Introduction

Estimated to affect half the world’s population during their lives traumatic brain injury (TBI) is a major public health problem and is a leading cause of neurodisability.¹ Up to 95% of TBI classified as mild based on the patient’s level of consciousness on presentation.² “Mild” however, is clearly a misnomer, with over 50% of patients reporting impairment up to 12 months after injury. Magnetic resonance imaging (MRI) offers the potential to improve both understanding of the pathophysiology underpinning patient outcome, as well as improve prediction at those at risk of persistent symptoms.

Methods

Patients with mTBI defined as a Glasgow Coma Score of 13-15 on presentation were included from two prospective observational cohorts; the the MRI sub-study of CENTER-TBI (Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury, n = 73)³ and eight patients recruited in Cambridge with a similar study protocol. All data collected were subject to national and local ethics review processes. Informed consent and/or the legal representative/next of kin was obtained for all subjects. All underwent a minimum of two scanning sessions; MR1 within 72 hours and MR2 within 30 days of injury. All MRI sessions were at 3 Tesla and sequences included volumetric T1, FLAIR, T2, susceptibility weighted imaging (SWI) and diffusion tensor imaging (DTI). Sequences were processed on a pipeline specially developed for TBI. MALP-EM was used to parcellate the brain into 15 regions of interest from which volumes were derived.⁴ FSL was used to process the DTI and white matter parcellation was performed using TractSeg, a convolutional neural network based approach that directly segments tracts in the field of fiber orientation distribution function peaks.⁵

Results

There was a similar overall incidence of scans positive for lesions reported between MR1 with MR2, but subarachnoid haemorrhage (tSAH) and intraventricular haemorrhage (IVH) showing a tendency to resolution. The overall composition of brain volume changed significantly between MR1 and MR2 (T2 = 4.065, p-value < 0.0001). Comparison of individual regions of interest showed that this change occurred predominantly in three regions of interest (Table 3); ventricular volume increased 1.06-fold ± 0.14 (p < 0.0001) convexity CSF volume increased 1.03-fold ± 0.15 (p = 0.0001), and cerebral white matter volume decreased 0.98-fold ± 0.03 (p = 0.0013) between the first and the second MR. Mean diffusivity significantly decreased between MR1 and MR2 in 13 tracts. There was no significant change in FA between the two time points. 63 patients with diffusion data available for all 13 tracts that changed between MR1 and MR2. Data from these patients was therefore used to derive three imaging phenotypes that describe the pattern of change using k means clustering of the log-ratios between the two time points of FA and MD. These were: patients in whom diffusion parameters continued to deteriorate between scans, with rising MD and falling FA (“Progressive injury”-phenotype); patients with no or little change in diffusion parameters (“Minimal change”-phenotype); and finally patients with falling MD and rising FA (“Pseudonormalisation”-phenotype). Concussion symptoms defined using the Rivermead Postconussion Symptom Score (RPQ) deteriorated in the “Progressive injury”-phenotype (deltaRPQ + 5.00, IQR +2.00 to +5.00), improved in the “Minimal change”-phenotype (deltaRPQ -4.5, IQR -9.25 to +1.75) and showed a variable evolution in the “Pseudonormalisation”-phenotype (delta RPQ zero, IQR -6.25 to +9.00), with a significant difference between phenotypes (p = 0.01698).

Discussion

This study demonstrates the dynamic changes that occurs after mTBI as defined using conventional and advanced MRI. The changes in lesion detection, while not directly affecting the clinical management of the patients, may be important as objective markers of injury, and may be useful as prognostic covariates. The volume loss between MR1 and MR2 is consistent with injury progression (eg Wallerian degeneration) rather than resolution of oedema as there was no significant difference to controls at MR1. The parcellation od DTI allowed for identification of clinically plausible phenotypic subsets, which correlated with trajectories of patient outcomes. We found that in those patients who had progressive change in their DTI metrics had worsening scores on the RPQ, versus those whose DTI metrics “pseudo-normalised” had reduced symptomatology.

Conclusion

The data presented here suggests that DTI may be used as a marker of both injury progression and recovery.

Acknowledgements

This work was supported by the European Union 7th Framework Program (EC grant 602150).