Vandekerckhove Ines, D'Hondt Lars, Gupta Dhruv, Van Den Bosch Bram, Van den Hauwe Marleen, Goemans Nathalie, De Waele Liesbeth, Van Campenhout Anja, Desloovere Kaat, De Groote Friedl
Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.
Department of Movement Sciences, KU Leuven, Leuven, Belgium.
J Neuroeng Rehabil. 2025 May 4;22(1):103. doi: 10.1186/s12984-025-01631-x.
Muscle weakness and contractures cause gait deficits in children with Duchenne muscular dystrophy (DMD) but their relative contributions are poorly understood and hence it is unclear whether contractures should be treated. Therefore, we aimed to differentiate the effect of muscle weakness in isolation from weakness and contractures combined on the gait patterns.
We used computer simulations that generate gait patterns based on a musculoskeletal model (without relying on experimental data) to establish the relationship between muscle impairments and gait deviations. We previously collected a longitudinal database of 137 repeated measurements in 30 boys with DMD and found that the data measured through 3D gait analysis could be clustered in three gait patterns. We estimated weakness based on data from fixed dynamometry, and contractures based on goniometry and clinical measures. Foot deformities were modeled by reducing the height of all foot segments and decreasing the strength of the intrinsic foot muscles. We created musculoskeletal models that either represented (1) the mean weakness; (2) the mean weakness and contractures; or (3) the mean weakness, contractures and foot deformities, in each gait pattern.
Simulations based on models with both weakness and contractures captured most (but not all) experimentally observed gait deviations, demonstrating the validity of our approach. While muscle weakness was primarily responsible for gait deviations, muscle contractures and foot deformities further contributed to gait deviations. Interestingly, the simulations predict that the combination of increasing weakness and contractures rather than increasing weakness alone causes loss of ambulation for the most affected gait pattern.
Predictive simulations have the potential to elucidate causal relationships between muscle impairments and gait deviations in boys with DMD. In the future, they could be used to design targeted interventions (e.g. stretching, assistive devices) to prolong ambulation.
肌肉无力和挛缩会导致杜氏肌营养不良症(DMD)患儿出现步态缺陷,但它们各自的相对作用尚不清楚,因此也不清楚是否应该治疗挛缩。所以,我们旨在区分单纯肌肉无力与肌肉无力合并挛缩对步态模式的影响。
我们使用基于肌肉骨骼模型生成步态模式的计算机模拟(不依赖实验数据)来建立肌肉损伤与步态偏差之间的关系。我们之前收集了30名DMD男孩137次重复测量的纵向数据库,发现通过三维步态分析测量的数据可聚类为三种步态模式。我们根据固定测力法的数据估计肌肉无力情况,根据角度测量法和临床测量估计挛缩情况。通过降低所有足部节段的高度并减弱足部固有肌肉的力量来模拟足部畸形。我们创建了分别代表(1)平均肌肉无力;(2)平均肌肉无力和挛缩;或(3)平均肌肉无力、挛缩和足部畸形的肌肉骨骼模型,每种模型对应一种步态模式。
基于同时存在肌肉无力和挛缩模型的模拟捕捉到了大部分(但不是全部)实验观察到的步态偏差,证明了我们方法的有效性。虽然肌肉无力是步态偏差的主要原因,但肌肉挛缩和足部畸形进一步加剧了步态偏差。有趣的是,模拟预测,对于受影响最严重的步态模式,肌肉无力和挛缩同时增加而非单纯肌肉无力增加会导致行走能力丧失。
预测性模拟有潜力阐明DMD男孩肌肉损伤与步态偏差之间的因果关系。未来,它们可用于设计有针对性的干预措施(如拉伸、辅助装置)以延长行走能力。