Temporal lobe contusions on computed tomography are associated with impaired 6-month functional recovery after mild traumatic brain injury: a TRACK-TBI study

Imaging Findings in Acute Traumatic Brain Injury: a National Institute of Neurological Disorders and Stroke Common Data Element-Based Pictorial Review and Analysis of Over 4000 Admission Brain Computed Tomography Scans from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study

In 2010, the National Institute of Neurological Disorders and Stroke (NINDS) created a set of common data elements (CDEs) to help standardize the assessment and reporting of imaging findings in traumatic brain injury (TBI). However, as opposed to other standardized radiology reporting systems, a visual overview and data to support the proposed standardized lexicon are lacking. We used over 4000 admission computed tomography (CT) scans of patients with TBI from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study to develop an extensive pictorial overview of the NINDS TBI CDEs, with visual examples and background information on individual pathoanatomical lesion types, up to the level of supplemental and emerging information (e.g., location and estimated volumes). We documented the frequency of lesion occurrence, aiming to quantify the relative importance of different CDEs for characterizing TBI, and performed a critical appraisal of our experience with the intent to inform updating of the CDEs. In addition, we investigated the co-occurrence and clustering of lesion types and the distribution of six CT classification systems. The median age of the 4087 patients in our dataset was 50 years (interquartile range, 29-66; range, 0-96), including 238 patients under 18 years old (5.8%). Traumatic subarachnoid hemorrhage (45.3%), skull fractures (37.4%), contusions (31.3%), and acute subdural hematoma (28.9%) were the most frequently occurring CT findings in acute TBI. The ranking of these lesions was the same in patients with mild TBI (baseline Glasgow Coma Scale [GCS] score 13-15) compared with those with moderate-severe TBI (baseline GCS score 3-12), but the frequency of occurrence was up to three times higher in moderate-severe TBI. In most TBI patients with CT abnormalities, there was co-occurrence and clustering of different lesion types, with significant differences between mild and moderate-severe TBI patients. More specifically, lesion patterns were more complex in moderate-severe TBI patients, with more co-existing lesions and more frequent signs of mass effect. These patients also had higher and more heterogeneous CT score distributions, associated with worse predicted outcomes. The critical appraisal of the NINDS CDEs was highly positive, but revealed that full assessment can be time consuming, that some CDEs had very low frequencies, and identified a few redundancies and ambiguity in some definitions. Whilst primarily developed for research, implementation of CDE templates for use in clinical practice is advocated, but this will require development of an abbreviated version. In conclusion, with this study, we provide an educational resource for clinicians and researchers to help assess, characterize, and report the vast and complex spectrum of imaging findings in patients with TBI. Our data provides a comprehensive overview of the contemporary landscape of TBI imaging pathology in Europe, and the findings can serve as empirical evidence for updating the current NINDS radiologic CDEs to version 3.0.

Data-driven distillation and precision prognosis in traumatic brain injury with interpretable machine learning

Traumatic brain injury (TBI) affects how the brain functions in the short and long term. Resulting patient outcomes across physical, cognitive, and psychological domains are complex and often difficult to predict. Major challenges to developing personalized treatment for TBI include distilling large quantities of complex data and increasing the precision with which patient outcome prediction (prognoses) can be rendered. We developed and applied interpretable machine learning methods to TBI patient data. We show that complex data describing TBI patients' intake characteristics and outcome phenotypes can be distilled to smaller sets of clinically interpretable latent factors. We demonstrate that 19 clusters of TBI outcomes can be predicted from intake data, a ~ 6× improvement in precision over clinical standards. Finally, we show that 36% of the outcome variance across patients can be predicted. These results demonstrate the importance of interpretable machine learning applied to deeply characterized patients for data-driven distillation and precision prognosis.

