Detection Of Traumatic Brain Injury Research Articles

First Demonstration of GaN HEMT-Based Handheld System for Noninvasive Detection of Traumatic Brain Injury Using Saliva

First Demonstration of GaN HEMT-Based Handheld System for Noninvasive Detection of Traumatic Brain Injury Using Saliva

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.

Paediatric Head Injury: Concordance between CT Findings and GCS Scores- A Retrospective Study in a Tertiary Care Hospital

Introduction: Computed Tomography (CT) remains the mainstay in the detection of traumatic brain injuries in children just as in the adult population. However, unnecessary and inadvertent use of CT in minor and less significant head injuries exposes children to harmful ionising radiation and subsequently increases the lifetime cancer risk. So, there is a need to use CT judiciously in cases of minor head injuries. The Glasgow Coma Score (GCS) can provide a comprehensive framework for proper stratification of neural impairment and head injury severity. Aim: To assess the concordance between CT scan findings and GCS scores in paediatric patients with acute Traumatic Brain Injury (TBI). Materials and Methods: This was a retrospective study of paediatric head injury cases who were referred to the Department of Radiodiagnosis, Mysore Medical College, Karnataka, India. from January 2021 to December 2021. The head CT of 110 patients was reviewed. Demographic details, mode of accident, CT findings, and GCS scores were collected from hospital records. Descriptive statistics were used and results were expressed in terms of frequency and percentages. Results: Out of 110 patients (mean age: 9.17±3.02 years) reviewed, males were 78 (71%) and females were 32 (29%). Road traffic accident was found to be the most common cause, i.e., in 71 patients (64.5%). The most common CT scan finding was fracture as seen in 12 cases. Out of 110 patients, 94 had mild injury according to GCS scores, 12 had a moderate head injury and four had a severe head injury. As the GCS scores decreased, the percentage of positive findings on CT increased. Conclusion: Percentage of positive CT findings was higher in the moderate and severe head injury category, where the role of CT scans in acute settings becomes valuable.

A comparison of computerized tomography and flair-SWI MRI results of patients with head injury attending the emergency department.

Detection of traumatic brain injury (TBI) is of vital importance in patients who apply to the emergency department with a history of trauma. The aim of initial imaging in patients with suspected TBI is to detect trauma-related injury quickly and accurately. In this study, the effectiveness of prospectively cranial computed tomography (CT) and fluid attenuation inversion recovery (FLAIR) and susceptibility weighted imaging (SWI) sequence magnetic resonance imaging (MRI) examination results of patients diagnosed with TBI in the emergency department in terms of bleeding detection was investigated in the light of the literature. Patients with traumatic brain injury who applied to the emergency department between 2016 and 2020 were included in this prospective study. Cranial CT and MRI images containing SWI-FLAIR sequence were taken on the same day, immediately after cranial CT, for a total of 500 patients. In our study, TBI was detected in 242 males (70.8%) and 100 females (29.2%), for a total of 342 patients. The mean age was 41.45, the mean GCS was 13.35. There was a history of trauma such as falling in 155 patients (45.3%), traffic accidents in 171 patients (50%), and trauma in 16 patients (4.7%). In the comparative evaluation of CT and FLAIR-SWI MRI examinations no bleeding was detected in the FLAIR-SWI sections of 239 patients who did not have bleeding on CT; however, bleeding was detected in FLAIR-SWI sections in 14 patients who did not have bleeding on CT. FLAIR-SWI MR, which is a more reliable examination method, should be performed before control CT, especially in patients with incompatible clinical and admission CT.

Deep learning for behaviour classification in a preclinical brain injury model.

