Traumatic Brain Injury: Imaging Patterns and Complications

Computed tomography imaging findings in head injury victims of conflict in Northern Ethiopia treated at the University of Gondar comprehensive specialized hospital

BACKGROUND

Head injuries pose a major global health issue, especially among young adults in developing countries. Data on head trauma patterns in conflict situations is scarce, and computed tomography (CT) is the main imaging method for evaluating acute head injuries.

OBJECTIVES

This study aimed to assess the CT scan patterns of traumatic head injury among northern Ethiopian victims of war who were treated at the University of Gondar Comprehensive Specialized Hospital during the armed conflict in 2020 and 2021.

METHODS

A cross-sectional study was conducted on 76 cases of traumatic head injury who underwent CT scans from November 1, 2020, to January 30, 2021, at the Department of Radiology. Data regarding age, sex, mechanism of injury, and CT scan findings were collected and analyzed.

RESULTS

A total of 76 patients were assessed, with 73 (96.1%) being males and a male-to-female ratio of 24:1. Ages ranged from 19 to 48 years, with the most affected group being ≤ 29 years (44 or 57.9%). Common head injury mechanisms included bullets (50%), blunt trauma (26%), and blasts (21%). Abnormal CT findings were noted in 60 cases (78.95%), with the most common findings being skull fractures (64.5%), cerebral contusions (33%), and metallic foreign bodies (36%). Scalp and brain hematoma, presence of soft tissue foreign body, pneumocephalus, and subfalcine herniation exhibited a statistically significant correlation with bullet injuries (p-value < 0.05).

CONCLUSION

This study found a high rate of abnormal CT scans mainly involving young males as the primary victims of traumatic head injuries in war-affected areas of Northern Ethiopia. The leading causes were bullet injuries, with common CT scan findings including skull fractures and cerebral contusions, many requiring immediate intervention. The high rate of abnormal CT scans in these patients underscores the need to improve access to CT scans in conflict-affected areas.

A Survey on the Management of Patients with Severe Traumatic Brain Injury During Pregnancy: The MAMA Study

BACKGROUND

Trauma, including traumatic brain injury (TBI), is the leading cause of nonobstetric maternal mortality during pregnancy. Few data are available regarding the optimal management of pregnant patients with TBI, leading to a lack of dedicated guidelines. We performed an international survey to examine the management of severe TBI in pregnant patients, focusing on monitoring, therapy, and intensive care practices.

METHODS

This survey, endorsed by the World Society of Emergency Surgery, was composed of a questionnaire with 79 items divided into four sections: (1) general information (items 1-7), (2) management of the maternal-fetal unit (items 8-43), (3) management of intracranial hypertension (items 44-76), and (4) specific considerations (items 77-79).

RESULTS

One hundred and twenty-two physicians from 110 centers in 35 countries responded. The main findings related to TBI care in pregnant patients included the following: (1) a lack of availability of a specific TBI protocol in pregnancy; (2) an increase in the utilization of magnetic resonance imaging as the primary neuroimaging tool; (3) higher hemoglobin thresholds for transfusion; and (4) a lower utilization of therapeutic hypothermia, neuromuscular blocking agents, and barbiturate coma. We also report large variability in the timing of cesarean section in pregnant patients with TBI (≥ 23 weeks of gestation) needing an emergency craniotomy (simultaneously 23% vs. later cesarean section 50.8%).

CONCLUSIONS

Great variability in the management of pregnant patients with severe TBI was identified worldwide from the results of our survey. These findings, highlighting the lack of robust evidence on this topic, will be helpful to stimulate future investigations and to promote educational efforts on this difficult scenario.

Magnetic resonance imaging in traumatic brain injury: a survey of clinical practitioners' experiences and views on current practice and obstacles

INTRODUCTION

Magnetic resonance imaging (MRI) has revolutionized our capacity to examine brain alterations in traumatic brain injury (TBI). However, little is known about the level of implementation of MRI techniques in clinical practice in TBI and associated obstacles.

METHODS

A diverse set of health professionals completed 19 multiple choice and free text survey questions.

RESULTS

Of the 81 respondents, 73.4% reported that they acquire/order MRI scans in TBI patients, and 66% indicated they would prefer MRI be more often used with this cohort. The greatest impediment for MRI usage was scanner availability (57.1%). Less than half of respondents (42.1%) indicated that they perform advanced MRI analysis. Factors such as dedicated experts within the team (44.4%) and user-friendly MRI analysis tools (40.7%), were listed as potentially helpful to implement advanced MRI analyses in clinical practice.

CONCLUSION

Results suggest a wide variability in the purpose, timing, and composition of the scanning protocol of clinical MRI after TBI. Three recommendations are described to broaden implementation of MRI in clinical practice in TBI: 1) development of a standardized multimodal MRI protocol; 2) future directions for the use of advanced MRI analyses; 3) use of low-field MRI to overcome technical/practical issues with high-field MRI.

Protective effects of wogonin in the treatment of central nervous system and degenerative diseases

Wogonin, an O-methylated flavonoid extracted from Scutellaria baicalensis, has demonstrated profound neuroprotective effects in a range of central nervous system (CNS) diseases. This review elucidates the pharmacological mechanisms underlying the protective effects of wogonin in CNS diseases, including ischemic stroke, hemorrhagic stroke, traumatic brain injury, epilepsy, anxiety, neurodegenerative diseases, and CNS infections. Wogonin modulates key signaling pathways, such as the MAPK, NF-κB, and ROS pathways, contributing to its anti-inflammatory, antioxidant, and antiapoptotic properties. In ischemic stroke models, wogonin reduces infarct size and enhances neurological outcomes by mitigating inflammation and oxidative stress. For patients with hemorrhagic stroke and traumatic brain injury, it accelerates hematoma regression, mitigates secondary brain damage, and promotes neurogenesis, making it an entirely new treatment option for patients with limited access to this type of therapy. Its anticonvulsant and anxiolytic effects are mediated through GABA-A receptor modulation. Moreover, wogonin shows promise in treating neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease by promoting autophagy and reducing neuroinflammation. Additionally, it exhibits antiviral properties, offering potential benefits against CNS infections. Despite extensive preclinical evidence, further clinical studies are warranted to confirm its efficacy and safety in humans. This review highlights the great therapeutic potential of wogonin in terms of CNS protection. However, despite the substantial preclinical evidence, further large-scale clinical studies are necessary. Future researchers need to further explore the long-term efficacy and safety of wogonin in clinical trials and translate it for early application in the clinical treatment of true CNS disorders.

Risk Estimation of Deep Venous Thrombosis in Polytrauma Patients with Traumatic Brain Injury: A Nomogram Approach

Background

Deep venous thrombosis (DVT), known to be a major factor in poor outcomes and death rates, is common after polytrauma with traumatic brain injury (TBI). In this study, a nomogram will be developed to predict the risk of DVT in polytrauma patients with TBI, since there is currently no specific and convenient diagnostic method.

Methods

A retrospective and observational trial was conducted between November 2021 and May 2023. The predictive model was created using a group of 349 polytrauma patients with TBI in a training set, with data collected between November 2021 and August 2022. A nomogram was presented after using multivariable logistic regression analysis to create the predictive model. Validation of the model was conducted internally. A separate group for validation included 298 patients seen consecutively between August 2022 and May 2023.

Results

A total of 647 trauma patients were included in the study. Out of these, 349 individuals were part of the training group, while 298 were part of the validation group. Training cohorts reported 32.1% and validation cohorts reported 31.9% DVT. Age, Smoking, Injury Severity Score (ISS), Glasgow Coma Scale (GCS), D-dimer, Mechanical ventilation (MV) and Application of Vasoactive Drugs (AVD) comprised the individualized prediction nomogram. The model exhibited strong discrimination, achieving a C-index of 0.783 and a statistically insignificant result (P=0.216) following the Hosmer-Lemeshow test. Nomogram calibration plots and decision curve analysis showed the nomogram's utility in predicting DVT.

Conclusion

Our study characterized the incidence of DVT in polytrauma patients with TBI and further emphasized that it represented a substantial health concern, as evidenced by its frequency. Using this nomogram, it is possible to predict DVT in polytrauma patients with TBI based on demographics and clinical risk factors.

Exploring New and Promising Genetic Biomarkers for Evaluating Traumatic Brain Injuries: A Case-Control Study

Traumatic brain injury (TBI) is a common cause of morbidity and death in all age groups, with an estimated 50 million people having brain injury due to trauma each year. Accurate blood-based biomarkers are needed to assist with diagnosis of patients across the spectrum of time and severity. Our objectives were to explore the diagnostic precision of time- and severity- related four blood-based biomarkers: AKT3, GSK-3β, hsa-miR-16-5p, and MALAT-1 for TBI for the purpose of diagnosis, prognosis, and follow-up. 40 samples were recruited as the following: 30 TBI patients and 10 healthy volunteers as controls with matched age and sex. They were divided according to the Glasgow Coma Scale into mild (mTBI), moderate (modTBI), and severe(sTBI) TBI. Blood samples were withdrawn at entry, and after 5 and 30 days, RT-PCR was used for measuring the expression level. The results showed upregulated expression levels of AKT3, hsa-miR-16-5p and significantly downregulated expression levels of GSK-3β in TBI patients compared to controls at all timings measured. mTBI patients showed a higher expression level of hsa-miR-16-5p compared with modTBI, and sTBI patients. MALAT-1 level showed a significant increase in severe cases only. We concluded that AKT3, hsa-miR-16-5p, and GSK-3β are excellent diagnostic biomarkers in TBI patients at initial assessment, as well as at 5 and 30 days following the injury. Moreover, MALAT-1 had good diagnostic value in sTBI patients, and its prognostic value extends to 30 days. GSK-3β was an excellent biomarker for detecting mTBI.

