conclusions
Non-Barrett's experts with AI support had a similar performance as experts in a video-based study.
Aims
AI has proven great potential in assisting endoscopists in diagnostics, however its role in therapeutic endoscopy remains unclear. Endoscopic submucosal dissection (ESD) is a technically demanding intervention with a slow learning curve and relevant risks like bleeding and perforation. Therefore, we aimed to develop an algorithm for the real-time detection and delineation of relevant structures during third-space endoscopy.
Methods
5470 still images from 59 full length videos (47 ESD, 12 POEM) were annotated. 179681 additional unlabeled images were added to the training dataset. Consequently, a DeepLabv3+ neural network architecture was trained with the ECMT semi-supervised algorithm (under review elsewhere). Evaluation of vessel detection was performed on a dataset of 101 standardized video clips from 15 separate third-space endoscopy videos with 200 predefined blood vessels.
Results
Internal validation yielded an overall mean Dice score of 85% (68% for blood vessels, 86% for submucosal layer, 88% for muscle layer). On the video test data, the overall vessel detection rate (VDR) was 94% (96% for ESD, 74% for POEM). The median overall vessel detection time (VDT) was 0.32 sec (0.3 sec for ESD, 0.62 sec for POEM).
Conclusions
Evaluation of the developed algorithm on a video test dataset showed high VDR and quick VDT, especially for ESD. Further research will focus on a possible clinical benefit of the AI application for VDR and VDT during third-space endoscopy.
Hintergrund/Zielsetzung
Der Beitrag befasst sich mit dem Wissenstand und der Einstellung der Bevölkerung. Betrachtet werden die Übermittlung und Verfügbarkeit von Gesundheitsdaten, Gesundheitsregister, die elektronische Patientenakte, Einwilligungsverfahren für die Übermittlung von Daten und der Zugriff auf Gesundheitsdaten zu Forschungszwecken.
Methoden
Die Studie basiert auf einer computergestützten Telefonbefragung (Dual-Frame) bei einer Zufallsstichprobe der Bevölkerung in Deutschland im Zeitraum 01.-27.06.2022 (n = 1.308).
Ergebnisse
Der Wissensstand zur Übermittlung von Gesundheitsdaten an Krankenkassen ist hoch, wohingegen das Vorhandensein zentraler Sterbe-, Impf- und Gesundheitsregister sowie der Zugriff auf Gesundheitsdaten durch behandelnde Ärztinnen und Ärzte überschätzt werden. Die Akzeptanz medizinischer Register ist sehr hoch. Die elektronische Patientenakte ist bei der Hälfte der Bevölkerung unbekannt, die Nutzungsbereitschaft ist eher gering ausgeprägt; bei der Übertragung von Daten wird eine Zustimmungsoption bevorzugt, und über achtzig Prozent würden die Daten der elektronischen Patientenakte zur Forschung freigeben. Drei Viertel würden ihre Gesundheitsdaten allgemein zur Forschung freigeben, insbesondere an Universitäten in Deutschland, wobei meist Anonymität Bedingung ist. Die Bereitschaft zur Datenfreigabe steigt mit der Höhe des Vertrauens in die Presse sowie in Universitäten und Hochschulen, und sie sinkt, wenn ein Datenleck als schwerwiegend erachtet wird.
Diskussion und Schlussfolgerung
In Deutschland besteht, wie in anderen europäischen Ländern, eine große Bereitschaft zur Freigabe von Gesundheitsdaten zu Forschungszwecken. Dagegen ist der Wunsch zur Nutzung der elektronischen Patientenakte eher gering. Ebenso niedrig ist die Akzeptanz einer Widerspruchsoption, die jedoch als Voraussetzung für eine erfolgreiche Einführung einer elektronischen Patientenakte gilt. Vertrauen in die Forschung und staatliche Stellen, die Gesundheitsdaten verarbeiten, sind zentrale Faktoren.
Semantic segmentation is an essential task in medical imaging research. Many powerful deep-learning-based approaches can be employed for this problem, but they are dependent on the availability of an expansive labeled dataset. In this work, we augment such supervised segmentation models to be suitable for learning from unlabeled data. Our semi-supervised approach, termed Error-Correcting Mean-Teacher, uses an exponential moving average model like the original Mean Teacher but introduces our new paradigm of error correction. The original segmentation network is augmented to handle this secondary correction task. Both tasks build upon the core feature extraction layers of the model. For the correction task, features detected in the input image are fused with features detected in the predicted segmentation and further processed with task-specific decoder layers. The combination of image and segmentation features allows the model to correct present mistakes in the given input pair. The correction task is trained jointly on the labeled data. On unlabeled data, the exponential moving average of the original network corrects the student’s prediction. The combined outputs of the students’ prediction with the teachers’ correction form the basis for the semi-supervised update. We evaluate our method with the 2017 and 2018 Robotic Scene Segmentation data, the ISIC 2017 and the BraTS 2020 Challenges, a proprietary Endoscopic Submucosal Dissection dataset, Cityscapes, and Pascal VOC 2012. Additionally, we analyze the impact of the individual components and examine the behavior when the amount of labeled data varies, with experiments performed on two distinct segmentation architectures. Our method shows improvements in terms of the mean Intersection over Union over the supervised baseline and competing methods. Code is available at https://github.com/CloneRob/ECMT.
Physical Education with Eduball Stimulates Non-Native Language Learning in Primary School Students
(2022)
Although the neuronal mechanisms of action and cognition are related, the division of intellectual and physical lessons is standard in schools. This is surprising, because numerous studies show that integrating physical education (PE) with teaching content stimulates critical skills. For example, several experiments indicate that Eduball-based PE (i.e., lessons in a sports hall during which students play team mini-games with educational balls with printed letters, numbers, and other signs) develops mathematical and language competencies. At the same time, the Eduball method does not slow down learners' physical development. However, we have little knowledge about the effects of such techniques on non-native language learning. Consequently, the absence of incorporating core academic subjects into PE in dual-language schools or during foreign language education is exceptionally high. Here, we replicated the Eduball experiment, but with the goal of testing this method for non-native language learning. Thus, the intervention occurred in a dual-language primary school and we evaluated second language (L2) learning. As before, we used the technique of parallel groups (experimental and control); in both groups, there were three 45-min PE classes per week. In the experimental class, two of them were held using Eduball. After a half-year experiment, children from the experimental group (one second-grade, N = 14) improved their non-native language skills significantly more than their peers from the control group (one second-grade, N = 12). These findings demonstrate that Eduball-type intervention stimulates non-native language learning in children. Hence, our report suggests that specific body training forms can support L2 learning.
Accurate and reliable information about three-dimensional (3D) knee joint laxity can prevent misdiagnosis and avoid incorrect treatments. Nevertheless, knee laxity assessments presented in the literature suffer from significant drawbacks such as soft tissue artifacts, restricting the knee within the measurement, and the absence of quantitative knee ligament property information. In this study, we demonstrated the applicability of a novel methodology for measuring 3D knee laxity, combining robotics- and image-based technology. As such technology has never been applied to healthy living subjects, the aims of this study were to develop novel technology to measure 3D knee laxity in vivo and to provide proof-of-concept 3D knee laxity measurements. To measure tibiofemoral movements, four healthy subjects were placed on a custom-built arthrometer located inside a low dose biplanar X-ray system with an approximately 60 deg knee flexion angle. Anteroposterior and mediolateral translation as well as internal and external rotation loads were subsequently applied to the unconstrained leg, which was placed inside a pneumatic cast boot. Bone contours were segmented in the obtained X-rays, to which subject-specific bone geometries from magnetic resonance imaging (MRI) scans were registered. Afterward, tibiofemoral poses were computed. Measurements of primary and secondary laxity revealed considerable interpersonal differences. The method differs from those available by the ability to accurately track secondary laxity of the unrestricted knee and to apply coupled forces in multiple planes. Our methodology can provide reliable information for academic knee ligament research as well as for clinical diagnostics in the future.
