Abstracts

Rationale: Task-based fMRI (tb-fMRI) is the only clinically available tool for non-invasive preoperative language mapping in children with drug-resistant epilepsy (DRE). Children’s cooperation during tb-fMRI is low, motion and network immaturity reduces reliability. Resting-state fMRI (rs-fMRI) emerges as a valid alternative, but clinical application remains challenging due to discrepancies in results and lack of standardized methodology, particularly in younger children with atypical language networks. Addition of functional Near-Infrared Spectroscopy (fNIRS), a lower-complexity technique, shows promise to overcome some of the limitations of rs-fMRI and enhance reliability. Our objective is to develop a combined approach utilizing fNIRS and rs-fMRI to reliably determine language lateralization and localization in children with DRE that are candidates for surgery.


Methods: We conducted a pilot feasibility study, including 45 children with DRE candidates for epilepsy surgery with tb-fMRI (2 tasks, verb generation and object naming in block design) and rs-fMRI (short video projection) and fNIRS with the same task protocol. Additionally, a structural T1w with the fNIRS cap and vitamin E markers was performed in a subgroup of 17 patients. For resting-state, an independent component analysis (ICA) approach with a template-matching procedure was used to identify language networks. For task-based analysis, a traditional general linear model approach was used. Based on the block averages obtained, contrast-to-noise ratio was calculated as a measurement of activation level for selected channels on HbO, Hbr and Hbt signals, respectively. Laterality index was obtained. A 3D-morphometric modelling pipeline of the vitamin E markers was performed to co-register fNIRS to structural and functional scans. An fNIRS-guided seed-based analysis was carried out and compared to both, tb-fMRI and ICA rs-fMRI. Dice coefficient between the language networks derived from the different methods was used to determine degree of overlap and concordance.

Results: A high incidence of atypical language lateralization was observed in tb-fMRI and rs-fMRI with acceptable concordance. ICA rs-fMRI tends to retrieve more extensive language networks than tb-fMRI. On the 17 children with the fNIRS-fMRI combined method, 83% of total or partial concordance with tb-fMRI was achieved. fNIRS was well tolerated by all children. Discrepancies in task-specific lateralization were observed in some participants. Other resting-state networks (e.g: ventral attention, auditory and somatosensory networks) were also retrieved with the combined method, requiring visual inspection.

Conclusions: The high incidence of atypical language development in children with DRE remains a challenge for non-invasive neuroimaging analysis. The combined approach using fNIRS and fMRI offers a novel alternative to localize language networks in children with DRE with potential to increase accessibility and reliability of non-invasive techniques. Larger cohorts and invasive confirmation is needed to further validate these method.



Funding: London Health Sciences Centre Academic Realignment Initiative