Traumatic posterior fossa extradural hematoma in children: a meta-analysis and institutional experience of its clinical course, treatment and outcomes

Posterior fossa extradural hematoma (PFEDH) is rare but has a greater incidence amongst children. It is also associated with a rapid deterioration. The aim of this study was to present the management of PFEDH through our institutional experience and a meta-analysis. A retrospective single institution review of all children from 2004 to 2024 who underwent craniotomy for PFEDH was undertaken. The collected variables included: demographics, type of trauma, clinical findings, computed tomography findings, and clinical course. A systematic review using Ovid Medline, Ovid Embase, and Cochrane Central Register of Controlled Trials (CENTRAL), and meta-analysis were performed. Nineteen children with PFEDH who underwent surgery were identified. All 19 (100%) patients benefited from good Glasgow Outcome Scale (GOS) score 4-5, and there were no incidences of in-hospital mortality. From the systematic review, 391 patients, across twenty-four studies and our series, were included. A total of 308 were treated with surgery, whereas 83 patients were treated conservatively. A comparative meta-analysis was not performed as the two groups were deemed too heterogeneous in clinical characteristics. Instead, single-arm meta-analyses were performed. The pooled incidence of patients initially under conservative management requiring surgery was 9.90% (95%CI 1.61;22.21%, I2 = 35.2). The incidence of good functional outcomes in patients managed surgically and conservatively were 93.68% (95%CI: 88.69;97.57%, I2 = 0.0%), and 99.99% (95%CI: 96.53;100%, I2 = 0.0%), respectively. Overall pooled of mortality in patients managed surgically and conservatively were 0.57% (95%CI: 0.00;2.87%, I2 = 0.0%) and 0.00% (95%CI: 0.00;1.18%, I2 = 0.0%). Overall, our study reiterates that pediatric PFEDH is uncommon, and patients often present atypically. Based on our institutional experience and extrapolating data from our meta-analysis of the wider literature, neurosurgical intervention is a reliable therapeutic option with good clinical outcomes.

Brain Function and Structure Changes in the Prognosis Prediction of Prolonged Disorders of Consciousness

OBJECTIVES

To observe the functional differences in the key brain areas in patients with different levels of consciousness after severe brain injury, and provide reference for confirming the objective diagnosis indicators for prolonged disorders of consciousness (pDoCs).

METHODS

This prospective study enrolled patients with pDoCs hospitalized in the department of rehabilitation medicine of our Hospital. Levels of consciousness and clinical outcomes were assessed according to diagnostic criteria and behavioral scales. Resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) of 30 patients with different levels of consciousness was performed. The patients were grouped as conscious or unconscious according to whether they regained consciousness during the 12-month follow-up.

RESULTS

Thirty patients were enrolled, including eight with unresponsive wakefulness syndrome/vegetative state, eight with minimally conscious state, six with emergence from the minimally conscious state, and eight with a locked-in syndrome. There were 19 and 11 patients in the conscious and unconscious groups. Compared with the unconscious group, the left basal nucleus was activated in the conscious group, and there were significant differences in white matter fiber bundles. Correlations were observed between the regional homogeneity (ReHo) value of the cerebellum and the Glasgow coma scale score (r = 0.387, P = 0.038) and between the ReHo value of the left temporal and the coma recovery scale-revised score (r = 0.394, P = 0.035).

CONCLUSIONS

The left insula and cerebellum might be important for regaining consciousness. The brain function activity and structural remodeling of the key brain regions and the activation level of the cerebellum are correlated with clinical behaviors and have potential application value for the prognosis prediction of pDoCs patients.

Evaluation of a compact cone beam CT concept with high image fidelity for point-of-care brain imaging

Cone beam computed tomography (CBCT) has potential advantages for developing portable, cost-effective point-of-care CT systems for intracranial imaging, such as early stroke diagnosis, hemorrhage detection, and intraoperative navigation. However, large volume imaging with flat panel detector based CBCT significantly increases the scattered radiation fluence which reduces its image quality and utility. To address these issues, a compact CBCT concept with enhanced image quality was investigated for intracranial imaging. The new system features a novel antiscatter collimator and data correction method to address the challenges in imaging large volumes with CBCT. A benchtop CBCT prototype was constructed. Imaging studies with anthropomorphic phantoms showed that soft tissue visualization, Hounsfield Unit (HU) accuracy, contrast, and spatial resolution increased significantly with the proposed CBCT concept, and they were comparable to the values measured in the gold standard multidetector-row CT (MDCT) images. Contrast-to-noise ratio (CNR) in CBCT images was within 12-31% of the CNR in MDCT images. These findings indicate that a compact CBCT system integrated with effective scatter suppression techniques may have increased utility in the context of brain imaging, and the proposed approach may enable the development of point-of-care CT systems for head imaging based on flat panel detector based CBCT technology.

Feasibility of thin-slice, low noise images created using multi-kernel synthesis to replace multiple image series in head CT

BACKGROUND

SynthesiZed Improved Resolution and Concurrent nOise reductioN (ZIRCON) is a multi-kernel synthesis method that creates a single series of thin-slice computed tomography (CT) images displaying low noise and high spatial resolution, increasing reader efficiency and minimizing partial volume averaging.

PURPOSE

To compare the diagnostic performance of a single set of ZIRCON images to two routine clinical image series using conventional CT head and bone reconstruction kernels for diagnosing intracranial findings and fractures in patients with trauma or suspected acute neurologic deficit.

MATERIAL AND METHODS

In total, 50 patients underwent clinically indicated head CT in the ER (15 normal, 35 abnormal cases). A non-reader neuroradiologist established the reference standard. Three neuroradiologists reviewed two routine clinical series (head and bone kernels) and a single ZIRCON series, detecting intracranial findings or fractures and rating confidence (0-100). Sensitivity, specificity, and jackknife free-response receiver operating characteristic (JAFROC) figure of merit (FOM) were compared (limit of non-inferiority: -0.10).

RESULTS

ZIRCON and conventional images demonstrated comparable performance for fractures (sensitivity: 51.5% vs. 54.5%; specificity: 40.2% vs. 34.2%) and intracranial findings (sensitivity: 88.2% vs. 91.4%; specificity: 77.2% vs. 73.7%).The estimated difference of JAFROC FOM demonstrated ZIRCON non-inferiority for acute pathologies overall (0.003 [95% CI=-0.051-0.057]) and fractures (0.048 [95% CI=-0.050-0.145]) but not for intracranial findings alone (-0.024 [95% CI=-0.100-0.052]).

CONCLUSION

Thin-slice, low noise, and high spatial resolution images can be created to display intracranial findings and fractures replacing multiple images series in head CT with similar performance. Future studies in more patients and further algorithmic development are warranted.

Portable Six-Channel Laser Speckle System for Simultaneous Cerebral Blood Flow and Volume Measurement with Potential Application for Characterization of Brain Injury

In regional cerebrovascular monitoring, cerebral blood flow (CBF) and cerebral blood volume (CBV) are key metrics. Simultaneous, non-invasive measurement of CBF and CBV at different brain locations would advance cerebrovascular monitoring and pave the way for brain injury detection, as current brain injury diagnostic methods are often constrained by high costs, limited sensitivity, and reliance on subjective symptom reporting. This study's aim is to develop a multi-channel non-invasive optical system for measuring CBF and CBV at different regions of the brain simultaneously with a cost-effective, reliable, and scalable system capable of detecting potential differences in CBF and CBV across different regions of the brain. The system is based on speckle contrast optical spectroscopy (SCOS) and consists of laser diodes and board cameras which have been both tested and investigated for safe use on the human head. Results on a cohort of five healthy subjects indicated that the dynamics of both CBF and CBV were synchronized and exhibited similar cardiac period waveforms across all six channels. As a preliminary investigation, we also explored the potential use of our six-channel system for detecting the physiological sequela of brain injury, involving a subject with significant structural brain damage compared to another with lesser structural brain damage. The six-point CBF and CBV measurements were compared to MRI scans, revealing that regions with altered blood dynamics closely correlated with the injury sites identified by MRI.

Traumatic brain injuries: a neuropsychological review

The best predictor of functional outcome in victims of traumatic brain injury (TBI) is a neuropsychological evaluation. An exponential growth of research into TBI has focused on diagnosis and treatment. Extant literature lacks a comprehensive neuropsychological review that is simultaneously scholarly and practical. In response, our group included, and went beyond a general overview of TBI's, which commonly include definition, types, severity, and pathophysiology. We incorporate reasons behind the use of particular neuroimaging techniques, as well as the most recent findings on common neuropsychological assessments conducted in TBI cases, and their relationship to outcome. In addition, we include tables outlining estimated recovery trajectories of different age groups, their risk factors and we encompass phenomenological studies, further covering the range of existing-promising tools for cognitive rehabilitation/remediation purposes. Finally, we highlight gaps in current research and directions that would be beneficial to pursue.

Disrupted Maturation of White Matter Microstructure After Concussion Is Associated With Internalizing Behavior Scores in Female Children

BACKGROUND

Some children who experience concussions, particularly females, develop long-lasting emotional and behavioral problems. Establishing the potential contribution of preexisting behavioral problems and disrupted white matter maturation has been challenging due to a lack of preinjury data.

