Prediction of Global Functional Outcome and Post-Concussive Symptoms after Mild Traumatic Brain Injury: External Validation of Prognostic Models in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study

The Australian Traumatic Brain Injury Initiative: Statement of Working Principles and Rapid Review of Methods to Define Data Dictionaries for Neurological Conditions

The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to develop a health informatics approach to collect data predictive of outcomes for persons with moderate-severe TBI across Australia. Central to this approach is a data dictionary; however, no systematic reviews of methods to define and develop data dictionaries exist to-date. This rapid systematic review aimed to identify and characterize methods for designing data dictionaries to collect outcomes or variables in persons with neurological conditions. Database searches were conducted from inception through October 2021. Records were screened in two stages against set criteria to identify methods to define data dictionaries for neurological conditions (International Classification of Diseases, 11th Revision: 08, 22, and 23). Standardized data were extracted. Processes were checked at each stage by independent review of a random 25% of records. Consensus was reached through discussion where necessary. Thirty-nine initiatives were identified across 29 neurological conditions. No single established or recommended method for defining a data dictionary was identified. Nine initiatives conducted systematic reviews to collate information before implementing a consensus process. Thirty-seven initiatives consulted with end-users. Methods of consultation were "roundtable" discussion (n = 30); with facilitation (n = 16); that was iterative (n = 27); and frequently conducted in-person (n = 27). Researcher stakeholders were involved in all initiatives and clinicians in 25. Importantly, only six initiatives involved persons with lived experience of TBI and four involved carers. Methods for defining data dictionaries were variable and reporting is sparse. Our findings are instructive for AUS-TBI and can be used to further development of methods for defining data dictionaries.

Contrasting Characteristics and Outcomes of Sports-Related and Non-Sports-Related Traumatic Brain Injury

Importance

Exposure to traumatic brain injury (TBI) has raised widespread concern over participation in sports, particularly over possible long-term consequences. However, little is known about the outcomes of individuals presenting to hospitals with sports-related TBI.

Objective

To compare the characteristics and outcomes of individuals presenting to hospitals with sports-related and non-sports-related TBI.

Design, Setting, and Participants

The CENTER-TBI (Collaborative European NeuroTrauma Effectiveness Research in TBI) observational cohort study was conducted at hospitals in 18 countries. The study enrolled 4509 patients who had TBI and had an indication for computed tomography (CT), of whom 4360 were 16 years or older. Outcomes were assessed at 3 and 6 months, and groups were compared using regression analyses adjusting for clinical and demographic differences. Data were collected between December 9, 2014, and December 17, 2017, and analyzed from August 2022 to March 2023.

Exposure

Sports-related and non-sports-related TBI with subgroups selected by severity of injury.

Main Outcomes and Measures

The main outcome was the Glasgow Outcome Scale-Extended (GOSE) at 6 months, with secondary outcomes covering postconcussion symptoms, health-related quality of life, and mental health.

Results

A total of 4360 patients were studied, including 256 (6%) with sports-related TBI (mean [SD] age, 38.9 [18.1] years; 161 [63%] male) and 4104 with non-sports-related TBI (mean [SD] age, 51.0 [20.2] years; 2773 [68%] male). Compared with patients with non-sports-related TBI, patients with sports-related TBI were younger, more likely to have tertiary education, more likely to be previously healthy, and less likely to have a major extracranial injury. After adjustment, the groups did not differ in incomplete recovery (GOSE scores <8) at 6 months (odds ratio [OR], 1.27; 95% CI, 0.90-1.78; P = .22 for all patients; OR, 1.20; 95% CI, 0.83-1.73; P = .34 for those with mild TBI; and OR, 1.19; 95% CI, 0.74-1.92; P = .65 for those with mild TBI and negative CT findings). At 6 months, there was incomplete recovery in 103 of 223 patients (46%) with outcomes in the sports-related TBI group, 65 of 168 (39%) in those with mild sports-related TBI, and 30 of 98 (31%) in those with mild sports-related TBI and negative CT findings. In contrast, at 6 months, the sports-related TBI group had lower prevalence of anxiety, depression, posttraumatic stress disorder, and postconcussion symptoms than the non-sports-related group.

