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Purpose: to compare different methods to calculate Laterality Index (LI), ametric which allows to evaluate hemispheric brain language dominance infunctional MRI examinations (fMRI).  Methods: Two methods were considered for calculating LI: LI AVE and LI VOL ,respectively based on the differences between measurements of average andvolume of fMRI signal in brain hemispheres. Laterality curves were obtainedcalculating values of LI VOL with increasing thresholds of fMRI signal andfitted with sigmoidal functions. A model for dominant and co-dominantclassification based on fit parameters has been developed. The two methods andthe sigmoidal model were applied to two cohorts of 93 epileptic patients and 27healthy subjects undergoing language fMRI examinations with association,understanding and fluency tasks.  Results: Despite the different definitions, LI AVE and LI VOL resulted inequivalent classification of language lateralization. The agreement ofneuroradiological clinical reports with classification of languagelateralization resulting from the proposed methods ranged from 94.6% to 89.2%for LI metrics and up to 100% for the sigmoidal model. The fit parameters ofthe sigmoidal function defined empirical thresholds useful for classificationbetween dominant and co-dominant, providing similar values for subjects andepileptic patients for fluency and association tasks. This result supports theidea of a unique model for language lateralization classification in epilepticpatients and healthy subjects.  Conclusions: Language lateralization in fMRI can be effectively assessed byobjective metrics. A novel approach based on sigmoidal fit of laterality curvesresulted in higher agreement with clinical reports providing furtherinformation about the strength of language lateralization.

Objective metrics for language lateralization of fMRI examinations: a  new model for the classification of hemispheric dominance in healthy subjects  and epileptic patients