Role of Advanced Multimodality Synthetic MRI and Dynamic Contrast-Enhanced MRI Derived Parameters in the Differentiating Neurocysticercosis and Tuberculomas.

Abstract

<h4>Purpose</h4>Ring-enhancing lesions (RELs) of the brain are frequently encountered but often pose diagnostic challenges. In tropical countries like India, neurocysticercosis (NCC) and tuberculomas are among the most common causes of intracranial RELs. Accurately distinguishing between the two is critical for appropriate treatment. To our knowledge, no prior study has combined synthetic MRI-derived parameters with DCE-MRI metrics to address this specific diagnostic dilemma. Out objective is to assess the diagnostic utility of relaxometry metrics from synthetic MRI, magnetization transfer ratio (MTR), and the volume transfer constant (K-trans) from dynamic contrast-enhanced (DCE) MRI in differentiating NCC from tuberculomas.<h4>Methods</h4>This prospective study included 53 patients with ring-enhancing brain lesions (24 NCC, 29 tuberculomas). All underwent conventional MRI, synthetic MRI, MT imaging, and DCE-MRI. Quantitative parameters (R1, R2, proton density, MTR, and K‑trans) were extracted from the lesion core, wall, and surrounding edema and analyzed using non-parametric statistical tests.<h4>Results</h4>Tuberculomas demonstrated significantly higher pre-contrast R1 and R2 values in the core than NCC. A core R2 cutoff of ≤ 15.90 s⁻¹ yielded 100% sensitivity and specificity. Wall MTR was also higher in tuberculomas (cutoff ≥ 0.22; 86% sensitivity, 88% specificity, positive predictive value (PPV) and negative predicative values (NPV) of 89.3% and 84.0% respectively). K‑trans values in the wall were elevated in tuberculomas, with a cutoff of ≥ 1.91 showing 79.31% sensitivity, 79.17% specificity, 82% PPV and 76% NPV.<h4>Conclusion</h4>Synthetic MRI-derived relaxometry and MTR provide objective, quantitative biomarkers to differentiate NCC from tuberculomas. The pre-contrast core R2 value emerged as the most discriminative parameter, enhancing diagnostic accuracy and supporting informed clinical decision-making.