Glibenclamide for Brain Contusions: Contextualizing a Promising Clinical Trial Design that Leverages an Imaging-Based TBI Endotype

TBI heterogeneity is recognized as a major impediment to successful translation of therapies that could improve morbidity and mortality after injury. This heterogeneity exists on multiple levels including primary injury, secondary injury/host-response, and recovery. One widely accepted type of primary-injury related heterogeneity is pathoanatomic-the intracranial compartment that is predominantly affected, which can include any combination of subdural, subarachnoid, intraparenchymal, diffuse axonal, intraventricular and epidural hemorrhages. Intraparenchymal contusions carry the highest risk for progression. Contusion expansion is one of the most important drivers of death and disability after TBI. Over the past decade, there has been increasing evidence of the role of the sulfonylurea-receptor 1-transient receptor potential melastatin 4 (SUR1-TRPM4) channel in secondary injury after TBI, including progression of both cerebral edema and intraparenchymal hemorrhage. Inhibition of SUR1-TRPM4 with glibenclamide has shown promising results in preclinical models of contusional TBI with benefits against cerebral edema, secondary hemorrhage progression of the contusion, and improved functional outcome. Early-stage human research supports the key role of this pathway in contusion expansion and suggests a benefit with glibenclamide inhibition. ASTRAL is an ongoing international multi-center double blind multidose placebo-controlled phase-II clinical trial evaluating the safety and efficacy of an intravenous formulation of glibenclamide (BIIB093). ASTRAL is a unique and innovative study that addresses TBI heterogeneity by limiting enrollment to patients with the TBI pathoanatomic endotype of brain contusion and using contusion-expansion (a mechanistically linked secondary injury) as its primary outcome. Both criteria are consistent with the strong supporting preclinical and molecular data. In this narrative review, we contextualize the development and design of ASTRAL, including the need to address TBI heterogeneity, the scientific rationale underlying the focus on brain contusions and contusion-expansion, and the preclinical and clinical data supporting benefit of SUR1-TRPM4 inhibition in this specific endotype. Within this framework, we summarize the current study design of ASTRAL which is sponsored by Biogen and actively enrolling with a goal of 160 participants.

Evaluating the state of non-invasive imaging biomarkers for traumatic brain injury

Non-invasive imaging biomarkers are useful for prognostication in patients with traumatic brain injury (TBI) at high risk for morbidity with invasive procedures. The authors present findings from a scoping review discussing the pertinent biomarkers. Embase, Ovid-MEDLINE, and Scopus were queried for original research on imaging biomarkers for prognostication of TBI in adult patients. Two reviewers independently screened articles, extracted data, and evaluated risk of bias. Data was synthesized and confidence evaluated with the linked evidence according to the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach. Our search yielded 3104 unique citations, 44 of which were included in this review. Study populations varied in TBI severity, as defined by Glasgow Coma Scale (GCS), including: mild (n=9), mild and moderate (n=3), moderate and severe (n=7), severe (n=6), and all GCS scores (n=17). Diverse imaging modalities were used for prognostication, predominantly computed tomography (CT) only (n=11), magnetic resonance imaging (MRI) only (n=9), and diffusion tensor imaging (DTI) (N=9). The biomarkers included diffusion coefficient mapping, metabolic characteristics, optic nerve sheath diameter, T1-weighted signal changes, cortical cerebral blood flow, axial versus extra-axial lesions, T2-weighted gradient versus spin echo, translocator protein levels, and trauma imaging of brainstem areas. The majority (93%) of studies identified that the imaging biomarker of interest had a statistically significant prognostic value; however, these are based on a very low to low level of quality of evidence. No study directly compared the effects on specific TBI treatments on the temporal course of imaging biomarkers. The current literature is insufficient to make a strong recommendation about a preferred imaging biomarker for TBI, especially considering GRADE criteria revealing low quality of evidence. Rigorous prospective research of imaging biomarkers of TBI is warranted to improve the understanding of TBI severity.

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.

