Lebenswissenschaften und Ethik
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Academic self-regulation is a key factor for motivation and learning achievement. Yet with the large range of individual factors, this is not a one-size-fits-all proposition. This study of L2 Technical English students at two German universities explored learners’ expectations and motivations, in particular regarding self-regulation and self-efficacy via the individual’s time investment in self-led study. In an initial survey, learners (N=1646) reported on their English skill levels and anticipated learning habits. Complementarily, the retrospective survey investigated learners’ (N=796) actual behavior during the course, their perceptions of language skill improvement, and their satisfaction. The initial survey indicates a clear understanding that time investment in self-regulated study will lead to greater improvement, an outcome confirmed in the retrospective survey. Additionally, students who invested more time in their coursework were more satisfied with their achievement, although most learners acknowledge they should have studied more. The results verify that learners recognize the nexus between self-regulation and language skill improvement, yet university students are not satisfied with their capacity to self-regulate their language learning strategies. While differences in students’ skill levels and academic self-efficacy result in divergent degrees of progress, students of all types report benefits to their language skills when motivated to self-regulated study.
Academic self-regulation is a key factor for motivation and learning achievement. Yet with the large range of individual factors, this is not a one-size-fits-all proposition. This study of L2 Technical English students at two German universities explored learners’ expectations and motivations, in particular regarding self-regulation and self-efficacy via the individual’s time investment in self-led study. In an initial survey, learners (N=1646) reported on their English skill levels and anticipated learning habits. Complementarily, the retrospective survey investigated learners’ (N=796) actual behavior during the course, their perceptions of language skill improvement, and their satisfaction. The initial survey indicates a clear understanding that time investment in self-regulated study will lead to greater improvement, an outcome confirmed in the retrospective survey. Additionally, students who invested more time in their coursework were more satisfied with their achievement, although most learners acknowledge they should have studied more. The results verify that learners recognize the nexus between self-regulation and language skill improvement, yet university students are not satisfied with their capacity to self-regulate their language learning strategies. While differences in students’ skill levels and academic self-efficacy result in divergent degrees of progress, students of all types report benefits to their language skills when motivated to self-regulated study.
English language skills are essential to professional communication in international engineering environments. Given the concomitant degree of specialization, university-level coursework in English for Specific Purposes is an essential component of engineering student preparation. This large-scale survey of university students of engineering in three European countries provides important insight into the most relevant language skills, with the goal of informing communicative, task-based curricula for Technical English courses.
Biological applications like vesicle membrane analysis involve the precise segmentation of 3D structures in noisy volumetric data, obtained by techniques like magnetic resonance imaging (MRI) or laser scanning microscopy (LSM). Dealing with such data is a challenging task and requires robust and accurate segmentation methods. In this article, we propose a novel energy model for 3D segmentation fusing various cues like regional intensity subdivision, edge alignment and orientation information. The uniqueness of the approach consists in the definition of a new anisotropic regularizer, which accounts for the unbalanced slicing of the measured volume data, and the generalization of an efficient numerical scheme for solving the arising minimization problem, based on linearization and fixed-point iteration. We show how the proposed energy model can be optimized globally by making use of recent continuous convex relaxation techniques. The accuracy and robustness of the presented approach are demonstrated by evaluating it on multiple real data sets and comparing it to alternative segmentation methods based on level sets. Although the proposed model is designed with focus on the particular application at hand, it is general enough to be applied to a variety of different segmentation tasks.
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.
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.
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.
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.
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.
This paper presents experiences with a digitalized concept for teaching control theory as minor subject with an integrated approach for lectures, exercises and practical sessions in the department of electrical engineering at the OTH Regensburg. The concept uses activating methods like blended learning and possibilities of digitalization of teaching implementing Just in Time Teaching and Peer Instruction. The basis for the new concept is the idea of constructive alignment. Furthermore this paper presents feedback from the students along with an accompanying scientific research over several semesters focusing on the development over past semesters.
