Application of a Computerized Language Lateralization Index from fMRI by a Group of Clinical Neuroradiologists

BACKGROUND AND PURPOSE: Deriving accurate language lateralization from fMRI studies in the clinical context can be difficult, with 10%–20% incorrect conclusions. Most interpretations are qualitative, performed by neuroimaging experts. Quantitative lateralization has been widely described but with little implementation in the clinical setting and is disadvantaged by the use of arbitrary threshold techniques. We investigated the application and utility of a nonthreshold CLI, in a clinical setting, as applied by a group of practicing neuroradiologists.

MATERIALS AND METHODS: Twenty-two patients with known language lateralization (11 left and 11 nonleft dominant) had their images reviewed by 8 neuroradiologists in 2 settings, all randomized, once by using a CLI and once without using a CLI. For each review, neuroradiologists recorded their impressions of lateralization for each language sequence, the overall lateralization conclusion, their impression of scan quality and noise, and the subjective confidence in their conclusion.

RESULTS: The inter-rater κ for lateralization was 0.64, which increased to 0.70 with the use of CLI. The group accuracy of overall lateralization was 78%, which increased to 81% with the use of a CLI. Using a CLI removed 2 instances of significant errors, with a neuroradiologist's impression of left lateralization in a patient with known right lateralization. Using a CLI had no effect on examinations with conclusions formed with either high confidence or no confidence.

CONCLUSIONS: Although the overall clinical benefit of a CLI is modest, the most significant impact is to reduce the most harmful misclassification errors, particularly in fMRI examinations that are suboptimal.