Volumetric MRI Findings in Mild Traumatic Brain Injury (mTBI) and Neuropsychological Outcome

Region of interest (ROI) volumetric assessment has become a standard technique in quantitative neuroimaging. ROI volume is thought to represent a coarse proxy for making inferences about the structural integrity of a brain region when compared to normative values representative of a healthy sample, adjusted for age and various demographic factors. This review focuses on structural volumetric analyses that have been performed in the study of neuropathological effects from mild traumatic brain injury (mTBI) in relation to neuropsychological outcome. From a ROI perspective, the probable candidate structures that are most likely affected in mTBI represent the target regions covered in this review. These include the corpus callosum, cingulate, thalamus, pituitary-hypothalamic area, basal ganglia, amygdala, and hippocampus and associated structures including the fornix and mammillary bodies, as well as whole brain and cerebral cortex along with the cerebellum. Ventricular volumetrics are also reviewed as an indirect assessment of parenchymal change in response to injury. This review demonstrates the potential role and limitations of examining structural changes in the ROIs mentioned above in relation to neuropsychological outcome. There is also discussion and review of the role that post-traumatic stress disorder (PTSD) may play in structural outcome in mTBI. As emphasized in the conclusions, structural volumetric findings in mTBI are likely just a single facet of what should be a multimodality approach to image analysis in mTBI, with an emphasis on how the injury damages or disrupts neural network integrity. The review provides an historical context to quantitative neuroimaging in neuropsychology along with commentary about future directions for volumetric neuroimaging research in mTBI.

Functional Connectivity in the Mouse Brainstem Represents Signs of Recovery from Concussion

Mild traumatic brain injury (mTBI) is one of the most frequent neurological disorders. Diagnostic criteria for mTBI are based on cognitive or neurological symptoms without fully understanding the neuropathological basis for explaining behaviors. From the neuropathological perspective of mTBI, recent neuroimaging studies have focused on structural or functional differences in motor-related cortical regions but did not compare topological network properties between the post-concussion days in the brainstem. We investigated temporal changes in functional connectivity and evaluated network properties of functional networks in the mouse brainstem. We observed a significantly decreased functional connectivity and global and local network properties on post-concussion day 7, which normalized on post-concussion day 14. Functional connectivity and local network properties on post-concussion day 2 were also significantly decreased compared with those on post-concussion day 14, but there were no significant group differences in global network properties between days 2 and 14. We also observed that the local efficiency and clustering coefficient of the brainstem network were significantly correlated with anxiety-like behaviors on post-concussion days 7 and 14. This study suggests that functional connectivity in the mouse brainstem provides vital recovery signs from concussion through functional reorganization.

Post-Concussion Symptoms and Disability in Adults with Mild Traumatic Brain Injury: A Systematic Review and Meta-Analysis

Studies investigating long-term symptoms and disability after mild traumatic brain injury (mTBI) have yielded mixed results. This systematic review and meta-analysis aimed to determine the prevalence of self-reported post-concussion symptoms (PCS) and disability following mTBI. We systematically searched MEDLINE, Embase, CINAHL, CENTRAL, and PsycInfo to identify inception cohort studies of adults with mTBI. Paired reviewers independently extracted data and assessed risk of bias with the Scottish Intercollegiate Guidelines Network criteria. We identified 43 eligible studies for the systematic review; 41 were rated as high risk of bias, primarily due to high attrition (> 20%). Twenty-one studies (49%) were included in the meta-analyses (five studies were narratively synthesized; 17 studies were duplicate reports). At 3-6 months post-injury, the estimated prevalence of PCS from random-effects meta-analyses was 31.3% (95% confidence interval [CI] = 25.4-38.4) using a lenient definition of PCS (2-4 mild severity PCS) and 18.3% (95% CI = 13.6-24.0) using a more stringent definition. The estimated prevalence of disability was 54.0% (95% CI = 49.4-58.6) and 29.6% (95% CI = 27.8-31.5) when defined as Glasgow Outcome Scale-Extended <8 and <7, respectively. The prevalence of symptoms similar to PCS was higher in adults with mTBI versus orthopedic injury (prevalence ratio = 1.57, 95% CI = 1.22-2.02). In a meta-regression, attrition rate was the only study-related factor significantly associated with higher estimated prevalence of PCS. Setting attrition to 0%, the estimated prevalence of PCS (lenient definition) was 16.1%. We conclude that nearly one in three adults who present to an emergency department or trauma center with mTBI report at least mild severity PCS 3-6 months later, but controlling for attrition bias, the true prevalence may be one in six. Studies with representative samples and high retention rates are needed.