METHODS

From the Adolescent Brain Cognitive Development cohort, 239 (90 female) children age 12.1 ± 0.6 years who experienced a concussion after study entry at 10.0 ± 0.6 years were compared to 6438 (3245 female) children without head injuries who were age 9.9 ± 0.6 years at baseline and 12.0 ± 0.6 years at follow-up. The Child Behavior Checklist was used to assess internalizing and externalizing behavior at study entry and follow-up. In the children with magnetic resonance imaging data available (concussion n = 134, comparison n = 3520), deep and superficial white matter was characterized by neurite density from restriction spectrum image modeling of diffusion magnetic resonance imaging. Longitudinal ComBat harmonization removed scanner effects. Linear regressions modeled 1) behavior problems at follow-up controlling for baseline behavior, 2) impact of concussion on white matter maturation, and 3) contribution of deviations in white matter maturation to postconcussion behavior problems.

RESULTS

Only female children with concussion had higher internalizing behavior problem scores. The youngest children with concussion showed less change in superficial white matter neurite density over 2 years than children with no concussion. In females with concussion, less change in superficial white matter neurite density was correlated with increased internalizing behavior problem scores.

CONCLUSIONS

Concussions in female children are associated with emotional problems beyond preinjury levels. Injury to superficial white matter may contribute to persistent internalizing behavior problems in females.

Innovations in detecting skull fractures: A review of computer-aided techniques in CT imaging

BACKGROUND/INTRODUCTION

Traumatic brain injury (TBI) remains a leading cause of disability and mortality, with skull fractures being a frequent and serious consequence. Accurate and rapid diagnosis of these fractures is crucial, yet current manual methods via cranial CT scans are time-consuming and prone to error.

METHODS

This review paper focuses on the evolution of computer-aided diagnosis (CAD) systems for detecting skull fractures in TBI patients. It critically assesses advancements from feature-based algorithms to modern machine learning and deep learning techniques. We examine current approaches to data acquisition, the use of public datasets, algorithmic strategies, and performance metrics RESULTS: The review highlights the potential of CAD systems to provide quick and reliable diagnostics, particularly outside regular clinical hours and in under-resourced settings. Our discussion encapsulates the challenges inherent in automated skull fracture assessment and suggests directions for future research to enhance diagnostic accuracy and patient care.

CONCLUSION

With CAD systems, we stand on the cusp of significantly improving TBI management, underscoring the need for continued innovation in this field.

Rate of abnormalities in quantitative MR neuroimaging of persons with chronic traumatic brain injury

BACKGROUND

Mild traumatic brain injury (mTBI) can result in lasting brain damage that is often too subtle to detect by qualitative visual inspection on conventional MR imaging. Although a number of FDA-cleared MR neuroimaging tools have demonstrated changes associated with mTBI, they are still under-utilized in clinical practice.

METHODS

We investigated a group of 65 individuals with predominantly mTBI (60 mTBI, 48 due to motor-vehicle collision, mean age 47 ± 13 years, 27 men and 38 women) with MR neuroimaging performed in a median of 37 months post-injury. We evaluated abnormalities in brain volumetry including analysis of left-right asymmetry by quantitative volumetric analysis, cerebral perfusion by pseudo-continuous arterial spin labeling (PCASL), white matter microstructure by diffusion tensor imaging (DTI), and neurometabolites via magnetic resonance spectroscopy (MRS).

RESULTS

All participants demonstrated atrophy in at least one lobar structure or increased lateral ventricular volume. The globus pallidi and cerebellar grey matter were most likely to demonstrate atrophy and asymmetry. Perfusion imaging revealed significant reductions of cerebral blood flow in both occipital and right frontoparietal regions. Diffusion abnormalities were relatively less common though a subset analysis of participants with higher resolution DTI demonstrated additional abnormalities. All participants showed abnormal levels on at least one brain metabolite, most commonly in choline and N-acetylaspartate.

CONCLUSION

We demonstrate the presence of coup-contrecoup perfusion injury patterns, widespread atrophy, regional brain volume asymmetry, and metabolic aberrations as sensitive markers of chronic mTBI sequelae. Our findings expand the historic focus on quantitative imaging of mTBI with DTI by highlighting the complementary importance of volumetry, arterial spin labeling perfusion and magnetic resonance spectroscopy neurometabolite analyses in the evaluation of chronic mTBI.

Research progress and prospects of benefit-risk assessment methods for umbilical cord mesenchymal stem cell transplantation in the clinical treatment of spinal cord injury

Over the past decade, we have witnessed the development of cell transplantation as a new strategy for repairing spinal cord injury (SCI). However, due to the complexity of the central nervous system (CNS), achieving successful clinical translation remains a significant challenge. Human umbilical cord mesenchymal stem cells (hUMSCs) possess distinct advantages, such as easy collection, lack of ethical concerns, high self-renewal ability, multilineage differentiation potential, and immunomodulatory properties. hUMSCs are promising for regenerating the injured spinal cord to a significant extent. At the same time, for advancing SCI treatment, the appropriate benefit and risk evaluation methods play a pivotal role in determining the clinical applicability of treatment plans. Hence, this study discusses the advantages and risks of hUMSCs in SCI treatment across four dimensions-comprehensive evaluation of motor and sensory function, imaging, electrophysiology, and autonomic nervous system (ANS) function-aiming to improve the rationality of relevant clinical research and the feasibility of clinical translation.

Aquaporin 2 in Cerebral Edema: Potential Prognostic Marker in Craniocerebral Injuries

Despite continuous medical advancements, traumatic brain injury (TBI) remains a leading cause of death and disability worldwide. Consequently, there is a pursuit for biomarkers that allow non-invasive monitoring of patients after cranial trauma, potentially improving clinical management and reducing complications and mortality. Aquaporins (AQPs), which are crucial for transmembrane water transport, may be significant in this context. This study included 48 patients, with 27 having acute (aSDH) and 21 having chronic subdural hematoma (cSDH). Blood plasma samples were collected from the participants at three intervals: the first sample before surgery, the second at 15 h, and the third at 30 h post-surgery. Plasma concentrations of AQP1, AQP2, AQP4, and AQP9 were determined using the sandwich ELISA technique. CT scans were performed on all patients pre- and post-surgery. Correlations between variables were examined using Spearman's nonparametric rank correlation coefficient. A strong correlation was found between aquaporin 2 levels and the volume of chronic subdural hematoma and midline shift. However, no significant link was found between aquaporin levels (AQP1, AQP2, AQP4, and AQP9) before and after surgery for acute subdural hematoma, nor for AQP1, AQP4, and AQP9 after surgery for chronic subdural hematoma. In the chronic SDH group, AQP2 plasma concentration negatively correlated with the midline shift measured before surgery (Spearman's ρ -0.54; p = 0.017) and positively with hematoma volume change between baseline and 30 h post-surgery (Spearman's ρ 0.627; p = 0.007). No statistically significant correlation was found between aquaporin plasma levels and hematoma volume for AQP1, AQP2, AQP4, and AQP9 in patients with acute SDH. There is a correlation between chronic subdural hematoma volume, measured radiologically, and serum AQP2 concentration, highlighting aquaporins' potential as clinical biomarkers.

Accuracy of Early Neuroprognostication in Pediatric Severe Traumatic Brain Injury

BACKGROUND

Children with severe traumatic brain injury (sTBI) are at risk for neurological sequelae impacting function. Clinicians are tasked with neuroprognostication to assist in decision-making. We describe a single-center study assessing clinicians' neuroprognostication accuracy.

METHODS

Clinicians of various specialties caring for children with sTBI were asked to predict their patients' functioning three to six months postinjury. Clinicians were asked to participate in the study if their patient had survived but not returned to baseline between day 4 and 7 postinjury. The outcome tool utilized was the functional status scale (FSS), ranging from 6 to 30 (best-worst function). Predicted scores were compared with actual scores three to six months postinjury. Lin concordance correlation coefficients were used to estimate agreement between predicted and actual FSS. Outcome was dichotomized as good (FSS 6 to 8) or poor (FSS ≥9). Positive and negative predictive values for poor outcome were calculated. Pessimistic prognostic prediction was defined as predicted worse outcome by ≥3 FSS points. Demographic and clinical variables were collected.

RESULTS

A total of 107 surveys were collected on 24 patients. Two children died. Fifteen children had complete (FSS = 6) or near-complete (FSS = 7) recovery. Mean predicted and actual FSS scores were 10.8 (S.D. 5.6) and 8.6 (S.D. 4.1), respectively. Predicted FSS scores were higher than actual scores (P < 0.001). Eight children had collective pessimistic prognostic prediction.

CONCLUSIONS

Clinicians predicted worse functional outcomes, despite high percentage of patients with near-normal function at follow-up clinic. Certain patient and provider factors were noted to impact accuracy and need to be studied in larger cohorts.

Functional connectivity-hemodynamic (un)coupling changes in chronic mild brain injury are associated with mental health and neurocognitive indices: a resting state fMRI study

PURPOSE

To examine hemodynamic and functional connectivity alterations and their association with neurocognitive and mental health indices in patients with chronic mild traumatic brain injury (mTBI).

METHODS

Resting-state functional MRI (rs-fMRI) and neuropsychological assessment of 37 patients with chronic mTBI were performed. Intrinsic connectivity contrast (ICC) and time-shift analysis (TSA) of the rs-fMRI data allowed the assessment of regional hemodynamic and functional connectivity disturbances and their coupling (or uncoupling). Thirty-nine healthy age- and gender-matched participants were also examined.

