TY - GEN A1 - Eger, Maximilian A1 - Bergstraesser, Marcel A1 - Dendorfer, Sebastian A1 - Lenich, Andreas A1 - Pfeifer, Christian T1 - Influence of radial head prosthetic design on humeroradial stability: Validation of a test rig therefore T2 - DOKU2022, Deutscher Kongress für Orthopädie und Unfallchirurgie, 25.-28. 10.2022, Berlin KW - radial head prostheses KW - humeroradial stability KW - radial head arthroplasty KW - subluxation Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0183-22dkou6115 PB - German Medical Science GMS Publishing House CY - Düsseldorf ER - TY - GEN A1 - Dendorfer, Sebastian T1 - KI-basierte mechanische Modelle für Prävention, Diagnostik und Rehabilitation T2 - Serien-Webmeeting zu AI - KI-basierte Bildanalyse zur computer-unterstützten Frakturerkennung, 09.11.22 Y1 - 2022 ER - TY - JOUR A1 - Melzner, Maximilian A1 - Pfeiffer, Christian A1 - Suess, Franz A1 - Dendorfer, Sebastian T1 - Musculoskeletal simulation of elbow stability for common injury patterns JF - Journal of Orthopaedic Research N2 - 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. KW - AnyBody KW - musculoskeletal simulation KW - elbow stability Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-54819 SN - 1554-527X N1 - Corresponding author: Maximilian Melzner VL - 41 IS - 6 SP - 1356 EP - 1364 PB - Wiley ER - TY - GEN A1 - Scheppach, Markus W. A1 - Mendel, Robert A1 - Probst, Andreas A1 - Meinikheim, Michael A1 - Palm, Christoph A1 - Messmann, Helmut A1 - Ebigbo, Alanna T1 - Artificial Intelligence (AI) – assisted vessel and tissue recognition during third space endoscopy (Smart ESD) T2 - Zeitschrift für Gastroenterologie N2 - 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. KW - Artificial Intelligence KW - Medical Image Computing KW - Endoscopy KW - Bildgebendes Verfahren KW - Medizin KW - Künstliche Intelligenz KW - Endoskopie Y1 - 2022 U6 - https://doi.org/10.1055/s-0042-1755110 VL - 60 IS - 08 PB - Georg Thieme Verlag CY - Stuttgart ER - TY - JOUR A1 - Eigenberger, Andreas A1 - Felthaus, Oliver A1 - Schratzenstaller, Thomas A1 - Haerteis, Silke A1 - Utpatel, Kirsten A1 - Prantl, Lukas T1 - The Effects of Shear Force-Based Processing of Lipoaspirates on White Adipose Tissue and the Differentiation Potential of Adipose Derived Stem Cells JF - cells N2 - 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. KW - white adipose tissue KW - lipograft KW - stem cells KW - fat grafting KW - surgery KW - cell-enriched lipotransfer KW - CELT KW - lipoaspirate Y1 - 2022 U6 - https://doi.org/10.3390/cells11162543 VL - 11 IS - 16 PB - MDPI CY - Basel ER - TY - GEN A1 - Melzner, Maximilian A1 - Pfeifer, Christian A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - Muskuloskeletal analysis of elbow stability for common injury patterns T2 - 27th Congress of the European Society of Biomechanics, 26 - 29 June 2022, Porto, Portugal Y1 - 2022 UR - https://drive.google.com/uc?id=1RBguxyHZE-Wr2y6ktOWK06_3lQg2M9Rb&export=download&confirm=t SP - 654 ER - TY - GEN A1 - Melzner, Maximilian A1 - Dendorfer, Sebastian T1 - Biomechanik und muskuloskeletale Simulation T2 - Jahreskongress des ISPO Deutschland e.V., 2./3. Juni 2022, Hedelberg Y1 - 2022 ER - TY - GEN A1 - Auer, Simon A1 - Reinker, Lukas A1 - Süß, Franz A1 - Dendorfer, Sebastian T1 - Comparing calculated and measured muscle activity of thigh muscles in dynamic motion. T2 - 27th Congress of the European Society of Biomechanics, 26 - 29 June 2022, Porto, Portugal Y1 - 2022 UR - https://drive.google.com/uc?id=1RBguxyHZE-Wr2y6ktOWK06_3lQg2M9Rb&export=download&confirm=t SP - 640 ER - TY - GEN A1 - Dendorfer, Sebastian T1 - Biomechanische Aspekte bei Sportverletzungen T2 - OT World Leipzig, Internationale Fachmesse und Weltkongress für Orthopädie und Rehatechnik, 10.-13. Mai 2022 Y1 - 2022 ER - TY - CHAP A1 - Rauber, David A1 - Mendel, Robert A1 - Scheppach, Markus W. A1 - Ebigbo, Alanna A1 - Messmann, Helmut A1 - Palm, Christoph T1 - Analysis of Celiac Disease with Multimodal Deep Learning T2 - Bildverarbeitung für die Medizin 2022: Proceedings, German Workshop on Medical Image Computing, Heidelberg, June 26-28, 2022 N2 - 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. KW - Deep Learning KW - Endoscopy Y1 - 2022 U6 - https://doi.org/10.1007/978-3-658-36932-3_25 SP - 115 EP - 120 PB - Springer Vieweg CY - Wiesbaden ER - TY - CHAP A1 - Nunes, Danilo Weber A1 - Hammer, Michael A1 - Hammer, Simone A1 - Uller, Wibke A1 - Palm, Christoph T1 - Classification of Vascular Malformations Based on T2 STIR Magnetic Resonance Imaging T2 - Bildverarbeitung für die Medizin 2022: Proceedings, German Workshop on Medical Image Computing, Heidelberg, June 26-28, 2022 N2 - 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. KW - Deep Learning KW - Magnetic Resonance Imaging KW - Vascular Malformations Y1 - 2022 U6 - https://doi.org/10.1007/978-3-658-36932-3_57 SP - 267 EP - 272 PB - Springer Vieweg CY - Wiesbaden ER - TY - GEN A1 - Englert, Carsten A1 - Dendorfer, Sebastian T1 - Einfluss der Rotatorenmanschette auf die glenohumerale Stabilität T2 - 20. Intensivkurs Schulterendoprothetik Marburg KW - Biomechanik Y1 - 2022 CY - Marburg ER - TY - JOUR A1 - Stelzer, Vera A1 - Krenkel, Lars T1 - 2D numerical investigations derived from a 3D dragonfly wing captured with a high-resolution micro-CT JF - Technology and health care : official journal of the European Society for Engineering and Medicine N2 - 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. KW - aerodynamics KW - computational fluid dynamics KW - Dragonfly wing KW - gliding flight KW - insect flight Y1 - 2022 U6 - https://doi.org/10.3233/THC-219010 N1 - Corresponding author: Vera Stelzer VL - 30 IS - 1 SP - 283 EP - 289 PB - IOS Press ER - TY - JOUR A1 - Saffert, Anne-Sophie A1 - Melzner, Maximilian A1 - Dendorfer, Sebastian T1 - Biomechanical analysis of the right elevated glenohumeral joint in violinists during legato-playing JF - Technology and Health Care N2 - 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. KW - Biomechanische Analyse KW - Schultergelenk KW - Verletzung KW - Violinspiel KW - biomechanics KW - violin KW - shoulder elevation KW - shoulder joint force KW - musculoskeletal disease Y1 - 2022 U6 - https://doi.org/10.3233/THC-219001 N1 - Corresponding author: Anne-Sophie Saffert VL - 30 IS - 1 SP - 177 EP - 186 PB - IOS Press ER -