Hemisphere-Specific Functional Remodeling and Its Relevance to Tumor Malignancy of Cerebral Glioma Based on Resting-State Functional Network Analysis - Cai, Siqi; Shi, Zhifeng; Jiang, Chunxiang; Wang, Kai; Chen, Liang; Ai, Lin; Zhang, Lijuan (Frontiers in Neuroscience, 2021)
Abstract Background: Functional remodeling may vary with tumor aggressiveness of glioma. Investigation of the functional remodeling is expected to provide scientific relevance of tumor characterization and disease management of glioma. In this study, we aimed to investigate the functional remodeling of the contralesional hemisphere and its utility in predicting the malignant grade of glioma at the individual level with multivariate logistic regression (MLR) analysis. Subjects and Methods: One hundred and twenty six right-handed subjects with histologically confirmed cerebral glioma were included with 80 tumors located in left hemisphere (LH) and 46 tumors located in right hemisphere (RH). Resting-state functional networks of contralesional hemisphere were constructed using human brainnetome atlas based on resting-state fMRI data. Functional connectivity and topological features of functional networks were quantified. The performance of functional features in predicting the glioma grade was evaluated using area under (AUC) the receiver operating characteristic curve (ROC). The dataset was divided into train and validation datasets. Features with high AUC value in malignancy classification on train dataset were determined as predictive features. MLR model was constructed based on predictive features and its classification performance was evaluated on train and validation dataset with 10-fold cross validation. Results: Predictive functional features showed apparent hemispheric specifications. MLR classification models constructed with age and predictive functional connectivity features (AUC of 0.853±0.079 and 1.000±0.000 for LH and RH group, respectively) and topological features (AUC of 0.788±0.150 and 0.897±0.165 for LH and RH group, respectively) achieved efficient performance in predicting the malignant grade of gliomas. Conclusion: Functional remodeling of the contralesional hemisphere was hemisphere-specific and highly predictive of the malignant grade of glioma. Network approach provides a novel pathway that may innovate glioma characterization and management at the individual level.