A novel method for prediction of postoperative global sagittal alignment based on full-body musculoskeletal modeling and posture optimization.

Abstract

Associations between spinal sagittal balance and pain and disability are well documented. Reciprocal changes after spinal surgery might be critical for the outcomes, but assessing their extent remains a challenge. This paper proposes a method for predicting full-body sagittal alignment including reciprocal changes in response to spinal fusion, based on musculoskeletal modeling and inverse-inverse dynamics approach. An established body model (AnyBody) was used, with fused segments modeled as rigid. Posture was optimized based on muscle expenditure minimization, following the concept of the cone of economy. The data of adult spinal fusion patients were obtained retrospectively from an ongoing clinical study. Patient spino-pelvic alignment, body weight and height, age- and pathology-related muscle deterioration, and underwent treatment details were represented in the model. Predicted postural changes were compared to follow-up radiographs to evaluate method validity. Twenty-one cases were analyzed in this preliminary study (age range = 48-74; number of fused segments 1-14). The model predictions correlated well with the radiographic measures at follow-up: TPA, r = 0.83; ΔPILL, r = 0.90; LL, r = 0.90; TK, r = 0.77. The model demonstrated high accuracy in predicting sagittal imbalance (positive predictive value = 1.00, negative predictive value = 0.75). The presented method for patient- and treatment-specific postoperative posture prediction can be used to guide preoperative planning of spinal fusion, but more extensive validation is needed.