Neutrophil-to-lymphocyte ratio (NLR) and monocyte-to-lymphocyte ratio (MLR) have been identified as potential prognostic markers in various conditions, including cancer, cardiovascular disease, and stroke. This study aims to investigate the dynamic changes of NLR and MLR following cerebral contusion and their associations with six-month outcomes.
Retrospective data were collected from January 2016 to April 2020, including patients diagnosed with cerebral contusion and discharged from two teaching-oriented tertiary hospitals in Southern China. Patient demographics, clinical manifestations, laboratory test results (neutrophil, monocyte, and lymphocyte counts) obtained at admission, 24 hours, and one week after cerebral contusion, as well as outcomes, were analyzed. An unfavorable outcome was defined as a Glasgow Outcome Score (GOS) of 0-3 at six months. Logistic regression analysis was performed to identify independent predictors of prognosis, while receiver characteristic curve analysis was used to determine the optimal cutoff values for NLR and MLR.
A total of 552 patients (mean age 47.40, SD 17.09) were included, with 73.19% being male. Higher NLR at one-week post-cerebral contusion (adjusted OR = 4.19, 95%CI, 1.16 - 15.16, P = 0.029) and higher MLR at admission and at 24 h (5.80, 1.40 - 24.02, P = 0.015; 9.06, 1.45 - 56.54, P = 0.018, respectively) were significantly associated with a 6-month unfavorable prognosis after adjustment for other risk factors by multiple logistic regression. The NLR at admission and 24 hours, as well as the MLR at one week, were not significant predictors for a 6-month unfavorable prognosis. Based on receiver operating characteristic curve analysis, the optimal thresholds of NLR at 1 week and MLR at admission after cerebral contusion that best discriminated a unfavorable outcome at 6-month were 6.39 (81.60% sensitivity and 70.73% specificity) and 0.76 (55.47% sensitivity and 78.26% specificity), respectively.
NLR measured one week after cerebral contusion and MLR measured at admission may serve as predictive markers for a 6-month unfavorable prognosis. These ratios hold potential as parameters for risk stratification in patients with cerebral contusion, complementing established biomarkers in diagnosis and treatment. However, further prospective studies with larger cohorts are needed to validate these findings.

Hemorrhagic progression of contusion (HPC) often occurs early in cerebral contusions (CC) patients, significantly impacting their prognosis. It is vital to promptly assess HPC and predict outcomes for effective tailored interventions, thereby enhancing prognosis in CC patients. We utilized the Attention-3DUNet neural network to semi-automatically segment hematomas from computed tomography (CT) images of 452 CC patients, incorporating 695 hematomas. Subsequently, 1502 radiomic features were extracted from 358 hematomas in 261 patients. After a selection process, these features were used to calculate the radiomic signature (Radscore). The Radscore, along with clinical features such as medical history, physical examinations, laboratory results, and radiological findings, was employed to develop predictive models. For prognosis (discharge Glasgow Outcome Scale score), radiomic features of each hematoma were augmented and fused for correlation. We employed various machine learning methodologies to create both a combined model, integrating radiomics and clinical features, and a clinical-only model. Nomograms based on logistic regression were constructed to visually represent the predictive procedure, and external validation was performed on 170 patients from three additional centers. The results showed that for HPC, the combined model, incorporating hemoglobin levels, Rotterdam CT score of 3, multi-hematoma fuzzy sign, concurrent subdural hemorrhage, international normalized ratio, and Radscore, achieved area under the receiver operating characteristic curve (AUC) values of 0.848 and 0.836 in the test and external validation cohorts, respectively. The clinical model predicting prognosis, utilizing age, Abbreviated Injury Scale for the head, Glasgow Coma Scale Motor component, Glasgow Coma Scale Verbal component, albumin, and Radscore, attained AUC values of 0.846 and 0.803 in the test and external validation cohorts, respectively. Selected radiomic features indicated that irregularly shaped and highly heterogeneous hematomas increased the likelihood of HPC, while larger weighted axial lengths and lower densities of hematomas were associated with a higher risk of poor prognosis. Predictive models that combine radiomic and clinical features exhibit robust performance in forecasting HPC and the risk of poor prognosis in CC patients. Radiomic features complement clinical features in predicting HPC, although their ability to enhance the predictive accuracy of the clinical model for adverse prognosis is limited.

BACKGROUND: The objective of this research was to examine the impact of the monocyte-to-lymphocyte ratio (MLR) on the advancement of hematoma after cerebral contusion.
METHODS: The clinical information and laboratory test findings of people with cerebral contusion were retrospectively analyzed. Using the tertiles of MLR, the study participants were categorized into three groups, enabling the evaluation of the correlation between MLR and the advancement of hematoma after cerebral contusion.
RESULTS: Among the cohort of patients showing progression, MLR levels were significantly higher compared with the nonprogress group (P < 0.001). The high MLR group had a significantly higher proportion of patients with hematoma progression compared with the medium and low MLR groups. However, the medium MLR group had a lower proportion of patients with hematoma progression compared with the low MLR group. High MLR levels were independently linked to a higher risk of hematoma progression (Odds Ratio 3.546, 95% Confidence Interval 1.187-10.597, P = 0.024). By incorporating factors such as Glasgow Coma Scale score on admission, anticoagulant/antiplatelet therapy, white blood cell count, and MLR into the model, the predictive performance of the model significantly improved (area under the curve 0.754).
CONCLUSIONS: Our study suggests that MLR may serve as a potential indicator for predicting the progression of hematoma after cerebral contusion. Further research is necessary to investigate the underlying pathological and physiological mechanisms that contribute to the association between MLR and the progression of hematoma after cerebral contusion and to explore its clinical implications.