Relationship between size and location of infarction beside lateral ventricle and motor recovery following rehabilitation

BACKGROUND: The lesions besides lateral ventricle and motor recovery following rehabilitation have hardly been studied. OBJECTIVE: To explore the relationship between the size, location of infarction beside the lateral ventricle and motor recovery following rehabilitation. METHODS: A prospective cohort of 55 patients submitted to a Rehabilitation Medical Center between January 2015 and June 2019 who suffered a single cerebral infarction beside the lateral ventricle were included in the study. The size and distance between the posterior margin and the frontal-middle line (FML) of the lesion were measured. Follow-up was conducted until the recovery was no longer progressing. Barthel index and Brunstrom stages were used to evaluate the outcome (full recovery, partial recovery and poor recovery). Variance analysis and nonparametric test were used for the comparison between groups. Multivariate logistic regression analysis was used to screen the factors affecting the outcomes. The Pearson correlation coefficient was used to compare the volume of infarction, behind the FML and the outcomes. RESULTS: Among the 55 patients, the outcome was full recovery (n = 28), partial recovery (n = 13) and poor recovery (n = 14). Multivariate logistic regression analysis showed that volume and location of the infarction were significantly correlated with the outcome (p = 0.039, 0.050). The lesion volume in the full recovery patients was significantly smaller than that in the poor recovery patients (p <  0.01). The posterior edge of the lesion in the full recovery patients behind the FML was statistically significant compared with that in the poor recovery patients (p <  0.01). Spearman correlation analysis showed that the motor recovery was negative correlation to lesion volume (r = –0.508, P <  0.01) and location (r = –0.450, P <  0.01) of the infarction. CONCLUSION: The motor recovery of patients with cerebral infarction beside lateral ventricle is related to the volume and location of the lesion. The larger the volume of the lesion, and the farther the posterior margin of the lesion to the FML, the worse the motor recovery.

Posttraumatic Headaches and Postcraniotomy Syndromes

Headaches following head trauma or craniotomy have multiple causes, each of which has characteristic imaging features. Posttraumatic headaches may relate to intracranial hemorrhage, fracture, shear injury, mass effect, or vascular injury. Various complications of craniotomy and craniectomy may manifest with headache. CT and MRI of the brain play important roles in diagnosing these causes of headache.

Return to work after mild traumatic brain injury: association with positive CT and MRI findings

Background

Return to work (RTW) might be delayed in patients with complicated mild traumatic brain injury (MTBI), i.e., MTBI patients with associated traumatic intracranial lesions. However, the effect of different types of lesions on RTW has not studied before. We investigated whether traumatic intracranial lesions detected by CT and MRI are associated with return to work and post-concussion symptoms in patients with MTBI.

Methods

We prospectively followed up 113 adult patients with MTBI that underwent a brain MRI within 3–17 days after injury. Return to work was assessed with one-day accuracy up to one year after injury. Rivermead Post-Concussion Symptoms Questionnaire (RPQ) and Glasgow Outcome Scale Extended (GOS-E) were conducted one month after injury. A Kaplan–Meier log-rank analysis was performed to analyze the differences in RTW.