The early detection of traumatic brain injuries can directly impact the prognosis and survival of patients. Preceding attempts to automate the detection and the assessment of the severity of traumatic brain injury continue to be based on clinical diagnostic methods, with limited tools for disease outcomes in large populations. Despite advances in machine and deep learning tools, current approaches still use simple trends of statistical analysis which lack generality. The effectiveness of deep learning to extract information from large subsets of data can be further emphasised through the use of more elaborate architectures. We therefore explore the use of a multiple input, convolutional neural network and long short-term memory (LSTM) integrated architecture in the context of traumatic injury detection through predicting the presence of brain injury in a murine preclinical model dataset. We investigated the effectiveness and validity of traumatic brain injury detection in the proposed model against various other machine learning algorithms such as the support vector machine, the random forest classifier and the feedforward neural network. Our dataset was acquired using a home cage automated (HCA) system to assess the individual behaviour of mice with traumatic brain injury or non-central nervous system (non-CNS) injured controls, whilst housed in their cages. Their distance travelled, body temperature, separation from other mice and movement were recorded every 15 minutes, for 72 hours weekly, for 5 weeks following intervention. The HCA behavioural data was used to train a deep learning model, which then predicts if the animals were subjected to a brain injury or just a sham intervention without brain damage. We also explored and evaluated different ways to handle the class imbalance present in the uninjured class of our training data. We then evaluated our models with leave-one-out cross validation. Our proposed deep learning model achieved the best performance and showed promise in its capability to detect the presence of brain trauma in mice.

Interdigitated Electrode Arrays for Electrochemical Immunosensing of Interleukin-6 in Cerebrospinal Fluid (CSF) and Serum

Electrochemical immunosensors combine the advantages of electrochemical transducers such as low cost, potential for miniaturization, and quantified readout with the selective properties of immunochemical recognition elements. Here we describe a simple, label-free electrochemical immunosensor for the rapid detection of traumatic brain injury (TBI) by quanitifcation of a cytokine interleukin-6 (IL-6) in cerebrospinal fluid (CSF). The sensor system consists of gold interdigitated electrode arrays (IDEAs) that are modified with self-assembled monolayers (SAMs) and IL-6 antibodies (IL-6 mAb) for antigen recognition and capture. Electrode modification was confirmed using surface characterization (FT-IR, fluorescence) and electrochemically via EIS. The sensor performance was evaluated in IL-6 spiked PBS solution: the LOD was determined to be 1.63 pg/mL, with a linear range across 4 orders of magnitude. The sensor exhibits selectivity against non-target cytokines TNF-α and IL-10. The detection of CSF and serum IL-6 using the outlined system will be discussed for use as a point-of-care (POC) diagnostic and prognostic tool for TBI.

Rapid detection of traumatic brain injury.

An optofluidic chip incorporating a surface-enhanced Raman-scattering substrate rapidly detects picomolar concentrations of biomarkers of traumatic brain injury in finger-prick blood samples from patients.

Use of high-sensitivity digital ELISA improves the diagnostic performance of circulating brain-specific proteins for detection of traumatic brain injury during triage

ABSTRACTBackground: Historically, limited sensitivity associated with traditional immunoassay methods has prevented the use of brain-specific proteins as blood biomarkers of traumatic brain injury (TBI) during triage, as these proteins exhibit low circulating concentrations. Digital ELISA is a newly-developed technique that is up to 1000 times more sensitive than conventional ELISA methods. The purpose of this study was to determine whether the use of digital ELISA over conventional ELISA improves the performance of brain-specific proteins as blood biomarkers of TBI during triage.Methods: Blood was sampled from TBI patients (n = 13) at emergency department admission, as well as from neurologically normal controls (n = 72). Serum levels of two brain-specific proteins, neurofilament light chain (NfL) and Tau, were measured via digital ELISA. Estimated conventional ELISA measures were generated by adjusting values according to the lower limits of detection achievable with commercially available conventional ELISA assays, and receiver operating characteristic (ROC) analysis was used to compare the diagnostic performance of digital ELISA measures to estimated conventional ELISA measures in terms of their ability to discriminate between TBI patients and controls.Results: Used in combination, digital ELISA measures of NfL and Tau could discriminate between groups with 100% sensitivity and 91.7% specificity. Estimated conventional ELISA measures could only discriminate between groups with 7.7% sensitivity and 94.4% specificity. This difference in diagnostic performance was statistically significant when comparing areas under ROC curves.Conclusions: The use of digital ELISA over conventional ELISA methods improves the diagnostic performance of circulating brain-specific proteins for detection of TBI during triage.