This paper focuses on the role of specific types of crisis (technological crisis, financial market crisis, natural disaster) and their effects on the demand for cash in an international context. As evidence from the last 30 years shows, demand for cash increases during periods of crisis, regardless of the nature of the crisis. The nature of the crisis does, however, determine whether small or large banknote denominations are affected more. This study finds that times of payment uncertainties are associated with increased demand for small denominations, probably reflecting an elevated demand for transaction balances. By contrast, in times of financial crisis or general economic uncertainty, the increased demand for cash is largely the result of consumers taking precautionary actions and building up non-transaction balances; for this reason, there is greater demand for large banknote denominations. This study finds that cash continues to play an important role in crisis management. Whether this function can also be fulfilled by a future central bank digital currency, however, remains to be seen.
BACKGROUND: Autologous fat grafting (AFG) has been established over the past two decades as an additive technique during and after breast reconstruction. Complete reconstruction of the breast mound with AFG alone represents an exceptional technique that has been published mostly in case reports or in studies with limited cases.The purpose of this study is to investigate the influence of three different techniques for breast reconstruction on the recovery of skin sensitivity at the reconstructed breast.
METHODS: The study included 30 patients after mastectomy following breast cancer. Three groups were examined: A) breast reconstruction by autologous fat grafting (AFG), B) breast reconstruction by deep inferior epigastric artery perforator flap (DIEP) and C) breast reconstruction by expander/implant (TE).Biometric data were compared; sensitivity tests were performed using Semmes-Weinstein monofilaments.The non-operated, healthy contralateral breasts of the patients were used as a reference.
RESULTS: While the traditional reconstruction techniques by microsurgical anastomosed perforator flap or expander/implant showed a strongly decreased or completely missing sensitivity of the skin, the tests after reconstruction by AFG represented high values of sensory recovery, which came close to the reference group of non-operated breasts.
CONCLUSION: To our knowledge, this is the first study to compare skin sensitivity after AFG-based reconstruction to established techniques for breast reconstruction. We could demonstrate in a limited group of patients, that breast reconstruction by autologous fat grafting can achieve higher values of skin sensitivity compared to traditional techniques.
The good availability and the large content of adult stem cells in adipose tissue has made it one of the most interesting tissues in regenerative medicine. Although lipofilling is one of the most frequent procedures in plastic surgery, the method still struggles with high absorption rates and volume losses of up to 70%. Therefore, many efforts have been made to optimize liposuction and to process the harvested tissue in order to increase fat graft retention. Because of their immunomodulatory properties, their cytokine secretory activity, and their differentiation potential, enrichment with adipose tissue-derived stem cells was identified as a promising tool to promote transplant survival. Here, we review the important parameters for lipofilling optimization. Finally, we present a new method for the enrichment of lipoaspirate with adipose tissue-derived stem cells and discuss the parameters that contribute to fat graft survival.
Customized additively manufactured (laser powder bed fused (L-PBF)) stents could improve the treatment of complex lesions by enhancing stent-artery conformity. However, geometric irregularities inherent for L-PBF stents are expected to influence not only their mechanical behavior but also their interaction with the artery. In this study, the influence of geometrical irregularities on stent-artery interaction is evaluated within a numerical framework. Thus, computed arterial stresses induced by a reconstructed L-PBF stent model are compared to those induced by the intended stent model (also representing a stent geometry obtained from conventional manufacturing processes) and a modified CAD stent model that accounts for the increased strut thickness inherent for L-PBF stents. It was found that, similar to conventionally manufactured stents, arterial stresses are initially related to the basic stent design/topology, with the highest stresses occurring at the indentations of the stent struts. Compared to the stent CAD model, the L-PBF stent induces distinctly higher and more maximum volume stresses within the plaque and the arterial wall. In return, the modified CAD model overestimates the arterial stresses induced by the L-PBF stent due to its homogeneously increased strut thickness and thus its homogeneously increased geometric stiffness compared with the L-PBF stent. Therefore, the L-PBF-induced geometric irregularities must be explicitly considered when evaluating the L-PBF stent-induced stresses because the intended stent CAD model underestimates the arterial stresses, whereas the modified CAD model overestimates them. The arterial stresses induced by the L-PBF stent were still within the range of values reported for conventional stents in literature, suggesting that the use of L-PBF stents is conceivable in principle. However, because geometric irregularities, such as protruding features from the stent surface, could potentially damage the artery or lead to premature stent failure, further improvement of L-PBF stents is essential.
The main focus of this paper is to describe the development and current state of policy, research and implementation of patient-centered care (PCC) and shared decision-making (SDM) in Germany. What is the current state in health policy? Since 2013, the Law on Patients' Rights has standardized all rights and responsibilities regarding medical care for patients in Germany. This comprises the right to informed decisions, comprehensive and comprehensible information, and decisions based on a clinician-patient partnership. In addition, reports and action plans such as the German Ethics Council's report on patient well-being, the National Health Literacy Action Plan, or the National Cancer Plan emphasize and foster PCC and SDM on a policy level. There are a number of public organizations in Germany that support PCC and SDM. How are patients and the public involved in health policy and research? Publishers and funding agencies increasingly demand patient and public involvement. Numerous initiatives and organizations are involved in publicizing ways to engage patients and the public. Also, an increasing number of public and research institutions have established patient advisory boards. How is PCC and SDM taught? Great progress has been made in introducing SDM into the curricula of medical schools and other health care providers' (HCPs) schools (e.g., nursing, physical therapy). What is the German research agenda? The German government and other public institutions have constantly funded research programs in which PCC and SDM are important topics. This yielded several large-scale funding initiatives and helped to develop SDM training programs for HCPs in different fields of health care and information materials. Recently, two implementation studies on SDM have been conducted. What is the current uptake of PCC and SDM in routine care, and what implementation efforts are underway? Compared to the last country report from 2017, PCC and SDM efforts in policy, research and education have been intensified. However, many steps are still needed to reliably implement SDM in routine care in Germany. Specifically, the further development and uptake of decision tools and countrywide SDM trainings for HCPs require further efforts. Nevertheless, an increasing number of decision support tools - primarily with support from health insurance funds and other public agencies - are to be implemented in routine care. Also, recent implementation efforts are promising. For example, reimbursement by health insurance companies of hospital-wide SDM implementation is being piloted. A necessary next step is to nationally coordinate the gathering and provision of the many PCC and SDM resources available.
