P15.03.A The value of 7 Tesla MR spectroscopic imaging for improved preoperative determination of the tumor grade and IDH status in gliomas: preliminary data

Abstract Introduction A new generation of MR spectroscopic imaging (MRSI) methods using 7T scanners have demonstrated the capability to resolve more neuro- and oncometabolites at higher resolutions than clinical routine MRSI. In a cohort glioma patients, we explored automated preoperative noninvasive classification IDH-mutation status tumor grade based on Methods This retrospective study included 36 patients (15 female) with histologically confirmed diffusely infiltrating WHO 2-4 (9 2, 9 3 18 4) known IDH (21 IDH1-mut, 15 IDH-wt) an available MRSI scan sufficient data quality. The 3D had 3.4 mm isotropic resolution minutes acquisition time. 12 spectral components were classified voxel-wise, including choline, glutamine glycine. Within segmentation 3T imaging, used random forest algorithm for voxel-wise mutation (into low or high grade). Training leave-one-out cross validation method (i.e., every patient set, other 35 datasets as training set) feature selection out combinations metabolite ratios (e.g., choline). resulting voxel classifications aggregated into mean probability per that was base receiver-operator characteristic (ROC) curves both status. Results obtained area under curve (AUC) determination 0.85 75% sensitivity 95% specificity). For determination, AUC 0.88 87% 89% comparison, would resulted in 0.66 both. Further, by individual lower AUCs all cases. Conclusions According our preliminary data, is capable determine correct specificity leveraging extended metabolic panel width amount. By increasing this future, intend confirm initial results also plan extend molecular-pathological features TERT). Thus, even microenvironments could be attempted. Further improvements methodology such absolute instead relative quantification aid these attempts. summary, has shown its potential improved characterization gliomas.