UNASSIGNED: Cerebral contusion (CC) results in a release of catecholamines, autonomic dysfunction and neural stimulation that can lead to a number of cardiac adverse events, so it is critical to determine these. So the objective of this study was to investigate the prognostic significance of electrocardiographic changes, particularly the effects of a prolonged corrected QT (QTc) interval in CC.
UNASSIGNED: In this retrospective cohort study, 110 patients with CC were evaluated. Age, sex, concomitant diseases, Glasgow Coma Scale on admission, radiological assessment of the contusion (location, size, course and presence of cerebral oedema), need for surgical intervention, length of hospital stay and the extended Glasgow Outcome Scale (GOS-E) were statistically analysed within the QTc interval by routine electrocardiography (ECG) on admission.
UNASSIGNED: The prolonged QTc interval was found to be associated with a higher incidence of cerebral oedema and a significantly higher risk of needing surgery. Patients with a prolonged QTc interval had a significantly larger contusion volume, greater midline shift and longer hospital stay, so their GOS-E score was significantly lower. A prolonged QTc interval on admission resulted in a hospital stay of more than eight days (sensitivity: 0.97 and specificity: 0.86), a higher risk of midline shift of more than 0.45 cm (P=0.006, sensitivity: 0.80 and specificity: 0.99) and a GOS-E score of <7 (sensitivity: 0.97 and specificity: 0.85).
UNASSIGNED: ECG changes on admission showing a prolonged QTc interval have prognostic significance in CC. This simple and easily applicable information should be taken into consideration at the time of clinical decision making which may prevent an adverse events survivor.

UNASSIGNED: Blood-brain barrier (BBB) dysregulation and pro-inflammatory signalling molecules are secondary factors that have been associated with injury severity and long-term clinical outcome following traumatic brain injury (TBI). However, the association between BBB permeability and inflammation is unknown in human TBI patients. In this study, we investigated whether BBI integrity as measured by Dynamic Contrast-Enhanced (DCE) Magnetic Resonance Imaging (MRI) correlates with plasma levels of immunological markers following TBI.
UNASSIGNED: Thirty-two TBI patients recruited from a neurosurgical unit were included in the study. Structural three-dimensional T1-weighted and DCE-MRI images were acquired on a 3T MRI at the earliest opportunity once the participant was sufficiently stable after patient admission to hospital. Blood sampling was performed on the same day as the MRI. The location and extents of the haemorrhagic and contusional lesions were identified. Immunological biomarkers were quantified from the participants\' plasma using a multiplex immunoassay. Demographic and clinical information, including age and Glasgow Coma Scale (GCS) were also collected and the immunological biomarker profiles were compared across controls and the TBI severity sub-groups. Contrast agent leakiness through blood-brain barriers (BBB) in the contusional lesions were assessed by fitting DCE-MRI using Patlak model and BBB leakiness characteristics of the participants were correlated with the immunological biomarker profiles.
UNASSIGNED: TBI patients showed reduced plasma levels of interleukin (IL)-1β, IFN-γ, IL-13, and chemokine (C-C motif) ligands (CCL)2 compared to controls and significantly higher levels of platelet-derived growth factor (PDGF-BB), IL-6, and IL-8. BBB leakiness of the contusional lesions did not significantly differ across different TBI severity sub-groups. IL-1ra levels significantly and positively correlated with the contusional lesion\'s BBB integrity as measured with DCE-MRI via an exponential curve relationship.
UNASSIGNED: This is the first study to combine DCE-MRI with plasma markers of inflammation in acute TBI patients. Our finding that plasma levels of the anti-inflammatory cytokine IL-1ra correlated negatively with increased leakiness of the BBB.

The emergency room management of a patient with external signs of cranial trauma and imaging showing brain hemorrhage can be dangerously misleading. This case of a patient with glioblastoma could only be timely diagnosed because of cautious evaluation of imaging findings. A 60-year-old patient presented to the emergency room after being found down with external signs of cranial trauma and a reduced level of consciousness. Computed tomography revealed a right frontal polar cortical hemorrhage of around 12 mm diameter with no perilesional edema or contrast enhancement. Likewise, the MRI showed no contrast enhancement. Before the scheduled MRI follow-up was performed the patient became symptomatic leading to an earlier repeat that showed massive progression. She underwent surgical resection that revealed the lesion to be an aggressive glioblastoma. High suspicion of an underlying neoplastic lesion in atypical brain hemorrhage in trauma patients is paramount. Short MRI follow-up is recommended as soon as the hematoma resorbs to prevent delays with potential impact or patient outcome.