In primary open-angle glaucoma (POAG), a neurodegenerative disease of the optic nerve (ON) and leading cause of blindness, the optic nerve head (ONH) undergoes marked structural extracellular matrix (ECM) changes, which contribute to its permanent deformation and to degeneration of ON axons. The remodeling process of the ECM causes changes in the biomechanical properties of the ONH and the peripapillary sclera, which is accompanied by an increased reactivity of the resident astrocytes. The molecular factors involved in the remodeling process belong to the Transforming growth factor (TGF)-β superfamily, especially TGF-β2. In previous publications we showed that TGF-β2 induced ECM alterations are mediated by Cellular Communication Network Factor (CCN)2/Connective Tissue Growth Factor (CTGF) and recently we showed that CCN2/CTGF is expressed by astrocytes of the ON under normal conditions. In this study we wanted to get a better understanding of the function of CCN2/CTGF under normal and pathologic conditions. To this end, we analyzed the glial lamina and peripapillary sclera of CCN2/CTGF overexpressing mice and studied the effect of CCN2/CTGF and increasing substratum stiffness on murine ON astrocytes in vitro. We observed enhanced astrocyte reactivity in the ONH, increased ECM protein synthesis in the peripapillary sclera and increased Ccn2/Ctgf expression in the ONH during the pathologic development in situ. CCN2/CTGF treatment of primary murine ON astrocytes induced a higher migration rate, and increase of ECM proteins including fibronectin, elastin and collagen type III. Furthermore, the astrocytes responded to stiffer substratum with increased glial fibrillary acidic protein, vimentin, actin and CCN2/CTGF synthesis. Finally, we observed the reinforced appearance of CCN2/CTGF in the lamina cribrosa of glaucomatous patients. We conclude that reactive changes in ONH astrocytes, induced by the altered biomechanical characteristics of the region, give rise to a self-amplifying process that includes increased TGF-β2/CCN2/CTGF signaling and leads to the synthesis of ECM molecules and cytoskeleton proteins, a process that in turn augments the stiffness at the ONH. Such a scenario may finally result in a vicious circle in the pathogenesis of POAG. The transgenic CTGF-overexpressing mouse model might be an optimal model to study the chronic pathological POAG changes in the ONH.
In Germany, midwives are involved in extensive antenatal and postnatal care. As health professionals, they can play a key role in strengthening health literacy (HL) of parents on how to prevent chronic allergic diseases in their children. The objective of this study is to explore midwives’ perspectives regarding HL-sensitive counselling in early childhood allergy prevention (ECAP). Twenty-four qualitative semi-structured interviews were conducted with midwives, and data were analyzed using qualitative content analysis. Only a small number of study participants were aware of HL as a concept. However, most of these use screening and counselling strategies which consider individual information needs and which support parental HL. HL sensitivity in counselling is largely based on the midwives’ “gut feelings” and counselling experience, rather than on formal education. The midwives were largely aware of evidence-based ECAP recommendations; however, allergy prevention was not seen as a stand-alone topic but as part of their general counselling on infant feeding and hygiene. They found parents to be more open to receiving complex prevention information during antenatal counselling. In order to strengthen midwives’ roles in HL-sensitive ECAP counselling, their formal education should provide them with explicit HL knowledge and counselling skills. ECAP should be an inherent part of antenatal care.
Autologous lipotransfer is a promising method for tissue regeneration, because white adipose tissue contains a heterogeneous cell population, including mesenchymal stem cells, endothelial cells, immune cells, and adipocytes. In order to improve the outcome, adipose tissue can be processed before application. In this study, we investigated changes caused by mechanical processing.
Lipoaspirates were processed using sedimentation, first-time centrifugation, shear-force homogenization, and second-time centrifugation. The average adipocyte size, stromal vascular cell count, and adipocyte depot size were examined histologically at every processing step. In addition, the adipose derived stem cells (ADSCs) were isolated and differentiated osteogenically and adipogenically. While homogenization causes a disruption of adipocyte depots, the shape of the remaining adipocytes is not changed. On average, these adipocytes are smaller than the depot adipocytes, they are surrounded by the ECM, and therefore mechanically more stable. The volume loss of adipocyte depots leads to a significant enrichment of stromal vascular cells such as ADSCs. However, the mechanical processing does not change the potential of the ADSCs to differentiate adipogenically or steogenically. It thus appears that mechanically processed lipoaspirates are promising for the reparation of even mechanically stressed tissue as that found in nasolabial folds. The changes resulting from the processing correspond more to a filtration of mechanically less stable components than to a manipulation of the tissue.
Introduction:
Neointimal hyperplasia after percutaneous coronary intervention remains a major determinant of in-stent restenosis (ISR). The extent of mechanical vessel injury correlates with ISR. A new ex vivo porcine stent model was introduced and evaluated comparing different stent designs.
Methods:
Coronary arteries were prepared from pig hearts from the slaughterhouse and used for ex vivo implantations of coronary stents. One basic stent design in two configurations (dogbone, DB; non-dogbone, NDB) was used. Vascular injury was determined according to a modified injury score (IS).
Results:
Standardized experimental conditions ensured comparable vessel dimensions and overstretch data. DB stents caused more severe IS compared to NDB stents. The mean IS and the IS at the distal end of all stents were significantly reduced for NDB stents (ISMean, DB, 1.16 ±0.12; NDB, 1.02 ±0.12; p=0.018; ISDist, DB, 1.39 ±0.28; NDB, 1.13 ±0.24; p=0.03).
Discussion/Conclusion:
The introduced ex-vivo model allowed the evaluation of different stent designs exclude unfavorable stent designs.
Exoskeletons were invented over 100 years ago but have only become popular in the last two decades, especially in the working industry as they can decrease work-related loads significantly. The most often used exoskeletons are for the lower back and shoulder since these are commonly affected body regions. All devices have in common that their purpose is to reduce internal loads of vulnerable body regions. Nevertheless, there is still little understanding on how biomechanical loading in the human body changes when exoskeletons are used. Therefore, further analyses are needed. A promising candidate for these are musculoskeletal models, which are based on an inverse dynamics approach and can calculate external parameters such as ground reaction forces or other interaction forces as well as internal parameters such as joint reaction forces or muscle activities. The various examples in the literature show that these models are increasingly used for assessing the biomechanical effects of exoskeletons on the human body. Furthermore, musculoskeletal models can calculate biomechanical loadings of humans with and without exoskeletons for all kinds of applications and allow an evaluation of their purpose.
Practical Relevance: This article highlights the possibilities of musculoskeletal models for assessing the design and efficiency of occupational exoskeletons. Several practical use cases are described along with distinct descriptions of common implications of musculoskeletal and exoskeleton modeling.
Elbow stability is derived from a combination of muscular, ligamentous, and bony structures. After an elbow trauma the stability of the joint is an important decision criterion for the subsequent treatment. The decision regarding non-operative/operative care depends mostly on subjective assessments of medical experts. Therefore, the aim of this study is to use musculoskeletal simulations as an objective assessment tool to investigate the extent to which failure of different stabilizers affects the elbow stability and how these observations correspond to the assessment from clinical practice. A musculoskeletal elbow simulation model was developed for this aim. To investigate the stability of the elbow, varus/valgus moments were applied under 0°, 45°and 90° flexion while the respective cubital angle was analyzed. This was performed for nine different injury scenarios, which were also evaluated for stability by clinical experts. With the results, it can be determined by which injury pattern and under which flexion angle the elbow stability is impaired regarding varus/valgus moments. The scenario with a complete failure of the medial and lateral ligaments and a fracture of the radial head was identified as having the greatest instability. The study presented a numerical determination of elbow stability against varus/valgus moments regarding clinical injury patterns, as well as a comparison of the numerical outcome with experience gained in clinical practice. The numerical predictions agree well with the assessments of the clinical specialists. Thus, the results from musculoskeletal simulation can make an important contribution to a more objective assessment of the elbow stability.
Biomechanical analysis of the right elevated glenohumeral joint in violinists during legato-playing
(2022)
BACKGROUND:
Many statistics reveal that violin players suffer most often from musculoskeletal disorders compared to musicians of other instrument groups. A common phenomenon, especially observed in violin beginners, is the tendency to elevate the right shoulder during playing the violin. This can probably lead to serious disorders in long-term practice with repetitive movements.