Conclusions and Relevance

In this cohort study of 4360 patients with TBI, functional limitations 6 months after injury were common after sports-related TBI, even mild sports-related TBI. Persisting impairment was evident in the sports-related TBI group despite better recovery compared with non-sports-related TBI on measures of mental health and postconcussion symptoms. These findings caution against taking an overoptimistic view of outcomes after sports-related TBI, even if the initial injury appears mild.

Long-Term Follow-Up of Critically Ill Patients With Traumatic Brain Injury: From Intensive Care Parameters to Patient and Caregiver-Reported Outcome

Abstract Traumatic brain injury (TBI) is associated with a high social and financial burden due to persisting (severe) disabilities. The consequences of TBI after intensive care unit (ICU) admission are generally measured with global disability screeners such as the Glasgow Outcome Scale-Extended (GOSE), which may lack precision. To improve outcome measurement after brain injury, a comprehensive clinical outcome assessment tool called the Minimal Dataset for Acquired Brain Injury (MDS-ABI) was recently developed. The MDS-ABI covers 12 life domains (demographics, injury characteristics, comorbidity, cognitive functioning, emotional functioning, energy, mobility, self-care, communication, participation, social support, and quality of life), as well as informal caregiver capacity and strain. In this cross-sectional study, we used the MDS-ABI among formerly ICU admitted patients with TBI to explore the relationship between dichotomized severity of TBI and long-term outcome. Our objectives were to: 1) summarize demographics, clinical characteristics, and long-term outcomes of patients and their informal caregivers, and 2) compare differences between long-term outcomes in patients with mild-moderate TBI and severe TBI based on Glasgow Coma Scale (GCS) scores at admission. Participants were former patients of a Dutch university hospital (total n = 52; mild-moderate TBI n = 23; severe TBI n = 29) and their informal caregivers (n = 45). Hospital records were evaluated, and the MDS-ABI was administered during a home visit. On average 3.2 years after their TBI, 62% of the patients were cognitively impaired, 62% reported elevated fatigue, and 69% experienced restrictions in ≥2 participation domains (most frequently work or education and going out). Informal caregivers generally felt competent to provide necessary care (81%), but 31% experienced a disproportionate caregiver burden. All but four patients lived at home independently, often together with their informal caregiver (81%). Although the mild-moderate TBI group and the severe TBI group had significantly different clinical trajectories, there were no persisting differences between the groups for patient or caregiver outcomes at follow-up. As a large proportion of the patients experienced long-lasting consequences beyond global disability or independent living, clinicians should implement a multi-domain outcome set such as the MDS-AB to follow up on their patients.

Prognostic Models for Global Functional Outcome and Post-Concussion Symptoms Following Mild Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study

After mild traumatic brain injury (mTBI), a substantial proportion of individuals do not fully recover on the Glasgow Outcome Scale Extended (GOSE) or experience persistent post-concussion symptoms (PPCS). We aimed to develop prognostic models for the GOSE and PPCS at 6 months after mTBI and to assess the prognostic value of different categories of predictors (clinical variables; questionnaires; computed tomography [CT]; blood biomarkers). From the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we included participants aged 16 or older with Glasgow Coma Score (GCS) 13-15. We used ordinal logistic regression to model the relationship between predictors and the GOSE, and linear regression to model the relationship between predictors and the Rivermead Post-concussion Symptoms Questionnaire (RPQ) total score. First, we studied a pre-specified Core model. Next, we extended the Core model with other clinical and sociodemographic variables available at presentation (Clinical model). The Clinical model was then extended with variables assessed before discharge from hospital: early post-concussion symptoms, CT variables, biomarkers, or all three categories (extended models). In a subset of patients mostly discharged home from the emergency department, the Clinical model was extended with 2-3-week post-concussion and mental health symptoms. Predictors were selected based on Akaike's Information Criterion. Performance of ordinal models was expressed as a concordance index (C) and performance of linear models as proportion of variance explained (R2). Bootstrap validation was used to correct for optimism. We included 2376 mTBI patients with 6-month GOSE and 1605 patients with 6-month RPQ. The Core and Clinical models for GOSE showed moderate discrimination (C = 0.68 95% confidence interval 0.68 to 0.70 and C = 0.70[0.69 to 0.71], respectively) and injury severity was the strongest predictor. The extended models had better discriminative ability (C = 0.71[0.69 to 0.72] with early symptoms; 0.71[0.70 to 0.72] with CT variables or with blood biomarkers; 0.72[0.71 to 0.73] with all three categories). The performance of models for RPQ was modest (R2 = 4% Core; R2 = 9% Clinical), and extensions with early symptoms increased the R2 to 12%. The 2-3-week models had better performance for both outcomes in the subset of participants with these symptoms measured (C = 0.74 [0.71 to 0.78] vs. C = 0.63[0.61 to 0.67] for GOSE; R2 = 37% vs. 6% for RPQ). In conclusion, the models based on variables available before discharge have moderate performance for the prediction of GOSE and poor performance for the prediction of PPCS. Symptoms assessed at 2-3 weeks are required for better predictive ability of both outcomes. The performance of the proposed models should be examined in independent cohorts.