Impact of parturition on maternal cardiovascular and neuronal integrity in a high risk cohort \u2013 a prospective cohort study

BackgroundTo better understand the profound multisystem changes in maternal physiology triggered by parturition, in particular in the underexplored neuronal system, by deploying a panel of pre- vs post-delivery maternal serum biomarkers, most notably the neuronal cytoskeleton constituent neurofilament light chain (NfL). This promising fluid biomarker is not only increasingly applied to investigate disease progression in numerous brain diseases, particularly in proteopathies, but also in detection of traumatic brain injury or monitoring neuroaxonal injury after ischemic stroke.MethodsThe study was nested within a prospective cohort study of pregnant women at risk of developing preeclampsia at the University Hospital of Basel. Paired ante- and postpartum levels of progesterone, soluble fms-like tyrosine kinase-1 (sFlt-1), placental growth factor (PlGF), mid-regional pro-atrial natriuretic peptide (MR-proANP), copeptin (CT-proAVP), and NfL were measured in 56 women with complete clinical data.ResultsPlacental delivery significantly decreased all placental markers: progesterone 4.5-fold, PlGF 2.2-fold, and sFlt-1 1.7-fold. Copeptin and MR-proANP increased slightly (1.4- and 1.2-fold, respectively). Unexpectedly, NfL levels (median [interquartile range]) increased significantly post-partum: 49.4 (34.7–77.8) vs 27.7 (16.7–31.4) pg/ml (p < 0.0001). Antepartum NfL was the sole independent predictor of NfL peri-partum change; mode of delivery, duration of labor, clinical characteristics and other biomarkers were all unrelated. Antepartum NfL levels were themselves independently predicted only by maternal age.ConclusionsParturition per se increases maternal serum NfL levels, suggesting a possible impact of parturition on maternal neuronal integrity.

Probability of Soluble Tissue Factor Release Lead to the Elevation of D-dimer as a Biomarker for Traumatic Brain Injury

D-dimer is a potential biomarker for the detection of traumatic brain injury (TBI). However, the mechanisms that trigger elevation of D-dimer in TBI remain unclear. The purpose of this study was to evaluate the reliability of D-dimer in blood as a biomarker for TBI and to determine the mechanisms involved in regulating its blood levels. Nine patients with moderate to severe isolated TBI (Glasgow Coma Scale [GCS] score 7–13) were admitted to our hospital from May 2013 to June 2014. Blood samples were collected from systemic arteries on arrival and at 1, 3, 5, and 7 days after injury. Blood levels of neuron specific enolase (NSE), D-dimer, and soluble tissue factor (sTF) were measured. NSE (33.4 ng/ml: normal <12.0 ng/ml) and D-dimer (56.1 μg/ml: normal <1.0 μg/ml) were elevated at admission and declined on day 1 after injury. At admission, there were significant correlations of D-dimer levels with NSE (R = 0.727, P = 0.026) and sTF (R = 0.803, P = 0.009) levels. The blood level of D-dimer accurately reflects the degree of brain tissue damage indicated by NSE levels. Our data suggest that release of sTF induced by brain tissue damage may activate the coagulation cascade, leading to elevation of D-dimer.

Volumetric Asymmetries of White Matter Tracts in Traumatic Brain Injury

Investigate the utility of volumetric asymmetry levels in contralateral white matter (WM) tracts for individual-level detection of traumatic brain injury (TBI).

Pediatric head trauma: an extensive review on imaging requisites and unique imaging findings.

The effects of trauma in children are different due to association with some anatomical and physiological differences compared with adults. The role of neuroimaging gains importance in early detection of traumatic brain injuries and prevention of secondary post-traumatic complications. Many algorithms are described for children with head trauma to decide the necessity of a computed tomography scan. The aims of this article are to describe differences of these algorithms, the mechanism of traumatic brain injury with radiological imaging findings in the pediatric population, and explain complications of undiagnosed traumatic brain lesions.

A Paper-Based Lateral Flow Strip for Protein Biomarker Detection

Protein biomarkers are becoming increasingly important in diagnosis and monitoring of diseases. Paper-based test strip is a promising technique for sensing protein biomarkers in point-of-care (POC) applications. This talk will demonstrate our effort to develop a paper-based test strips for detection of Traumatic Brain Injury (TBI) protein biomarker in blood plasma by utilizing employing surface-enhanced Raman scattering (SERS) for signal transduction. The detection of limit (LOD) of this paper test strip for TBI protein biomarker is lower than the cut off value that is present in patient blood plasma. This paper-based lateral flow device has a potential application in POC setting.

