Johanna Monsalves MD, Presenter: Nothing to Disclose

Michael John Paldino MD, Abstract Co-Author: Nothing to Disclose

Wei Zhang PhD, Abstract Co-Author: Nothing to Disclose

Lynn Chapieski PhD, Abstract Co-Author: Nothing to Disclose

Patients with epilepsy are at high risk for language and other cognitive impairment.  Several white matter pathways have been implicated in such dysfunction.  However, great potential exists to detect indirect associations between a proposed biomarker and a particular cognitive function, particularly in populations whose cerebral connectivity and brain function are both extensively abnormal.  The goal of this study was to measure the independent contribution of well-described white matter pathways to language function in a cohort of pediatric patients with epilepsy.

Patients were retrospectively identified from an existing database of pediatric epilepsy patients with the following inclusion criteria:  1. Diffusion tensor imaging acquired at 3 Tesla; 2. Language function measured by a neuropsychologist. The following tracts were analyzed: corpus callosum, corticospinal tracts (CSP), inferior longitudinal fasciculi (ILF), inferior fronto-occipital fasciculi (IFOF), uncinate fasciculi (UF), and arcuate fasciculi (AF).  Mean diffusivity (ADC), axial diffusivity (e1), and fractional anisotropy (FA) were calculated for each tract.  A machine learning algorithm (random forest) measured the independent contribution of metrics from each tract to the clinical phenotype.  In other words, the importance of each tract was measured after adjusting for the contribution of all other tracts.

Twenty patients met criteria (age: 4-18 years).  All tracts were identified in all patients except the AF, which was not identified on the right in 8 patients and not identified on the left in 1 subject.  Metrics related only to the left UF, IFOF, and AF were independently associated with the clinical phenotype (Figure 1).  In addition, the machine learning algorithm was highly accurate in predicting the individual patient language scores on the basis of tract metrics.

Quantitative metrics derived from the left uncinate,inferior fronto-occipital, and arcuate fasciculi were independently associated with language function.

Our findings highlight the importance of these three association pathways in human language function.

Monsalves, J, Paldino, M, Zhang, W, Chapieski, L, Independent Contribution of Individual White Matter Pathways to Language Function in a Cohort of Pediatric Epilepsy Patients.  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/14014058.html