Use of Support Vector Machines Approach via ComBat Harmonized Diffusion Tensor Imaging for the Diagnosis and Prognosis of Mild Traumatic Brain Injury: A CENTER-TBI Study

The prediction of functional outcome after mild traumatic brain injury (mTBI) is challenging. Conventional magnetic resonance imaging (MRI) does not do a good job of explaining the variance in outcome, as many patients with incomplete recovery will have normal-appearing clinical neuroimaging. More advanced quantitative techniques such as diffusion MRI (dMRI), can detect microstructural changes not otherwise visible, and so may offer a way to improve outcome prediction. In this study, we explore the potential of linear support vector classifiers (linearSVCs) to identify dMRI biomarkers that can predict recovery after mTBI. Simultaneously, the harmonization of fractional anisotropy (FA) and mean diffusivity (MD) via ComBat was evaluated and compared for the classification performances of the linearSVCs. We included dMRI scans of 179 mTBI patients and 85 controls from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI), a multi-center prospective cohort study, up to 21 days post-injury. Patients were dichotomized according to their Extended Glasgow Outcome Scale (GOSE) scores at 6 months into complete (n = 92; GOSE = 8) and incomplete (n = 87; GOSE <8) recovery. FA and MD maps were registered to a common space and harmonized via the ComBat algorithm. LinearSVCs were applied to distinguish: (1) mTBI patients from controls and (2) mTBI patients with complete from those with incomplete recovery. The linearSVCs were trained on (1) age and sex only, (2) non-harmonized, (3) two-category-harmonized ComBat, and (4) three-category-harmonized ComBat FA and MD images combined with age and sex. White matter FA and MD voxels and regions of interest (ROIs) within the John Hopkins University (JHU) atlas were examined. Recursive feature elimination was used to identify the 10% most discriminative voxels or the 10 most discriminative ROIs for each implementation. mTBI patients displayed significantly higher MD and lower FA values than controls for the discriminative voxels and ROIs. For the analysis between mTBI patients and controls, the three-category-harmonized ComBat FA and MD voxel-wise linearSVC provided significantly higher classification scores (81.4% accuracy, 93.3% sensitivity, 80.3% F1-score, and 0.88 area under the curve [AUC], p < 0.05) compared with the classification based on age and sex only and the ROI approaches (accuracies: 59.8% and 64.8%, respectively). Similar to the analysis between mTBI patients and controls, the three-category-harmonized ComBat FA and MD maps voxelwise approach yields statistically significant prediction scores between mTBI patients with complete and those with incomplete recovery (71.8% specificity, 66.2% F1-score and 0.71 AUC, p < 0.05), which provided a modest increase in the classification score (accuracy: 66.4%) compared with the classification based on age and sex only and ROI-wise approaches (accuracy: 61.4% and 64.7%, respectively). This study showed that ComBat harmonized FA and MD may provide additional information for diagnosis and prognosis of mTBI in a multi-modal machine learning approach. These findings demonstrate that dMRI may assist in the early detection of patients at risk of incomplete recovery from mTBI.

Neuro-psychiatric symptoms in directly and indirectly blast exposed civilian survivors of urban missile attacks

BACKGROUND

Blast-explosion may cause traumatic brain injury (TBI), leading to post-concussion syndrome (PCS). In studies on military personnel, PCS symptoms are highly similar to those occurring in post-traumatic stress disorder (PTSD), questioning the overlap between these syndromes. In the current study we assessed PCS and PTSD in civilians following exposure to rocket attacks. We hypothesized that PCS symptomatology and brain connectivity will be associated with the objective physical exposure, while PTSD symptomatology will be associated with the subjective mental experience.