The progress of medical genetics leads to a significant increase in genetic knowledge and a vast expansion of genetic diagnostics. However, it is still unknown how these changes will be integrated into medical practice and how they will change patients' and healthy persons' perception and evaluation of genetic diagnoses and genetic knowledge. Therefore, we carried out a comprehensive questionnaire survey with more than 500 patients, clients seeking genetic counseling, health care staff, and healthy persons (N = 523). The questionnaire survey covered detailed questions on the value of genetic diagnoses for the different groups of study participants, the right to know or not to know genetic diagnoses, possible differences between genetic and other medical diagnoses, and the practical use and implications of genetic knowledge with a special focus on hereditary neuropsychiatric diseases. A huge majority of the participants (90.7%) stated to have a right to learn every aspect of her or his genetic make-up. Similarly, study participants showed high interest (81.8%) in incidental health care findings-independent of whether the diseases are treatable or not. One can derive from the data outcome that study participants did not follow the implications of a "genetic exceptionalism" and often considered genetic findings as equivalent in relation to other medical diagnoses.
We propose a new permanent magnet system for Kibble balance experiments, which combines advantages of the magnet designs invented by the National Physical Laboratory (NPL) and by the Bureau International des Poids et Mesures (BIPM). The goal of the proposed magnet system is to minimize the coil-current effect and to optimize the shielding at the same time. In the proposed design, a permanent magnet system with two gaps, each housing a coil, is employed to minimize the coil current effect, by reducing the linear coil-current dependence reported for the single air gap design by at least one order of magnitude. Both air gaps of the magnet are completely surrounded by high-permeability material, and hence the coils are shielded from outside magnetic fields and no magnetic field leaks outside of the magnet system. An example of the new magnet system is given and the analysis shows that the magnetic field in the air gap can be optimized to meet the requirement to be used in Kibble balances.
Hintergrund
Inhalte von Public Health werden in Deutschland in gesundheitsbezogenen Studiengängen an Hochschulen und Universitäten gelehrt. Ziel dieser Studie war es, Daten zur Lehre und zur Kooperation von Lehrenden von Public Health in gesundheitsbezogenen Studiengängen in Deutschland zur Verfügung zu stellen.
Methode
Eine Querschnittsuntersuchung wurde online-basiert vom 01.06. bis 15.09.2015 an 93 Hochschulen/Universitäten in Deutschland mit 351 Studiengangsverantwortlichen aus gesundheitsbezogenen Studiengängen durchgeführt. Einbezogen wurden Public Health Studiengänge und gesundheitsbezogene Studiengänge, deren Hochschulen bzw. Universitäten entweder Mitglied in der "Deutschen Gesellschaft für Sozialmedizin und Prävention" (DGSMP) oder in der Gesellschaft "Hochschulen für Gesundheit" (HOGE) sind. Teilgenommen an dieser Studie haben N=104 Studiengangsverantwortliche (43% Männer, 57% Frauen). In Public Health Studiengängen wurden „Global Health" und "Umwelt und Gesundheit" als Studieninhalte häufiger als in gesundheitsbezogenen Studiengängen benannt; in gesundheitsbezogenen Studiengängen wurden häufiger "Ethik" und "Gesundheitspsychologie" als Lehrinhalte benannt. Finanzielle Unterstützungen durch die Hochschulen/ Universitäten sowie strukturierte Partnerschaften zwischen Hochschulen und/ oder Universitäten werden von Lehrenden an Hochschulen (36%) und an Universitäten (40%) gewünscht. Lehrende an Hochschulen wünschen darüber hinaus Promotionspartnerschaften.
Schlussfolgerung
Bisher gibt es in Deutschland keine einheitlichen fachlichen Qualitätskriterien für Absolvierende von Public Health bzw. gesundheitsbezogenen Studiengängen. Zudem gibt es nach Aussage der Studiengangsverantwortlichen dieser Studiengänge wenig Kooperation zwischen Lehrenden der Public Health bzw. der gesundheitsbezogenen Studiengänge.
