Diagnosis Of Diffuse Axonal Injury Research Articles

Prediction for the prognosis of diffuse axonal injury using automated pupillometry

ObjectivePrevious studies have reported various predictive indicators of diffuse axonal injury (DAI), but no consensus has not been reached. Although the efficiency of automated pupillometry in patients with consciousness disorder has been widely reported, there are few reports of its use in patients with DAI. This study aimed to investigate the significance of pupillary findings in predicting the prognosis of DAI. Patients and MethodsWe included patients admitted to our center with a diagnosis of DAI from June 1, 2021 to June 30, 2022. Pupillary findings in both eyes were quantitatively measured by automated pupillometry every 2 hours after admission. We statistically examined the correlations between automated pupillometry parameters, the patients’ characteristics, and outcomes such as the Glasgow Outcome Scale Extended (GOSE) after 6 months from injury, the time to follow command, and so on. ResultsAmong 22 patients included in this study, five had oculomotor nerve palsy. Oculomotor nerve palsy was correlated with all outcomes, whereas Marshall computed tomography (CT) classification, Injury severity score (ISS) and DAI grade were correlated with few outcomes. Some of the automated pupillometry parameters were significantly correlated with GOSE at 6 months after injury, and many during the first 24 hours of measurement were correlated with the time to follow command. Most of these results were not affected by adjustment using sedation period, ISS or Marshall CT classification. A subgroup analysis of patients without oculomotor nerve palsy revealed that many of the automated pupillometry parameters during the first 24 hours of measurement were significantly correlated with most of the outcomes. The cutoff values that differentiated a good prognosis (GOSE 5–8) from a poor prognosis (GOSE 1–4) were constriction velocity (CV) 1.43 (AUC = 0.81(0.62–1), p = 0.037) and maximum constriction velocity (MCV) 2.345 (AUC = 0.78 (0.58–0.98), p = 0.04). The cutoff values that differentiated the time to follow command into within 7 days and over 8 days were percentage of constriction 8 (AUC = 0.89 (0.68–1), p = 0.011), CV 0.63 (AUC = 0.92 (0.78–1), p = 0.013), MCV 0.855 (AUC = 0.9 (0.74–1), p = 0.017) and average dilation velocity 0.175 (AUC = 0.95 (0.86–1), p = 0.018). ConclusionsThe present results indicate that pupillary findings in DAI are a strong predictive indicator of the prognosis, and that quantitative measurement of them using automated pupillometry could facilitate enhanced prediction for the prognosis of DAI.

Segmented 3D Echo Planar Acquisition for Rapid Susceptibility-Weighted Imaging: Application to Microhemorrhage Detection in Traumatic Brain Injury.

Susceptibility-weighted imaging (SWI) provides superior image contrast of cerebral microhemorrhages (CMBs). It is based on a three-dimensional (3D) gradient echo (GRE) sequence with a relatively long imaging time. To evaluate whether an accelerated 3D segmented echo planar imaging SWI is comparable to GRE SWI in detecting CMBs in traumatic brain injury (TBI). Prospective. Four healthy volunteers and 46 consecutive subjects (38.0 ± 14.4 years, 16 females; 12 mild, 13 moderate, and 7 severe TBI). A 3 T scanner/3D gradient echo and 3D segmented echo planar imaging (segEPI). Brain images were acquired using GRE and segEPI in a single session (imaging time=9minutes 47 seconds and 1minute 30 seconds, respectively). The signal-to-noise ratio (SNR) calculated from healthy volunteer thalamus and centrum semiovale were compared. CMBs were counted by three raters blinded to diagnostic information. A t-test was used to assess SNR difference. Pearson correlation and Wilcoxon signed-rank test were performed using CMB counts. The intermethod agreement was evaluated using Bland-Altman method. Intermethod and interrater reliabilities of image-based diffuse axonal injury (DAI) diagnoses were evaluated using Cohen's kappa and percent agreement. P ≤ 0.05 was considered statistically significant. Thalamus SNRs were 16.9 ± 2.2 and 16.5 ± 3 for GRE and segEPI (P=0.84), respectively. Centrum semiovale SNRs were 25.8 ± 4.6 and 21.1 ± 2.7 (P=0.13). The correlation coefficient of CMBs was 0.93, and differences were not significant (P=0.56-0.85). For DAI diagnoses, Cohen's kappa was 0.62-0.84 and percent agreement was 85%-94%. CMB counts on segEPI and GRE were highly correlated, and DAI diagnosis was made equally effectively. segEPI SWI can potentially replace GRE SWI in detecting TBI CMBs, especially when time constraints are critical. 1 TECHNICAL EFFICACY: Stage 2.