METHODS

Two hundred eighty nine residents of explosion sites have participated in the current study. Participants completed self-report of PCS and PTSD. The association between objective and subjective factors of blast and clinical outcomes was assessed using multivariate analysis. White-matter (WM) alterations and cognitive abilities were assessed in a sub-group of participants (n = 46) and non-exposed controls (n = 16). Non-parametric analysis was used to compare connectivity and cognition between the groups.

RESULTS

Blast-exposed individuals reported higher PTSD and PCS symptomatology. Among exposed individuals, those who were directly exposed to blast, reported higher levels of subjective feeling of danger and presented WM hypoconnectivity. Cognitive abilities did not differ between groups. Several risk factors for the development of PCS and PTSD were identified.

CONCLUSIONS

Civilians exposed to blast present higher PCS/PTSD symptomatology as well as WM hypoconnectivity. Although symptoms are sub-clinical, they might lead to the future development of a full-blown syndrome and should be considered carefully. The similarities between PCS and PTSD suggest that despite the different etiology, namely, the physical trauma in PCS and the emotional trauma in PTSD, these are not distinct syndromes, but rather represent a combined biopsychological disorder with a wide spectrum of behavioral, emotional, cognitive and neurological symptoms.

Traumatic Brain Injury during the SARS-CoV-2 Pandemics in Slovenia: A Single Center Study

(1) Background: The SARS-CoV-2 pandemic had a significant impact on the management of traumatic brain injury (TBI). We aimed to compare the clinical characteristics and outcomes of TBI patients before and during the SARS-CoV-2 pandemic.; (2) Methods: We analyzed depicted data from existing medical records on sex, age, mechanism of injury, clinical performance at admission and discharge, neuroimaging, laboratory values at admission, mortality, duration of hospitalization, and referrals after discharge from the traumatology department for all adult patients during the SARS-CoV-2 pandemic and a year before. Variables were compared using the Chi-square or t-test between both groups.; (3) Results: Most patients had mild (n = 477), followed by moderate (11) and severe (11) TBI. Mild TBI was less frequent during the SARS-CoV-2 period (n = 174 vs. n = 303). The incidence of high falls increased during the SARS-CoV-2 period (14.5% vs. 24.7%; p < 0.05) in the group with mild TBI. Patients had similar mean Glasgow Coma Scales (GCS), Glasgow Outcome Scales-Extended (GOSE), and glucose levels at admission before and during the pandemic. Serum ethanol levels were significantly lower during the SARS-CoV-2 period (1.3 ± 0.7 mmol/L vs. 0.7 ± 1.2 mmol/L; p < 0.001). At discharge, the mean GCS was significantly lower (14.7 ± 1.8 vs. 14.1 ± 0.5; p < 0.05) for patients treated during the SARS-CoV-2 period than before the SARS-CoV-2 period. There were no differences in GOSE; (4) Conclusions: our results demonstrated a significant impact of SARS-CoV-2 pandemic on the frequency, mechanism, and consequences of TBI, and may help improve care for our patients.

Risk Factors for High Symptom Burden Three Months after Traumatic Brain Injury and Implications for Clinical Trial Design: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study

More than 75% of patients presenting to level I trauma centers in the United States with suspicion of TBI sufficient to require a clinical computed tomography scan report injury-related symptoms 3 months later. There are currently no approved treatments, and few clinical trials have evaluated possible treatments. Efficient trials will require subject inclusion and exclusion criteria that balance cost-effective recruitment with enrolling individuals with a higher chance of benefiting from the interventions. Using data from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study, we examined the relationship of 3-month symptoms to pre-injury, demographic, and acute characteristics as well as 2-week symptoms and blood-based biomarkers to identify and evaluate factors that may be used for sample enrichment for clinical trials. Many of the risk factors for TBI symptoms reported in the literature were supported, but the effect sizes of each were small or moderate (< 0.5). The only factors with large effect sizes when predicting 3-month symptom burden were TBI-related (i.e., post-concussive) and post-traumatic stress symptom levels at 2 weeks (respective effect sizes 1.13 and 1.34). TBI severity was not significantly associated with 3-month symptom burden (p = 0.37). Using simulated data to evaluate the effect of enrichment, we showed that including only people with high symptom burden at 2 weeks would permit trials to reduce the sample size by half, with minimal increase in screening, as compared with enrolling an unenriched sample. Clinical trials aimed at reducing symptoms after TBI can be efficiently conducted by enriching the included sample with people reporting a high early symptom burden.