Amide proton transfer-weighted MRI detection of traumatic brain injury in rats

The purpose of this study was to explore the capability and uniqueness of amide proton transfer-weighted (APTw) imaging in the detection of primary and secondary injury after controlled cortical impact (CCI)-induced traumatic brain injury (TBI) in rats. Eleven adult rats had craniotomy plus CCI surgery under isoflurane anesthesia. Multi-parameter MRI data were acquired at 4.7 T, at eight time points (1, 6 h, and 1, 2, 3, 7, 14, and 28 days after TBI). At one and six hours post-injury, average APTw signal intensities decreased significantly in the impacted and peri-lesional areas due to tissue acidosis. A slightly high APTw signal was seen in the core lesion area with respect to the peri-lesional area, which was due to hemorrhage, as shown by T2*w. After the initial drop, the APTw signals dramatically increased in some peri-lesional areas at two and three days post-injury, likely due to the secondary inflammatory response. The use of APTw MRI has the potential to introduce a novel molecular neuroimaging approach for the simultaneous detection of ischemia, hemorrhage, and neuroinflammation in TBI.

Enzymatic Detection of Traumatic Brain Injury Related Biomarkers.

Electrochemical detection methods have been popular in the medical diagnostics field. Several well-known devices such as the self-monitoring blood glucose meter have relied on electrochemical techniques for their sensitivity, and ability to make direct measurements without optical labels. Currently, no point-of-care or handheld diagnostic tool exists to quantify the severity of a traumatic brain injury (TBI). We have shown that enzymatic detection of norepinephrine (NE), a biomarker which can indicate TBI severity, using impedance-based electrochemical techniques can achieve the required sensitivity, ∼100pg/mL. Furthermore, the first steps have been taken to quantify NE in whole blood solutions and to optimize the technique for a handheld device.

Targeted nanoparticles for the non-invasive detection of traumatic brain injury by optical imaging and fluorine magnetic resonance imaging

Necrosis is a form of cell death that occurs only under pathological conditions such as ischemic diseases and traumatic brain injury (TBI). Non-invasive imaging of the affected tissue is a key component of novel therapeutic interventions and measurement of treatment responses in patients. Here, we report a bimodal approach for the detection and monitoring of TBI. PEGylated poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs), encapsulating both near infrared (NIR) fluorophores and perfluorocarbons (PFCs), were targeted to necrotic cells. We used cyanine dyes such as IRDye 800CW, for which we have previously demonstrated specific targeting to intracellular proteins of cells that have lost membrane integrity. Here, we show specific in vivo detection of necrosis by optical imaging and fluorine magnetic resonance imaging (19F MRI) using newly designed PLGA NP(NIR700 + PFC)-PEG-800CW. Quantitative ex vivo optical imaging and 19F MR spectroscopy of NIR-PFC content in injured brain regions and in major organs were well correlated. Both modalities allowed the in vivo identification of necrotic brain lesions in a mouse model of TBI, with optical imaging being more sensitive than 19F MRI. Our results confirm increased blood pool residence time of PLGA NPs coated with a PEG layer and the successful targeting of TBI-damaged tissue. A single PLGA NP containing NIR-PFC enables both rapid qualitative optical monitoring of the TBI state and quantitative 3D information from deeper tissues on the extent of the lesion by MRI. These necrosis-targeting PLGA NPs can potentially be used for clinical diagnosis of brain injuries.

A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury.

The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI.

The impact of data preprocessing in traumatic brain injury detection using functional magnetic resonance imaging.

Traumatic brain injury (TBI) can adversely affect a person's thinking, memory, personality and behavior. For this reason new and better biomarkers are being investigated. Resting state functional network connectivity (rsFNC) derived from functional magnetic resonance (fMRI) imaging is emerging as a possible biomarker. One of the main concerns with this technique is the appropriateness of methods used to correct for subject movement. In this work we used 50 mild TBI patients and matched healthy controls to explore the outcomes obtained from different fMRI data preprocessing. Results suggest that correction for motion variance before spatial smoothing is the best alternative. Following this preprocessing option a significant group difference was found between cerebellum and supplementary motor area/paracentral lobule. In this case the mTBI group exhibits an increase in rsFNC.