Methodology for forensic diagnosis of diffuse axonal injury

An original methodological approach for forensic diagnostics of diffuse axonal injury (DAI) was developed based on the comprehensive study results. The approach is based on the algorithm of expert actions, including utilizing the developed rational methods set to identify pathognomonic morphological features using accessible and effective histological techniques. Also, the approach includes ways of analysis and estimation of these features. The proposed methodological approach aims to provide an objective diagnosis of this type of traumatic brain injury (TBI) and establish the age of its acute post-traumatic period. The known and generally accepted definitions of DAI and TBI are clarified.

Clinical presentation and gross appearance of diffuse axonal injury in the early post-injury period

The objective of the study was to investigate and characterize the clinical presentation, and establish macroscopic diagnostic signs of diffuse axonal injury (DAI) in the early (up to 3 days) post-injury period. In DAI, coma develops immediately after head injury and persists for 3 days post-injury until death. The coma is accompanied by dominant primary stem neurological symptoms, hemodynamic and respiratory disturbances and does not progress to a vegetative state. Lifetime computed tomography reveals cerebral hemorrhage in 40.5% of cases. We established the macroscopic signs of head injury in DAI. For the postmortem diagnosis of DAI, a detailed macroscopic appearance of pathognomonic cerebral hemorrhages is given, which are most frequently (67.5%) localized in the corpus callosum (CC), namely in the area from its genu to the middle of the trunk (97%). A rational, improved scheme of excision of CC trunk areas for the histological study is proposed.

ROLE OF MRI IN THE EVALUATION OF DIFFUSE AXONAL INJURY

INTRODUCTION: Diffuse axonal injury (DAI) is a relatively less common but severe form of traumatic brain injury. It occurs due to shearing forces and is identied as one of the most important causes of morbidity and mortality in patients with traumatic brain injury. MRI is found to be diagnostic when CTndings are normal and there are persistent unexplained neurologic ndings or at subacute and chronic periods. AIM: To evaluate the role of MRI in the diagnosis of diffuse axonal injury. MATERIALAND METHODS: 9 Subjects were identied retrospectively with the diagnosis of DAI on MRI in last 2 years. The 1.5TMRI scans of the patients with DAI included: T1 and T2- weighted imaging, FLAIR imaging and T2*-weighted gradient echo (GRE) imaging. Lesions were identied and compared on all sequences. RESULTS: The lesions were in cerebral white matter location in the cases of mild DAI, whereas in the severe DAI located in basal ganglia, corpus callosum, dorsal part of the brain stem as well as the cerebral white matter. For Haemorrhagic lesions, GRE is the best tool to detect haemorrhagic DAIs. For Non-haemorrhagic lesion, FLAIR and DWI are the best current tool to detect small and non-haemorrhagic parenchymal lesions, displayed as hyperintense lesions.

The original method for corpus callosum autopsy study in the case of diffuse axonal brain injury

The article offers an original method for human corpus callosum autopsy examination in the case of diffuse axonal injury (DAI) and a rational scheme for sampling its zones for microscopic examination, aimed at determining the morphological characteristics of injuries, taking into account their anatomical and topographic localization. The results of the comparative study prove the objectivity and high efficiency of the proposed approach to post-mortem diagnosis of DAI.