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.
"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.
In order to fix a fracture using minimally invasive surgery approaches, surgeons are drilling complex and tiny bones with a 2 dimensional X-ray as single imaging modality in the operating room. Our novel haptic force-feedback and visual assisted training system will potentially help hand surgeons to learn the drilling procedure in a realistic visual environment. Within the simulation, the collision detection as well as the interaction between virtual drill, bone voxels and surfaces are important. In this work, the chai3d collision detection and force calculation algorithms are combined with a physics engine to simulate the bone drilling process. The chosen Bullet-Physics-Engine provides a stable simulation of rigid bodies, if the collision model of the drill and the tool holder is generated as a compound shape. Three haptic points are added to the K-wire tip for removing single voxels from the bone. For the drilling process three modes are proposed to emulate the different phases of drilling in restricting the movement of a haptic device.
Background:
The aim of the study was to compare the two irradiation modes with (FF) and without flattening filter (FFF) for three different treatment techniques for simultaneous integrated boost radiation therapy of patients with right sided breast cancer.
Methods:
An Elekta Synergy linac with Agility collimating device is used to simulate the treatment of 10 patients. Six plans were generated in Monaco 5.0 for each patient treating the whole breast and a simultaneous integrated boost (SIB) volume: intensity modulated radiation therapy (IMRT), volumetric modulated arc therapy (VMAT) and a tangential arc VMAT (tVMAT), each with and without flattening filter. Plan quality was assessed considering target coverage, sparing of the contralateral breast, the lungs, the heart and the normal tissue. All plans were verified by a 2D-ionisation-chamber-array and delivery times were measured and compared. The Wilcoxon test was used for statistical analysis with a significance level of 0.05.
Results:
Significantly best target coverage and homogeneity was achieved using VMAT FFF with V95% = (98.7 +/- 0.8) % and HI = (8.2 +/- 0.9) % for the SIB and V95% = (98.3 +/- 0.7) % for the PTV, whereas tVMAT showed significantly lowest doses to the contralateral organs at risk with a D-mean of (0.7 +/- 0.1) Gy for the contralateral lung, (1.0 +/- 0.2) Gy for the contralateral breast and (1.4 +/- 0.2) Gy for the heart. All plans passed the gamma evaluation with a mean passing rate of (99.2 +/- 0.8) %. Delivery times were significantly reduced for VMAT and tVMAT but increased for IMRT, when FFF was used. Lowest delivery times were observed for tVMAT FFF with (1:20 +/- 0:07) min.
Conclusion:
Balancing target coverage, OAR sparing and delivery time, VMAT FFF and tVMAT FFF are considered the preferable of the investigated treatment options in simultaneous integrated boost irradiation of right sided breast cancer for the combination of an Elekta Synergy linac with Agility and the treatment planning system Monaco 5.0.
One common method to fix fractures of the human hand after an accident is an osteosynthesis with Kirschner wires (K-wires) to stabilize the bone fragments. The insertion of K-wires is a delicate minimally invasive surgery, because surgeons operate almost without a sight. Since realistic training methods are time consuming, costly and insufficient, a virtual-reality (VR) based training system for the placement of K-wires was developed. As part of this, the current work deals with the real-time bone drilling simulation using a haptic force-feedback device.
To simulate the drilling, we introduce a virtual fixture based force-feedback drilling approach. By decomposition of the drilling task into individual phases, each phase can be handled individually to perfectly control the drilling procedure. We report about the related finite state machine (FSM), describe the haptic feedback of each state and explain, how to avoid jerking of the haptic force-feedback during state transition.
The usage of the virtual fixture approach results in a good haptic performance and a stable drilling behavior. This was confirmed by 26 expert surgeons, who evaluated the virtual drilling on the simulator and rated it as very realistic. To make the system even more convincing, we determined real drilling feed rates through experimental pig bone drilling and transferred them to our system. Due to a constant simulation thread we can guarantee a precise drilling motion.
