Morphometric evaluation of traumatic axonal injury and the correlation with post-traumatic cerebral atrophy and functional outcome

Abstract

Introduction Imaging plays a crucial role in the diagnosis, prognosis and follow-up of traumatic brain injury. Whereas computed tomography plays a pivotal role in the acute setting, magnetic resonance imaging is best suited to detect the true extent of traumatic brain injury, and more specifically diffuse axonal injury. Post-traumatic brain atrophy is a well-known complication of traumatic brain injury. Purpose This study investigated the correlation between diffuse axonal injury detected with fluid-attenuated inversion recovery and susceptibility-weighted imaging magnetic resonance imaging, post-traumatic brain atrophy and functional outcome (Glasgow outcome scale – extended). Materials and methods Twenty patients with a closed head injury and diffuse axonal injury detected with fluid-attenuated inversion recovery and susceptibility-weighted imaging were included. The total volumes of the diffuse axonal injury fluid-attenuated inversion recovery lesions were determined for each subject’s initial (<14 days) and follow-up magnetic resonance scan (average: day 303 ± 83 standard deviation). The different brain volumes were automatically quantified using a validated and both US Food and Drug Administration-cleared and CE-marked machine learning algorithm (icobrain). The number of susceptibility-weighted imaging lesions and functional outcome scores (Glasgow outcome scale – extended) were retrieved from the Collaborative European NeuroTrauma Effectiveness Research Traumatic Brain Injury dataset. Results The volumetric fluid-attenuated inversion recovery diffuse axonal injury lesion load showed a significant inverse correlation with functional outcome (Glasgow outcome scale – extended) ( r = −0.57; P = 0.0094) and white matter volume change ( r = −0.50; P = 0.027). In addition, white matter volume change correlated significantly with the Glasgow outcome scale – extended score ( P = 0.0072; r = 0.58). Moreover, there was a strong inverse correlation between longitudinal fluid-attenuated inversion recovery lesion volume change and whole brain volume change ( r = −0.63; P = 0.0028). No significant correlation existed between the number of diffuse axonal injury susceptibility-weighted imaging lesions, brain atrophy and functional outcome. Conclusions Volumetric analysis of diffuse axonal injury on fluid-attenuated inversion recovery imaging and automated brain atrophy calculation are potentially useful tools in the clinical management and follow-up of traumatic brain injury patients with diffuse axonal injury.

Neuronal tau pathology worsens late-phase white matter degeneration after traumatic brain injury in transgenic mice

“…White matter atrophy, demyelination, and neuroinflammation develop after TBI in wild-type mice, yet our results show a significant impact of phosphorylated tau pathology on each of these pathological features in the progression from the subacute to chronic phase (Figs. 7,8,9,10,11,12). In the s-TBI model, we have shown persistent axon damage and corpus callosum atrophy by neuropathology and MRI fractional anisotropy with volume analysis at 8 and 10 weeks post-injury [10,54].…”

“…In contrast to prior mouse TBI studies [5, 27, 58], we found significant effects of human tau transgene expression on the progression of white matter pathology between subacute to chronic time points post-injury (Figs. 7,8,9,10). Corpus callosum width and myelination measures were used as indicators of post-traumatic neurodegeneration after s-TBI and r-mTBI.…”

“…Traumatic brain injury (TBI) can lead to post-traumatic neurodegeneration of gray and white matter brain regions that is associated with poor patient outcomes [ 9 , 34 ]. More specifically, diffuse axonal injury in the corpus callosum is associated with post-traumatic neurodegeneration and unfavorable functional outcomes, as measured using the Glasgow Outcome Scale (GOS) or the Glasgow Outcome Scale-Extended (GOSE) [ 34 , 83 ].…”

Machine Learning in Neuroimaging of Traumatic Brain Injury: Current Landscape, Research Gaps, and Future Directions

“…Mohamed (2022) employed a CNN to predict favorable or unfavorable outcomes using the Glasgow Outcome Scale (GOS) from MRIs of 38 patients who sustained moderate or severe TBI with MRI evidence of DAI, achieving a sensitivity of 0.997 and AUROC of 0.917 [77]. Bohyn (2022) applied the FDA-cleared machine learning software icobrain to calculate brain lesion volumes in 20 DAI patients, correlating whitematter volume changes with GOS [78]. Tjerkaski (2022) used an RF model with gradient-echo and susceptibility-weighted imaging to develop a novel MRI-based traumatic axonal injury (TAI) grading system to discern between favorable and unfavorable outcomes, achieving an AUC of 0.72 [39].…”

“…For instance, Icometrix's icobrain tbi for CT automates the detection and quantification of intracranial lesions, with correlations closely mirroring expert assessments [95]. Their MRIfocused counterpart, icobrain tbi for MRI, identifies traumatic axonal injuries and correlates lesion load with functional outcomes and brain volume changes [78]. Considering the challenges of assessing axonal injury using traditional imaging [96], machine learning provides a valuable augmentation.…”