OBJECTIVE:
For this reason, this study investigated the relationship between the right shoulder elevation and the force in the right glenohumeral joint during violin playing. It was hypothesized that the forces in the right glenohumeral joint are higher during playing with the right shoulder raised compared to playing in normal posture.
METHODS:
Motion capture data from four experienced violinists was recorded and processed by means of musculoskeletal simulation to get the force and elevation angle while playing with raised shoulder and in normal position.
RESULTS:
The results indicate that the absolute values of the resulting force, as well as the forces in the mediolateral, inferosuperior, and anteroposterior directions, are higher in playing the violin with the shoulder raised than in a normal posture.
CONCLUSIONS:
Elevating the right shoulder while playing the violin may pose a potential problem.
Thinking like a Lawyer - Human Rights and Their Association with the Plastic Surgeon of Today
(2022)
Plastic surgeons are trained to perform a wide repertoire of surgeries-ranging from standard local procedures to highly specialized operations. Therefore, plastic surgeons treat a plethora of clinical presentations and address multiple patient needs. Their daily workflow is increasingly entwined with legal topics. The concrete legal
interpretation falls within the remit of legal experts.
However, by understanding the legal basics of selected surgical procedures, plastic surgeons may generate synergies in patient care and clinical practice. The legal situation is to be elucidated based on the German Basic Law (GBL) and the European Convention on Human Rights
(ECHR).
Purpose
Lipofilling has been established as a standard technique for contour enhancement following breast reconstruction. However, there is a paucity in current literature regarding the use of this technique for complete reconstruction of the female breast as an alternative to conventional techniques, such as expander or flap-based procedures. In particular, the influence of pre-operative irradiation for successful reconstruction has rarely been examined in published studies. Here, the authors describe their experience with successful fat injection in pre-radiated breasts in comparison with non-pre-radiated patients.
Methods
In this retrospective study, we examined a total of 95 lipofilling treatments on 26 patients (28 breasts). All of them experienced mastectomy following breast cancer; local breast defects after partial resection of the gland were not included in this study. In total, 47 lipofilling procedures in 12 non-irradiated patients (14 breasts) and 48 procedures in 14 irradiated women (also 14 breasts) were performed. Per session, approximately 297 +/- 112 cc of adipose tissue was grafted in group A (no radiotherapy) and approximately 259 +/- 93 cc was grafted in group B (radiotherapy).
Results
Among the group of women without pre-operative radiation, 71% of breast reconstructions limited to lipofilling only showed constant engraftment of fat tissue with a successful reconstructive result, whereas only 21% of the patients with pre-radiated breasts showed complete reconstruction of the breast with a permanent fat in-growth.
Conclusion
Preoperative radiotherapy significantly impedes successful completion of breast reconstructions planned only by autologous fat transfer. Patients should be selected individually and carefully for complete breast reconstruction using lipofilling only.
At risk of reproductive disadvantage? Exploring fertility awareness among migrant women in Germany
(2022)
This study examined awareness about fertility among immigrant women and non-migrants in Germany. The social relevance of infertility and fertility treatment is increasing in Western countries due to continually low overall birth rates, a high rate of childlessness, and a gap between the desired and actual numbers of children. While there is growing interest in infertility and reproductive medicine in general, previous studies have rarely included immigrant or ethnic minorities in Europe. This study investigated whether knowledge on the age-related fertility decline (ARFD) varies between migrant groups and the majority group, and the role of education. Working hypotheses were drawn from theoretical considerations on frameworks of migrant assimilation. The analysis was based on data collected in a social science pilot study on reproductive medicine, representative of the general population (‘NeWiRe’ 2014–2015). The sample included 962 women aged 18–50 years living in Germany. Approximately 81% of the sample were immigrants who originated from Turkey, Poland, the Balkan countries or countries of the (post-Soviet) Commonwealth of Independent States. While rather poor overall, knowledge on ARFD was found to be significantly lower in the migrant groups compared with the majority group. This minority-group disadvantage cannot be explained by sociodemographic or cultural variables. Future research should include minority groups in empirical studies on awareness about fertility in order to better understand the causes of this disadvantage, and the potential reproductive needs of migrants.
Cybersecurity and Ethics
(2022)
The text aims to demonstrate that establishing cybersecurity is not only a technical challenge, but that legal, economic, or organizational aspects also play at least as important a role. The provision of cybersecurity raises ethical questions, since cybersecurity can affect moral values such as autonomy, freedom, or privacy. If measurements necessary for the provision of cybersecurity shall be accepted, it is essential to find a balance between the different claims of all stakeholders involved. This aim is achieved through a detailed ethical analysis accompanied by an extensive literature study. As the most important result of this analysis, it becomes obvious that cybersecurity is in competition or even conflict with other values and interests, and that establishing cybersecurity always involves a trade-off. Not only can there be no 100 percent cybersecurity for technical reasons, but if other values and interests are to be considered, this inevitably leads to compromises in cybersecurity.
Due to the various demands for lecturers, there is only a limited time to prepare lectures and lab courses. Therefore, it is necessary to invest the time target-oriented for optimal student learning success. A theoretic model is developed to structure course preparation work regarding scientific content, didactic preparation, and course presentation. Model parameters have to be chosen for each course depending on topic complexity, the lecturer’s prior knowledge, and the already available preparation from the prior semesters. With these parameters, a course preparation model for a complete semester is developed. Analytic models for different optimization strategies are introduced according to the overall goal of the lecturer. Numerical optimization is done to find the appropriate course preparation times to reach an optimal course preparation for high student learning success. It is seen that due to the different optimization strategies, the preparation time results vary and no single truth is given. But this optimization system gives hints on how to invest preparation time target-oriented for high student learning success.
Aims
Congenital breast asymmetry represents a particular challenge to the classic techniques of plastic surgery given the young age of patients at presentation. This study reviews and compares the long-term results of traditional breast augmentation using silicone implants and the more innovative technique of lipografting.
Methods
To achieve this, we not only captured subjective parameters such as satisfaction with outcome and symmetry, but also objective parameters including breast vol-ume and anthropometric measurements. The objective examination was performed manually and by using the Vectra H2 photogrammetry scanning system.
Results
Differences between patients undergoing either implant augmentation or lipograft were revealed not to be significant with respect to patient satisfaction with surgical outcome (p= 0.55) and symmetry (p= 0.69). Furthermore, a breast symmetry of 93 % was reported in both groups. Likewise, no statistically significant volume difference between the left and right breasts was observed in both groups (p\0.41). However, lipograft patients needed on average 2.9 procedures to achieve the desired result, compared with 1.3 for implant augmentation. In contrast, patients treated with implant augmentation may require anumber of implant changes during their lifetime.
Conclusion
Both methods may be considered for patients presenting with congenital breast asymmetry.
Vascular malformations (VMs) are a rare condition. They can be categorized into high-flow and low-flow VMs, which is a challenging task for radiologists. In this work, a very heterogeneous set of MRI images with only rough annotations are used for classification with a convolutional neural network. The main focus is to describe the challenging data set and strategies to deal with such data in terms of preprocessing, annotation usage and choice of the network architecture. We achieved a classification result of 89.47 % F1-score with a 3D ResNet 18.
Background:
Reliable, time- and cost-effective, and clinician-friendly diagnostic tools are cornerstones in facial palsy (FP) patient management. Different automated FP grading systems have been developed but revealed persisting downsides such as insufficient accuracy and cost-intensive hardware. We aimed to overcome these barriers and programmed an automated grading system for FP patients utilizing the House and Brackmann scale (HBS).
