Value of diffusion tensor imaging in differentiating high-grade from low-grade gliomas

Area of Science:

• Neuroimaging
• Radiology
• Oncology

Background:

• Gliomas are primary brain tumors with varying grades.
• Differentiating high-grade glioma (HGG) from low-grade glioma (LGG) pre-surgically is crucial for treatment planning.
• Conventional MRI has limitations in distinguishing these tumor grades.

Purpose of the Study:

• To evaluate the efficacy of diffusion tensor imaging (DTI) in differentiating HGG from LGG.
• To identify specific DTI parameters that best distinguish between glioma grades.

Main Methods:

• Conventional MRI and DTI were performed on 43 patients with cerebral gliomas prior to surgery.
• Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were measured in various regions of interest (ROIs).
• Receiver operating characteristic (ROC) curves were used to assess the diagnostic accuracy of imaging parameters.

Main Results:

• No significant difference in mean FA values was observed between LGG and HGG groups.
• ADC values (including minimal ADC) in the solid tumoral region and peritumoral edema, along with ADC ratios of the solid tumoral region, were statistically significant in differentiating HGG from LGG (p < 0.05).
• The ratio of ADC in the solid tumoral region to the normal corpus callosum demonstrated the highest predictive accuracy (AUC = 0.74).

Conclusions:

• Apparent diffusion coefficient (ADC) values, minimal ADC values, and ADC ratios within the solid tumoral region are valuable tools for differentiating HGG from LGG.
• DTI parameters, particularly ADC-based metrics, offer improved diagnostic capability for glioma grading.