A nomogram predicting postoperative recurrence risk in SF1/TPIT nonfunctioning pituitary neuroendocrine tumors: integration of tumor heterogeneity quantification on T2-weighted imaging.

Abstract

Nonfunctioning pituitary neuroendocrine tumors (NF-PitNETs) can recur despite gross-total resection (GTR), and the accurate prediction of tumor recurrence remains a major clinical challenge. In this study, authors aimed to evaluate the predictive value of the T2-weighted signal coefficient of variation (T2-CV) and develop an integrated prognostic nomogram for recurrence-free survival (RFS) in NF-PitNET. Tumor heterogeneity was assessed using T2-weighted MRI. Clinical, radiological, and pathological variables were retrospectively collected on patients with a PitNET diagnosis between 2011 and 2024. Kaplan-Meier analysis was used for survival assessment of each parameter. A multivariate Cox proportional hazards model was employed to identify independent predictors of RFS, and a prognostic nomogram was subsequently developed based on these significant factors. The total score derived from the nomogram was used to stratify patients into distinct risk groups. This study included 596 patients with NF-PitNET who underwent GTR. Multivariate analysis identified four independent factors associated with shorter RFS: age < 41 years, Knosp grade 3-4, T2-CV ≥ 0.442, and Ki-67 index ≥ 3% (all p < 0.001). A nomogram incorporating these variables was developed and demonstrated superior predictive accuracy (area under the curve [AUC] = 0.801) compared to any single predictor alone (p < 0.001). The nomogram achieved a concordance index of 0.82, demonstrating good calibration and strong clinical applicability. Its time-dependent receiver operating characteristic analysis further demonstrated AUC values of 0.85, 0.89, 0.84, 0.86, and 0.82 at 12, 24, 36, 48, and 60 months, respectively, indicating particular strength in short-term recurrence prediction. Furthermore, applying a cutoff score of 72.41, the nomogram effectively stratified patients into high- and low-risk groups, which were differentiated by significantly different median RFS (81.17 vs 99.93 months, respectively, HR 7.364, 95% CI 4.375-12.393, p < 0.001). T2-CV, a novel quantitative MRI parameter, serves as an independent predictor of RFS in patients following GTR of NF-PitNET. A nomogram integrating T2-CV with other key prognostic factors demonstrated high accuracy in identifying high-risk individuals.