Methods:
Image datasets of 86 patients seen at the Department of Plastic, Hand, and Reconstructive Surgery at the University Hospital Regensburg, Germany, between June 2017 and May 2021, were used to train the neural network and evaluate its accuracy. Nine facial poses per patient were analyzed by the algorithm.
Results:
The algorithm showed an accuracy of 100%. Oversampling did not result in altered outcomes, while the direct form displayed superior accuracy levels when compared to the modular classification form (n = 86; 100% vs. 99%). The Early Fusion technique was linked to improved accuracy outcomes in comparison to the Late Fusion and sequential method (n = 86; 100% vs. 96% vs. 97%).
Conclusions:
Our automated FP grading system combines high-level accuracy with cost- and time-effectiveness. Our algorithm may accelerate the grading process in FP patients and facilitate the FP surgeon’s workflow.
BACKGROUND:
Due to their corrugated profile, dragonfly wings have special aerodynamic characteristics during flying and gliding. OBJECTIVE: The aim of this study was to create a realistic 3D model of a dragonfly wing captured with a high-resolution micro-CT. To represent geometry changes in span and chord length and their aerodynamic effects, numerical investigations are carried out at different wing positions. METHODS:
The forewing of a Camacinia gigantea was captured using a micro-CT. After the wing was adapted an error-free 3D model resulted. The wing was cut every 5 mm and 2D numerical analyses were conducted in Fluent® 2020 R2 (ANSYS, Inc., Canonsburg, PA, USA). RESULTS: The highest lift coefficient, as well as the highest lift-to-drag ratio, resulted at 0 mm and an angle of attack (AOA) of 5∘. At AOAs of 10∘ or 15∘, the flow around the wing stalled and a Kármán vortex street behind the wing becomes
CONCLUSIONS:
The velocity is higher on the upper side of the wing compared to the lower side. The pressure acts vice versa. Due to the recirculation zones that are formed in valleys of the corrugation pattern the wing resembles the form of an airfoil.
The present paper provides an overview on current developments of cash usage and issue of central bank digital currency (CBDC) in the euro area and proposes a possible design of a digital euro that allows for instant offline payments. Cash usage at the point-of-sale decreased perceptibly in the past years mainly due to the ongoing trend towards digitalization. However, we show that there are also indications that consumers were somewhat pushed into cashless payments by government regulations and supply-side restrictions by commercial banks. Nonetheless, overall demand for euro cash remained strong and even increased relative to GDP since the financial crisis in 2008. In this process, however, we observe a supply-driven shift towards lower banknote denominations. Central banks all over the world are intensively thinking about the potential issue of CBDC as a substitute or complement to cash. Based on some of its preferred characteristics, we propose a double pre-paid scheme combining central elements of TARGET Instant Payment Settlement and electronic money features enabling offline and online instant payments. Since anonymity is categorically discarded by the ECB and as cash has some special advantages from a consumer perspective, the digital euro will rather co-circulate with cash than replace it in transactions.
We conceptualize the new phenomenon of the Fractional Chief InformationOfficer (CIO) as a part-time executive who usually works for more than one pri-marily small- to medium-sized enterprise (SME) and develop promising avenuesfor future research on Fractional CIOs. We conduct an empirical study by drawingon semi-structured interviews with 40 individuals from 10 different countries whooccupy a Fractional CIO role. We derive a definition for the Fractional CIO, dis-tinguish it from other forms of employment, and compare it with existing researchon CIO roles. Further, we find four salient engagement types of Fractional CIOsoffering value for SMEs in various situations: Strategic IT management, Restruc-turing, Rapid scaling, and Hands-on support. The results reveal similarities withexisting CIO roles as well as novel insights concerning the different engagementtypes. Lastly, we propose a research agenda for the Fractional CIO field, based onfour research themes derived from existing CIO research and insights from theinterviews.
Clinical setting
Third space procedures such as endoscopic submucosal dissection (ESD) and peroral endoscopic myotomy (POEM) are complex minimally invasive techniques with an elevated risk for operator-dependent adverse events such as bleeding and perforation. This risk arises from accidental dissection into the muscle layer or through submucosal blood vessels as the submucosal cutting plane within the expanding resection site is not always apparent. Deep learning algorithms have shown considerable potential for the detection and characterization of gastrointestinal lesions. So-called AI – clinical decision support solutions (AI-CDSS) are commercially available for polyp detection during colonoscopy. Until now, these computer programs have concentrated on diagnostics whereas an AI-CDSS for interventional endoscopy has not yet been introduced. We aimed to develop an AI-CDSS („Smart ESD“) for real-time intra-procedural detection and delineation of blood vessels, tissue structures and endoscopic instruments during third-space endoscopic procedures.
Characteristics of Smart ESD
An AI-CDSS was invented that delineates blood vessels, tissue structures and endoscopic instruments during third-space endoscopy in real-time. The output can be displayed by an overlay over the endoscopic image with different modes of visualization, such as a color-coded semitransparent area overlay, or border tracing (demonstration video). Hereby the optimal layer for dissection can be visualized, which is close above or directly at the muscle layer, depending on the applied technique (ESD or POEM). Furthermore, relevant blood vessels (thickness> 1mm) are delineated. Spatial proximity between the electrosurgical knife and a blood vessel triggers a warning signal. By this guidance system, inadvertent dissection through blood vessels could be averted.
Technical specifications
A DeepLabv3+ neural network architecture with KSAC and a 101-layer ResNeSt backbone was used for the development of Smart ESD. It was trained and validated with 2565 annotated still images from 27 full length third-space endoscopic videos. The annotation classes were blood vessel, submucosal layer, muscle layer, electrosurgical knife and endoscopic instrument shaft. A test on a separate data set yielded an intersection over union (IoU) of 68%, a Dice Score of 80% and a pixel accuracy of 87%, demonstrating a high overlap between expert and AI segmentation. Further experiments on standardized video clips showed a mean vessel detection rate (VDR) of 85% with values of 92%, 70% and 95% for POEM, rectal ESD and esophageal ESD respectively. False positive measurements occurred 0.75 times per minute. 7 out of 9 vessels which caused intraprocedural bleeding were caught by the algorithm, as well as both vessels which required hemostasis via hemostatic forceps.
Future perspectives
Smart ESD performed well for vessel and tissue detection and delineation on still images, as well as on video clips. During a live demonstration in the endoscopy suite, clinical applicability of the innovation was examined. The lag time for processing of the live endoscopic image was too short to be visually detectable for the interventionist. Even though the algorithm could not be applied during actual dissection by the interventionist, Smart ESD appeared readily deployable during visual assessment by ESD experts. Therefore, we plan to conduct a clinical trial in order to obtain CE-certification of the algorithm. This new technology may improve procedural safety and speed, as well as training of modern minimally invasive endoscopic resection techniques.
Aims
Barrett´s esophagus related neoplasia (BERN) is difficult to detect and characterize during endoscopy, even for expert endoscopists. We aimed to assess the add-on effect of an Artificial Intelligence (AI) algorithm (Barrett-Ampel) as a decision support system (DSS) for non-expert endoscopists in the evaluation of Barrett’s esophagus (BE) and BERN.
Methods
Twelve videos with multimodal imaging white light (WL), narrow-band imaging (NBI), texture and color enhanced imaging (TXI) of histologically confirmed BE and BERN were assessed by expert and non-expert endoscopists. For each video, endoscopists were asked to identify the area of BERN and decide on the biopsy spot. Videos were assessed by the AI algorithm and regions of BERN were highlighted in real-time by a transparent overlay. Finally, endoscopists were shown the AI videos and asked to either confirm or change their initial decision based on the AI support.
