Prediction of Sustentaculum Tali Sustentacular Screw Length based on Linear Regression Model

Area of Science:

• Orthopedic Surgery
• Medical Imaging
• Anatomy

Background:

• Calcaneal fractures pose surgical challenges due to complex anatomy and imprecise screw placement.
• Traditional methods risk complications like joint penetration and nerve damage.

Purpose of the Study:

• To develop accurate models for predicting screw length in calcaneus fractures.
• To improve surgical precision and reduce complications in treating posterior facet (PF) and articulatio calcaneocuboidea (AC) fractures.

Main Methods:

• Analysis of 66 adult calcaneus specimens using micro-CT scanning and anatomical measurements.
• Division of the calcaneus into anterior, middle, posterior, and ST regions.
• Application of linear regression to correlate anatomical parameters with screw lengths for AC and PF fixation.

Main Results:

• Developed linear regression models: G1 = -1.96 + 0.71F1 + 0.48F8 + 0.39F9 (AC) and G2 = 3.95 + 0.28F1 + 0.59F8 + 0.31F9 (PF).
• Validated predicted screw lengths via Micro-CT, confirming accurate insertion without medial cortex perforation.
• Models based on both CT and anatomical data showed high predictive accuracy.

Conclusions:

• Linear regression models accurately predict AC/PF screw lengths, enhancing surgical precision.
• These models can improve outcomes for calcaneal fracture fixation.
• Future work includes data expansion and exploring machine learning for improved prediction.