TH‐A‐18C‐09: Ultra‐Fast Monte Carlo Simulation for Cone Beam CT Imaging of Brain Trauma

Purpose:Application of cone‐beam CT (CBCT) to low‐contrast soft tissue imaging, such as in detection of traumatic brain injury, is challenged by high levels of scatter. A fast, accurate scatter correction method based on Monte Carlo (MC) estimation is developed for application in high‐quality CBCT imaging of acute brain injury.Methods:The correction involves MC scatter estimation executed on an NVIDIA GTX 780 GPU (MC‐GPU), with baseline simulation speed of ˜1e7 photons/sec. MC‐GPU is accelerated by a novel, GPU‐optimized implementation of variance reduction (VR) techniques (forced detection and photon splitting). The number of simulated tracks and projections is reduced for additional speed‐up. Residual noise is removed and the missing scatter projections are estimated via kernel smoothing (KS) in projection plane and across gantry angles. The method is assessed using CBCT images of a head phantom presenting a realistic simulation of fresh intracranial hemorrhage (100 kVp, 180 mAs, 720 projections, source‐detector distance 700 mm, source‐axis distance 480 mm).Results:For a fixed run‐time of ˜1 sec/projection, GPU‐optimized VR reduces the noise in MC‐GPU scatter estimates by a factor of 4. For scatter correction, MC‐GPU with VR is executed with 4‐fold angular downsampling and 1e5 photons/projection, yielding 3.5 minute run‐time per scan, and de‐noised with optimized KS. Corrected CBCT images demonstrate uniformity improvement of 18 HU and contrast improvement of 26 HU compared to no correction, and a 52% increase in contrast‐tonoise ratio in simulated hemorrhage compared to “oracle” constant fraction correction.Conclusion:Acceleration of MC‐GPU achieved through GPU‐optimized variance reduction and kernel smoothing yields an efficient (&lt;5 min/scan) and accurate scatter correction that does not rely on additional hardware or simplifying assumptions about the scatter distribution. The method is undergoing implementation in a novel CBCT dedicated to brain trauma imaging at the point of care in sports and military applications.Research grant from Carestream Health. JY is an employee of Carestream Health.

Novel Strategies for Biodetection: Preliminary Application to Traumatic Brain Injury

ABSTRACTThe sensor team at the Los Alamos National Laboratory is an integrated multidisciplinary group that develops both core technologies as well as accessory tools for efficient biodetection. We have developed a waveguide-based optical biosensor for the efficient and ultra-sensitive, rapid detection of biological agents. We have previously demonstrated the use of this technology for the detection of biomarkers associated with many diseases. Herein, we present the preliminary data demonstrating the extension of this technology to the discovery and detection of Traumatic Brain Injury (TBI). TBI afflicts a significant percentage of US troops deployed in Iraq and Afghanistan, but is difficult to diagnose efficiently. Currently, only neuropsychological questionnaires are being used for the diagnosis of this condition, which can range from mild concussion to severe brain damage. The ultimate goal of this project is to develop a rapid biomarker-based diagnostic for TBI in blood. However, this cannot be accomplished until a comprehensive repertoire of biomarkers secreted during brain injury is established. This requires an integrated biomarker discovery and detection approach that is sampled directly from human serum and cerebrospinal fluid.The results reported here are preliminary steps in that direction wherein we aim to develop two different methods for the discovery of novel biomarkers of TBI in blood and cerebrospinal fluid, as well as develop assays for two biomarkers on an ultra-sensitive waveguide-based platform that was developed at LANL. We were able to evaluate two different methods for biomarker discovery: Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and two dimensional gel electrophoresis (2-DE) in serum samples. In addition to development of depletion protocols to remove abundant proteins in serum, we were also able to detect spiked TBI biomarkers using both methods. However, the results clearly show that for protein biomarkers, MALDI MS is much more sensitive than 2-DE. We also developed a sandwich immunoassay on a waveguide-based platform for a TBI biomarker, procalcitonin, using commercially available antibodies. We show with our methods that we were able to directly detect procalcitonin from human serum. While our discovery and detection methods show promising results, these methods need to be further optimized before we can apply it to clinically relevant samples.