Results
Barrett-Ampel correctly identified all areas of BERN, irrespective of the imaging modality (WL, NBI, TXI), but misinterpreted two inflammatory lesions (Accuracy=75%). Expert endoscopists had a similar performance (Accuracy=70,8%), while non-experts had an accuracy of 58.3%. When AI was implemented as a DSS, non-expert endoscopists improved their diagnostic accuracy to 75%.
Conclusions
AI may have the potential to support non-expert endoscopists in the assessment of videos of BE and BERN. Limitations of this study include the low number of videos used. Randomized clinical trials in a real-life setting should be performed to confirm these results.
ARTIFICIAL INTELLIGENCE (AI) – ASSISTED VESSEL AND TISSUE RECOGNITION IN THIRD-SPACE ENDOSCOPY
(2022)
Aims
Third-space endoscopy procedures such as endoscopic submucosal dissection (ESD) and peroral endoscopic myotomy (POEM) are complex interventions with elevated risk of operator-dependent adverse events, such as intra-procedural bleeding and perforation. We aimed to design an artificial intelligence clinical decision support solution (AI-CDSS, “Smart ESD”) for the detection and delineation of vessels, tissue structures, and instruments during third-space endoscopy procedures.
Methods
Twelve full-length third-space endoscopy videos were extracted from the Augsburg University Hospital database. 1686 frames were annotated for the following categories: Submucosal layer, blood vessels, electrosurgical knife and endoscopic instrument. A DeepLabv3+neural network with a 101-layer ResNet backbone was trained and validated internally. Finally, the ability of the AI system to detect visible vessels during ESD and POEM was determined on 24 separate video clips of 7 to 46 seconds duration and showing 33 predefined vessels. These video clips were also assessed by an expert in third-space endoscopy.
Results
Smart ESD showed a vessel detection rate (VDR) of 93.94%, while an average of 1.87 false positive signals were recorded per minute. VDR of the expert endoscopist was 90.1% with no false positive findings. On the internal validation data set using still images, the AI system demonstrated an Intersection over Union (IoU), mean Dice score and pixel accuracy of 63.47%, 76.18% and 86.61%, respectively.
Conclusions
This is the first AI-CDSS aiming to mitigate operator-dependent limitations during third-space endoscopy. Further clinical trials are underway to better understand the role of AI in such procedures.
The endoscopic features associated with eosinophilic esophagitis (EoE) may be missed during routine endoscopy. We aimed to develop and evaluate an Artificial Intelligence (AI) algorithm for detecting and quantifying the endoscopic features of EoE in white light images, supplemented by the EoE Endoscopic Reference Score (EREFS). An AI algorithm (AI-EoE) was constructed and trained to differentiate between EoE and normal esophagus using endoscopic white light images extracted from the database of the University Hospital Augsburg. In addition to binary classification, a second algorithm was trained with specific auxiliary branches for each EREFS feature (AI-EoE-EREFS). The AI algorithms were evaluated on an external data set from the University of North Carolina, Chapel Hill (UNC), and compared with the performance of human endoscopists with varying levels of experience. The overall sensitivity, specificity, and accuracy of AI-EoE were 0.93 for all measures, while the AUC was 0.986. With additional auxiliary branches for the EREFS categories, the AI algorithm (AI-EoEEREFS) performance improved to 0.96, 0.94, 0.95, and 0.992 for sensitivity, specificity, accuracy, and AUC, respectively. AI-EoE and AI-EoE-EREFS performed significantly better than endoscopy beginners and senior fellows on the same set of images. An AI algorithm can be trained to detect and quantify endoscopic features of EoE with excellent performance scores. The addition of the EREFS criteria improved the performance of the AI algorithm, which performed significantly better than endoscopists with a lower or medium experience level.
The early diagnosis of cancer in Barrett’s esophagus is crucial for improving the prognosis. However, identifying Barrett’s esophagus-related neoplasia (BERN) is challenging, even for experts [1]. Four-quadrant biopsies may improve the detection of neoplasia, but they can be associated with sampling errors. The application of artificial intelligence (AI) to the assessment of Barrett’s esophagus could improve the diagnosis of BERN, and this has been demonstrated in both preclinical and clinical studies [2] [3].
In this video demonstration, we show the accurate detection and delineation of BERN in two patients ([Video 1]). In part 1, the AI system detects a mucosal cancer about 20 mm in size and accurately delineates the lesion in both white-light and narrow-band imaging. In part 2, a small island of BERN with high-grade dysplasia is detected and delineated in white-light, narrow-band, and texture and color enhancement imaging. The video shows the results using a transparent overlay of the mucosal cancer in real time as well as a full segmentation preview. Additionally, the optical flow allows for the assessment of endoscope movement, something which is inversely related to the reliability of the AI prediction. We demonstrate that multimodal imaging can be applied to the AI-assisted detection and segmentation of even small focal lesions in real time.
Celiac disease is an autoimmune disorder caused by gluten that results in an inflammatory response of the small intestine.We investigated whether celiac disease can be detected using endoscopic images through a deep learning approach. The results show that additional clinical parameters can improve the classification accuracy. In this work, we distinguished between healthy tissue and Marsh III, according to the Marsh score system. We first trained a baseline network to classify endoscopic images of the small bowel into these two classes and then augmented the approach with a multimodality component that took the antibody status into account.
In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy, for example, bleeding and perforation. A DeepLabv3-based model was trained to delineate vessels, tissue structures and instruments on endoscopic still images from such procedures. The mean cross-validated Intersection over Union and Dice Score were 63% and 76%, respectively. Applied to standardised video clips from third-space endoscopic procedures, the algorithm showed a mean vessel detection rate of 85% with a false-positive rate of 0.75/min. These performance statistics suggest a potential clinical benefit for procedure safety, time and also training.
CRISPR (clustered regularly interspaced short palindromic repeats) systems are one of the most fascinating tools of the current era in molecular biotechnology. With the ease that they provide in genome editing, CRISPR systems generate broad opportunities for targeting mutations. Specifically in recent years, disease-causing mutations targeted by the CRISPR systems have been of main research interest; particularly for those diseases where there is no current cure, including cancer. KRAS mutations remain untargetable in cancer. Mutations in this oncogene are main drivers in common cancers, including lung, colorectal and pancreatic cancers, which are severe causes of public health burden and mortality worldwide, with no cure at hand. CRISPR systems provide an opportunity for targeting cancer causing mutations. In this review, we highlight the work published on CRISPR applications targeting KRAS mutations directly, as well as CRISPR applications targeting mutations in KRAS-related molecules. In specific, we focus on lung, colorectal and pancreatic cancers. To date, the limited literature on CRISPR applications targeting KRAS, reflect promising results. Namely, direct targeting of mutant KRAS variants using various CRISPR systems resulted in significant decrease in cell viability and proliferation in vitro, as well as tumor growth inhibition in vivo. In addition, the effect of mutant KRAS knockdown, via CRISPR, has been observed to exert regulatory effects on the downstream molecules including PI3K, ERK, Akt, Stat3, and c-myc. Molecules in the KRAS pathway have been subjected to CRISPR applications more often than KRAS itself. The aim of using CRISPR systems in these studies was mainly to analyze the therapeutic potential of possible downstream and upstream effectors of KRAS, as well as to discover further potential molecules. Although there have been molecules identified to have such potential in treatment of KRAS-driven cancers, a substantial amount of effort is still needed to establish treatment strategies based on these discoveries. We conclude that, at this point in time, despite being such a powerful directed genome editing tool, CRISPR remains to be underutilized for targeting KRAS mutations in cancer. Efforts channelled in this direction, might pave the way in solving the long-standing challenge of targeting the KRAS mutations in cancers.