Delayed Diagnosis of Diffuse Axonal Injury Causes an Increase in Mortality

Kiran Rasane, Rohit MBBS, MS; Xinyue Zhang, Christina MD; Enrique Rincon, Javier MD; Afzal, Hussain MBBS; Alejandro Aldana, Jose MD; Ghosh, Esha MS; Alejandro Fonseca, Ricardo MD; Canas, Melissa MD; Noor Ilahi, Obeid MBBS FACS; Vincent Bochicchio, Grant MD, FACS Author Information

The Value of CT and MRI Examination in the Diagnosis of Diffuse Axonal Injury

Objective: To compare the number of detections of diffuse axonal injury (DAI) lesions between CT and MRI routine sequences (T1WI, T2WI, FLAIR) and special sequences (DWI, SWI). There is no difference in the detection rate of hemorrhagic lesions and non-hemorrhagic lesions with diffuse axonal injury, and more clinically valuable diagnostic methods are obtained to improve the clinical understanding of the detection and disease of diffuse axonal injury. Methods: The paper collected 37 cases of clinical data and imaging data of patients with diffuse axonal injury clinically diagnosed from March 2017 to January 2019 in our hospital. The patients underwent CT scan of the Department of Radiology in our hospital within 72 hours after the injury, and MRI was performed one week after admission according to the stable condition. The imaging data was obtained from the radiology consciousness readings. Results: A total of 37 patients underwent imaging studies. The number of missed CT scans in the brainstem was relatively small compared with other locations, and the number of missed diagnosis of lesions in the cerebellum was higher. In the conventional MRI sequence, FLAIR detected the most lesions, and the difference between the number of lesions detected by T1WI and T2WI was statistically significant (χ2 = 22.930, P = 0.011 < 0.05). Among the special sequences, the number of SWI lesions was the highest, and the difference between DWI and SWI was statistically significant (χ2 = 13.090, P = 0.002 < 0.05). The number of detected CT, FLAIR and SWI was compared. The number of SWI detected was the most, and the difference was statistically significant (χ2 = 19.634, P = 0.033 < 0.05). DWI had the highest detection rate for hemorrhagic lesions, followed by FLAIR (χ2 = 188.168, P < 0.001). SWI had the highest detection rate for hemorrhagic lesions, followed by DWI (χ2 = 1363.452, P < 0.001). Conclusion: The most common number of lesions detected in patients with DAI is the SWI sequence. For the detection of hemorrhagic lesions, SWI has obvious advantages. In non-hemorrhagic lesions, the detection rate of DWI is significantly higher than other sequences. Therefore, it can be said that the DWI and SWI sequences provide an important imaging basis for the definitive diagnosis of DAI, and have high application value.

Serum levels of tau protein increase according to the severity of the injury in DAI rat model.

Traumatic brain injury (TBI) in the form of diffuse axonal injury (DAI) is difficult to diagnose in the early phase of the injury. Early diagnosis of DAI may provide opportunity for developing treatment and management strategies. Tau protein has been demonstrated to increase in the early phase of TBI with high diagnostic accuracy in patients with DAI. We tested the biological plausibility of tau protein using a rat DAI model by evaluating the association between serum tau levels and the severity of brain injury.DAI was induced in animals using the Marmarou model.After a survival of 60 minutes, rats were anesthetized and sacrificed after obtaining blood samples (5ml) from the heart. Eighteenratswereemployedin the present studyand were randomly subjected to sham-operated control (n=4), mild DAI (n=7), and severe DAI (n=7). Of seven severe DAI rats, two rats that had focal injury caused by skull fracture were excluded in the measurement of tau protein level. The serum levels of tau protein in the rat DAI model were found to increase significantly and consistently according to the severity of the injury.Rats with DAI showed significantly higher serum levels of tau protein compared to sham rats; the severe DAI rats had higher levels of tau than moderate DAI and sham rats (sham vs. mild, P=0.02; mild vs. severe, P=0.02). In conclusion, serum tau protein levels may be useful as a biomarker for diagnosing and estimating the severity of DAI in the early phase.

Does Diffuse Axonal Injury MRI Grade Really Correlate with Functional Outcome?

