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Linking Joint Impairment and Gait Biomechanics in Patients with Juvenile Idiopathic Arthritis

 
: Montefiori, Erica; Modenese, Luca; Marco, Roberto di; Magni-Manzoni, Silvia; Malattia, Clara; Petrarca, Maurizio; Ronchetti, Anna; Tanturri De Horatio, Laura; Dijkhuizen, Pieter van; Wang, Anqi; Wesarg, Stefan; Viceconti, Marco; Mazzà, Claudia

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Volltext ()

Annals of biomedical engineering (2019), Online First, 13 S.
ISSN: 0191-5649
ISSN: 0090-6964
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer IGD ()
Guiding Theme: Individual Health; Research Area: Computer graphics (CG); Research Area: Computer vision (CV); Research Area: (Interactive) simulation (SIM); Research Area: Modeling (MOD); magnetic resonance imaging (MRI); medical modeling; kinematic simulation

Abstract
Juvenile Idiopathic Arthritis (JIA) is a paediatric musculoskeletal disease of unknown aetiology, leading to walking alterations when the lower-limb joints are involved. Diagnosis of JIA is mostly clinical. Imaging can quantify impairments associated to inflammation and joint damage. However, treatment planning could be better supported using dynamic information, such as joint contact forces (JCFs). To this purpose, we used a musculoskeletal model to predict JCFs and investigate how JCFs varied as a result of joint impairment in eighteen children with JIA. Gait analysis data and magnetic resonance images (MRI) were used to develop patient-specific lower-limb musculoskeletal models, which were evaluated for operator-dependent variability (< 3.6°, 0.05 N kg21 and 0.5 BW for joint angles, moments, and JCFs, respectively). Gait alterations and JCF patterns showed high between-subjects variability reflecting the pathology heterogeneity in the cohort. Higher joint impairment, assessed with MRI-based evaluation, was weakly associated to overall joint overloading. A stronger correlation was observed between impairment of one limb and overload of the contralateral limb, suggesting risky compensatory strategies being adopted, especially at the knee level. This suggests that knee overloading during gait might be a good predictor of disease progression and gait biomechanics should be used to inform treatment planning.

: http://publica.fraunhofer.de/dokumente/N-548916.html