Morphological characteristics of apical intervertebral discs as predictors of curve progression in adolescents with idiopathic scoliosis

BACKGROUND CONTEXT: Quantitative disc analysis offers an objective approach for assessing intervertebral disc morphology in patients with adolescent idiopathic scoliosis (AIS). Such analyses have potential to enhance predictions regarding disease progression and guide clinical decisions on surgical intervention timing. PURPOSE: To characterize morphological differences in apical intervertebral discs between AIS patients requiring surgery within five years and those managed nonoperatively, and to develop a predictive model for surgical intervention. STUDY DESIGN/SETTING: This retrospective case-control study was conducted at a single tertiary referral center specializing in spinal deformity surgery. PATIENT SAMPLE: The study analyzed data from 99 patients diagnosed with AIS, comprising 50 who underwent surgical correction within 5 years and 49 managed conservatively, all of whom had baseline MRI scans performed as part of standard care. OUTCOME MEASURES: Key outcome measures included nucleus pulposus (NP) and disc signal intensity, NP area, NP location, transition zone slopes, and disc asymmetry indices derived from MRI analyses. The primary endpoint was the requirement for surgical intervention within 5 years of initial MRI. METHODS: MRI scans were retrospectively analyzed to quantify disc morphological characteristics at the apex of the spinal curve. Patients requiring surgical correction within 5 years were compared to nonsurgical controls. Predictors of surgical intervention were identified using backward input binary logistic regression to construct an optimized predictive model. RESULTS: Patients requiring surgery were younger (p=.004), exhibited larger Cobb angles (p<.001), and had apical discs more frequently located in the lower thoracic region (p=.024). Surgical patients demonstrated higher mean NP signal intensity (p=.011), steeper anterior (p=.049) and concave (p=.006) transition zone slopes, and greater overall coronal transition zone symmetry (p=.022). The resulting statistical model predicted surgical intervention with 81.8% accuracy (p<.001, AUC=0.894), outperforming prediction based on Cobb angle alone. Predictors in the final model included age, main Cobb angle, and concave transition zone slope. CONCLUSIONS: Quantitative disc analysis reveals distinct morphological features at the apical disc that are predictive of surgical intervention in AIS. A predictive model incorporating these features outperforms traditional metrics such as Cobb angle alone, underscoring the added value of advanced disc morphology evaluation. CLINICAL SIGNIFICANCE: Incorporating quantitative disc metrics into early AIS evaluation may enhance risk stratification, inform monitoring intervals, and support timely surgical decision-making—facilitating more personalized patient care.