Diffuse axonal injury (DAI) is a common form of primary head injury. This study was done to see the association of DAI grades with extended Glasgow Outcome Scale (GOSE). We retrospectively reviewed the charts and radiology reports of a cohort of patients discharged with the diagnosis of diffuse axonal injury. We collected data on variables like age, sex, Glasgow Coma Scale (GCS) at admission, grade of DAI, length of hospital stay, and occurrence of post-traumatic seizures. We contacted the patients after 6 months to assess their GOSE. Outcome analysis was done with SPSS version23. For 40 patients, DAI and 6-month GOSE were available for analysis. Mean age was 27.8 years, with male to female ratio of 12:1. There were 8 patients with DAI grade I (20.5%), 13 patients with DAI grade II (33.3%), and 18 patients with DAI grade III (46.2%). Nine of 39 patients (23.07%) had post-traumatic seizures. Mean GCS at admission was 9.67. Mean length of hospital stay was 24.12 days. Mean GOSE after 6 months was 6.10. There were 5 mortalities. Patients with low mean GCS portended significant unfavorable outcome. Higher DAI grades were not associated with unfavorable outcome. Mean GCS at presentation is a better predictor of outcome after DAI rather than its grade.

ITRAQ-based proteomic analysis discovers potential biomarkers of diffuse axonal injury in rats

Diffuse axonal injury (DAI) is one of the most common and severe pathological consequences of traumatic brain injury (TBI). The molecular mechanism of DAI is highly complicated and still elusive, yet a clear understanding is crucial for the diagnosis, treatment, and prognosis of DAI. In our study, we used rats to establish a DAI model and applied isobaric tags for relative and absolute quantitation (iTRAQ) coupled with liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis to identify differentially expressed proteins (DEPs) in the corpus callosum. As a result, a total of 514 proteins showed differential expression between the injury groups and the control. Among these DEPs, 14 common DEPs were present at all seven time points postinjury (1, 3, 6, 12, 24, 48, and 72 h). Next, bioinformatic analysis was performed to elucidate the pathogenesis of DAI, which was found to possibly involve calcium ion–regulatory proteins (e.g., calsenilin and ryanodine receptor 2), cytoskeleton organization (e.g., peripherin, NFL, NFM, and NFH), apoptotic processes (e.g., calsenilin and protein kinase C delta type), and inflammatory response proteins (e.g., complement C3 and C-reactive protein). Moreover, peripherin and calsenilin were successfully confirmed by western blotting to be significantly upregulated during DAI, and immunohistochemical (IHC) analysis revealed that their expression increased and could be observed in axons after injury, thus indicating their potential as DAI biomarkers. Our experiments not only provide insight into the molecular mechanisms of axonal injury in rats during DAI but also give clinicians and pathologists important reference data for the diagnosis of DAI. Our findings may expand the list of DAI biomarkers and improve the postmortem diagnostic rate of DAI.

Tau protein as a diagnostic marker for diffuse axonal injury.

BackgroundDiffuse axonal injury (DAI) is difficult to identify in the early phase of traumatic brain injury (TBI) using common diagnostic methods. Tau protein is localized specifically in nerve axons. We hypothesized that serum level of tau can be a useful biomarker to diagnose DAI in the early phase of TBI.Methods & resultsWe measured serum tau levels in 40 TBI patients who were suspected of DAI within 6 hours after TBI to evaluate the accuracy of the tau level as a diagnostic marker for DAI. Diagnosis of DAI was confirmed according to magnetic resonance imaging (MRI) findings. The serum tau level in the DAI group (n = 13) was significantly higher than that in the non-DAI group (n = 27) (DAI vs. non-DAI, 25.3 [0 to 99.1] pg/mL vs. 0 [0 to 44.4] pg/mL, P = 0.03)). A receiver-operating characteristic curve to evaluate the diagnostic ability of serum tau level within 6 hours for DAI showed an area under the curve of 0.690 with 74.1% for sensitivity and 69.2% for specificity. Serum tau level was not significantly higher in unfavorable outcome group (Glasgow Outcome scale [GOS] score = 1–3 at hospital discharge) compared with favorable outcome group (GOS score = 4–5) (P = 0.19).ConclusionsTau protein may be a useful biomarker for diagnosis of DAI in the early phase of TBI.

Integrated Proteomics and Metabolomic Analyses of Plasma Injury Biomarkers in a Serious Brain Trauma Model in Rats.