Results

Full RTW-% one year after injury was 98%. There were 38 patients with complicated MTBI, who had delayed median RTW compared to uncomplicated MTBI group (17 vs. 6 days), and more post-concussion symptoms (median RPQ 12.0 vs. 6.5). Further, RTW was more delayed in patients with multiple types of traumatic intracranial lesions visible in MRI (31 days, n = 19) and when lesions were detected in the primary CT (31 days, n = 24). There were no significant differences in GOS-E.

Conclusions

The imaging results that were most clearly associated with delayed RTW were positive primary CT and multiple types of lesions in MRI. RTW-% of patients with MTBI was excellent and a single intracranial lesion does not seem to be a predictive factor of disability to work.

Mild-to-Moderate Traumatic Brain Injury: A Review with Focus on the Visual System

Traumatic Brain Injury (TBI) is a major global public health problem. Neurological damage from TBI may be mild, moderate, or severe and occurs both immediately at the time of impact (primary injury) and continues to evolve afterwards (secondary injury). In mild (m)TBI, common symptoms are headaches, dizziness and fatigue. Visual impairment is especially prevalent. Insomnia, attentional deficits and memory problems often occur. Neuroimaging methods for the management of TBI include computed tomography and magnetic resonance imaging. The location and the extent of injuries determine the motor and/or sensory deficits that result. Parietal lobe damage can lead to deficits in sensorimotor function, memory, and attention span. The processing of visual information may be disrupted, with consequences such as poor hand-eye coordination and balance. TBI may cause lesions in the occipital or parietal lobe that leave the TBI patient with incomplete homonymous hemianopia. Overall, TBI can interfere with everyday life by compromising the ability to work, sleep, drive, read, communicate and perform numerous activities previously taken for granted. Treatment and rehabilitation options available to TBI sufferers are inadequate and there is a pressing need for new ways to help these patients to optimize their functioning and maintain productivity and participation in life activities, family and community.

Relationship Between CT Head Findings and Long-term Recovery in Children with Complicated Mild Traumatic Brain Injury

PRIMARY OBJECTIVE

Complicated mild traumatic brain injury (C-mTBI) refers to CT positive patients with clinically mild TBI. This study investigates the association between CT head findings at time of injury and recovery of paediatric patients with C-mTBI.

RESEARCH DESIGN

Retrospective survey and chart review.

METHODS

For paediatric patients with C-mTBI (N = 77), CT findings associated with corresponding degree and lengths of recovery from C-mTBI using logistic regression analysis.

RESULTS

There was a trend that the odds of incomplete recovery at the time of survey was higher for older children than for younger children (OR = 1.14, 95% CI = 0.98-1.32, p = 0.072). There was a trend that the odds of incomplete recovery (OR = 6.26, 95% CI = 0.97-40.57, p = 0.054) and longer duration for recovery (OR = 8.14, 95% CI = 0.78-84.46, p = 0.079) was higher for children with multiple haemorrhagic contusions than those with single haemorrhagic contusion. No other imaging patterns predicted degree or length of recovery with statistical significance (p > 0.05).

CONCLUSIONS

Other than the presence of multiple haemorrhagic contusions, no other pattern of imaging abnormality in paediatric C-mTBI appears to be associated with degree or length of recovery. Further studies with larger cohorts are encouraged.

A Prognostic Model for Predicting One-Month Outcomes among Emergency Department Patients with Mild Traumatic Brain Injury and a Presenting Glasgow Coma Scale of Fifteen

