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Juvenile idiopathic arthritis (JIA) is a broad term that describes a clinically heterogeneous group of arthritis which has an onset before age of 16 years. JIA which affects approximately one in 1,000 children represents the leading cause of childhood disability from a musculoskeletal disorder.

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Clinical Concept:

Juvenile idiopathic arthritis (JIA) is a broad term that describes a clinically heterogeneous group of arthritis which has an onset before age of 16 years, lasts more than 6 weeks and is of unknown origin. The cause and pathogenesis of JIA are still poorly understood, but likely they include both genetic and environmental components. Moreover, disease heterogeneity implies that different factors probably contribute to its pathogenesis and causes. Affected joints develop synovial proliferation and infiltration by inflammatory cells which may ultimately lead to destructive lesions of joint structures, disability and high disease‐related costs. Indeed, JIA which affects approximately one in 1,000 children represents the leading cause of childhood disability from a musculoskeletal disorder.

Current classification, which is based on clinical criteria, is still unsatisfactory: considerable heterogeneity in disease course and treatment response exists, both between and within subtypes of JIA. Unfortunately, the present ability to predict the disease course and outcome is limited.

MD-Paedigree Goals:

Within the FP6 Health-e-Child project, ICT tools for diagnosis and scoring of JIA, based on image data of the wrist, have been developed. This framework is the basis for the developments planned for MD-Paedigree.

Comprehensive and accurate computer models derived from patient‐specific data across multiple scales covering body, organs, tissues, and molecular levels are developed. This data is gathered and stored in a standardised manner building upon the Health‐e‐Child software tools developed for wrist analysis in the context of JIA. These tools are extended for the purpose of integrating model information related to a wider range of joints, covering morphology, gait analysis, bio/genetic data.

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