Prediction of proximal junctional kyphosis and failure after corrective surgery for adult spinal deformity: an MRI-based model combining bone and paraspinal muscle quality metrics

Abstract

BACKGROUNDProximal junctional kyphosis (PJK) and proximal junctional failure (PJF) are common complications observed after adult spinal deformity (ASD) surgery and major cause for unplanned reoperations. In addition to spinal alignment, osteoporosis and paraspinal muscle (PSM) degeneration are reportedly indispensable factors that account for PJK/PJF. PURPOSETo investigate the utility of the preoperative risk assessment model using MRI-based skeletomuscular metrics in predicting PJK and/or PJF(PJK/PJF) after ASD correction. STUDY DESIGNRetrospective case-control study. PATIENT SAMPLEConsecutive series of 149 patients at a single academic institution. OUTCOME MEASURESMRI-based measurements of vertebral bone quality at upper instrumented vertebra (VBQ-U) score and fat infiltration rate (FI%) of paraspinal muscle (PSM). METHODSWe performed a retrospective analysis of patients with ASD who underwent ≥5-segment fusion. The vertebral bone quality (VBQ) scoring system was used to assess the bone quality. The PSM quality including FI% and cross-sectional area (CSA) was evaluated. Multivariate logistic regression was performed to determine potential risk factors of PJK/PJF. RESULTSOf 149 patients who underwent ASD surgery, PJK/PJF was found in 45(30.2%). Mean VBQ-U scores were 3.45±0.64 and 3.00±0.56 for patients with and without PJK/PJF (p<.001). Mean FI% of PSM(L3/L4) was 27.9±12.8 and 20.7±13.3 for patients with and without PJK/PJF (p<.001). On multivariate analysis, the VBQ-U score and FI% of PSM were significant independent predictors of PJK/PJF. The AUC for the novel risk assessment model is 0.806, with a predictive accuracy of 86.7%. CONCLUSIONIn patients undergoing ASD correction, paraspinal muscle and vertebral bone quality significantly outweigh radiographic alignment parameters in predicting PJK/PJF. The MRI-based risk assessment model offers a valuable tool for early assessing individualized risk for PJK/PJF.