Virtual fixtures based force-feedback calculation is able to simulate force-feedback assisted bone drilling with high quality and, thus, will have a great potential in developing medical applications.
Background: Currently, it is common practice to use three-dimensional (3D) printers not only for rapid prototyping in the industry, but also in the medical area to create medical applications for training inexperienced surgeons. In a clinical training simulator for minimally invasive bone drilling to fix hand fractures with Kirschner-wires (K-wires), a 3D-printed hand phantom must not only be geometrically but also haptically correct. Due to a limited view during an operation, surgeons need to perfectly localize underlying risk structures only by feeling of specific bony protrusions of the human hand.
Methods: The goal of this experiment is to imitate human soft tissue with its haptic and elasticity for a realistic hand phantom fabrication, using only a dual-material 3D printer and support-material-filled metamaterial between skin and bone. We present our workflow to generate lattice structures between hard bone and soft skin with iterative cube edge (CE) or cube face (CF) unit cells. Cuboid and finger shaped sample prints with and without inner hard bone in different lattice thickness are constructed and 3D printed.
Results: The most elastic available rubber-like material is too firm to imitate soft tissue. By reducing the amount of rubber in the inner volume through support material (SUP), objects become significantly softer. Without metamaterial, after disintegration, the SUP can be shifted through the volume and thus the body loses its original shape. Although the CE design increases the elasticity, it cannot restore the fabric form. In contrast to CE, the CF design increases not only the elasticity but also guarantees a local limitation of the SUP. Therefore, the body retains its shape and internal bones remain in its intended place. Various unit cell sizes, lattice thickening and skin thickness regulate the rubber material and SUP ratio. Test prints with higher SUP and lower rubber material percentage appear softer and vice versa. This was confirmed by an expert surgeon evaluation. Subjects adjudged pure rubber-like material as too firm and samples only filled with SUP or lattice structure in CE design as not suitable for imitating tissue. 3D-printed finger samples in CF design were rated as realistic compared to the haptic of human tissue with a good palpable bone structure.
Conclusions: We developed a new dual-material 3D print technique to imitate soft tissue of the human hand with its haptic properties. Blowy SUP is trapped within a lattice structure to soften rubber-like 3D print material, which makes it possible to reproduce a realistic replica of human hand soft tissue.
Background: For surgical fixation of bone fractures of the human hand, so-called Kirschner-wires (K-wires) are drilled through bone fragments. Due to the minimally invasive drilling procedures without a view of risk structures like vessels and nerves, a thorough training of young surgeons is necessary. For the development of a virtual reality (VR) based training system, a three-dimensional (3D) printed phantom hand is required. To ensure an intuitive operation, this phantom hand has to be realistic in both, its position relative to the driller as well as in its haptic features. The softest 3D printing material available on the market, however, is too hard to imitate human soft tissue. Therefore, a support-material (SUP) filled metamaterial is used to soften the raw material. Realistic haptic features are important to palpate protrusions of the bone to determine the drilling starting point and angle. An optical real-time tracking is used to transfer position and rotation to the training system.
Methods: A metamaterial already developed in previous work is further improved by use of a new unit cell. Thus, the amount of SUP within the volume can be increased and the tissue is softened further. In addition, the human anatomy is transferred to the entire hand model. A subcutaneous fat layer and penetration of air through pores into the volume simulate shiftability of skin layers. For optical tracking, a rotationally symmetrical marker attached to the phantom hand with corresponding reference marker is developed. In order to ensure trouble-free position transmission, various types of marker point applications are tested.
Results: Several cuboid and forearm sample prints lead to a final 30 centimeter long hand model. The whole haptic phantom could be printed faultless within about 17 hours. The metamaterial consisting of the new unit cell results in an increased SUP share of 4.32%. Validated by an expert surgeon study, this allows in combination with a displacement of the uppermost skin layer a good palpability of the bones. Tracking of the hand marker in dodecahedron design works trouble-free in conjunction with a reference marker attached to the worktop of the training system.