暂无摘要。

BACKGROUND: Acute traumatic intraparenchymal hematoma (tICH) expansion is a major cause of clinical deterioration after brain contusion. Here, an accurate prediction tool for acute tICH expansion is proposed.
METHODS: A multicenter hospital-based study for multivariable prediction model was conducted among patients (889 patients in a development dataset and 264 individuals in an external validation dataset) with initial and follow-up computed tomography (CT) imaging for tICH volume evaluation. Semi-automated software was employed to assess tICH expansion. Two multivariate predictive models for acute tICH expansion were developed and externally validated.
RESULTS: A total of 198 (22.27%) individuals had remarkable acute tICH expansion. The novel Traumatic Parenchymatous Hematoma Expansion Aid (TPHEA) model retained several variables, including age, coagulopathy, baseline tICH volume, time to baseline CT time, subdural hemorrhage, a novel imaging marker of multihematoma fuzzy sign, and an inflammatory index of monocyte-to-lymphocyte ratio. Compared with multihematoma fuzzy sign, monocyte-to-lymphocyte ratio, and the basic model, the TPHEA model exhibited optimal discrimination, calibration, and clinical net benefits for patients with acute tICH expansion. A TPHEA nomogram was subsequently introduced from this model to facilitate clinical application. In an external dataset, this device showed good predicting performance for acute tICH expansion.
CONCLUSIONS: The main predictive factors in the TPHEA nomogram are the monocyte-to-lymphocyte ratio, baseline tICH volume, and multihematoma fuzzy sign. This user-friendly tool can estimate acute tICH expansion and optimize personalized treatments for individuals with brain contusion.

Controlled cortical impact (CCI) on porcine brain is often utilized to investigate the pathophysiology and functional outcome of focal traumatic brain injury (TBI), such as cerebral contusion (CC). Using a finite element (FE) model of the porcine brain, the localized brain strain and strain rate resulting from CCI can be computed and compared to the experimentally assessed cortical lesion. This way, tissue-level injury metrics and corresponding thresholds specific for CC can be established. However, the variability and uncertainty associated with the CCI experimental parameters contribute to the uncertainty of the provoked cortical lesion and, in turn, of the predicted injury metrics. Uncertainty quantification via probabilistic methods (Monte Carlo simulation, MCS) requires a large number of FE simulations, which results in a time-consuming process. Following the recent success of machine learning (ML) in TBI biomechanical modeling, we developed an artificial neural network as surrogate of the FE porcine brain model to predict the brain strain and the strain rate in a computationally efficient way. We assessed the effect of several experimental and modeling parameters on four FE-derived CC injury metrics (maximum principal strain, maximum principal strain rate, product of maximum principal strain and strain rate, and maximum shear strain). Next, we compared the in silico brain mechanical response with cortical damage data from in vivo CCI experiments on pig brains to evaluate the predictive performance of the CC injury metrics. Our ML surrogate was capable of rapidly predicting the outcome of the FE porcine brain undergoing CCI. The now computationally efficient MCS showed that depth and velocity of indentation were the most influential parameters for the strain and the strain rate-based injury metrics, respectively. The sensitivity analysis and comparison with the cortical damage experimental data indicate a better performance of maximum principal strain and maximum shear strain as tissue-level injury metrics for CC. These results provide guidelines to optimize the design of CCI tests and bring new insights to the understanding of the mechanical response of brain tissue to focal traumatic brain injury. Our findings also highlight the potential of using ML for computationally efficient TBI biomechanics investigations.

UNASSIGNED: Cerebral contusions (CC) represent a frequent lesion in traumatic brain injury, with potential morbidity from mass effect and tissue loss. Better understanding of the mechanical etiology will help to improve head protection. The goal of this study is to investigate the threshold for mechanical impact parameters to induce CC in an in vivo porcine controlled cortical impact model.
UNASSIGNED: Thirty-four adult male pigs underwent craniotomy and controlled cortical impact with a hemispherical tip on intact dura under general anesthesia. Peak impact depth varied between 1.1 and 12.6 mm, and impact velocity between 0.4 and 2.2 m/s while the dwell time was kept at 200 ms. Two days following impact, the animals underwent magnetic resonance (MR) imaging of the brain, and were subsequently sacrificed for brain extraction. CC damage was investigated by magnetic resonance imaging and histology.
UNASSIGNED: All animals recovered from the impact without overt neurological deficit. Provoked injuries were histologically confirmed to be CC. Decreasing probability of cortical damage and white matter edema volume was observed with decreasing impact depth and velocity. No CC could be demonstrated below a product of impact depth and velocity of 0.8 mm*m/s, whereas the probability for CC was one third below 15 mm*m/s. The threshold for CC development as estimated from the current series of experiments, was situated at an impact depth of 2.0 mm and impact velocity of 0.4 m/s.
UNASSIGNED: Mechanical thresholds for CC development could be explored in the current porcine controlled cortical impact model. Findings will be used to further refine a cerebral contusion porcine model with volumetric histology data in light of future finite element cerebral contusion validation studies.