The lack of well-performing prognostic models for early prognostication of outcomes remains a major barrier to improving the clinical care of patients with mild traumatic brain injury (mTBI). We aimed to derive a prognostic model for predicting incomplete recovery at 1-month in emergency department (ED) patients with mTBI and a presenting Glasgow Coma Scale (GCS) score of 15 who were enrolled in the HeadSMART (Head Injury Serum Markers for Assessing Response to Trauma) study. The derivation cohort included 355 participants with complete baseline (day-of-injury) and follow-up data. The primary outcome measure was the Glasgow Outcome Scale Extended (GOSE) at 1-month and incomplete recovery was defined as a GOSE <8. At 1-month post-injury, incomplete recovery was present in 58% (n = 205) of participants. The final multi-variable logistic regression model included six variables: age in years (odds ratio [OR] = 0.98; 95% confidence interval [CI]: 0.97-1.00), positive head CT (OR = 4.42; 95% CI: 2.21-9.33), history of depression (OR = 2.59; 95% CI: 1.47-4.69), and self-report of moderate or severe headache (OR = 2.49; 95% CI: 1.49-4.18), difficulty concentrating (OR = 3.17; 95% CI: 1.53-7.04), and photophobia (OR = 4.17; 95% CI: 2.08-8.92) on the day-of-injury. The model was validated internally using bootstrap resampling (1000 resamples), which revealed a mean over-optimism value of 0.01 and an optimism-corrected area under the curve (AUC) of 0.79 (95% CI: 0.75-0.85). A prognostic model for predicting incomplete recovery among ED patients with mTBI and a presenting GCS of 15 using easily obtainable clinical and demographic variables has acceptable discriminative accuracy. External validation of this model is warranted.

Magnetic Resonance Imaging Findings Are Associated with Long-Term Global Neurological Function or Death after Traumatic Brain Injury in Critically Ill Children

The identification of children with traumatic brain injury (TBI) who are at risk of death or poor global neurological functional outcome remains a challenge. Magnetic resonance imaging (MRI) can detect several brain pathologies that are a result of TBI; however, the types and locations of pathology that are the most predictive remain to be determined. Forty-two critically ill children with TBI were recruited prospectively from pediatric intensive care units at five Canadian children's hospitals. Pathologies detected on subacute phase MRIs included cerebral hematoma, herniation, cerebral laceration, cerebral edema, midline shift, and the presence and location of cerebral contusion or diffuse axonal injury (DAI) in 28 regions of interest were assessed. Global functional outcome or death more than 12 months post-injury was assessed using the Pediatric Cerebral Performance Category score. Linear modeling was employed to evaluate the utility of an MRI composite score for predicting long-term global neurological function or death after injury, and nonlinear Random Forest modeling was used to identify which MRI features have the most predictive utility. A linear predictive model of favorable versus unfavorable long-term outcomes was significantly improved when an MRI composite score was added to clinical variables. Nonlinear Random Forest modeling identified five MRI variables as stable predictors of poor outcomes: presence of herniation, DAI in the parietal lobe, DAI in the subcortical white matter, DAI in the posterior corpus callosum, and cerebral contusion in the anterior temporal lobe. Clinical MRI has prognostic value to identify children with TBI at risk of long-term unfavorable outcomes.

Predictors of six-month inability to return to work in previously employed subjects after mild traumatic brain injury: A TRACK-TBI pilot study

Introduction:

Return to work (RTW) is an important milestone of mild traumatic brain injury (mTBI) recovery. The objective of this study was to evaluate whether baseline clinical variables, three-month RTW, and three-month postconcussional symptoms (PCS) were associated with six-month RTW after mTBI.

Methods:

Adult subjects from the prospective multicenter Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot study with mTBI (Glasgow Coma Scale 13–15) who were employed at baseline, with completed three-and six-month RTW status, and three-month Acute Concussion Evaluation (ACE), were extracted. Univariate and multivariable analyses were performed for six-month RTW, with focus on baseline employment, three-month RTW, and three-month ACE domains (physical, cognitive, sleep, and/or emotional postconcussional symptoms (PCS)). Odds ratios (OR) and 95% confidence intervals [CI] were reported. Significance was assessed at p < 0.05.

