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Initial Modelling Results in Juvenile Idiopathic Arthritis

New biomechanical biomarkers to predict JIA progression

The JIA team has successfully developed the entire clinical study plan, including ad hoc protocols for imaging and gait analysis. These protocols have been applied to a patient zero in each centre, sent to the data repository, and analysed by the technical partners to confirm the data are of the quality necessary for patient-specific modelling. The groups in Sheffield and Fraunhofer have then started the processing of the data from the next four patients and transformed them into four patient-specific dynamic musculoskeletal models of the lower limb and foot complex by merging gait analysis and MRI data. The open source NMSBuilder and Opensimm softwares have been used to this purpose. The models have been constructed based on the Month 0 MRI ankle data, as well as the Month 6 MRI lower limb data. Initial model results have yielded  data on ankle joint loading as well as muscle activation patterns. These results will be coupled with a finite element model of the tibio-tarsal joint, which we are currently developing. Both models will provide a number of biomechanical biomarkers that will be used to quantify and predict the mechnaisms that underly the JIA progression.


Author: Claudia Mazzà, Phd, Department of Mechanical Engineering, University of Sheffield

An Automatic Method for Segmentation

A personalised model of treatment from medical imaging

Musculoskeletal disorders can cause severe long-term pain and physical disabilities. For their diagnosis, surgical planning, post-operative assessment and overall decision support, the patient-specific modelling of the musculoskeletal system is an important challenge that can greatly contribute to or hinder the final result. MD-Paedigree aims to explore the use of complex multiscale biomechanical models of the musculoskeletal system for two of its selected disease areas (Juvenile idiopathic arthritits and Neurological and neuromuscular diseases), in order to deliver personalised models of treatment for each patient using as much as possible the information available from medical imaging and gait analysis.


To achieve the above mentioned final goal, as a first important step a software for automatic segmentation of limb structures from medical images has been developed. This software has been developed to work specifically on MRI images, which allow the extraction of the geometries of bones and muscles due to the good contrast shown among soft tissues, and are thus considered a gold-standard modality for the musculoskeletal geometry. The results are indeed encouraging: in fact, the quantitative evaluation results of the segmentation from MRI performed well in all MD-Paedigree datasets so far: the implemented method was successful at automatically extracting an exhaustive set of individual structures as well as important landmarks.

Author: Maria Jimenez Costa, PhD in Computer Science, Siemens.

This article was originally published in Md-Paedigree Newsletter-Issue 3

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