Quantitative structural neuroimaging of mild traumatic brain injury in the Chronic Effects of Neurotrauma Consortium (CENC): Comparison of volumetric data within and across scanners.

BACKGROUND: An important component of the multicentre Chronic Effects of Neurotrauma Consortium (CENC) project is the development of improved quantitative magnetic resonance imaging (MRI) methods, including volumetric analysis. Although many studies routinely employ quality assurance (QA) procedures including MR and human phantoms to promote accuracy and monitor site differences, few studies perform rigorous direct comparisons of these data nor report findings that enable inference regarding site-to-site comparability. These gaps in evaluating cross-site differences are concerning, especially given the well-established differences that can occur between data acquired on scanners with different manufacturer, hardware or software. METHODS: This study reports findings on (1) a series of studies utilizing two MR phantoms to interrogate machine-based variability using data collected on the same magnet, (2) a human phantom repeatedly imaged on the same scanner to investigate within-subject, within-site variability and (3) a human phantom imaged on three different scanners to examine within subject, between-site variability. RESULTS: Although variability is relatively minimal for the phantom scanned on the same magnet, significantly more variability is introduced in a human subject, particularly when regions are relatively small or multiple sites used. CONCLUSION: Vigilance when combining data from different sites is suggested and that future efforts address these issues.

Supervised learning technique for the automated identification of white matter hyperintensities in traumatic brain injury.

BACKGROUND: White matter hyperintensities (WMHs) are foci of abnormal signal intensity in white matter regions seen with magnetic resonance imaging (MRI). WMHs are associated with normal ageing and have shown prognostic value in neurological conditions such as traumatic brain injury (TBI). The impracticality of manually quantifying these lesions limits their clinical utility and motivates the utilization of machine learning techniques for automated segmentation workflows. METHODS: This study develops a concatenated random forest framework with image features for segmenting WMHs in a TBI cohort. The framework is built upon the Advanced Normalization Tools (ANTs) and ANTsR toolkits. MR (3D FLAIR, T2- and T1-weighted) images from 24 service members and veterans scanned in the Chronic Effects of Neurotrauma Consortium's (CENC) observational study were acquired. Manual annotations were employed for both training and evaluation using a leave-one-out strategy. Performance measures include sensitivity, positive predictive value, [Formula: see text] score and relative volume difference. RESULTS: Final average results were: sensitivity = 0.68 ± 0.38, positive predictive value = 0.51 ± 0.40, [Formula: see text] = 0.52 ± 0.36, relative volume difference = 43 ± 26%. In addition, three lesion size ranges are selected to illustrate the variation in performance with lesion size. CONCLUSION: Paired with correlative outcome data, supervised learning methods may allow for identification of imaging features predictive of diagnosis and prognosis in individual TBI patients.

The Relation of Focal Lesions to Cortical Thickness in Pediatric Traumatic Brain Injury.

In a sample of children with traumatic brain injury, this magnetic resonance imaging (MRI)-based investigation examined whether presence of a focal lesion uniquely influenced cortical thickness in any brain region. Specifically, the study explored the relation of cortical thickness to injury severity as measured by Glasgow Coma Scale score and length of stay, along with presence of encephalomalacia, focal white matter lesions or presence of hemosiderin deposition as a marker of shear injury. For comparison, a group of children without head injury but with orthopedic injury of similar age and sex were also examined. Both traumatic brain injury and orthopedic injury children had normally reduced cortical thickness with age, assumed to reflect neuronal pruning. However, the reductions observed within the traumatic brain injury sample were similar to those in the orthopedic injury group, suggesting that in this sample traumatic brain injury, per se, did not uniquely alter cortical thickness in any brain region at the group level. Injury severity in terms of Glasgow Coma Scale or longer length of stay was associated with greater reductions in frontal and occipitoparietal cortical thickness. However, presence of focal lesions were not related to unique changes in cortical thickness despite having a prominent distribution of lesions within frontotemporal regions among children with traumatic brain injury. Because focal lesions were highly heterogeneous, their association with cortical thickness and development appeared to be idiosyncratic, and not associated with group level effects.