Results:

In 152 patients aged 40.7 ± 15.0years, 72% were employed full-time at baseline. Three- and six-month RTW were 77.6% and 78.9%, respectively. At three months, 59.2%, 47.4%, 46.1% and 31.6% scored positive for ACE physical, cognitive, sleep, and emotional PCS domains, respectively. Three-month RTW predicted six-month RTW (OR = 19.80, 95% CI [7.61–51.52]). On univariate analysis, scoring positive in any three-month ACE domain predicted inability for six-month RTW (OR = 0.10–0.11). On multivariable analysis, emotional symptoms predicted inability to six-month RTW (OR = 0.19 [0.04–0.85]). Subjects who scored positive in all four ACE domains were more likely to be unable to RTW at six months (4 domains: 58.3%, vs. 0-to-3 domains: 9.5%; multivariable OR = 0.09 [0.02–0.33]).

Conclusions:

Three-month post-injury is an important time point at which RTW status and PCS should be assessed, as both are prognostic markers for six-month RTW. Clinicians should be particularly vigilant of patients who present with emotional symptoms, and patients with symptoms across multiple PCS categories, as these patients are at further risk of inability to RTW and may benefit from targeted evaluation and support.

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.

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 majority of traumatic brain injuries (TBIs) are categorized as mild, according to a baseline Glasgow Coma Scale (GCS) score of 13-15. Prognostic models that were developed to predict functional outcome and persistent post-concussive symptoms (PPCS) after mild TBI have rarely been externally validated. We aimed to externally validate models predicting 3-12-month Glasgow Outcome Scale Extended (GOSE) or PPCS in adults with mild TBI. We analyzed data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) project, which included 2862 adults with mild TBI, with 6-month GOSE available for 2374 and Rivermead Post-Concussion Symptoms Questionnaire (RPQ) results available for 1605 participants. Model performance was evaluated based on calibration (graphically and characterized by slope and intercept) and discrimination (C-index). We validated five published models for 6-month GOSE and three for 6-month PPCS scores. The models used different cutoffs for outcome and some included symptoms measured 2 weeks post-injury. Discriminative ability varied substantially (C-index between 0.58 and 0.79). The models developed in the Corticosteroid Randomisation After Significant Head Injury (CRASH) trial for prediction of GOSE <5 discriminated best (C-index 0.78 and 0.79), but were poorly calibrated. The best performing models for PPCS included 2-week symptoms (C-index 0.75 and 0.76). In conclusion, none of the prognostic models for early prediction of GOSE and PPCS has both good calibration and discrimination in persons with mild TBI. In future studies, prognostic models should be tailored to the population with mild TBI, predicting relevant end-points based on readily available predictors.

Polytrauma Is Associated with Increased Three- and Six-Month Disability after Traumatic Brain Injury: A TRACK-TBI Pilot Study

Polytrauma and traumatic brain injury (TBI) frequently co-occur and outcomes are routinely measured by the Glasgow Outcome Scale-Extended (GOSE). Polytrauma may confound GOSE measurement of TBI-specific outcomes. Adult patients with TBI from the prospective Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study had presented to a Level 1 trauma center after injury, received head computed tomography (CT) within 24 h, and completed the GOSE at 3 months and 6 months post-injury. Polytrauma was defined as an Abbreviated Injury Score (AIS) ≥3 in any extracranial region.

