AUTHOR=Stillo David , Danielli Ethan , Ho Rachelle A. , DeMatteo Carol , Hall Geoffrey B. , Bock Nicholas A. , Connolly John F. , Noseworthy Michael D. 

TITLE=Localization and Identification of Brain Microstructural Abnormalities in Paediatric Concussion

JOURNAL=Frontiers in Human Neuroscience

VOLUME=Volume 15 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2021.657374

DOI=10.3389/fnhum.2021.657374

ISSN=1662-5161

ABSTRACT=In the United States, approximately 2.53 million people sustain a concussion each year. Relative to adults, youth show greater cognitive deficits following concussion and a longer recovery. An accurate and reliable imaging method is needed to determine injury severity and symptom resolution. The primary objective of this study was to characterize concussions with diffusion tensor imaging (DTI). This was performed through a normative Z-scoring analysis of DTI metrics, fractional anisotropy, axial diffusivity and radial diffusivity, to quantify patient specific injuries and identify commonly damaged brain regions in paediatric concussion patients relative to healthy controls. It was hypothesized that personalizing the detection analysis through normative Z-scoring would provide understanding of trauma-induced microstructural damage. Concussion patients were volunteers recruited from the Emergency Department of the McMaster Children’s Hospital with a recent concussion (n=26), nine males and 17 females, mean age 14.22 +/- 2.64, while healthy paediatric brain DTI datasets (25 males and 24 females, mean age = 13.52+/-1.03) were obtained from an MRI data repository. Significant abnormalities were commonly found in the longitudinal fasciculus, fronto-occipital fasciculus, and corticospinal tract, while unique abnormalities were localized in a number of other areas reflecting the individuality of each child’s injury. Total brain injury burden, as determined by the number of regions with outlier fractional anisotropy Z-scores, significantly correlated with post-concussion symptoms score (PCSS; p<0.038) and age of injury (p<0.001). These results show that DTI was able to detect microstructural changes caused by concussion, on a per-person basis, and has potential to be a useful tool for improving diagnostic accuracy and prognosis of a concussion.