Regional brain morphometry predicts memory rehabilitation outcome after traumatic brain injury

Abstract

Cognitive deficits following traumatic brain injury (TBI) commonly include difficulties with memory, attention, and executive dysfunction. These deficits are amenable to cognitive rehabilitation, but optimally selecting rehabilitation programs for individual patients remains a challenge. Recent methods for quantifying regional brain morphometry allow for automated quantification of tissue volumes in numerous distinct brain structures. We hypothesized that such quantitative structural information could help identify individuals more or less likely to benefit from memory rehabilitation. Fifty individuals with TBI of all severities who reported having memory difficulties first underwent structural MRI scanning. They then participated in a 12 session memory rehabilitation program emphasizing internal memory strategies (I-MEMS). Primary outcome measures (HVLT, RBMT) were collected at the time of the MRI scan, immediately following therapy, and again at 1-month post-therapy. Regional brain volumes were used to predict outcome, adjusting for standard predictors (e.g., injury severity, age, education, pretest scores). We identified several brain regions that provided significant predictions of rehabilitation outcome, including the volume of the hippocampus, the lateral prefrontal cortex, the thalamus, and several subregions of the cingulate cortex. The prediction range of regional brain volumes were in some cases nearly equal in magnitude to prediction ranges provided by pretest scores on the outcome variable. We conclude that specific cerebral networks including these regions may contribute to learning during I-MEMS rehabilitation, and suggest that morphometric measures may provide substantial predictive value for rehabilitation outcome in other cognitive interventions as well.

Keywords: behavioral neurology; brain trauma; cognitive rehabilitation; memory; morphometrics; semantic clustering; structural neuroimaging.

Figure 1

Brain morphometric parcellation results for an example subject, identifying key regions from this study. (A,B) Lateral and medial representations of the inflated cortical surface showing the 75 parcellated cortical regions per hemisphere. Only the left hemisphere is shown, laterally (A) and medially (B). (C) Coronal slice highlighting several subcortical structures automatically identified by the Freesurfer algorithms (thalamus, ventral diencephalon, hippocampus, basal ganglia, etc).

Figure 2

Example surface reconstruction in a case of substantial right temporal lobe encephalomalacia. (A) T1-weighted axial MRI image through the region of degeneration (oval). (B) Close up of T1 with overlay of the surfaces generated at the white-/gray-matter interface (green) and the pial surface (red). (C) Inflated right hemisphere showing curvature (reds = depth of sulci, greens = peak of gyri), with minimal curvature in the region of degeneration. (D) Re-folded surface with individual regional cortical labels (colors).

Figure 3

Depiction of the relationship between HVLT delayed correct recall score at posttest 2 versus the volume of (A) the hippocampus, and (B) the posterior dorsal cingulate gyrus. Simple least-squares lines are plotted; detailed regression results appear in Tables 4 and 5.

Figure 4

Relationship between our functionally relevant outcome (RBMT) 1-month post-therapy and the volume of the pMCC. A simple least-squares regression line is plotted. Results from the multiple regression model appears in Table 6.