RESULTS

Patients with chronic mTBI displayed hypoconnectivity in bilateral hippocampi and parahippocampal gyri and increased connectivity in parietal areas (right angular gyrus and left superior parietal lobule (SPL)). Slower perfusion (hemodynamic lag) in the left anterior hippocampus was associated with higher self-reported symptoms of depression (r =  - 0.53, p = .0006) and anxiety (r =  - 0.484, p = .002), while faster perfusion (hemodynamic lead) in the left SPL was associated with lower semantic fluency (r =  - 0.474, p = .002). Finally, functional coupling (high connectivity and hemodynamic lead) in the right anterior cingulate cortex (ACC)) was associated with lower performance on attention and visuomotor coordination (r =  - 0.50, p = .001), while dysfunctional coupling (low connectivity and hemodynamic lag) in the left ventral posterior cingulate cortex (PCC) and right SPL was associated with lower scores on immediate passage memory (r =  - 0.52, p = .001; r =  - 0.53, p = .0006, respectively). Uncoupling in the right extrastriate visual cortex and posterior middle temporal gyrus was negatively associated with cognitive flexibility (r =  - 0.50, p = .001).

CONCLUSION

Hemodynamic and functional connectivity differences, indicating neurovascular (un)coupling, may be linked to mental health and neurocognitive indices in patients with chronic mTBI.

Machine learning models for predicting early hemorrhage progression in traumatic brain injury

This study explores the progression of intracerebral hemorrhage (ICH) in patients with mild to moderate traumatic brain injury (TBI). It aims to predict the risk of ICH progression using initial CT scans and identify clinical factors associated with this progression. A retrospective analysis of TBI patients between January 2010 and December 2021 was performed, focusing on initial CT evaluations and demographic, comorbid, and medical history data. ICH was categorized into intraparenchymal hemorrhage (IPH), petechial hemorrhage (PH), and subarachnoid hemorrhage (SAH). Within our study cohort, we identified a 22.2% progression rate of ICH among 650 TBI patients. The Random Forest algorithm identified variables such as petechial hemorrhage (PH) and countercoup injury as significant predictors of ICH progression. The XGBoost algorithm, incorporating key variables identified through SHAP values, demonstrated robust performance, achieving an AUC of 0.9. Additionally, an individual risk assessment diagram, utilizing significant SHAP values, visually represented the impact of each variable on the risk of ICH progression, providing personalized risk profiles. This approach, highlighted by an AUC of 0.913, underscores the model's precision in predicting ICH progression, marking a significant step towards enhancing TBI patient management through early identification of ICH progression risks.

Utility of brain imaging in pediatric patients with a suspected accidental spinal injury but no brain injury-related symptoms

PURPOSE

Imaging is the gold standard in diagnosing traumatic brain injury, but unnecessary scans should be avoided, especially in children and adolescents. Clinical decision-making rules often help to distinguish the patients who need imaging, but if spinal trauma is suspected, concomitant brain imaging is often conducted. Whether the co-occurrence of brain and spine injuries is high enough to justify head imaging in patients without symptoms suggesting brain injury is unknown.

OBJECTIVE

This study aims to assess the diagnostic yield of brain MRI in pediatric patients with suspected or confirmed accidental spinal trauma but no potential brain injury symptoms.

METHODS

We retrospectively reviewed the medical and imaging data of pediatric patients (under 18 years old) who have undergone concomitant MRI of the brain and spine because of acute spinal trauma in our emergency radiology department over a period of 8 years. We compared the brain MRI findings in patients with and without symptoms suggesting brain injury and contrasted spine and brain MRI findings.

RESULTS

Of 179 patients (mean age 11.7 years, range 0-17), 137 had symptoms or clinical findings suggesting brain injury, and 42 did not. None of the patients without potential brain injury symptoms had traumatic findings in brain MRI. This finding also applied to patients with high-energy trauma (n = 47) and was unrelated to spinal MRI findings.

CONCLUSION

Pediatric accidental trauma patients with suspected or confirmed spine trauma but no symptoms or clinical findings suggesting brain injury seem not to benefit from brain imaging.

Chronic immunosuppression across 12 months and high ability of acute and subacute CNS-injury biomarker concentrations to identify individuals with complicated mTBI on acute CT and MRI

BACKGROUND

Identifying individuals with intracranial injuries following mild traumatic brain injury (mTBI), i.e. complicated mTBI cases, is important for follow-up and prognostication. The main aims of our study were (1) to assess the temporal evolution of blood biomarkers of CNS injury and inflammation in individuals with complicated mTBI determined on computer tomography (CT) and magnetic resonance imaging (MRI); (2) to assess the corresponding discriminability of both single- and multi-biomarker panels, from acute to chronic phases after injury.

METHODS

Patients with mTBI (n = 207), defined as Glasgow Coma Scale score between 13 and 15, loss of consciousness < 30 min and post-traumatic amnesia < 24 h, were included. Complicated mTBI - i.e., presence of any traumatic intracranial injury on neuroimaging - was present in 8% (n = 16) on CT (CT+) and 12% (n = 25) on MRI (MRI+). Blood biomarkers were sampled at four timepoints following injury: admission (within 72 h), 2 weeks (± 3 days), 3 months (± 2 weeks) and 12 months (± 1 month). CNS biomarkers included were glial fibrillary acidic protein (GFAP), neurofilament light (NFL) and tau, along with 12 inflammation markers.

RESULTS

The most discriminative single biomarkers of traumatic intracranial injury were GFAP at admission (CT+: AUC = 0.78; MRI+: AUC = 0.82), and NFL at 2 weeks (CT+: AUC = 0.81; MRI+: AUC = 0.89) and 3 months (MRI+: AUC = 0.86). MIP-1β and IP-10 concentrations were significantly lower across follow-up period in individuals who were CT+ and MRI+. Eotaxin and IL-9 were significantly lower in individuals who were MRI+ only. FGF-basic concentrations increased over time in MRI- individuals and were significantly higher than MRI+ individuals at 3 and 12 months. Multi-biomarker panels improved discriminability over single biomarkers at all timepoints (AUCs > 0.85 for admission and 2-week models classifying CT+ and AUC ≈ 0.90 for admission, 2-week and 3-month models classifying MRI+).

CONCLUSIONS

The CNS biomarkers GFAP and NFL were useful single diagnostic biomarkers of complicated mTBI, especially in acute and subacute phases after mTBI. Several inflammation markers were suppressed in patients with complicated versus uncomplicated mTBI and remained so even after 12 months. Multi-biomarker panels improved diagnostic accuracy at all timepoints, though at acute and 2-week timepoints, the single biomarkers GFAP and NFL, respectively, displayed similar accuracy compared to multi-biomarker panels.

Clinical Management in Traumatic Brain Injury

Traumatic brain injury is one of the leading causes of morbidity and mortality worldwide and is one of the major public healthcare burdens in the US, with millions of patients suffering from the traumatic brain injury itself (approximately 1.6 million/year) or its repercussions (2-6 million patients with disabilities). The severity of traumatic brain injury can range from mild transient neurological dysfunction or impairment to severe profound disability that leaves patients completely non-functional. Indications for treatment differ based on the injury's severity, but one of the goals of early treatment is to prevent secondary brain injury. Hemodynamic stability, monitoring and treatment of intracranial pressure, maintenance of cerebral perfusion pressure, support of adequate oxygenation and ventilation, administration of hyperosmolar agents and/or sedatives, nutritional support, and seizure prophylaxis are the mainstays of medical treatment for severe traumatic brain injury. Surgical management options include decompressive craniectomy or cerebrospinal fluid drainage via the insertion of an external ventricular drain. Several emerging treatment modalities are being investigated, such as anti-excitotoxic agents, anti-ischemic and cerebral dysregulation agents, S100B protein, erythropoietin, endogenous neuroprotectors, anti-inflammatory agents, and stem cell and neuronal restoration agents, among others.

"NeuroVanguard": a contemporary strategy in neuromonitoring for severe adult brain injury patients

Severe acute brain injuries, stemming from trauma, ischemia or hemorrhage, remain a significant global healthcare concern due to their association with high morbidity and mortality rates. Accurate assessment of secondary brain injuries severity is pivotal for tailor adequate therapies in such patients. Together with neurological examination and brain imaging, monitoring of systemic secondary brain injuries is relatively straightforward and should be implemented in all patients, according to local resources. Cerebral secondary injuries involve factors like brain compliance loss, tissue hypoxia, seizures, metabolic disturbances and neuroinflammation. In this viewpoint, we have considered the combination of specific noninvasive and invasive monitoring tools to better understand the mechanisms behind the occurrence of these events and enhance treatment customization, such as intracranial pressure monitoring, brain oxygenation assessment and metabolic monitoring. These tools enable precise intervention, contributing to improved care quality for severe brain injury patients. The future entails more sophisticated technologies, necessitating knowledge, interdisciplinary collaboration and resource allocation, with a focus on patient-centered care and rigorous validation through clinical trials.

