Abstract
Background Concussions are among the most common sport-related injuries. While symptoms remain the most widely studied outcome, other measures such as resting state functional magnetic resonance imaging (rsfMRI) are being increasingly studied to better understand the neurophysiology of concussion. The basis for rsfMRI is the temporal blood oxygen level dependent (BOLD) signal, which shows complex changes in brain activity over the course of a scan. The BOLD signal can be operationalized in many ways, which effects how the data are analyzed and interpreted. It is therefore important for neuroimaging researchers to understand which rsfMRI metric is most discriminatory between concussion subjects and healthy controls, as such knowledge may aid in the design of future studies. The primary purpose of our study was to employ a random forest approach to determine which BOLD signal metric (of which we selected six) was most discriminatory between concussion subjects and healthy controls. As a secondary objective, we aimed to understand which anatomical regions of interest in the brain were most discriminatory between these two groups.Methods We performed a secondary data analysis of prospectively collected concussion data (n = 28), alongside healthy control data retrieved through an open-source neuroimaging repository (n = 379). After pre-processing data in CONN 21a, six BOLD metrics were computed: mean, standard deviation, Lyapunov exponent, sample entropy, amplitude of low frequency fluctuations (ALFF), and fractional ALFF (fALFF). Using a 60/20/20 (training/testing/validation) split of the data, random forest models were built using 'scikit-learn' and 'imbalanced-learn' to determine which metrics and anatomical regions of interest were most discriminatory between concussion and healthy subjects.Results We found that ALFF was the most discriminatory BOLD metric, with an ROC AUC = 0.993. With respect to regions of interest, we found that the BOLD signal from the cerebellum, vermis, and putamen (left) were most often discriminatory.Conclusions Our study provides concussion neuroimaging researchers with insight into which rsfMRI metrics may be discriminatory between groups, as well as which anatomical regions may help distinguish between concussion and healthy subjects. This may inform the design of new research studies that take aim at assessing or monitoring concussion using rsfMRI.Trial registration: Not applicable.