A quantitative approach for measuring laterality in clinical fMRI for preoperative language mapping

Area of Science:

• Neuroimaging
• Cognitive Neuroscience
• Clinical Neurology

Background:

• Functional MRI (fMRI) is vital for presurgical language mapping.
• Current fMRI methods lack standardization, hindering data integration and comparison across institutions.
• This limits the assessment of different language mapping approaches.

Purpose of the Study:

• To develop a quantitative analytic framework for language laterality in clinical fMRI.
• To address challenges in combining/comparing fMRI data across institutions.
• To establish a standardized methodology for reliable presurgical language mapping.

Main Methods:

• Retrospective analysis of fMRI data from 59 patients undergoing presurgical language mapping.
• Comparison of regional masks for capturing language activations.
• Systematic exploration of laterality indices (LIs) based on task and activation threshold.
• Determination of optimal percentile threshold for LI calculation.

Main Results:

• A functional mask derived from fMRI literature meta-analysis outperformed anatomical masks in capturing language activations.
• The LI approach with percentile thresholding quantifies language task lateralization efficacy.
• The 92nd percentile threshold optimally reproduced original clinical radiology reports.

Conclusions:

• A quantitative framework using a functional mask and percentile thresholding standardizes language laterality assessment in fMRI.
• This framework enables data combination and comparison across tasks and patients.
• The proposed method accurately reproduces clinical assessments of language laterality.