Automatisierte vs. nTMS-basierte Analyse zur Identifizierung des motorischen Kortex und des kortikospinalen Trakts bei motorisch eloquenten Hirntumoren

nTMS is a reliable tool for accurate identification of the motor cortex (M1) and corticospinal tract (CST) and allows prediction of individual risk for new/progressive postoperative paresis in motor-associated brain tumors. However, it requires appropriate technical and personnel resources. In this study, we assessed the feasibility of identifying M1 and CST based on an anatomical mapping-based algorithm of a navigation planning software in comparison to the clinically established and validated nTMS motor mapping.

A retrospective analysis of a consecutive, prospective cohort of patients with brain tumors in motor eloquent areas who underwent preoperative nTMS motor mapping was performed. For both methods, the infiltration of M1 and CST, the tumor tract distance (TTD) and the fractional anisotropy (FA) were assessed. The agreement is measured with dice score and the overlap coefficient using the nTMS motor map as ground truth.

101 patients (46 females) with a mean age of 51 years (range: 20-86 years) were included. All patients suffered from brain tumors (74 contrast-enhancing tumors, 29 tumor recurrences), of whom edema was present in M1 in 50 cases. The automated algorithm visualized the precentral gyrus in all but in one subject (99%) and the corticospinal tract in all subjects (100%). However, limited results with clearly implausible components (e.g. extended segmentations beyond M1 / restricted segmentations with only a few parts of M1 / tracts that clearly do not correspond to the course of the CST) were observed in 60 cases for M1 (59.4%) and 56 cases for CST (55.4%). Significant differences were found in TTD between the two models (mean+-SD: 4+-6 mm, p=.0001). On average, the overlap for M1 segmentation was 40% (range: 0-86%), and the dice score of the CST tractography was 35% (range: 6-78%).

Automated anatomical-based segmentation of M1 and tractography of CST was feasible in almost all cases. However, nTMS is necessary for proper surgical planning, especially in cases where the tumor and perifocal edema interfere with the results of automated anatomical-based algorithm, highlighting the importance of individual functional mapping. Big data analysis and neural networks may help to improve the accuracy and efficiency of automated algorithms.