The Australian Traumatic Brain Injury Initiative: Systematic Review of Predictive Value of Biological Markers for People With Moderate-Severe Traumatic Brain Injury

The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to co-design a data resource to predict outcomes for people with moderate-severe traumatic brain injury (TBI) across Australia. Fundamental to this resource is the data dictionary, which is an ontology of data items. Here, we report the systematic review and consensus process for inclusion of biological markers in the data dictionary. Standardized database searches were implemented from inception through April 2022. English-language studies evaluating association between a fluid, tissue, or imaging marker and any clinical outcome in at least 10 patients with moderate-severe TBI were included. Records were screened using a prioritization algorithm and saturation threshold in Research Screener. Full-length records were then screened in Covidence. A pre-defined algorithm was used to assign a judgement of predictive value to each observed association, and high-value predictors were discussed in a consensus process. Searches retrieved 106,593 records; 1,417 full-length records were screened, resulting in 546 included records. Two hundred thirty-nine individual markers were extracted, evaluated against 101 outcomes. Forty-one markers were judged to be high-value predictors of 15 outcomes. Fluid markers retained following the consensus process included ubiquitin C-terminal hydrolase L1 (UCH-L1), S100, and glial fibrillary acidic protein (GFAP). Imaging markers included computed tomography (CT) scores (e.g., Marshall scores), pathological observations (e.g., hemorrhage, midline shift), and magnetic resonance imaging (MRI) classification (e.g., diffuse axonal injury). Clinical context and time of sampling of potential predictive indicators are important considerations for utility. This systematic review and consensus process has identified fluid and imaging biomarkers with high predictive value of clinical and long-term outcomes following moderate-severe TBI.

Hippo cell signaling and HS-proteoglycans regulate tissue form and function, age-dependent maturation, extracellular matrix remodeling, and repair

This review examined how Hippo cell signaling and heparan sulfate (HS)-proteoglycans (HSPGs) regulate tissue form and function. Despite being a nonweight-bearing tissue, the brain is regulated by Hippo mechanoresponsive cell signaling pathways during embryonic development. HS-proteoglycans interact with growth factors, morphogens, and extracellular matrix components to regulate development and pathology. Pikachurin and Eyes shut (Eys) interact with dystroglycan to stabilize the photoreceptor axoneme primary cilium and ribbon synapse facilitating phototransduction and neurotransduction with bipolar retinal neuronal networks in ocular vision, the primary human sense. Another HSPG, Neurexin interacts with structural and adaptor proteins to stabilize synapses and ensure specificity of neural interactions, and aids in synaptic potentiation and plasticity in neurotransduction. HSPGs also stabilize the blood-brain barrier and motor neuron basal structures in the neuromuscular junction. Agrin and perlecan localize acetylcholinesterase and its receptors in the neuromuscular junction essential for neuromuscular control. The primary cilium is a mechanosensory hub on neurons, utilized by YES associated protein (YAP)-transcriptional coactivator with PDZ-binding motif (TAZ) Hippo, Hh, Wnt, transforming growth factor (TGF)-β/bone matrix protein (BMP) receptor tyrosine kinase cell signaling. Members of the glypican HSPG proteoglycan family interact with Smoothened and Patched G-protein coupled receptors on the cilium to regulate Hh and Wnt signaling during neuronal development. Control of glycosyl sulfotransferases and endogenous protease expression by Hippo TAZ YAP represents a mechanism whereby the fine structure of HS-proteoglycans can be potentially modulated spatiotemporally to regulate tissue morphogenesis in a similar manner to how Hippo signaling controls sialyltransferase expression and mediation of cell-cell recognition, dysfunctional sialic acid expression is a feature of many tumors.

Appropriate incorporation of susceptibility-weighted magnetic resonance imaging into routine imaging protocols for accurate diagnosis of traumatic brain injuries: a systematic review

Traumatic brain injury (TBI) results from physical or traumatic injuries to the brain's surrounding bony structures and associated tissues, which can lead to various sequelae, including simple concussion, acute epidural hematoma, parenchymal contusions, subarachnoid hemorrhage, diffuse axonal injury, and chronic traumatic encephalopathy. Susceptibility-weighted imaging (SWI) has enhanced the accuracy of neuroimaging for these injuries. SWI is based on 3D gradient echo magnetic resonance imaging (MRI) with long echo times and flow compensation. Owing to its sensitivity to deoxyhemoglobin, hemosiderin, iron, and calcium, SWI is extremely informative and superior to conventional MRI for the diagnosis and follow-up of patients with acute, subacute, and prolonged hemorrhage. This systematic review aimed to evaluate and summarize the published articles that report SWI results for the evaluation of TBI and to determine correlations between clinical status and SWI results. Consequently, our analysis also aimed to identify the appropriate MRI sequences to use in the assessment of patients with TBI. We searched the Medline and Embase online electronic databases for relevant papers published from 2012 onwards. We found that SWI had higher sensitivity than gradient echo MRI in detecting and characterizing microbleeds in TBIs and was able to differentiate diamagnetic calcifications from paramagnetic microhemorrhages. However, it is important that future research not only continues to evaluate the utility of SWI in TBIs but also attempts to overcome the limitations of the studies described in this review, which should help validate the conclusions and recommendations from our analysis.

Enhancing hospital course and outcome prediction in patients with traumatic brain injury: A machine learning study

PURPOSE

We aimed to use machine learning (ML) algorithms with clinical, lab, and imaging data as input to predict various outcomes in traumatic brain injury (TBI) patients.

METHODS

In this retrospective study, blood samples were analyzed for glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1). The non-contrast head CTs were reviewed by two neuroradiologists for TBI common data elements (CDE). Three outcomes were designed to predict: discharged or admitted for further management (prediction 1), deceased or not deceased (prediction 2), and admission only, prolonged stay, or neurosurgery performed (prediction 3). Five ML models were trained. SHapley Additive exPlanations (SHAP) analyses were used to assess the relative significance of variables.

RESULTS

Four hundred forty patients were used to predict predictions 1 and 2, while 271 patients were used in prediction 3. Due to Prediction 3's hospitalization requirement, deceased and discharged patients could not be utilized. The Random Forest model achieved an average accuracy of 1.00 for prediction 1 and an accuracy of 0.99 for prediction 2. The Random Forest model achieved a mean accuracy of 0.93 for prediction 3. Key features were extracranial injury, hemorrhage, UCH-L1 for prediction 1; The Glasgow Coma Scale, age, GFAP for prediction 2; and GFAP, subdural hemorrhage volume, and pneumocephalus for prediction 3, per SHAP analysis.

CONCLUSION

Combining clinical and laboratory parameters with non-contrast CT CDEs allowed our ML models to accurately predict the designed outcomes of TBI patients. GFAP and UCH-L1 were among the significant predictor variables, demonstrating the importance of these biomarkers.

Screening Performance of S100 Calcium-Binding Protein B, Glial Fibrillary Acidic Protein, and Ubiquitin C-Terminal Hydrolase L1 for Intracranial Injury Within Six Hours of Injury and Beyond

The Scandinavian NeuroTrauma Committee (SNC) guidelines recommend S100 calcium-binding protein B (S100B) as a screening tool for early detection of Traumatic brain injury (TBI) in patients presenting with an initial Glasgow Coma Scale (GCS) of 14-15. The objective of the current study was to compare S100B's diagnostic performance within the recommended 6-h window after injury, compared with glial fibrillary acidic protein (GFAP) and UCH-L1. The secondary outcome of interest was the ability of these biomarkers in detecting traumatic intracranial pathology beyond the 6-h mark. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) core database (2014-2017) was queried for data pertaining to all TBI patients with an initial GCS of 14-15 who had a blood sample taken within 6 h of injury in which the levels of S100B, GFAP, and UCH-L1 were measured. As a subgroup analysis, data involving patients with blood samples taken within 6-9 h and 9-12 h were analyzed separately for diagnostic ability. The diagnostic ability of these biomarkers for detecting any intracranial injury was evaluated based on the area under the receiver operating characteristic curve (AUC). Each biomarker's sensitivity, specificity, and accuracy were also reported at the cutoff that maximized Youden's index. A total of 531 TBI patients with GCS 14-15 on admission had a blood sample taken within 6 h, of whom 24.9% (n = 132) had radiologically confirmed intracranial injury. The AUCs of GFAP (0.86, 95% confidence interval [CI]: 0.82-0.90) and UCH-L1 (0.81, 95% CI: 0.76-0.85) were statistically significantly higher than that of S100B (0.74, 95% CI: 0.69-0.79) during this time. There was no statistically significant difference in the predictive ability of S100B when sampled within 6 h, 6-9 h, and 9-12 h of injury, as the p values were >0.05 when comparing the AUCs. Overlapping AUC 95% CI suggests no benefit of a combined GFAP and UCH-L1 screening tool over GFAP during the time periods studied [0.87 (0.83-0.90) vs. 0.86 (0.82-0.90) when sampled within 6 h of injury, 0.83 (0.78-0.88) vs. 0.83 (0.78-0.89) within 6 to 9 h and 0.81 (0.73-0.88) vs. 0.79 (0.72-0.87) within 9-12 h]. Targeted analysis of the CENTER-TBI core database, with focus on the patient category for which biomarker testing is recommended by the SNC guidelines, revealed that GFAP and UCH-L1 perform superior to S100B in predicting CT-positive intracranial lesions within 6 h of injury. GFAP continued to exhibit superior predictive ability to S100B during the time periods studied. S100B displayed relatively unaltered screening performance beyond the diagnostic timeline provided by SNC guidelines. These findings suggest the need for a reevaluation of the current SNC TBI guidelines.