Conclusions: In this work, an optically tracked and haptically correct phantom hand was developed using dual-material 3D printing, which can be easily integrated into a surgical training system.
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.
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
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
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.
Regarding the prevention of injuries and rehabilitation of the human hand, musculoskeletal simulations using an inverse dynamics approach allow for insights of the muscle recruitment and thus acting forces on the hand. Currently, several hand models from various research groups are in use, which are mainly validated by the comparison of numerical and anatomical moment arms. In contrast to this validation and model-building technique by cadaver studies, the aim of this study is to further validate a recently published hand model [1] by analyzing numerically calculated muscle activities in comparison to experimentally measured electromyographical signals of the muscles. Therefore, the electromyographical signals of 10 hand muscles of five test subjects performing seven different hand movements were measured. The kinematics of these tasks were used as input for the hand model, and the numerical muscle activities were computed. To analyze the relationship between simulated and measured activities, the time difference of the muscle on- and off-set points was calculated, which resulted in a mean on- and off-set time difference of 0.58 s between the experimental data and the model. The largest differences were detected for movements that mainly addressed the wrist. One major issue comparing simulated and measured muscle activities of the hand is cross-talk. Nevertheless, the results show that the hand model fits the experiment quite accurately despite some limitations and is a further step toward patient-specific modeling of the upper extremity.
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.
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.
Outputs of musculoskeletal models should be considered probabilistic rather than deterministic as they are affected by inaccuracies and estimations associated with the development of the model. One of these uncertainties being critical for modeling arises from the determination of the muscles' line of action and the physiological cross-sectional area. Therefore, the aim of this study was to evaluate the outcome sensitivity of model predictions from a musculoskeletal hand model in comparison to the uncertainty of these input parameters. For this purpose, the kinematics and muscle activities of different hand movements (abduction of the fingers, abduction of the thumb, and flexion of the thumb) were recorded. One thousand simulations were calculated for each movement using the Latin hypercube sampling method with a corresponding variation of the muscle origin/insertion points and the cross-sectional area. Comparing the standard hand to simulations incorporating uncertainties of input parameters shows no major deviations in on- and off-set time point of muscle activities. About 60% of simulations are located within a ± 30% interval around the standard model concerning joint reaction forces. The comparison with the variation of the input data leads to the conclusion that the standard hand model is able to provide not over-scattered outcomes and, therefore, can be considered relatively stable. These results are of practical importance to the personalization of a musculoskeletal model with subject-specific bone geometries and hence changed muscle line of action.
We propose an automatic approach for early detection of adenocarcinoma in the esophagus. High-definition endoscopic images (50 cancer, 50 Barrett) are partitioned into a dataset containing approximately equal amounts of patches showing cancerous and non-cancerous regions. A deep convolutional neural network is adapted to the data using a transfer learning approach. The final classification of an image is determined by at least one patch, for which the probability being a cancer patch exceeds a given threshold. The model was evaluated with leave one patient out cross-validation. With sensitivity and specificity of 0.94 and 0.88, respectively, our findings improve recently published results on the same image data base considerably. Furthermore, the visualization of the class probabilities of each individual patch indicates, that our approach might be extensible to the segmentation domain.
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.
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.
Background and Objectives
Older adults in long-term residential aged care experience loneliness and reduced quality of life (QoL). Biographical approaches use the recall of the past events to increase self-efficacy, promote acceptance, and improve QoL. The aim of the systematic review was to examine the effectiveness of biographical approaches in improving the QoL of older adults in long-term residential aged care.
Research Design and Methods
This systematic review was conducted in accordance with PRISMA guidelines, using databases Medline, CINAHL, and the Cochrane Library. A 2-phase search strategy was used to identify research literature relating to the use of biographical interventions. Narrative analysis was used to synthesize results.