A Systematic Review of Treatments of Post-Concussion Symptoms

Approximately 10−20% of patients who have sustained a mild Traumatic Brain Injury (mTBI) show persistent post-concussion symptoms (PCS). This review aims to summarize the level of evidence concerning interventions for PCS. Following the PRISMA guidelines, we conducted a systematic review regarding interventions for PCS post-mTBI until August 2021 using the Medline, Cochrane, and Embase databases. Inclusion criteria were the following: (1) intervention focusing on PCS after mTBI, (2) presence of a control group, and (3) adult patients (≥18 y.o). Quality assessment was determined using the Incog recommendation level, and the risk of bias was assessed using the revised Cochrane risk-of-bias tool. We first selected 104 full-text articles. Finally, 55 studies were retained, including 35 that obtained the highest level of evidence. The risk of bias was high in 22 out of 55 studies. Cognitive training, psycho-education, cognitive behavioral therapy, and graded return to physical activity demonstrated some effectiveness on persistent PCS. However, there is limited evidence of the beneficial effect of Methylphenidate. Oculomotor rehabilitation, light therapy, and headache management using repetitive transcranial magnetic stimulation seem effective regarding somatic complaints and sleep disorders. The preventive effect of early (<3 months) interventions remains up for debate. Despite its limitations, the results of the present review should encourage clinicians to propose a tailored treatment to patients according to the type and severity of PCS and could encourage further research with larger groups.

Post-Concussion Symptoms Rule: Derivation and Validation of a Clinical Decision Rule for Early Prediction of Persistent Symptoms after a Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is a common problem. Depending on diagnostic criteria, 13 to 62% of those patients develop persistent post-concussion symptoms (PPCS). The main objective of this prospective multi-center study is to derive and validate a clinical decision rule (CDR) for the early prediction of PPCS. Patients aged ≥14 years were included if they presented to one of our seven participating emergency departments (EDs) within 24 h of an mTBI. Clinical data were collected in the ED, and symptom evolution was assessed at 7, 30 and 90 days post-injury using the Rivermead Post-Concussion Questionnaire (RPQ). The primary outcome was PPCS at 90 days after mTBI. A predictive model called the Post-Concussion Symptoms Rule (PoCS Rule) was developed using the methodological standards for CDR. Of the 1083 analyzed patients (471 and 612 for the derivation and validation cohorts, respectively), 15.6% had PPCS. The final model included the following factors assessed in the ED: age, sex, history of prior TBI or mental health disorder, headache in ED, cervical sprain and hemorrhage on computed tomography. The 7-day follow-up identified additional risk factors: headaches, sleep disturbance, fatigue, sensitivity to light, and RPQ ≥21. The PoCS Rule had a sensitivity of 91.4% and 89.6%, a specificity of 53.8% and 44.7% and a negative predictive value of 97.2% and 95.8% in the derivation and validation cohorts, respectively. The PoCS Rule will help emergency physicians quickly stratify the risk of PPCS in mTBI patients and better plan post-discharge resources.

Management of moderate to severe traumatic brain injury: an update for the intensivist

Traumatic brain injury (TBI) remains one of the most fatal and debilitating conditions in the world. Current clinical management in severe TBI patients is mainly concerned with reducing secondary insults and optimizing the balance between substrate delivery and consumption. Over the past decades, multimodality monitoring has become more widely available, and clinical management protocols have been published that recommend potential interventions to correct pathophysiological derangements. Even while evidence from randomized clinical trials is still lacking for many of the recommended interventions, these protocols and algorithms can be useful to define a clear standard of therapy where novel interventions can be added or be compared to. Over the past decade, more attention has been paid to holistic management, in which hemodynamic, respiratory, inflammatory or coagulation disturbances are detected and treated accordingly. Considerable variability with regards to the trajectories of recovery exists. Even while most of the recovery occurs in the first months after TBI, substantial changes may still occur in a later phase. Neuroprognostication is challenging in these patients, where a risk of self-fulfilling prophecies is a matter of concern. The present article provides a comprehensive and practical review of the current best practice in clinical management and long-term outcomes of moderate to severe TBI in adult patients admitted to the intensive care unit.

Does poor methodological quality of prediction modeling studies translate to poor model performance? An illustration in traumatic brain injury

BACKGROUND

Prediction modeling studies often have methodological limitations, which may compromise model performance in new patients and settings. We aimed to examine the relation between methodological quality of model development studies and their performance at external validation.

