Noninvasive Prediction of Language Lateralization Through Arcuate Fasciculus Tractography in Patients With Low-Grade Gliomas: Correlation With The Wada Test

Abstract

Language lateralization is unique to humans, so clarifying dominant side is helpful for removing gliomas involving language areas. This study investigated the arcuate fasciculus (AF) reconstructed by diffusion tensor imaging–based tractography (DTT) in predicting language lateralization in patients with low-grade gliomas. Wada test was performed to determine the language Dominant Hemisphere (DH) and the Contralateral Hemisphere. DTI data [1.5-T magnetic resonance imaging (MRI)] was used to reconstruct AF by two independent operators using a DTT method. Fiber number, volume, and fractional anisotropy (FA) of bilateral reconstructed AF were measured. Lateralization indexes (LIs), including Number Index (NI), Volume Index (VI), and FA Index (FI), were accordingly calculated by mean values. A total of 21 patients with WHO Grade II gliomas in the left hemisphere were included. Every patient received a successful Wada test and reconstruction of bilateral AF. DTT metrics of reconstructed AF, such as fiber number, volume, and FA, showed significantly asymmetric between hemispheres. All the LI (NI, VI, and FI) values were statistically higher in the DH determined by the Wada test. No discrepancy was found between the prediction using the cutoff values of DTT metrics and the results of WADA test. The Kappa values were 0.829, 0.696, and 0.611, indicating NI and VI as more reliable predictor than FI although FI itself may also be feasible. Compared with the Wada test, we consider that DTT of AF is a non-invasive, simple, relatively accurate, and feasible method in predicting language lateralization in patients with low-grade gliomas.

Exploring the arcuate fasciculus from a clinical perspective

“…If accuracy and precision are pursued, the nerve fiber structure near or distant from the lesion should also be included. The predicted value mainly comprised various types of eigenvalues from DTI sequences, such as FA, ADC, volume, and length values, among others ( Wu et al, 2022 ). In recent years, the connection between post-stroke aphasia and arcuate tract changes has become one of the hotspots.…”

“…In a research group in China using the DTT method to predict postoperative language function in low-grade gliomas, the volume and number of the arcuate tract fibers can afford better reliability than the FA value, which once again confirms the noninvasive archetype. Also, the description of the eigenvalues of the bundle has predictability ( Wu et al, 2022 ).…”