Quantifying Structural Connectivity in Brain Tumor Patients

Brain tumors are characterised by infiltration along the white matter tracts, posing significant challenges to precise treatment. Mounting evidence shows that an infiltrative tumor can interfere with the brain network diffusely. Therefore, quantifying structural connectivity has potential to identify tumor invasion and stratify patients more accurately. The tract-based statistics (TBSS) is widely used to measure the white matter integrity. This voxel-wise method, however, cannot directly quantify the connectivity of brain regions. Tractography is a fiber tracking approach, which has been widely used to quantify brain connectivity. However, the performance of tractography on the brain with tumors is biased by the tumor mass effect. A robust method of quantifying the structural connectivity in brain tumor patients is still lacking. 

Here we propose a method which could provide robust estimation of tract strength for brain tumor patients. Specifically, we firstly construct an unbiased tract template in healthy subjects using tractography. The voxel projection procedure of TBSS is employed to quantify the tract connectivity in patients, based on the location of each tract fiber from the template. To further improve the standard TBSS, we propose an approach of iterative projection of tract voxels, under the guidance of tract orientation measured by voxel-wise eigenvectors. Compared to the conventional tractography methods, our approach is more sensitive in reflecting functional relevance. Further, the different extent of network disruption revealed by our approach correspond to the clinical prior knowledge of tumor histology. The proposed method could provide a robust estimation of the structural connectivity for brain tumor patients.