Results
Twenty-one studies met inclusion criteria for this review, comprising both group and individual interventions. The findings were inconsistent. Subjective elements of QoL of older adults improved in a narrow majority of the studies. Of a total of 21 outcomes investigated in group interventions, 11 resulted in significant improvements in QoL. The 16 outcomes of the individual interventions resulted in 10 significant improvements. The most significant influence was observed in life satisfaction. Group reminiscence also had a particularly strong influence on self-esteem.
Discussion and Implications
Although benefits were observed, it remains unclear why some interventions led to improvements in subjective elements of QoL and others did not. Exploration of the participant perspective through qualitative data collection and more detailed description of interventions in future studies could lead to a better understanding of the treatment components that are related to improved outcomes for older adults.
This study presents a new measure of value systems, the Motivational Value Systems Questionnaire (MVSQ), which is based on a theory of value systems by psychologist Clare W. Graves. The purpose of the instrument is to help people identify their personal hierarchies of value systems and thus become more aware of what motivates and demotivates them in work-related contexts. The MVSQ is a forced-choice (FC) measure, making it quicker to complete and more difficult to intentionally distort, but also more difficult to assess its psychometric properties due to ipsativity of FC data compared to rating scales. To overcome limitations of ipsative data, a Thurstonian IRT (TIRT) model was fitted to the questionnaire data, based on a broad sample of <i>N</i> = 1,217 professionals and students. Comparison of normative (IRT) scale scores and ipsative scores suggested that MVSQ IRT scores are largely freed from restrictions due to ipsativity and thus allow interindividual comparison of scale scores. Empirical reliability was estimated using a sample-based simulation approach which showed acceptable and good estimates and, on average, slightly higher test-retest reliabilities. Further, validation studies provided evidence on both construct validity and criterion-related validity. Scale score correlations and associations of scores with both age and gender were largely in line with theoretically - and empirically-based expectations, and results of a multitrait-multimethod analysis supports convergent and discriminant construct validity. Criterion validity was assessed by examining the relation of value system preferences to departmental affiliation which revealed significant relations in line with prior hypothesizing. These findings demonstrate the good psychometric properties of the MVSQ and support its application in the assessment of value systems in work-related contexts.
The success of artificial intelligence in medicine is based on the need for large amounts of high quality training data. Sharing of medical image data, however, is often restricted by laws such as doctor-patient confidentiality. Although there are publicly available medical datasets, their quality and quantity are often low. Moreover, datasets are often imbalanced and only represent a fraction of the images generated in hospitals or clinics and can thus usually only be used as training data for specific problems. The introduction of generative adversarial networks (GANs) provides a mean to generate artificial images by training two convolutional networks. This paper proposes a method which uses GANs trained on medical images in order to generate a large number of artificial images that could be used to train other artificial intelligence algorithms. This work is a first step towards alleviating data privacy concerns and being able to publicly share data that still contains a substantial amount of the information in the original private data. The method has been evaluated on several public datasets and quantitative and qualitative tests showing promising results.
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.
Physical inactivity is a problem in Europe, contributing to various non-communicable diseases (NCDs). While health sciences offer data and models for preventing the development of NCDs through health promotion, they do not explain the dynamics between the different institutions and actors in the health field. Neofunctionalism refers to these different actors and suggests that their interaction leads to the construction of a supranational authority, allowing the actors to cooperate on common policies, rules and institutions, resulting in integration and Europeanization. Indeed, there are a variety of European Union (EU) institutions and policies concerned with physical activity (PA), however, the purpose of this paper is to analyze if Europeanization and integration are happening in PA promotion, through the lens of neofunctionalism. Analysis uses process tracing for investigating the emergence of PA on the EU agenda, the legal background, existing policies and institutions. Findings indicate that Europeanization and integration of PA promotion are happening, although the opportunity for actions of the EU are restricted to voluntary actions of the EU Member States due to the agreements in the Treaty of Lisbon. This only allows the EU institutions to apply soft law approaches on PA promotion, which seems to be implemented in some Member States despite its non-binding character. The findings are discussed and further implications for public health professionals and policies outlined.
