Understanding load distribution in high tibial osteotomies: An inverse Discrete Element Analysis approach

Area of Science:

• Orthopedic surgery
• Biomechanics
• Medical imaging analysis

Background:

• Knee osteotomies have a high rate of suboptimal outcomes, necessitating advancements in preoperative planning.
• Current clinical metrics may not fully capture the complex biomechanical changes after knee osteotomy.

Purpose of the Study:

• To develop and validate an inverse Discrete Element Analysis (iDEA) approach for patient-specific knee pressure pattern calculation.
• To compare iDEA-derived pressure patterns with traditional clinical metrics (angular measurements, Joint Space Width) pre- and postoperatively.
• To assess the correlation between changes in joint mechanics and stress distribution after knee osteotomy.

Main Methods:

• Personalized knee geometries were created from Weight-Bearing Computed Tomography (WBCT) scans using Statistical Shape Modeling.
• iDEA was employed to compute preoperative, postoperative, and control pressure distributions.
• Traditional angular measurements and Joint Space Width (JSW) were calculated; statistical analyses included ANOVA, Kruskal-Wallis, and Spearman rank tests.

Main Results:

• Preoperative angular measurements and JSW ratios differed significantly between patients and controls.
• Postoperatively, most angular differences normalized, but iDEA revealed significantly higher peak stress ratios preoperatively.
• Two patients showed postoperative worsening in JSW and pressure patterns despite improved angular alignment; JSW increases correlated with mean stress decreases.

Conclusions:

• The iDEA approach effectively quantifies intra-articular pressure, demonstrating a general normalization post-knee osteotomy.
• iDEA identified postoperative deteriorations missed by traditional metrics, highlighting its added value in surgical assessment.
• This framework supports the effectiveness of knee osteotomy while offering a more comprehensive evaluation of surgical outcomes.