A Predictive Formula for Sagittal Vertical Axis in Japanese Women Using Spinopelvic-Hip Mismatch

Area of Science:

• Spine surgery
• Radiographic analysis
• Biomechanical modeling

Background:

• Sagittal vertical axis (SVA) is a critical measure of spinal alignment.
• Accurate SVA prediction is essential for surgical planning in spinal deformities.
• Existing predictive models may not fully capture complex spinopelvic-hip interactions.

Purpose of the Study:

• To develop a novel and simplified predictive formula for SVA in women.
• To incorporate spinopelvic-hip mismatch into SVA prediction.
• To enhance the accuracy of SVA assessment using standard lateral radiographs.

Main Methods:

• Retrospective analysis of 257 female patients across three cohorts.
• Measurement of radiographic parameters including pelvic incidence (PI), thoracic kyphosis (TK), and pelvic femoral angle (PFA).
• Development of a predictive formula using Lasso and multiple linear regression, validated externally.

Main Results:

• Pelvic incidence (PI), thoracic kyphosis (TK), and spinopelvic-hip mismatch [PFA-(PI-LL)] were significant predictors of SVA.
• The derived formula demonstrated high predictive accuracy (R²=0.858 training, R²=0.851 validation).
• The formula is: SVA=627.588+0.8612×PI+2.637×TK (T9-12)-3.616×{PFA-(PI-LL)}.

Conclusions:

• A novel, practical predictive formula for SVA in women has been developed.
• The formula integrates spinopelvic-hip mismatch, reflecting compensatory hip mechanisms.
• This tool may improve SVA prediction accuracy and aid individualized surgical planning.