Diagnostic performance of 3.0 Tesla diffusion tensor imaging in the assessment of brain stem glioma grading.

Purpose: This study aimed to investigate the role of 3 Tesla Dif-fusion tensor imaging (DTI) in the assessment of brainstem glioma (BSG) grading.

Materials and methods: The study comprised 22 patients, including pathology-proven 6 brainstem low-grade gliomas (BS-LGG) and 16 brainstem high-grade gliomas (BS-HGG). Characteristics including age, gender, fractional anisotropy (FA), mean diffusivity (MD) of the tumor, peritumoral region, and the ratio of tumor FA to parenchymal FA, as well as tumor MD to parenchymal MD (rFA and rMD), were compared using Mann-Whitney U test, Shapiro-Wilk test, and Chi-square test. Receiver operating characteristic (ROC) curve analysis was used in the study to determine cut-off values and diagnostic values for grading brainstem gliomas (BSG) using diffusion tensor imaging (DTI).

Results: Our study revealed no significant difference in age and gender between the BS-LGG and BS-HGG groups (p>0.05). Fractional anisotropy (FA) indices on DTI MRI were found to be highly valuable in grading BSG, with an area under the curve (AUC) of 0.958 - 0.979 when using cut-off values of tFA, pFA, rtFA, and rpFA at 0.318, 0.378, 0.424, and 0.517, respectively. Particularly, rtFA demonstrated the hi-ghest diagnostic value with a sensitivity (Se) of 100%, specificity (Sp) of 93.8%, and AUC of 0.079. Conversely, the indices of tumor mean diffusivity (tMD), peritumoral edema region mean diffusivity (pMD), rtMD, and rpMD showed no diagnostic value in grading BSG.

Conclusion: The fractional anisotropy (FA) value on DTI between the tumor region and normal brain parenchyma holds significant value in diagnosing brainstem gliomas (BSG) grading, thereby playing a crucial role in treatment planning and predicting outcomes for patients with brainstem gliomas.