METHODS

We systematically searched for externally validated multivariable prediction models that predict functional outcome following moderate or severe traumatic brain injury. Risk of bias and applicability of development studies was assessed with the Prediction model Risk Of Bias Assessment Tool (PROBAST). Each model was rated for its presentation with sufficient detail to be used in practice. Model performance was described in terms of discrimination (AUC), and calibration. Delta AUC (dAUC) was calculated to quantify the percentage change in discrimination between development and validation for all models. Generalized estimation equations (GEE) were used to examine the relation between methodological quality and dAUC while controlling for clustering.

RESULTS

We included 54 publications, presenting ten development studies of 18 prediction models, and 52 external validation studies, including 245 unique validations. Two development studies (four models) were found to have low risk of bias (RoB). The other eight publications (14 models) showed high or unclear RoB. The median dAUC was positive in low RoB models (dAUC 8%, [IQR - 4% to 21%]) and negative in high RoB models (dAUC - 18%, [IQR - 43% to 2%]). The GEE showed a larger average negative change in discrimination for high RoB models (- 32% (95% CI: - 48 to - 15) and unclear RoB models (- 13% (95% CI: - 16 to - 10)) compared to that seen in low RoB models.

CONCLUSION

Lower methodological quality at model development associates with poorer model performance at external validation. Our findings emphasize the importance of adherence to methodological principles and reporting guidelines in prediction modeling studies.

Neuroanatomical Substrates and Symptoms Associated With Magnetic Resonance Imaging of Patients With Mild Traumatic Brain Injury

Importance

Persistent symptoms after mild traumatic brain injury (mTBI) represent a major public health problem.

Objective

To identify neuroanatomical substrates of mTBI and the optimal timing for magnetic resonance imaging (MRI).

Design, Setting, and Participants

This prospective multicenter cohort study encompassed all eligible patients from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study (December 19, 2014, to December 17, 2017) and a local cohort (November 20, 2012, to December 19, 2013). Patients presented to the hospital within 24 hours of an mTBI (Glasgow Coma Score, 13-15), satisfied local criteria for computed tomographic scanning, and underwent MRI scanning less than 72 hours (MR1) and 2 to 3 weeks (MR2) after injury. In addition, 104 control participants were enrolled across all sites. Data were analyzed from January 1, 2019, to December 31, 2020.

Exposure

Mild TBI.

Main Outcomes and Measures

Volumes and diffusion parameters were extracted via automated bespoke pipelines. Symptoms were measured using the Rivermead Post Concussion Symptoms Questionnaire in the short term and the extended Glasgow Outcome Scale at 3 months.

Results

Among the 81 patients included in the analysis (73 CENTER-TBI and 8 local), the median age was 45 (interquartile range [IQR], 24-59; range, 14-85) years, and 57 (70.4%) were male. Structural sequences were available for all scans; diffusion data, for 73 MR1 and 79 MR2 scans. After adjustment for multiple comparisons between scans, visible lesions did not differ significantly, but cerebral white matter volume decreased (MR2:MR1 ratio, 0.98; 95% CI, 0.96-0.99) and ventricular volume increased (MR2:MR1 ratio, 1.06; 95% CI, 1.02-1.10). White matter volume was within reference limits on MR1 scans (patient to control ratio, 0.99; 95% CI, 0.97-1.01) and reduced on MR2 scans (patient to control ratio, 0.97; 95% CI, 0.95-0.99). Diffusion parameters changed significantly between scans in 13 tracts, following 1 of 3 trajectories. Symptoms measured by Rivermead Post Concussion Symptoms Questionnaire scores worsened in the progressive injury phenotype (median, +5.00; IQR, +2.00 to +5.00]), improved in the minimal change phenotype (median, -4.50; IQR, -9.25 to +1.75), and were variable in the pseudonormalization phenotype (median, 0.00; IQR, -6.25 to +9.00) (P = .02). Recovery was favorable for 33 of 65 patients (51%) and was more closely associated with MR1 than MR2 (area under the curve, 0.87 [95% CI, 0.78-0.96] vs 0.75 [95% CI, 0.62-0.87]; P = .009).

Conclusions and Relevance

These findings suggest that advanced MRI reveals potential neuroanatomical substrates of mTBI in white matter and is most strongly associated with odds of recovery if performed within 72 hours, although future validation is required.