Univariate regressions were performed using known GOSE clinical cutoffs. Multi-variable regressions were performed for the 3- and 6-month GOSE, controlling for known demographic and injury predictors. Of 361 subjects (age 44.9 ± 18.9 years, 69.8% male), 69 (19.1%) suffered polytrauma. By Glasgow Coma Scale (GCS) assessment, 80.1% had mild, 5.8% moderate, and 14.1% severe TBI. On univariate logistic regression, polytrauma was associated with increased odds of moderate disability or worse (GOSE ≤6; 3 month odds ratio [OR] = 2.57 [95% confidence interval (CI): 1.50-4.41; 6 month OR = 1.70 [95% CI: 1.01-2.88]) and death/severe disability (GOSE ≤4; 3 month OR = 3.80 [95% CI: 2.03-7.11]; 6 month OR = 3.33 [95% CI: 1.71-6.46]). Compared with patients with isolated TBI, more polytrauma patients experienced a decline in GOSE from 3 to 6 months (37.7 vs. 24.7%), and fewer improved (11.6 vs. 22.6%). Polytrauma was associated with greater univariate ordinal odds for poorer GOSE (3 month OR = 2.79 [95% CI: 1.73-4.49]; 6 month OR = 1.73 [95% CI: 1.07-2.79]), which was conserved on multi-variable ordinal regression (3 month OR = 3.05 [95% CI: 1.76-5.26]; 6 month OR = 2.04 [95% CI: 1.18-3.42]). Patients with TBI with polytrauma are at greater risk for 3- and 6-month disability compared with those with isolated TBI. Methodological improvements in assessing TBI-specific disability, versus disability attributable to all systemic injuries, will generate better TBI outcomes assessment tools.

Traumatic Brain Injury: Imaging Patterns and Complications

While the diagnosis of traumatic brain injury (TBI) is a clinical decision, neuroimaging remains vital for guiding management on the basis of identification of intracranial pathologic conditions. CT is the mainstay of imaging of acute TBI for both initial triage and follow-up, as it is fast and accurate in detecting both primary and secondary injuries that require neurosurgical intervention. MRI is more sensitive for the detection of certain intracranial injuries (eg, axonal injuries) and blood products 24-48 hours after injury, but it has limitations (eg, speed, accessibility, sensitivity to motion, and cost). The evidence primarily supports the use of MRI when CT findings are normal and there are persistent unexplained neurologic findings or at subacute and chronic periods. Radiologists should understand the role and optimal imaging modality to use, in addition to patterns of primary brain injury and their influence on the risk of developing secondary brain injuries related to herniation. ^©RSNA, 2019 See discussion on this article by Mathur and Nicolaou.

Age and sex-mediated differences in six-month outcomes after mild traumatic brain injury in young adults: a TRACK-TBI study

Introduction: Risk factors for young adults with mTBI are not well understood. Improved understanding of age and sex as risk factors for impaired six-month outcomes in young adults is needed. Methods: Young adult mTBI subjects aged 18-39 years (18-29y; 30-39y) with six-month outcomes were extracted from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study. Multivariable regressions were performed for outcomes with age, sex, and the interaction factor age-group*sex as variables of interest, controlling for demographic and injury variables. Mean-differences (B) and 95% CIs are reported. Results: One hundred mTBI subjects (18-29y, 70%; 30-39y, 30%; male, 71%; female, 29%) met inclusion criteria. On multivariable analysis, age-group*sex was associated with six-month post-traumatic stress disorder (PTSD; PTSD Checklist-Civilian version); compared with female 30-39y, female 18-29y (B= -19.55 [-26.54, -4.45]), male 18-29y (B= -19.70 [-30.07, -9.33]), and male 30-39y (B= -15.49 [-26.54, -4.45]) were associated with decreased PTSD symptomatology. Female sex was associated with decreased six-month functional outcome (Glasgow Outcome Scale-Extended (GOSE): B= -0.6 [1.0, -0.1]). Comparatively, 30-39y scored higher on six-month nonverbal processing speed (Wechsler Adult Intelligence Scale-Processing Speed Index (WAIS-PSI); B= 11.88, 95% CI [1.66, 22.09]). Conclusions: Following mTBI, young adults aged 18-29y and 30-39y may have different risks for impairment. Sex may interact with age for PTSD symptomatology, with females 30-39y at highest risk. These results may be attributable to cortical maturation, biological response, social modifiers, and/or differential self-report. Confirmation in larger samples is needed; however, prevention and rehabilitation/counseling strategies after mTBI should likely be tailored for age and sex.