Trial reportNeurosurgical review2026
Differentiation of high-grade glioma and primary central nervous system lymphoma based on imaging heterogeneity scoring system.
Trial report in Neurosurgical review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
To evaluate the diagnostic value of a magnetic resonance imaging (MRI)-based imaging heterogeneity scoring system for differentiating high-grade glioma (HGG) from primary central nervous system lymphoma (PCNSL). This multicenter retrospective study analyzed clinical and preoperative MRI data from 314 pathologically confirmed cases (HGG = 167, PCNSL = 147), comprising 211 patients with single lesions (HGG = 130, PCNSL = 81) and 103 with multifocal lesions (HGG = 37, PCNSL = 66). Patients were randomly assigned to training (single-lesion: n = 147; multifocal: n = 72) and validation (single-lesion: n = 64; multifocal: n = 31) sets in a 7:3 ratio. Distinctive imaging features were used to construct separate logistic regression (LR) models for single-lesion and multifocal-lesion cases, with corresponding scoring systems developed. A baseline model incorporating conventional predictors was developed for comparison. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves (area under the curve [AUC], 95% confidence interval [CI]), Hosmer-Lemeshow tests (goodness-of-fit), calibration curves, and decision curve analysis (DCA). A sensitivity analysis was performed on excluded steroid-treated patients. For single-lesion cases, the training and validation AUCs were 0.940 (95%CI: 0.897-0.983) and 0.908 (0.836-0.981), respectively. Multifocal models achieved training and validation AUCs of 0.960 (0.921-0.999) and 0.927 (0.805-1.000). The heterogeneity scoring system demonstrated significant incremental value over the baseline model (ΔAUC: +0.160-0.290). Hosmer-Lemeshow tests indicated excellent model fit (single-lesion training: χ²= 2.489, P = 0.778; validation: χ² = 6.193, P= 0.185; multifocal training: χ² = 1.760, P = 0.881; validation: χ² = 9.241, P = 0.055). DCA demonstrated substantial net clinical benefit across threshold probabilities. The scoring systems established diagnostic thresholds as follows: ≥ 19 points for HGG (single-lesion) and > 19 points (multifocal), with lower scores indicating PCNSL. Center-stratified validation and repeated cross-validation confirmed strong generalizability across institutions (AUC: 0.934-0.941). The system maintained robust performance in the sensitivity analysis of steroid-treated patients. This MRI heterogeneity-based scoring system provides robust diagnostic accuracy for distinguishing HGG from PCNSL, serving as an objective clinical decision-support tool.
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