Degradation and release of tannic acid from an injectable tissue regeneration bead matrix in vivo
(2021)
The development of multifunctional biomaterials as both tissue regeneration and drug delivery devices is currently a major focus in biomedical research. Tannic Acid (TA), a naturally occurring plant polyphenol, displays unique medicinal abilities as an antioxidant, an antibiotic, and as an anticancer agent. TA has applications in biomaterials acting as a crosslinker in polymer hydrogels improving thermal stability and mechanical properties. We have developed injectable cell seeded collagen beads crosslinked with TA for breast reconstruction and anticancer activity following lumpectomy. This study determined the longevity of the bead implants by establishing a degradation time line and TA release profile in vivo. Beads crosslinked with 0.1% TA and 1% TA were compared to observe the differences in TA concentration on degradation and release. We found collagen/TA beads degrade at similar rates in vivo, yet are resistant to complete degradation after 16 weeks. TA is released over time in vivo through diffusion and cellular activity. Changes in mechanical properties in collagen/TA beads before implantation to after 8 weeks in vivo also indicate loss of TA over a longer period of time. Elastic moduli decreased uniformly in both 0.1% and 1% TA beads. This study establishes that collagen/TA materials can act as a drug delivery system, rapidly releasing TA within the first week following implantation. However, the beads retain TA long term allowing them to resist degradation and remain in situ acting as a cell scaffold and tissue filler. This confirms its potential use as an anticancer and minimally invasive breast reconstructive device following lumpectomy.
Aim of the study was to develop a standardized model system to investigate endodontic irrigation techniques and assess the efficiency of different activation methods on the removal of hard tissue debris in complex root canal systems. Mesial roots of mandibular molars were firstly scanned by micro-computed tomography (µCT) and allocated to three groups of irrigant activation: sonic activation (EDDY, VDW, Munich, Germany), laser activation (AutoSWEEPS, FOTONA, Ljubljana, Slovenia) and conventional needle irrigation (control). Roots were fixed in individual 3D-printed holders to facilitate root canal enlargement under constant irrigation with NaOCl (5%). To enable standardized quantification of remaining debris, BaSO4-enriched dentine powder was compacted into the canals, followed by another µCT-scan. The final irrigation was performed using 17% ethylenediaminetetraacetic acid (EDTA) and 5% sodium hypochlorite (NaOCl) with the respective activation method, and the volume of remaining artificial debris was quantified after a final µCT-scan. The newly developed model system allowed for reliable, reproducible and standardized assessment of irrigation methods. Activation of the irrigant proved to be significantly more effective than conventional needle irrigation regarding the removal of debris, which persisted particularly in the apical third of the root canal in the control group. The efficiency of irrigation was significantly enhanced with laser- and sonic-based activation, especially in the apical third.
One of the fundamental challenges in L-PBF of filigree geometries, such as aortic stents used in biomedical applications, is the requirement for a robust yet easily removable support structure that allows each component to be successfully fabricated without distortion. To solve this challenge, an integrative experimental approach was attempted in the present study by identifying an optimal support structure design and an optimized support removal strategy for this design. The specimens were manufactured using four different support structure designs based on the geometry exposed to the laser beam during the L-PBF. Support removal procedures included sand blasting (SB), glass bead blasting (GB), and electrochemical polishing (ECP). The two best-performing designs (line and cross) were chosen due to shorter lead times and lower material consumption. As an additional factor that indicates a stable design, the breaking load requirement to remove the support structures was determined. A modified line support with a 145° included angle was shown to be the best support structure design in terms of breaking load, material consumption, and manufacturing time. All three procedures were used to ensure residue-free support removal for this modified line support design, with ECP proving to be the most effective.
Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years, the resting-state fMRI (RS-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere. Twenty patients suffering from brain lesions close to supposed language-relevant cortical areas were included. RS-fMRI and task-based (TB-fMRI) were performed for the purpose of preoperative language assessment. TB-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language-critical and language-supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the TB-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice index. Thereby, the RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly. In general, the results suggest that determining language dominance in the human brain is feasible both with TB-fMRI and RS-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.
Objectives
The European University Association (EUA) defines “employability” as a major goal of higher education. Therefore, competence-based orientation is an important aspect of education. The representation of a standardized job profile in the field of medical informatics, which is based on the most common labor market requirements, is fundamental for identifying and conveying the learning goals corresponding to these competences.
Methods
To identify the most common requirements, we extracted 544 job advertisements from the German job portal, STEPSTONE. This process was conducted via a program we developed in R with the “rvest” library, utilizing web crawling, web extraction, and text mining. After removing duplicates and filtering for jobs that required a bachelor's degree, 147 job advertisements remained, from which we extracted qualification terms. We categorized the terms into six groups: professional expertise, soft skills, teamwork, processes, learning, and problem-solving abilities.
Results
The results showed that only 45% of the terms are related to professional expertise, while 55% are related to soft skills. Studies of employee soft skills have shown similar results. The most prevalent terms were programming, experience, project, and server. Our second major finding is the importance of experience, further underlining how essential practical skills are.
Conclusions
Previous studies used surveys and narrative descriptions. This is the first study to use web crawling, web extraction, and text mining. Our research shows that soft skills and specialist knowledge carry equal weight. The insights gained from this study may be of assistance in developing curricula for medical informatics.
As mobile technology continues to improve, more and more professional services are being offered as mobile apps. This paradigm shift also affects eHealth applications. Digital identities in nation-wide eHealth infrastructures are often realized via smart cards, which however, do not support mobile applications well. In this paper we propose a concept of a mobile eID for eHealth based on smartphones with embedded secure hardware, an mobile authenticator app and an account manager as well as an Identity Provider (IdP) as backend services. The practical applicability of the concept is shown using the example of the German eHealth infrastructure. Our method generates a cryptographic key pair in secure hardware on the user’s smartphone, registers it on the IdP and uses it to authenticate on the IdP. The security of the private key and the integrity of the smartphone is also validated and attestated. The user’s established smartcard-based identity "Electronic Health Card" (EHC) forms the trust anchor. To authenticate against specialist eHealth apps the IdP issues standard-compliant OAuth2.0/OIDC tokens with a limited period of validity. Furthermore, in our security analysis we demonstrate that based on specific security requirements for smartphones and operating systems, at least the eIDAS security level "substantial" related to the technical security aspects of the system can be achieved. On the basis of this research German legislation was adjusted and "digital identities" supplementary to the smartcard-based EHC will be issued from 2023 in the German eHealth infrastructure.
Embodiment theories have proposed a reciprocal relationship between emotional state and bodily reactions. Besides large body postures, recent studies have found emotions to affect rather subtle bodily expressions, such as slumped or upright sitting posture. This study investigated back muscle activity as an indication of an effect of positive and negative emotions on the sitting position. The electromyography (EMG) activity of six back muscles was recorded in 31 healthy subjects during exposure to positive and negative affective pictures. A resting period was used as a control condition. Increased muscle activity patterns in the back were found during the exposure to negative emotional stimuli, which was mainly measured in the lumbar and thorax regions. The positive emotion condition caused no elevated activity. The findings show that negative emotions lead to increased differential muscle activity in the back and thus corroborate those of previous research that emotion affects subtle bodily expressions.