An overview of mild traumatic brain injuries and emerging therapeutic targets

The majority of traumatic brain injuries (TBIs), approximately 90%, are classified as mild (mTBIs). Globally, an estimated 4 million injuries occur each year from concussions or mTBIs, highlighting their significance as a public health crisis. TBIs can lead to substantial long-term health consequences, including an increased risk of developing Alzheimer's Disease, Parkinson's Disease (PD), chronic traumatic encephalopathy (CTE), and nearly doubling one's risk of suicide. However, the current management of mTBIs in clinical practice and the available treatment options are limited. There exists an unmet need for effective therapy. This review addresses various aspects of mTBIs based on the most up-to-date literature review, with the goal of stimulating translational research to identify new therapeutic targets and improve our understanding of pathogenic mechanisms. First, we provide a summary of mTBI symptomatology and current diagnostic parameters such as the Glasgow Coma Scale (GCS) for classifying mTBIs or concussions, as well as the utility of alternative diagnostic parameters, including imaging techniques like MRI with diffusion tensor imaging (DTI) and serum biomarkers such as S100B, NSE, GFAP, UCH-L1, NFL, and t-tau. Our review highlights several pre-clinical concussion models employed in the study of mTBIs and the underlying cellular mechanisms involved in mTBI-related pathogenesis, including axonal damage, demyelination, inflammation, and oxidative stress. Finally, we examine a selection of new therapeutic targets currently under investigation in pre-clinical models. These targets may hold promise for clinical translation and address the pressing need for more effective treatments for mTBIs.

Classification and Characterization of Traumatic Brain Injuries in the Northern Region of Sweden

BACKGROUND

Traumatic brain injury (TBI) is a common cause of death and disability, the incidence of which in northern Sweden is not fully investigated. This study classifies and characterize epidemiological and demographic features of TBIs in a defined population in Umeå county, Sweden. Specifically, to evaluate frequencies of (1) intracranial lesions detected with computed tomography (CT), (2) need for emergency intervention, and (3) hospital admission, in minimal, mild, moderate, and severe TBI, respectively.

METHODS

The data were gathered from 4057 TBI patients visiting our emergency room (ER) during a two-year period (2015-2016), of whom 56% were men and approximately 95% had minimal TBIs (Glasgow Coma Scale (GCS), score 15).

RESULTS

Of all injuries, 97.8% were mild (GCS 14-15), 1.7% were moderate (GCS 9-13), and 0.5% were severe (GCS < 9). CT scans were performed on 46% of the patients, with 28% being hospitalized. A high annual TBI incidence of 1350 cases per 100,000 citizens was found. The mortality rate was 0.5% with the majority as expected in the elderly group (>80 years).

CONCLUSIONS

Minimal TBIs were not as mild as previously reported, with a relatively high frequency of abnormal CT findings and a high mortality rate. No emergency intervention was required in patients in the GCS 13-15 group with normal CT scans. These findings have implications for clinical practice in the ER with the suggestion to include biomarkers to reduce unnecessary CT scans.

Massive traumatic subarachnoid hemorrhage mimicking aneurysmal subarachnoid hemorrhage

INTRODUCTION

Massive traumatic subarachnoid hemorrhage (tSAH) is a rare but potentially life-threatening condition that can mimic the clinical presentation of aneurysmal subarachnoid hemorrhage (aSAH). The accurate differentiation between these two entities is crucial, as their management and prognoses significantly differ.

CASE PRESENTATION

We present a case of a 64-year-old male patient who presented to our emergency department after being involved in a motor vehicle collision. His radiological findings on a computed tomography (CT) scan were suggestive of aSAH based on its location, which showed massive SAH in bilateral sylvian fissures and the basal cisterns. There was no evidence of vasospasm. The patient later developed a stroke despite the use of Nimodipine.

CONCLUSION

While traumatic subarachnoid hemorrhage mimicking aneurysmal subarachnoid hemorrhage is a recognized phenomenon, it is relatively uncommon. We present a case of massive tSAH complicated by a stroke with no evidence of aneurysm on cerebral angiogram, shedding light on the diagnostic challenges in differentiating tSAH from aSAH and emphasizing the importance of accurate diagnosis for appropriate management, in addition, we aim to remind the readers that trauma may be a cause for massive SAH and should prompt a medical SAH management plan.

Prognostic Value of Serum Biomarkers in Patients With Moderate-Severe Traumatic Brain Injury, Differentiated by Marshall Computer Tomography Classification

Prognostication is challenging in patients with traumatic brain injury (TBI) in whom computed tomography (CT) fails to fully explain a low level of consciousness. Serum biomarkers reflect the extent of structural damage in a different way than CT does, but it is unclear whether biomarkers provide additional prognostic value across the range of CT abnormalities. This study aimed to determine the added predictive value of biomarkers, differentiated by imaging severity. This prognostic study used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study (2014-2017). The analysis included patients aged ≥16 years with a moderate-severe TBI (Glasgow Coma Scale [GCS] <13) who had an acute CT and serum biomarkers obtained ≤24h of injury. Of six protein biomarkers (GFAP, NFL, NSE, S100B, Tau, UCH-L1), the most prognostic panel was selected using lasso regression. The performance of established prognostic models (CRASH and IMPACT) was assessed before and after the addition of the biomarker panel and compared between patients with different CT Marshall scores (Marshall score <3 vs. Marshall score ≥3). Outcome was assessed at six months post-injury using the extended Glasgow Outcome Scale (GOSE), and dichotomized into favorable and unfavorable (GOSE <5). We included 872 patients with moderate-severe TBI. The mean age was 47 years (range 16-95); 647 (74%) were male and 438 (50%) had a Marshall CT score <3. The serum biomarkers GFAP, NFL, S100B and UCH-L1 provided complementary prognostic information; NSE and Tau showed no added value. The addition of the biomarker panel to established prognostic models increased the area under the curve (AUC) by 0.08 and 0.03, and the explained variation in outcome by 13-14% and 7-8%, for patients with a Marshall score of <3 and ≥3, respectively. The incremental AUC of biomarkers for individual models was significantly greater when the Marshall score was <3 compared with ≥3 (p < 0.001). Serum biomarkers improve outcome prediction after moderate-severe TBI across the range of imaging severities and especially in patients with a Marshall score <3.

Validation of a deep learning model for traumatic brain injury detection and NIRIS grading on non-contrast CT: a multi-reader study with promising results and opportunities for improvement

PURPOSE

This study aimed to assess and externally validate the performance of a deep learning (DL) model for the interpretation of non-contrast computed tomography (NCCT) scans of patients with suspicion of traumatic brain injury (TBI).

METHODS

This retrospective and multi-reader study included patients with TBI suspicion who were transported to the emergency department and underwent NCCT scans. Eight reviewers, with varying levels of training and experience (two neuroradiology attendings, two neuroradiology fellows, two neuroradiology residents, one neurosurgery attending, and one neurosurgery resident), independently evaluated NCCT head scans. The same scans were evaluated using the version 5.0 of the DL model icobrain tbi. The establishment of the ground truth involved a thorough assessment of all accessible clinical and laboratory data, as well as follow-up imaging studies, including NCCT and magnetic resonance imaging, as a consensus amongst the study reviewers. The outcomes of interest included neuroimaging radiological interpretation system (NIRIS) scores, the presence of midline shift, mass effect, hemorrhagic lesions, hydrocephalus, and severe hydrocephalus, as well as measurements of midline shift and volumes of hemorrhagic lesions. Comparisons using weighted Cohen's kappa coefficient were made. The McNemar test was used to compare the diagnostic performance. Bland-Altman plots were used to compare measurements.

RESULTS

One hundred patients were included, with the DL model successfully categorizing 77 scans. The median age for the total group was 48, with the omitted group having a median age of 44.5 and the included group having a median age of 48. The DL model demonstrated moderate agreement with the ground truth, trainees, and attendings. With the DL model's assistance, trainees' agreement with the ground truth improved. The DL model showed high specificity (0.88) and positive predictive value (0.96) in classifying NIRIS scores as 0-2 or 3-4. Trainees and attendings had the highest accuracy (0.95). The DL model's performance in classifying various TBI CT imaging common data elements was comparable to that of trainees and attendings. The average difference for the DL model in quantifying the volume of hemorrhagic lesions was 6.0 mL with a wide 95% confidence interval (CI) of - 68.32 to 80.22, and for midline shift, the average difference was 1.4 mm with a 95% CI of - 3.4 to 6.2.

CONCLUSION

While the DL model outperformed trainees in some aspects, attendings' assessments remained superior in most instances. Using the DL model as an assistive tool benefited trainees, improving their NIRIS score agreement with the ground truth. Although the DL model showed high potential in classifying some TBI CT imaging common data elements, further refinement and optimization are necessary to enhance its clinical utility.

Maximizing the Clinical Value of Blood-Based Biomarkers for Mild Traumatic Brain Injury

Mild traumatic brain injury (TBI) and concussion can have serious consequences that develop over time with unpredictable levels of recovery. Millions of concussions occur yearly, and a substantial number result in lingering symptoms, loss of productivity, and lower quality of life. The diagnosis may not be made for multiple reasons, including due to patient hesitancy to undergo neuroimaging and inability of imaging to detect minimal damage. Biomarkers could fill this gap, but the time needed to send blood to a laboratory for analysis made this impractical until point-of-care measurement became available. A handheld blood test is now on the market for diagnosis of concussion based on the specific blood biomarkers glial fibrillary acidic protein (GFAP) and ubiquitin carboxyl terminal hydrolase L1 (UCH-L1). This paper discusses rapid blood biomarker assessment for mild TBI and its implications in improving prediction of TBI course, avoiding repeated head trauma, and its potential role in assessing new therapeutic options. Although we focus on the Abbott i-STAT TBI plasma test because it is the first to be FDA-cleared, our discussion applies to any comparable test systems that may become available in the future. The difficulties in changing emergency department protocols to include new technology are addressed.

