Strategic white matter injury associated with long-term information processing speed deficits in mild traumatic brain injury

Abstract

Deficits in information processing speed (IPS) are among the earliest and most prominent cognitive manifestations in mild traumatic brain injury (mTBI). We investigated the impact of white matter fiber location on IPS outcome in an individual basis assessment. A total of 112 acute mild TBI with all CT negative underwent brain DTI and blood sampling for inflammation cytokines within 7 days postinjury and 72 age- and sex matched healthy controls with same assessments were enrolled. IPS outcome was assessed by the trail making test at 6-12 month postinjury in mild TBI. Fractional anisotropy (FA) features were extracted using a novel lesion-load analytical strategy to capture spatially heterogeneous white matter injuries and minimize implicit assumptions of uniform injury across diverse clinical presentations. Acute mild TBI exhibited a general pattern of increased and decreased FA in specific white matter tracts. The power of acute FA measures to identify patients developing IPS deficits with 92% accuracy and further improved to 96% accuracy by adding inflammation cytokines. The classifiers predicted individual's IPS and working memory ratings (r = .74 and .80, respectively, p < .001). The thalamo-cortical circuits and commissural tracts projecting or connecting frontal regions became important predictors. This prognostic model was also verified by an independent replicate sample. Our findings highlighted damage to frontal interhemispheric and thalamic projection fiber tracts harboring frontal-subcortical neuronal circuits as a predictor for processing speed performance in mild TBI.

Keywords: DTI; information processing speed; mild traumatic brain injury; prognosis; serum inflammation cytokine.

FIGURE 1

Summary of methods. (a) Skeletonized diffusion metric for white matter tracts was measured from 98 patients with mild TBI and 70 matched healthy controls. Additional thalamo‐cortical tracts were defined by using probabilistic tractography in 10 separate healthy controls. (b) lesion‐load analytical strategy to capture spatially heterogeneous white matter injuries from the skeletonized diffusion metric; (c) Patients were grouped into those whose information processing speed (IPS) score was improved to the normal level or not at follow‐up visit. (d) SVM was used to examine whether structural DTI measured at acute phase can divide patients into the above two groups. (e) Comparison of predicted performance with only lesion‐load abnormality features or combination with serum cytokine

FIGURE 2

Most important weighted lesion‐load cluster in specific fiber tracts as predictors and showing significant differences between PAT1 and PAT2, as well as PAT2 and healthy controls (p < .05, Bonferroni correction for multiple comparisons). These tracts included the left thalamus‐SFG tract with both low and high diffusion clusters, left cingulum (hippocampus) with high diffusion cluster, left anterior thalamic radiation, right uncinate fasciculus and genu of CC with low diffusion cluster. PAT1, patients with recovery to the normal level for the IPS; PAT2, patients with incomplete recovery for the IPS; HC, healthy controls. IPS, information processing speed; L, left; R, right

FIGURE 3

Cognitive function predicted using support vector regression (SVR). SVR was trained by using DTI classifier in identify patients with information processing speed (IPS) (rated by Trail‐making A test score, TMTA) deficit to predict the individual IPS profile (a) and working memory (b) (rated by back forward digit sequencing, BDS). There were significant positive relations between the true neuropsychological score and the predicted value for both IPS and working memory