An amateur radio lecture was developed and is conducted within the general education program of the Ostbayerische Technische Hochschule Regensburg. This course enables the students to participate in a variety of activities within the university. Different learning formats for communication engineering are carried out in combination with an amateur radio station of the university. Additionally, some of the projects serve as anchor points for increased visibility of the university in local society, e.g. by carrying out public events in connection with the local amateur radio community. It is seen that this course together with the amateur radio station have several positive effects for technical education and university visibility.
Background:
Adolescent substance use is a global and local (Hawaii) problem. Therefore, the study goal was to develop and investigate the effect of an adolescent substance use prevention intervention website in Hawaii.
Methods:
A website was developed including drug overviews, health effects, how to stay away, external prevention and treatment resources, and an evaluation. Three grade 11 classes completed a baseline (T1) survey based on website content and a follow-up (T2) assessment after a 15-minute website interaction. - Results: At T1, 63/72 and at T2, 62 students participated (16–17 years old; 92% female; 87.2% Filipino). The number correct increased from 48.0% (SD = 14.5) at T1 to 82.0% (SD = 15.3) at T2 (t(59) = 13.5, p < .001). Eleven of twelve topics improved (p < .5) which addressed mental disorder drug use, workplace meth-use in Hawaii, Americans in need of drug/alcohol treatment, stimulant drugs, side effects of drugs, drug related domestic/child abuse, short-term drug effects, Hawaii and national methuse, chemicals in drugs, how to stay away, and ways of treatment.
Conclusions:
Adolescents improved their substance use prevention understanding. This is promising considering the brief, inexpensive, potentially scalable intervention which can be implemented within high school curricula.
Purpose
Congenital breast asymmetry is a serious gynecological malformation for affected patients. The condition hits young women in puberty and is associated with socio-esthetic handicap, depression, and psychosexual problems. Surgical treatment is usually early in the patient's lifetime, so a long-term sustainable solution is important. Although postoperative outcome has been evaluated in several studies before, this study is the first to analyze which objective parameters have the greatest influence on subjective satisfaction with long-term results.
Methods
Thirty-four patients diagnosed with congenital breast asymmetry that underwent either lipofilling or implant therapy between the years of 2008 to 2019 were examined. On average, our collective comprised patients seven years after surgery. Data were mainly gathered through manual measurements, patient-reported outcome measures (Breast Q™), and breast volumetry based on 3D scans (Vectra® H2, Canfield Scientific).
Results
Among all analyzed parameters, only areolar diameter correlated significantly negatively with the subjective outcome satisfaction of the patient. Regarding the subjective assessment of postoperative satisfaction with similarity of the breasts, again the mean areolar diameter, but also the difference in areolar diameter and breast volume between the right and left breasts correlated significantly negatively.
Conclusion
Areolar diameter was revealed as being a significant factor influencing subjective long-term satisfaction in breast asymmetry patients. Moreover, 3D volumetry proves to be an effective tool to substantiate subjective patient assessments. Our findings may lead to further improvements to surgical planning and will be expanded in further studies.
Gemeinsam Klug Entscheiden – Initiative der AWMF und ihrer
Fachgesellschaften – ein Werkstattberich
(2017)
Gemeinsam Klug Entscheiden ist eine Initiative der AWMF und ihrer
Fachgesellschaften, mit dem Ziel, Empfehlungen zu Versorgungsaspek-
ten in die Versorgung zu bringen, für die ein großes Verbesserungspoten-
tial besteht. Der Impuls dafür wurde durch die TOP-5-Listen der Choosing
Wisely Kampagne gegeben. Ziel des Posters ist es das Vorgehen und die
Methodik für eine evidenzbasierte Entwicklung bekannt zu machen und
zu diskutieren im Hinblick auf Machbarkeit und Verbesserungspotential.
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.
