Diagnostic value of diffusion-weighted imaging, apparent diffusion coefficient and dynamic contrast enhanced values in 3T head MRI on glioma grading

BACKGROUND: Gliomas are the most common primary intracranial tumors, graded I-IV based on histopathological and imaging features. Diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are advanced MRI techniques aiding glioma grading. ADC reflects tissue microstructure, while DCE-MRI evaluates perfusion and angiogenesis. These methods correlate with glioma grades, distinguishing low-and high-grade tumors. This study investigates DWI, ADC, and DCE-MRI parameters in glioma grading using 3T MRI in Makassar. METHODS: This cross-sectional study analyzed retrospective MRI data from Makassar (2020-2024), including patients with glioma confirmed via surgery and pathology. Statistical tests assessed DWI, ADC, and DCE correlations with glioma grading. Sensitivity, specificity, and cutoff points were determined using receiver operating characteristic (ROC) curves; P<0.05 indicated significance. RESULTS: This study analyzed 34 glioma patients, revealing key diagnostic findings. Low-grade gliomas predominantly occurred in younger patients, with astrocytoma as the most common subtype, while glioblastoma prevailed in high-grade cases. Diffusion-weighted imaging (DWI) showed 69% sensitivity and 100% specificity. Apparent diffusion coefficient (ADC) values significantly correlated with glioma grades, averaging 0.77 mm²/s for high-grade and 1.54 mm²/s for low-grade gliomas (P<0.001). Perfusion parameters like transfer constant (Ktrans) and AUC-TC also demonstrated diagnostic value, supporting ADC, time-signal intensity (TIC), and DCE-MRI as reliable tools for glioma grading with high sensitivity and specificity. CONCLUSIONS: DWI-MRI and ADC values effectively differentiate glioma grades, with Ktrans, reflux constant (Kep), TIC curves, maximum rise slope (MAXSlope), and AUC-TC providing additional predictive value for histopathological distinction.