Role of Diffusion Weighted Magnetic Resonance Imaging in Predicting Grade of Intracranial Gliomas in Adult Age Group

Abstract

Background: Gliomas, the most prevalent primary brain tumors, are classified by the World Health Organization (WHO) into low-grade
(grades 1 and 2) and high-grade (grades 3 and 4) categories. Low-grade gliomas typically affect younger individuals and have a more favorable prognosis, while high-grade gliomas are more common in adults and are associated with poorer outcomes. Accurate early grading of gliomas is crucial for determining appropriate management strategies and prognoses. Advanced magnetic resonance imaging (MRI) techniques, particularly diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping, offer noninvasive alternatives that can detect pathological changes in gliomas by assessing alterations in cellularity and extracellular spaces.

Objective: The aim of this study is to evaluate the role of Diffusion Weighted Imaging in predicting grade of gliomas in adult age group.

Material & Method: This cross-sectional study, conducted at Dhaka Medical College & Hospital from March 2022 to February 2024, evaluated the efficacy of DWI in predicting glioma grades. The study included patients diagnosed with gliomas who underwent imaging investigations.

Result: The study analyzed 50 glioma patients, comprising 32 males (64%) and 18 females (36%), with a mean age of 55.6 ± 13.05 years. Data analysis revealed that high-grade gliomas exhibited significantly lower ADC values compared to low-grade gliomas (p< 0.001). Receiver operating characteristic (ROC) curve analysis demonstrated high accuracy in glioma grading based on ADC values, with an area under the curve (AUC) of 0.945 and an optimal cut-off value of 816.5. MRI findings showed excellent sensitivity (92.31%) and specificity (81.82%) in detecting high-grade gliomas.

Conclusion: Diffusion-weighted MRI, combined with ADC mapping, serves as a valuable noninvasive tool for preoperative glioma grading, aiding in clinical decision-making and potentially reducing the need for invasive procedures.