Results of WICOVIR Gargle Pool PCR Testing in German Schools Based on the First 100,000 Tests
(2021)
Background:
Opening schools and keeping children safe from SARS-CoV-2 infections at the same time is urgently needed to protect children from direct and indirect consequences of the COVID-19 pandemic. To achieve this goal, a safe, efficient, and cost-effective SARS-CoV-2 testing system for schools in addition to standard hygiene measures is necessary.
Methods:
We implemented the screening WICOVIR concept for schools in the southeast of Germany, which is based on gargling at home, pooling of samples in schools, and assessment of SARS-CoV-2 by pool rRT-PCR, performed decentralized in numerous participating laboratories. Depooling was performed if pools were positive, and results were transmitted with software specifically developed for the project within a day. Here, we report the results after the first 13 weeks in the project.
Findings:
We developed and implemented the proof-of-concept test system within a pilot phase of 7 weeks based on almost 17,000 participants. After 6 weeks in the main phase of the project, we performed >100,000 tests in total, analyzed in 7,896 pools, identifying 19 cases in >100 participating schools. On average, positive children showed an individual CT value of 31 when identified in the pools. Up to 30 samples were pooled (mean 13) in general, based on school classes and attached school staff. All three participating laboratories detected positive samples reliably with their previously established rRT-PCR standard protocols. When self-administered antigen tests were performed concomitantly in positive cases, only one of these eight tests was positive, and when antigen tests performed after positive pool rRT-PCR results were already known were included, 3 out of 11 truly positive tests were also identified by antigen testing. After 3 weeks of repetitive WICOVIR testing twice weekly, the detection rate of positive children in that cohort decreased significantly from 0.042 to 0.012 (p = 0.008).
Interpretation:
Repeated gargle pool rRT-PCR testing can be implemented quickly in schools. It is an effective, valid, and well-received test system for schools, superior to antigen tests in sensitivity, acceptance, and costs.
Introduction Paediatricians, general practitioners (GPs) and midwives in primary care are important sources of information for parents on early childhood allergy prevention (ECAP). Research has shown that preventive counselling by health professionals can be effective in improving patients' health literacy (HL) and health behaviour. Providing effective advice relies on two factors. First, health professionals need be up-to-date with research evidence on ECAP, to consider popular misconceptions and fears and to translate this knowledge into clear recommendations for parents (knowledge translation). Second, they need to know and apply counselling techniques and create a practice setting which accommodates parental HL needs (health literacy-responsive care). The objective of this study is to explore and assess how German health professionals take up and translate ECAP evidence into appropriate recommendations for parents, how they consider HL in counselling and practice organisation and what barriers and enablers they find in their performance of HL-responsive ECAP. Methods and analysis The study has a sequential mixed-method design, in two phases. In the first phase, qualitative semi-structured expert interviews will be conducted with health professionals (paediatricians, GPs and midwives) at primary care level and professional policy level. Data collection is ongoing until January 2022. In the second phase, based on the qualitative results, a standardised questionnaire will be developed, and pilot-tested in a wider population of German health professionals. The findings of both phases will be integrated. Ethics and dissemination The study has received ethical approval from the Ethics Committee of the University of Regensburg (18-1205-101). The results will be published in international peer-reviewed open access journals and via presentations at scientific conferences. The results will also be shared with German health professionals, decision-makers and potential funders of interventions.
On closer examination, the concept of civil society becomes blurred, for instance, on the crucial question of who belongs to civil society. The different answers to this question show how controversial the concept of civil society is, since it cannot be assumed that members of civil society would be morally particularly preferable actors. If, however, the conceptual foundations of and the question of membership in civil society already raise doubts about this concept, the recourse to civil society as a means against fake news and hate speech itself, which is often heard in public debates, becomes doubtful.
Musculoskeletal lower back load of accoucheurs during childbirth – A pilot and feasibility study
(2021)
Introduction: Back problems represent one of the leading causes of accouchers' work-related musculoskeletal morbidities. The correct execution of birth-related maneuvers including manual perineal protection is crucial not only for the mother and child but also for obstetricians and midwives to reduce any strain on their musculoskeletal system. Therefore, the overall aim of this study was to test the feasibility of determining the effect of different accouchers' postures (standing and kneeling) on their musculoskeletal system.
Methods: The biomechanical analysis is based on musculoskeletal simulations that included motion recordings of real deliveries as well as deliveries conducted on a birthing simulator. These simulations were then used to determine individual joints' loads.
Results: In the kneeling posture, both a low intra-operator variability and a lower average maximum load of the lower back was observed. For the standing position the spine load was reduced by pivoting the elbow on the accouchers' thigh, which in turn was associated with a significantly greater load on the shoulder joint.
Conclusion: The study demonstrated the feasibility of our technique to assess joints loads. It also provided initial data indicating that a posture that reduces spinal flexion and tilt, achieved in this study by the kneeling, can significantly reduce the strain on the practitioner's musculoskeletal system.
"Topographic Shift": a new digital approach to evaluating topographic changes of the female breast
(2021)
Purpose
To assess precise topographic changes of the breast, objective documentation and evaluation of pre- and postoperative results are crucial. New technologies for mapping the body using digital, three-dimensional surface measurements have offered novel ways to numerically assess the female breast. Due to the lack of clear demarcation points of the breast contour, the selection of landmarks on the breast is highly dependent on the examiner, and, therefore, is prone to error when conducting before-after comparisons of the same breast. This study describes an alternative to volumetric measurements, focusing on topographic changes of the female breast, based on three-dimensional scans.
Method
The study was designed as an interventional prospective study of 10 female volunteers who had planned on having aesthetic breast augmentation with anatomical, textured implants. Three dimensional scans of the breasts were performed intraoperatively, first without and then with breast implants. The topographic change was determined as the mean distance between two three-dimensional layers before and after augmentation. This mean distance is defined as the Topographic Shift. Results The mean implant volume was 283 cc (SD = 68.6 cc, range = 210-395 cc). The mean Topographic Shift was 7.4 mm (SD = 1.9 mm, range = 4.8-10.7 mm). The mean Topographic Shifts per quadrant were: I: 8.0 mm (SD = 3.3 mm); II: 9.2 mm (SD = 3.1 mm); III: 6.9 mm (SD = 3.5 mm); IV: 1.9 mm (SD = 4.3 mm).
Conclusion
The Topographic Shift, describing the mean distance between two three-dimensional layers (for example before and after a volume changing therapy), is a new approach that can be used for assessing topographic changes of a body area. It was found that anatomical, textured breast implants cause a topographic change, particularly on the upper breast, in quadrant II, the decollete.
Biomechanical Analysis of the Right Elevated Glenohumeral Joint in Violinists during Legato-Playing
(2021)
BACKGROUND:
Many statistics reveal that violin players suffer most often from musculoskeletal disorders compared to musicians of other instrument groups. A common phenomenon, especially observed in violin beginners, is the tendency to elevate the right shoulder during playing the violin. This can probably lead to serious disorders in long-term practice with repetitive movements.
OBJECTIVE:
For this reason, this study investigated the relationship between the right shoulder elevation and the force in the right glenohumeral joint during violin playing. It was hypothesized that the forces in the right glenohumeral joint are higher during playing with the right shoulder raised compared to playing in normal posture.
METHODS:
Motion capture data from four experienced violinists was recorded and processed by means of musculoskeletal simulation to get the force and elevation angle while playing with raised shoulder and in normal position.
RESULTS:
The results indicate that the absolute values of the resulting force, as well as the forces in the mediolateral, inferosuperior, and anteroposterior directions, are higher in playing the violin with the shoulder raised than in a normal posture.
CONCLUSIONS: Elevating the right shoulder while playing the violin may pose a potential problem.