Diffuse axonal injury (DAI) is a prevalent and serious brain injury with significant morbidity and disability. However, the underlying pathogenesis of DAI remains largely unclear, and there are still no objective laboratory-based tests available for clinicians to make an early diagnosis of DAI. An integrated analysis of metabolomic data and proteomic data may be useful to identify all of the molecular mechanisms of DAI and novel potential biomarkers. Therefore, we established a rat model of DAI, and applied an integrated UPLC-Q-TOF/MS-based metabolomics and isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis to obtain unbiased profiling data. Differential analysis identified 34 metabolites and 43 proteins in rat plasma of the injury group. Two metabolites (acetone and 4-Hydroxybenzaldehyde) and two proteins (Alpha-1-antiproteinase and Alpha-1-acid glycoprotein) were identified as potential biomarkers for DAI, and all may play important roles in the pathogenesis of DAI. Our study demonstrated the feasibility of integrated metabolomics and proteomics method to uncover the underlying molecular mechanisms of DAI, and may help provide clinicians with some novel diagnostic biomarkers and therapeutic targets.

Histopathology mapping of biochemical changes in diffuse axonal injury by FTIR micro-spectroscopy.

The diagnosis of diffuse axonal injury (DAI) is an important task in forensic pathology and clinical medicine. This study aimed to explore the use of Fourier transform infrared spectroscopy (FTIR) to detect DAI. The DAI area of the rat model was detected point by point by the FTIR-mapping system. Infrared spectral data of DAI were obtained by selecting the amide A band, CH3 symmetric stretching, collagen triple-helix structure and asymmetric stretching vibrational frequency of nucleic acid and phospholipid PO2 as the target peak positions. The system can automatically draw infrared spectral color pathological images. In the DAI group, the amide A protein secondary amine N-H stretching vibration and the collagen triple-helix structure of the high-absorption area were consistent with the DAI area confirmed by the silver and β-APP staining. The CH3 symmetric stretching, nucleic acid and phospholipid PO2 symmetric stretching vibration absorption spectra showed no significant differences between the experimental and verification groups. The FTIR-mapping technique can visually express the molecular characteristics of DAI, which is expected to be applied to the pathological diagnosis of DAI.

GCS score and MRI grading does not predicts the outcome in dai patients - a prospective study

Abstract Diffuse axonal injury (DAI) is a type of brain injury due to extensive lesions in white matter tract occurring over a wide area. It is one of the most common and devastating types of traumatic brain injury and major cause of unconsciousness and persistent vegetative state after head trauma. DAI occurs in about half of all cases of severe head trauma. The study was undertaken to correlate the GCS at time of admission and Grade of DAI with the outcome. Aim: - To correlate GCS Score and MRI grading with the outcome in DAI patients. Setting and Design: - A 3 months prospective study was conducted in Department of Neurosurgery. Material and Method: - Sources of Data: - Patients admitted with clinical diagnosis of Diffuse Axonal Injury under Department of Neurosurgery. Sample size: - 50 cases of Diffuse Axonal Injury. Inclusion Criteria: - All traumatic DAI Patients requiring ICU care. Exclusion Criteria: - Head injury patients requiring Surgery. Patients other findings on imaging as contusion, EDH, SDH, IVH.Patients with Sepsis. Patients with other co morbid Illness as DM, Hypertension. Patients who were haemodynamically unstable at the time of admission. Patients with other systemic injuries. Statistical Analysis. Data so collected was analysed using IBM SPSS Statistics Windows, version 20.0 (Armonk, NY: IBM Corp) for the generation of descriptive and inferential statistics. The statistical significant difference among age groups was determined by Chi square test and one way analyses of variance. The level of significance was set at p˂0.05. Results: Distribution of patients according to Gender and MRI Grading shown in Table 1. Total 50 patients were evaluated out of which 38 (76%) were male and 12 (24%) were female. Number of patients according to Grading [Table 2 and Fig. 1] Out of 50 patients admitted 10% (5) constitutes Grade 1 DAI, 28% (14) grade II, and 62% (31) Grade III. Grades of DAI according to age of patients [Table 3]. Mean age in Grade I patients was 20.83±3.63, Grade II 23.36±7.089 and in Grade III 22.32±11.38. Comparisons of Mean ICU stay Mean Hospital stay and Mortality in Different GCS Groups [Table 4]. In patients with GCS 3-8 the mean ICU stay was 18.48±14.53, mean hospital stay was 37.24±12.31 and Mortality was 15.21%, in patients with GCS 9-12, mean ICU stay was 10.5±4.12, Hospital stay 19.4±5.79 and mortality was 25%. Comparison of Mean ICU stay, and Ventilator stay in different MRI Grade [Table 5]. In patients with Grade I DAI Mean ICU stay was 17.13±14.65 and Mean Ventilator stay was 6.24±2.57, In Grade II DAI mean ICU stay was 20.57±15.45 and Ventilator stay was 12.01±3.82 and in Grade III mean ICU stay was 23.4±15.41 and mean Ventilator stay was 10.89±2.58. Mortality of patients in different Grades and GCS groups [Table 6 and Fig 2] In patients with GCS 9-12 and Grade III only 1 patient died, while in patients with GCS 3- 8 total 7 died, 2 in Grade I, 2 in Grade II and 3 in Grade III. Complications [Table 7] Out of 5 patients in Grade I, electrolyte imbalance was seen in 1 patient in the form of hypernatraemia, 1 patient developed seizure, and septicaemia was seen in 1 and 1 patient developed shock. In patients with Grade II DAI out of 14 patients 1 had ventilator associated pneumonia, hypernatraemia was seen in 1, 1patient developed bed sore, seizures seen in 3, 2 had septicaemia & shock was seen in 2, and in 1drug reaction occurred. Out of 31 patients with Grade III DAI 2 developed ventilator associated pneumonia, hypernatraemia and hyponatraemia was seen in 2 & 1 patient respectively, 2 developed bedsore, seizure in 1 and septicaemia and shock was seen in 3-3 patients. Conclusion:-Diffuse axonal injury is a very common finding in traumatic head injury patients. Magnetic resonance imaging and GCS scoring does not have appropriate prognostic value in pure DAI patients and a better survival rate can be achieved with dedicated neurocritical care and neurosurgical management.