Prognostic Neuroimaging Biomarkers in Acute Vascular Brain Injury and Traumatic Brain Injury

Prognostic imaging biomarkers after acute brain injury inform treatment decisions, track the progression of intracranial injury, and can be used in shared decision-making processes with families. Herein, key established biomarkers and prognostic scoring systems are surveyed in the literature, and their applications in clinical practice and clinical trials are discussed. Biomarkers in acute ischemic stroke include computed tomography (CT) hypodensity scoring, diffusion-weighted lesion volume, and core infarct size on perfusion imaging. Intracerebral hemorrhage biomarkers include hemorrhage volume, expansion, and location. Aneurysmal subarachnoid biomarkers include hemorrhage grading, presence of diffusion-restricting lesions, and acute hydrocephalus. Traumatic brain injury CT scoring systems, contusion expansion, and diffuse axonal injury grading are reviewed. Emerging biomarkers including white matter disease scoring, diffusion tensor imaging, and the automated calculation of scoring systems and volumetrics are discussed.

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.

Image Quality Improvement in Deep Learning Image Reconstruction of Head Computed Tomography Examination

In this study, we assess image quality in computed tomography scans reconstructed via DLIR (Deep Learning Image Reconstruction) and compare it with iterative reconstruction ASIR-V (Adaptive Statistical Iterative Reconstruction) in CT (computed tomography) scans of the head. The CT scans of 109 patients were subjected to both objective and subjective evaluation of image quality. The objective evaluation was based on the SNR (signal-to-noise ratio) and CNR (contrast-to-noise ratio) of the brain's gray and white matter. The regions of interest for our study were set in the BGA (basal ganglia area) and PCF (posterior cranial fossa). Simultaneously, a subjective assessment of image quality, based on brain structure visibility, was conducted by experienced radiologists. In the assessed scans, we obtained up to a 54% increase in SNR for gray matter and a 60% increase for white matter using DLIR in comparison to ASIR-V. Moreover, we achieved a CNR increment of 58% in the BGA structures and 50% in the PCF. In the subjective assessment of the obtained images, DLIR had a mean rating score of 2.8, compared to the mean score of 2.6 for ASIR-V images. In conclusion, DLIR shows improved image quality compared to the standard iterative reconstruction of CT images of the head.

Dual-energy computed tomography material decomposition improves prediction accuracy of hematoma expansion in traumatic intracranial hemorrhage

OBJECTIVE

The angiographic spot sign (AS) on CT angiography (CTA) is known to be useful for predicting expansion in intracranial hemorrhage, but its use is limited due to its relatively low sensitivity. Recently, dual-energy computed tomography (DECT) has been shown to be superior in distinguishing between hemorrhage and iodine. This study aimed to evaluate the diagnostic performance of hematoma expansion (HE) using DECT AS in traumatic intracranial hemorrhage.

METHODS

We recruited participants with intracranial hemorrhage confirmed via CTA for suspected traumatic cerebrovascular injuries. We evaluated AS on both conventional-like and fusion images of DECT. AS is grouped into three categories: intralesional enhancement without change, delayed enhancement (DE), and growing contrast leakage (GL). HE was evaluated by measuring hematoma size on DECT and follow-up CT. Logistic regression analysis was used to evaluate whether AS on fusion images was a significant risk factor for HE. Diagnostic accuracy was calculated, and the results from conventional-like and fusion images were compared.

RESULTS

Thirty-nine hematomas in 24 patients were included in this study. Of these, 18 hematomas in 13 patients showed expansion on follow-up CT. Among the expanders, AS and GL on fusion images were noted in 13 and 5 hematomas, respectively. In non-expanders, 10 and 1 hematoma showed AS and GL, respectively. In the logistic regression model, GL on the fusion image was a significant independent risk factor for predicting HE. However, when AS was used on conventional-like images, no factors significantly predicted HE. In the receiver operating characteristic curve analysis, the area under the curve of AS on the fusion images was 0.71, with a sensitivity and specificity of 66.7% and 76.2%, respectively.

CONCLUSIONS

GL on fusion images of DECT in traumatic intracranial hemorrhage is a significant independent radiologic risk factor for predicting HE. The AS of DECT fusion images has improved sensitivity compared to that of conventional-like images.

Prediction of In-Hospital Mortality in Patients With Traumatic Brain Injury Using the Rotterdam and Marshall CT Scores: A Retrospective Study From Western India

Objective Head trauma of any severity, including concussions and skull fractures, can cause a traumatic brain injury (TBI). Prognostication plays a vital role in the scenario of urgency put forth by TBI. The application of CT-based scoring systems developed by the Rotterdam CT score and Marshall classification system appears to be appropriate for the early and precise prediction of clinical outcomes in TBI patients. The present study was designed to determine the predictive value of the Rotterdam CT score and Marshall classification system for in-hospital mortality in patients with TBI. Methods All adult patients (≥ 18 years) with acute traumatic brain injury presented over a period from February 2019 to November 2022 were included. Only those patients who had undergone a plain CT scan of the brain during the initial presentation at the emergency department (ED) were considered. Patients who presented with penetrating brain injury as well as those who died on arrival or who died prior to the initial CT scan of the brain were excluded. A total of 127 patients were included in the final data analysis. Based on initial CT-scan findings, the Rotterdam CT score and Marshall classification system were calculated in order to predict in-hospital mortality. Results The study was dominated by male patients (85.8%) as compared to female patients (14.2%). The overall mortality rate was 32.3% (n = 41). The mortality rate among males and females was 30.3% (33/109) and 44.4% (8/18), respectively. As per the Glasgow Coma Scale (GCS) classification, the severity of the injury was mild in 12.6% of the study subjects, moderate in 22%, and severe in 65.4%. The mortality rate among the patients with mild severity was 12.5% (2/16), while it was 28.6% in moderate (8/28) and 37.3% (31/83) in the severe category group. The best cut-off point of the Rotterdam score for predicting mortality was >4 (as per the Youden Index), which had a sensitivity and specificity of 60.98% and 90.70%, respectively, while the cut-off point of the Marshall CT classification for predicting mortality was >3 (as per the Youden Index), which had a sensitivity of 82.93% and a specificity of 75.58%. There was only a minor difference in the area under the curve (AUC) value of the receiver operating characteristic curve (ROC) curve between the Rotterdam CT score (0.827) and the Marshall classification system (0.833). Conclusion The Rotterdam and Marshall CT scores have demonstrated significant independent prognostic value and may serve as a useful initial evaluation tool for risk stratification of in-hospital mortality among patients with TBI.

Opening the black box of traumatic brain injury: a holistic approach combining human 3D neural tissue and an in vitro traumatic brain injury induction device

Traumatic brain injury (TBI) is caused by a wide range of physical events and can induce an even larger spectrum of short- to long-term pathophysiologies. Neuroscientists have relied on animal models to understand the relationship between mechanical damages and functional alterations of neural cells. These in vivo and animal-based in vitro models represent important approaches to mimic traumas on whole brains or organized brain structures but are not fully representative of pathologies occurring after traumas on human brain parenchyma. To overcome these limitations and to establish a more accurate and comprehensive model of human TBI, we engineered an in vitro platform to induce injuries via the controlled projection of a small drop of liquid onto a 3D neural tissue engineered from human iPS cells. With this platform, biological mechanisms involved in neural cellular injury are recorded through electrophysiology measurements, quantification of biomarkers released, and two imaging methods [confocal laser scanning microscope (CLSM) and optical projection tomography (OPT)]. The results showed drastic changes in tissue electrophysiological activities and significant releases of glial and neuronal biomarkers. Tissue imaging allowed us to reconstruct the injured area spatially in 3D after staining it with specific nuclear dyes and to determine TBI resulting in cell death. In future experiments, we seek to monitor the effects of TBI-induced injuries over a prolonged time and at a higher temporal resolution to better understand the subtleties of the biomarker release kinetics and the cell recovery phases.

Conventional MR Imaging in Trauma Management in Adults

MR imaging has been shown to have higher sensitivity than computed tomography (CT) for traumatic intracranial soft tissue injuries as well as most cases of intracranial hemorrhage, thus making it a significant adjunct to CT in the management of traumatic brain injury, mostly in the subacute to chronic phase, but may also be of use in the acute phase, when there are persistent neurologic symptoms unexplained by prior imaging.

Deep learning-based reconstruction can improve the image quality of low radiation dose head CT

OBJECTIVES

To evaluate the image quality of deep learning-based reconstruction (DLR), model-based (MBIR), and hybrid iterative reconstruction (HIR) algorithms for lower-dose (LD) unenhanced head CT and compare it with those of standard-dose (STD) HIR images.

METHODS

This retrospective study included 114 patients who underwent unenhanced head CT using the STD (n = 57) or LD (n = 57) protocol on a 320-row CT. STD images were reconstructed with HIR; LD images were reconstructed with HIR (LD-HIR), MBIR (LD-MBIR), and DLR (LD-DLR). The image noise, gray and white matter (GM-WM) contrast, and contrast-to-noise ratio (CNR) at the basal ganglia and posterior fossa levels were quantified. The noise magnitude, noise texture, GM-WM contrast, image sharpness, streak artifact, and subjective acceptability were independently scored by three radiologists (1 = worst, 5 = best). The lesion conspicuity of LD-HIR, LD-MBIR, and LD-DLR was ranked through side-by-side assessments (1 = worst, 3 = best). Reconstruction times of three algorithms were measured.

