Predicting Cognitive Functioning in High-Grade Glioma: Evaluating Different Representations of Tumor Location in a Common Space

Abstract Introduction : Cognitive functioning is increasingly considered when making treatment decisions for patients with a brain tumor in view of a personalized onco-functional balance. Ideally, one can predict cognitive functioning of individual patients to make treatment decisions considering this balance. To make accurate predictions, an informative representation of tumor location is pivotal, yet comparisons of representations are lacking. Therefore, this study compares brain atlases and principal component analysis to represent voxel-wise tumor location. Methods Pre-operative cognitive functioning was predicted for 246 patients with a high-grade glioma across eight cognitive tests while using different representations of voxel-wise tumor location as predictors. Voxel-wise tumor location was represented using 13 different frequently-used population average atlases, 13 randomly generated atlases, and 13 representations based on principal component analysis. ElasticNet predictions were compared between representations and against a model solely using tumor volume as a predictor. Results Preoperative cognitive functioning could only partly be predicted from the representations of tumor location. Representations based on principal component analysis resulted in better predictions compared to those based on population average- and random atlases. Population average atlases did not result in better predictions when compared to random atlases. Discussion For the prediction of cognitive performances, representations based on principal component analysis should be favored over population average atlases for prediction if the decrease in interpretability is acceptable. Population average atlases possibly cannot distinguish between functionally distinct areas when applied to patients with a glioma. Researchers should develop and validate methods for individual parcellations in the presence of lesions.