Predicting Forefoot-Orthosis Interactions in Rheumatoid Arthritis Using Computational Modelling.

Area of Science:

• Biomechanics
• Rheumatology
• Computational modeling

Background:

• Foot orthoses are used to alleviate forefoot pressure and pain in rheumatoid arthritis (RA).
• Previous computational modeling studies on orthoses have typically focused on a single healthy individual.
• Understanding biomechanical variations in RA patients is crucial for effective orthotic design.

Purpose of the Study:

• To determine if simplified forefoot models yield different biomechanical predictions at the orthotic interface.
• To compare predictions between individuals with varying rheumatoid arthritis severity and a healthy control.
• To assess the influence of foot morphology and clinical factors on biomechanical outcomes.

Main Methods:

• Developed simplified forefoot computational models from MRI data of 13 RA participants and 1 healthy control.
• Measured bony morphology and soft tissue thickness to assess foot deformity.
• Compared model predictions (shear strain, plantar pressure, pressure gradient, soft tissue volume) with clinical data (BMI, LFIS-IF).

Main Results:

• Forefoot models showed distinct biomechanical predictions between RA patients and the healthy control, and among RA patients.
• Medial first metatarsal head curvature and Body Mass Index (BMI) showed moderate to strong correlations with model predictions.
• No clear relationships were found between model predictions and clinical indicators like bursitis, erosion, synovial hypertrophy, or LFIS-IF scores.

Conclusions:

• Simplified forefoot models can differentiate biomechanical responses at the orthotic interface across individuals with RA and healthy controls.
• Subject-specific modeling holds potential for developing personalized orthotic devices to enhance skin and soft tissue health.
• The variability in model predictions underscores the necessity of population-based assessments for foot orthoses, rather than single-subject studies.