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OBJECTIVE: In motor eloquent glioma surgery, the value of intraoperative diffusion tensor (iDT) imaging was not established to preserve motor function. This study aimed to investigate a relationship between postoperative motor function and iDT imaging parameters, including fractional anisotropy (FA), mean diffusivity (MD), and shortest distance (SD) from resected tumor margin to the corticospinal tract (CST) of gliomas in motor eloquent areas. METHODS: This retrospective study enrolled 20 patients with newly diagnosed supratentorial glioma who underwent surgery and intraoperative magnetic resonance imaging at our hospital. Patients were divided into two groups (i.e., worsening and non-worsening groups) based on their manual muscle test scores before and three months after surgery. We obtained the mean FA and MD values bilaterally, along with identification of the CST and determined the ratios (the affected side / the contralateral side). The SD was measured between the CST and the resected margin of the tumor. We evaluated the quantitative analysis of these parameters related to motor functional outcomes. Moreover the correlation was measured between these parameters and the maximum reduction rate of cortical motor evoked potentials (MEPs) during surgery. RESULTS: In the worsening group (n = 5), the mean FA ratio was lower and the mean MD ratio was higher compared with the non-worsening group (n = 15; P &amp;lt; 0.001 and P &amp;lt; 0.01, respectively). Cut-off values were 0.87 for FA and 1.08 for MD. SD was 7.95 mm in the non-worsening group and 0.44 mm in the worsening group (P &amp;lt; 0.01). These iDT based parameters, the mean FA ratio and the SD, were well correlated with the maximum reduction rate in MEP (R = 0.72 and 0.80, respectively). CONCLUSIONS: The mean ratio of FA, MD, and SD using iDT imagings predict postoperative motor function and help in optimal surgical planning in patients with motor eloquent glioma.

NI-18 A Quantitative Analysis of Intraoperative 3T-Diffusion Tensor Imaging parameters for Functional Prediction with Motor Eloquent Glioma Patients