1H-MR Spectroscopy as a Decision-Support Tool in the Differential Diagnosis of Intracranial Lesions: A Real-World Bicentric Retrospective Cohort

Abstract

Purpose: To evaluate whether proton MR spectroscopy (1H-MRS) improves the differentiation of tumoral from non-tumoral intracranial lesions beyond conventional MRI, and to quantify its effect on diagnostic confidence, in a consecutive real-world bicentric cohort of diagnostically ambiguous lesions. Methods: This retrospective, bicentric observational study screened 122 consecutive patients who underwent brain MRI with 1H-MRS at two imaging centers, of whom 99 were eligible for final analysis after excluding 23 patients due to insufficient follow-up (<12 months) or incomplete reference standard. The reference standard was histopathological confirmation in 43 cases (43.4%) and structured clinico-radiological follow-up of at least 12 months in 56 cases (56.6%). The reporting radiologist’s binary diagnostic impression and confidence score were recorded before and after 1H-MRS. Conventional MRI alone was compared to MRI plus 1H-MRS using the exact McNemar test; Cho/NAA discrimination was assessed by ROC analysis with bootstrap confidence intervals, and confidence change by the Wilcoxon signed-rank test. Secondary analyses comprised an intention-to-diagnose analysis of all 99 examinations, counting non-diagnostic spectra as test failures, and an evaluable-case sensitivity analysis restricted to histopathologically confirmed patients with interpretable spectra. Results: Of 99 examinations, 89 (89.9%) yielded interpretable spectra. In the primary analysis, qualitative MRS interpretation demonstrated sensitivity of 76.0% (95% CI: 61.8–86.9), specificity of 94.9% (95% CI: 82.7–99.4), and accuracy of 84.3% (CI: 75.0–91.1), compared with 54.0%, 89.7% and 69.7% (59.0–79.0) for conventional MRI alone (exact McNemar p = 0.024). ROC analysis of the Cho/NAA ratio (n = 89) yielded an AUC of 0.858 (0.774–0.931); the exploratory, cohort-specific Youden-optimal cut-off was 1.41 (sensitivity 78.0%, specificity 87.2%). In the intention-to-diagnose analysis including all 99 examinations, accuracy was 78.8% (69.4–86.4). Diagnostic confidence increased significantly after 1H-MRS (median 1 to 2; Wilcoxon p < 0.001; effect size r = 0.81), with moderate or major added value in 71 of 99 examinations (71.7%). Conclusions: In a diagnostically heterogeneous real-world cohort, 1H-MRS significantly improved the accuracy achievable with conventional MRI alone and substantially increased reported diagnostic confidence, with high specificity but only moderate sensitivity. A zone-based Cho/NAA interpretative framework better reflects biological overlap than rigid binary thresholds. As this study assessed diagnostic accuracy and reported confidence rather than therapeutic decisions or patient outcomes, 1H-MRS should be regarded as an adjunctive decision-support modality rather than a standalone classifier in routine neuro-oncologic workflows.