Abstract
Laxity tests are performed to diagnose ligament injuries or to estimate subject-specific ligament properties. While the current laxity tests are easy to perform, they are not optimized to isolate specific ligament bundles. Therefore, we developed a methodology to identify optimal laxity tests to either stretch specific ligaments relatively more than other ligaments or maximally stretch a specific ligament within the boundaries of maximally applied loads to the knee. The method was applied to a subject-specific knee model and the identified optimal laxity tests compared against standard tests. For the laxity tests isolating the stretch in a specific ligament, we found laxity tests that performed better for all ligament bundles except a few where neither the optimal nor standard laxity tests could isolate the ligament. We found force ratios, between the force change in the ligament of interest compared to the maximal force change in the other ligaments, of over 2.0 for six ligament bundles with the optimized load cases whereas the standard laxity tests only resulted in one bundle over 2.0. For the tests to maximally load the ligament of interest, increased force changes were seen for all optimal load cases and force changes of over 200 N were seen for six ligament bundles whereas only one bundle had a force change over 200N with the standard laxity tests. Our results show that there is a potential to develop better laxity tests than those performed today and emerging laxity test equipment enable implementation of such tests.
Originalsprog | Engelsk |
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Artikelnummer | 103871 |
Tidsskrift | Medical Engineering and Physics |
Vol/bind | 107 |
ISSN | 1350-4533 |
DOI | |
Status | Udgivet - sep. 2022 |
Bibliografisk note
Funding Information:This work was supported by the Independent Research Fund Denmark under the Sapere Aude program (grant number DFF‐4184‐00018 ), research project 1 program (grant number 0136-00090B ) and research project 2 program (grant number 1032-00036B ), the Innovation Fund Denmark under the InnoExplorer program (grant number 0158-00002 ) and Life Science Innovation North Denmark (grant number: RFN-17-0027 ).
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