Metals are involved in many processes of life. They are needed for enzymatic reactions, are involved in healthy processes but also yield diseases if the metal homeostasis is disordered. Therefore, the interest to assess the spatial distribution of metals is rising in biomedical science. Imaging metal (and non-metal) isotopes by laser ablation mass spectrometry with inductively coupled plasma (LA-ICP-MS) requires a special software solution to process raw data obtained by scanning a sample line-by-line. As no software ready to use was available we developed an interactive software tool for Image Generation and Analysis (IMAGENA). Unless optimised for LA-ICP-MS, IMAGENA can handle other raw data as well. The general purpose was to reconstruct images from a continuous list of raw data points, to visualise these images, and to convert them into a commonly readable image file format that can be further analysed by standard image analysis software. The generation of the image starts with loading a text file that holds a data column of every measured isotope. Specifying general spatial domain settings like the data offset and the image dimensions is done by the user getting a direct feedback by means of a preview image. IMAGENA provides tools for calibration and to correct for a signal drift in the y-direction. Images are visualised in greyscale as well a pseudo-colours with possibilities for contrast enhancement. Image analysis is performed in terms of smoothed line plots in row and column direction.
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.
GinJinn: An object-detection pipeline for automated feature extraction from herbarium specimens
(2020)
PREMISE:
The generation of morphological data in evolutionary, taxonomic, and ecological studies of plants using herbarium material has traditionally been a labor-intensive task. Recent progress in machine learning using deep artificial neural networks (deep learning) for image classification and object detection has facilitated the establishment of a pipeline for the automatic recognition and extraction of relevant structures in images of herbarium specimens.
METHODS AND RESULTS:
We implemented an extendable pipeline based on state-of-the-art deep-learning object-detection methods to collect leaf images from herbarium specimens of two species of the genus Leucanthemum. Using 183 specimens as the training data set, our pipeline extracted one or more intact leaves in 95% of the 61 test images.
CONCLUSIONS:
We establish GinJinn as a deep-learning object-detection tool for the automatic recognition and extraction of individual leaves or other structures from herbarium specimens. Our pipeline offers greater flexibility and a lower entrance barrier than previous image-processing approaches based on hand-crafted features.
Polarised light imaging (PLI) utilises the birefringence of the myelin sheaths in order to visualise the orientation of nerve fibres in microtome sections of adult human post-mortem brains at ultra-high spatial resolution. The preparation of post-mortem brains for PLI involves fixation, freezing and cutting into 100-μm-thick sections. Hence, geometrical distortions of histological sections are inevitable and have to be removed for 3D reconstruction and subsequent fibre tracking. We here present a processing pipeline for 3D reconstruction of these sections using PLI derived multimodal images of post-mortem brains. Blockface images of the brains were obtained during cutting; they serve as reference data for alignment and elimination of distortion artefacts. In addition to the spatial image transformation, fibre orientation vectors were reoriented using the transformation fields, which consider both affine and subsequent non-linear registration. The application of this registration and reorientation approach results in a smooth fibre vector field, which reflects brain morphology. PLI combined with 3D reconstruction and fibre tracking is a powerful tool for human brain mapping. It can also serve as an independent method for evaluating in vivo fibre tractography.
The number of patients with Barret’s esophagus (BE) has increased in the last decades. Considering the dangerousness of the disease and its evolution to adenocarcinoma, an early diagnosis of BE may provide a high probability of cancer remission. However, limitations regarding traditional methods of detection and management of BE demand alternative solutions. As such, computer-aided tools have been recently used to assist in this problem, but the challenge still persists. To manage the problem, we introduce the infinity Restricted Boltzmann Machines (iRBMs) to the task of automatic identification of Barrett’s esophagus from endoscopic images of the lower esophagus. Moreover, since iRBM requires a proper selection of its meta-parameters, we also present a discriminative iRBM fine-tuning using six meta-heuristic optimization techniques. We showed that iRBMs are suitable for the context since it provides competitive results, as well as the meta-heuristic techniques showed to be appropriate for such task.