Efficiency of High and Standard Value Diffusion-Weighted Magnetic Resonance Imaging in Grading of Gliomas

Background: Glioma is the most common fatal malignant tumor of the CNS. Early detection of glioma grades based on diffusion-weighted imaging (DWI) properties is considered one of the most recent noninvasive promising tools in the assessment of glioma grade and could be helpful in monitoring patient prognosis and response to therapy.

Aim: This study aimed to investigate the accuracy of DWI at both standard and high values ( = 1000 s/mm and  = 3000 s/mm) to distinguish high-grade glioma (HGG) from low-grade glioma (LGG) in clinical practice based on histopathological results.

Materials And Methods: Twenty-three patients with glioma had DWI at l.5 T MR using two different values ( = 1000 s/mm and  = 3000 s/mm) at Al-Shifa Medical Complex after obtaining ethical and administrative approvals, and data were collected from March 2019 to March 2020. Minimum, maximum, and mean of apparent diffusion coefficient (ADC) values were measured through drawing region of interest (ROI) on a solid part at ADC maps. Data were analyzed by using the MedCalc analysis program, version 19.0.4, receiver operating characteristic (ROC) curve analysis was done, and optimal cutoff values for grading gliomas were determined. Sensitivity and specificity were also calculated.

Results: The obtained results showed the ADC, ADC, ADC, and ADC were performed to differentiate between LGG and HGG at both standard and high values. Moreover, ADC values were inversely proportional to glioma grade, and these differences are more obvious at high value. Minimum ADC values using standard value were 1.13 ± 0.17 × 10 mm/s, 0.89 ± 0.85 × 10 mm/s, and 0.82 ± 0.17 × 10 mm/s for grades II, III, and IV, respectively. Concerning high value, ADC values were 0.76 ± 0.07 × 10 mm/s, 0.61 ± 0.01 × 10 mm/s, and 0.48 ± 0.07 × 10 mm/s for grades II, III, and IV, respectively. ADC values were inversely correlated with results of glioma grades, and the correlation was stronger at ADC ( = -0.722, ≤ 0.001). The ADC achieved the highest diagnostic accuracy with an area under the curve (AUC) of 0.618, 100% sensitivity, 85.7% specificity, and 85.7% accuracy for glioma grading at a cutoff point of ≤0.618 × 10 mm/s. The high value showed stronger agreement with histopathology compared with standard value results ( = 0.89 and 0.79), respectively.

Conclusion: The ADC values decrease with an increase in tumor cellularity. Meanwhile, high value provides better tissue contrast by reflecting more tissue diffusivity. Therefore, ADC-derived parameters at high value are more useful in the grading of glioma than those obtained at standard value. They might be a better surrogate imaging sequence in the preoperative evaluation of gliomas.