RESULTS

The effective dose of LD was 25% lower than that of STD. Lower image noise, higher GM-WM contrast, and higher CNR were observed in LD-DLR and LD-MBIR than those in STD (all, p ≤ 0.035). Compared with STD, the noise texture, image sharpness, and subjective acceptability were inferior for LD-MBIR and superior for LD-DLR (all, p < 0.001). The lesion conspicuity of LD-DLR (2.9 ± 0.2) was higher than that of HIR (1.2 ± 0.3) and MBIR (1.8 ± 0.4) (all, p < 0.001). Reconstruction times of HIR, MBIR, and DLR were 11 ± 1, 319 ± 17, and 24 ± 1 s, respectively.

CONCLUSION

DLR can enhance the image quality of head CT while preserving low radiation dose level and short reconstruction time.

KEY POINTS

• For unenhanced head CT, DLR reduced the image noise and improved the GM-WM contrast and lesion delineation without sacrificing the natural noise texture and image sharpness relative to HIR. • The subjective and objective image quality of DLR was better than that of HIR even at 25% reduced dose without considerably increasing the image reconstruction times (24 s vs. 11 s). • Despite the strong noise reduction and improved GM-WM contrast performance, MBIR degraded the noise texture, sharpness, and subjective acceptance with prolonged reconstruction times relative to HIR, potentially hampering its feasibility.

Imaging of Head Trauma: Pearls and Pitfalls

Traumatic brain injury is one of the most common causes of morbidity and mortality and significantly impacts the patients' quality of life and socioeconomic status. It can be classified into primary and secondary injuries. Primary injury occurs at the time of the initial head trauma, such as skull fracture, extra-axial hemorrhage, brain contusion, and diffuse axonal injury. Secondary injury develops later as complications such as diffuse cerebral edema, brain herniation, and chronic traumatic encephalopathy. This article describes the indication for imaging, imaging modalities, recommended imaging protocols, and imaging findings of primary and secondary injuries, including pitfalls of each pathology.

Imaging Findings on Head Computed Tomography Scans in Victims of Intimate Partner Violence

OBJECTIVE

The aim of the study is to analyze the imaging findings and injury patterns seen on head computed tomography (CT) examinations performed on survivors of intimate partner violence (IPV).

METHODS

An institutional review board-approved retrospective analysis of 668 patients reporting IPV to our institution's violence intervention and prevention program between January 2013 and June 2018 identified 40 unique patients with radiological findings visible on head CT. All injuries visible on head CT were analyzed based on the anatomic location and injury type. Demographics, IPV screening at the time of injury, concomitant, prior, and subsequent injuries to the index head injury were also recorded.

RESULTS

Our study cohort had 36 women and 4 men with a mean age at presentation of 43 ± 13 years (mean ± SD), 91 unique injuries with 57 (62.6%) isolated soft tissue injuries, 4 (3.2%) fractures, 13 (14.3%) intra-axial, and 17 (18.7%) extra-axial injuries. Soft tissue injuries and intra-axial injuries occurred most commonly in the frontal region (45.6% and 38.5%), followed by the parietal region (22.8% and 23.1%), while most extra-axial injuries were subdural hematomas (41.2%). Left-sided injuries accounted for 49% (45/91) with 29/91 right-sided (32%) and 17/91 bilateral (19%) injuries. The IPV screening occurred in 44% of injury visits (22/50). Concomitant injuries were seen in 14/50 injury visits (28%), most commonly being in the lower extremity (6/14, 42.9% [% of visits with concomitant injuries]) followed by the upper extremity (5/14, 35.7%), while 52% of visits (26/50) were preceded by prior injuries and 68% of events (34/50) were followed by subsequent injuries.

CONCLUSIONS

Isolated soft tissue swelling is the most common manifestation of IPV on head CT scans with frontoparietal region being the most common site. Synchronous and metachronous injuries are frequent.

An end-end deep learning framework for lesion segmentation on multi-contrast MR images-an exploratory study in a rat model of traumatic brain injury

Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra-areas of secondary neural injury which are crucial targets for therapeutic interventions. Segmenting manually areas of ongoing changes like necrosis, edema, hematoma, and inflammation is tedious, error-prone, and biased. Using the multi-parametric MR data from a rodent model study, we demonstrate the effectiveness of an end-end deep learning global-attention-based UNet (GA-UNet) framework for automatic segmentation and quantification of TBI lesions. Longitudinal MR scans (2 h, 1, 3, 7, 14, 30, and 60 days) were performed on eight Sprague-Dawley rats after controlled cortical injury was performed. TBI lesion and sub-regions segmentation was performed using 3D-UNet and GA-UNet. Dice statistics (DSI) and Hausdorff distance were calculated to assess the performance. MR scan variations-based (bias, noise, blur, ghosting) data augmentation was performed to develop a robust model.Training/validation median DSI for U-Net was 0.9368 with T2w and MPRAGE inputs, whereas GA-UNet had 0.9537 for the same. Testing accuracies were higher for GA-UNet than U-Net with a DSI of 0.8232 for the T2w-MPRAGE inputs.Longitudinally, necrosis remained constant while oligemia and penumbra decreased, and edema appearing around day 3 which increased with time. GA-UNet shows promise for multi-contrast MR image-based segmentation/quantification of TBI in large cohort studies.

Early management of isolated severe traumatic brain injury patients in a hospital without neurosurgical capabilities: a consensus and clinical recommendations of the World Society of Emergency Surgery (WSES)

BACKGROUND

Severe traumatic brain-injured (TBI) patients should be primarily admitted to a hub trauma center (hospital with neurosurgical capabilities) to allow immediate delivery of appropriate care in a specialized environment. Sometimes, severe TBI patients are admitted to a spoke hospital (hospital without neurosurgical capabilities), and scarce data are available regarding the optimal management of severe isolated TBI patients who do not have immediate access to neurosurgical care.

METHODS

A multidisciplinary consensus panel composed of 41 physicians selected for their established clinical and scientific expertise in the acute management of TBI patients with different specializations (anesthesia/intensive care, neurocritical care, acute care surgery, neurosurgery and neuroradiology) was established. The consensus was endorsed by the World Society of Emergency Surgery, and a modified Delphi approach was adopted.

RESULTS

A total of 28 statements were proposed and discussed. Consensus was reached on 22 strong recommendations and 3 weak recommendations. In three cases, where consensus was not reached, no recommendation was provided.

CONCLUSIONS

This consensus provides practical recommendations to support clinician's decision making in the management of isolated severe TBI patients in centers without neurosurgical capabilities and during transfer to a hub center.

Carotid canal fracture with internal carotid artery transection: A deadly trauma

Carotid artery injuries are rare with an incidence of 1%-2.6% in trauma patients. They are associated with high morbi-mortality rates, with mortality ranging from 19% to 43%. The diagnosis relies mainly on computed tomography angiography in the emergency setting; however, it is fundamental to be able to suspect carotid artery injuries on non-contrast computed tomography, as the latter is the routine imaging tool for trauma patients. We report the case of a young male, victim of a blunt high velocity motor-vehicle trauma. He was unconscious, with abundant epistaxis and hypovolemic shock. A fracture of the left carotid canal on non-contrast computed tomography was seen, raising concern for an arterial injury. A computed tomography angiography was performed subsequently revealing a transection of the internal carotid artery. This type of injury is highly lethal, and its management relies on urgent surgical intervention, and endovascular treatment, with the purpose of controlling the hemorrhage.

Automated detection of axonal damage along white matter tracts in acute severe traumatic brain injury

New techniques for individualized assessment of white matter integrity are needed to detect traumatic axonal injury (TAI) and predict outcomes in critically ill patients with acute severe traumatic brain injury (TBI). Diffusion MRI tractography has the potential to quantify white matter microstructure in vivo and has been used to characterize tract-specific changes following TBI. However, tractography is not routinely used in the clinical setting to assess the extent of TAI, in part because focal lesions reduce the robustness of automated methods. Here, we propose a pipeline that combines automated tractography reconstructions of 40 white matter tracts with multivariate analysis of along-tract diffusion metrics to assess the presence of TAI in individual patients with acute severe TBI. We used the Mahalanobis distance to identify abnormal white matter tracts in each of 18 patients with acute severe TBI as compared to 33 healthy subjects. In all patients for which a FreeSurfer anatomical segmentation could be obtained (17 of 18 patients), including 13 with focal lesions, the automated pipeline successfully reconstructed a mean of 37.5 ± 2.1 white matter tracts without the need for manual intervention. A mean of 2.5 ± 2.1 tracts resulted in partial or failed reconstructions and needed to be reinitialized upon visual inspection. The pipeline detected at least one abnormal tract in all patients (mean: 9.1 ± 7.9) and accurately discriminated between patients and controls (AUC: 0.91). The number and neuroanatomic location of abnormal tracts varied across patients and levels of consciousness. The premotor, temporal, and parietal sections of the corpus callosum were the most commonly damaged tracts (in 10, 9, and 8 patients, respectively), consistent with prior histopathological studies of TAI. TAI measures were not associated with concurrent behavioral measures of consciousness. In summary, we provide proof-of-principle evidence that an automated tractography pipeline has translational potential to detect and quantify TAI in individual patients with acute severe TBI.