Correlation between CD8+ T cells′ balance and prognosis for patients with diffuse axonal injury

Objective To study the correlation between CD8+ T cells′ balance and prognosis for patients with diffuse axonal injury(DAI). Methods To collect the 41 patients with DAI as observation group, with 33 cases light craniocerebral injury (LCI) patients and 35 healthy volunteers as control group. We detect the peripheral blood CD8+ CD28 + T cells and CD8+ CD28-T cell percentage, and calculate the ratio of both. The subjects working curve method (ROC) of the above CD8+ T cells and its ratio were used to predict the prognosis of patients with DAI efficiency evaluation. Results ⑴ Compared with control group, CD8+ CD28+ T cells in patients with DAI and LCI increased significantly, and DAI was significantly higher than that of LCI group (P<0.05). Compared with control group, CD8+ CD28-T cells in patients with DAI were decreased, but no statistical difference was found between LCI and the control group, but DAI group was significantly lower than the LCI group (P<0.05). ⑵ CD8+ CD28-T cells and CD8+ CD28+ /CD8+ CD28- ratio were correlated with DAI diagnosis (P=0.003, 0.000). When the percentage of CD8+ CD28-T cells =2.95%, the sensitivity of the diagnosis of DAI was 87.49%, 86.21%; When the ratio of CD8+ CD28+ /CD8+ CD28-=7.39, the sensitivity was 92.63%, 90.71%. ⑶ a total of 7 cases of patients died within 1 week after injury, CD8+ CD28+ T cells and CD8+ CD28+ /CD8+ CD28- ratio were significantly negative correlated with survival time (r=-0.739, -0.834, P=0.021, 0.002), and CD8+ CD28-T cells were significantly positive correlated with survival time (r=0.782, P=0.006). Conclusions Decreasing CD8+ CD28-T cells and higher CD8+ CD28+ /CD8+ CD28- ratio in patients with DAI immunological characteristics, especially the ratio (balance) is closely corrected with the diagnosis and prognosis of DAI. Key words: Diffuse axonal injury/IM; CD8-positive T-lymphocytes/ME; Prognosis

Integration of 1H NMR- and UPLC-Q-TOF/MS-based plasma metabonomics study to identify diffuse axonal injury biomarkers in rat

