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DOI 10.1007/s11517-025-03396-w

Медицинская библиотека · Medical & biological engineering & computing · 2025

Ligament pre-tension determines outcome in sacroiliac joint in silicon modelling.

Heyland Mark, Schmidt Hendrik, Schömig Friederike, Maikath Daven, Deppe Dominik, Pumberger Matthias, Duda Georg N, Ziegeler Katharina, Damm Philipp

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Аннотация

Biomechanical analyses of the sacroiliac joint (SIJ) are limited. We hypothesize that influence of ligament pre-tension on strain and relative joint movement is morphologically sex-specific and more pronounced than effects of body weight. Finite element models were developed from CTs of a larger cohort (N = 818) for typical male (TMJ) and typical female joint (TFJ) geometries. For different loading scenarios, stresses were higher in TFJ than TMJ for same pre-tension, only considering sex-specific morphology. Loading in antero-posterior direction caused highest stresses and relative movement. Ligament pre-tension was most sensitive with mean sensitivity factor (change output [%]/change input [%]): 71.04/33.64 for translation, 43.09/4.02 for rotation, 2.11/ - 8.97 for stress for TFJ/TMJ respectively. Mean sensitivity factor of ligament stiffness was - 1.14/ - 1.06 for translation, - 0.90/ - 0.89 for rotation and 0.17/0.13 for stress, while mean sensitivity of load intensity was 1.09/1.10 for translation, 0.91/0.88 for rotation and 0.54/0.58 for stress for TFJ/TMJ respectively. Relative motion was more sensitive to parameter variations than stress. The hypothesis was confirmed: influence of ligament pre-tension on stress but especially relative joint movement of SIJ is morphologically sex-specific and larger than body weight effects. As this may play a crucial role in pain development, ligament pre-tension must be verified in situ in the future.

Для цитирования: Heyland Mark, Schmidt Hendrik, Schömig Friederike, Maikath Daven, Deppe Dominik, Pumberger Matthias, Duda Georg N, Ziegeler Katharina, Damm Philipp. Ligament pre-tension determines outcome in sacroiliac joint in silicon modelling.. Medical & biological engineering & computing. 2025. DOI: 10.1007/s11517-025-03396-w.

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