A biomechanical digital twin of Legg–Calvé–Perthes disease deformity
By
Luke G. Johnson
David R. Wilson
Kishore Mulpuri
December 1, 2025
Clinical Scorecard: A Digital Biomechanical Model of Deformities Associated with Legg–Calvé–Perthes Disease
At a Glance
Category Detail
Condition Legg–Calvé–Perthes disease (LCPD), a pediatric hip condition causing residual deformities Key Mechanisms Femoral head asphericity, flattening, joint incongruency, acetabular dysplasia leading to mechanical stress and osteoarthritis Target Population Pediatric patients with LCPD and adults with residual deformities Care Setting Orthopedic surgical and rehabilitation settings, including preoperative planning and postoperative management
Key Highlights
Residual LCPD deformity increases pain, reduces quality of life, and leads to high osteoarthritis incidence in adulthood. Surgical intervention aims to reduce bony impingement and mechanical stress to delay total hip arthroplasty. Patient-specific dynamic biomechanical models ('digital twins') can predict chondrolabral stress and improve treatment planning. Guideline-Based Recommendations
Diagnosis
Use intraoperative range-of-motion inspection to diagnose functional pathology due to difficulty identifying impingement location from static imaging. Management
Surgical intervention for severe cases to reduce pain and improve function. Consider gait and activity adjustments early after healing to delay symptom onset and surgery. Monitoring & Follow-up
Monitor preoperative pain scores and radiographic osteoarthritis as predictors of surgical failure. Use patient-specific biomechanical modeling to assess chondrolabral stress during motion. Risks
Surgical failure rate reported at 16% in follow-up studies. High mechanical stress from impingement contributes to osteoarthritis development. Patient & Prescribing Data
Patients with severe unilateral LCPD deformity, including young adults post-healing
Digital twin models incorporating patient-specific anatomy and dynamic loading can inform surgical planning and preventative strategies.
Clinical Best Practices
Develop patient-specific dynamic biomechanical models to predict stress distributions during joint motion. Incorporate MRI-based segmentation and finite element analysis for accurate representation of cartilage and labrum. Account for physiologic variations in material properties and measurement errors in joint angles to improve model reliability. References