Diffuse axonal injury (DAI) is much common during traumatic brain injury (TBI) and is associated with high mortality and poor neurological outcome. Although many studies have been examined, there are still no reliable objective diagnostic modalities available for clinicians to make an early diagnosis of DAI. Therefore, we established a rat model of DAI, applying an integrated 1H NMR- and UPLC-Q-TOF/MS-based metabonomics approach to identify differentially changed metabolites in plasma. A total of twenty-two metabolites in the injury group were identified as differentially changed. Among them, four metabolites, glutamine, pyruvate, glycerol and phosphocholine, were identified as candidate biomarkers based on their high fold-changes and biological functions, and may play important roles in axonal injury progression in DAI. Our study not only identified several novel biomarkers that improved our understanding of the metabolic events underlying DAI, but also may provide some potential novel therapeutic targets for preventing axonal injury in DAI.

Screening of Differential Expression Proteins in Rat Brain Tissues after DAI by iTRAQ-LC-MS/MS

To screen for the differential expression proteins in brain tissues of SD rat after diffuse axonal injury （DAI） by isobaric tag for relative and absolute quantification-liquid chromatograph-mass spectrometer/mass spectrometer （iTRAQ-LC-MS/MS）, and to explore potential biomarkers available for the diagnosis of DAI. Animal models of DAI were established with the Marmarou method as reference, and the subjects were divided into blank control group （n=4）, sham strike group （n=4） and fatal strike group （n=4）, respectively. The proteins in rat brain tissues were detected by iTRAQ-LC-MS/MS, and bioinformatics analysis and verification were performed on the results and screened for the differential expression proteins. A total of 2 016 proteins were identified and quantified. The bioinformatics analysis revealed that the proteins had wide distribution and function, and participated in different biological processes. There were 16 proteins showed differential expression in fatal strike group, including one up-regulated expression protein and 15 down-regulated expression proteins. The results of iTRAQ-LC-MS/MS were confirmed by Western blotting method. Multiple differential expression proteins in rat brain tissues after DAI can be screened by iTRAQ-LC-MS/MS. This not only indicates a research direction for exploring the pathogenesis of DAI, but also provides potential biomarkers available for the diagnosis of DAI.

Diffuse Axonal Injury: Epidemiology, Outcome and Associated Risk Factors.

Diffuse axonal injury (DAI), a type of traumatic injury, is known for its severe consequences. However, there are few studies describing the outcomes of DAI and the risk factors associated with it. This study aimed to describe the outcome for patients with a primary diagnosis of DAI 6 months after trauma and to identify sociodemographic and clinical factors associated with mortality and dependence at this time point. Seventy-eight patients with DAI were recruited from July 2013 to February 2014 in a prospective cohort study. Patient outcome was analyzed using the Extended Glasgow Outcome Scale (GOS-E) within 6 months of the traumatic injury. The mean Injury Severity Score was 35.0 (SD = 11.9), and the mean New Injury Severity Score (NISS) was 46.2 (SD = 15.9). Mild DAI was observed in 44.9% of the patients and severe DAI in 35.9%. Six months after trauma, 30.8% of the patients had died, and 45.1% had shown full recovery according to the GOS-E. In the logistic regression model, the severity variables – DAI with hypoxia, as measured by peripheral oxygen saturation, and hypotension with NISS value – had a statistically significant association with patient mortality; on the other hand, severity of DAI and length of hospital stay were the only significant predictors for dependence. Therefore, severity of DAI emerged as a risk factor for both mortality and dependence.

Diffuse Axonal Injury: Pathological and Clinical Aspects

Diffuse axonal and vascular injuries are the initial pathological findings in victims of diffuse brain trauma Macroscopic findings include deep contusions and multiple petechial hemorrhages primarily involving cerebral white matter basal ganglia and upper brainstem Histologically amyloid precursor protein staining still remains the gold standard for microscopic detection of diffuse axonal damage A number of other histological and immunohistochemical techniques have emerged over time aiding the diagnosis of diffuse axonal injury There has been little success however in the microscopic differentiation of traumatic from non traumatic causes of diffuse axonal injury This review explains various pathological and clinical aspects of traumatic axonal and vascular injuries including current scenarios in microscopic detection of diffuse axonal injury as well as their limitations