Defining the Optimal Midline Shift Threshold to Predict Poor Outcome in Patients with Supratentorial Spontaneous Intracerebral Hemorrhage

Can the radiomics features of intracranial aneurysms predict the prognosis of aneurysmal subarachnoid hemorrhage?

Objectives

This study attempted to determine potential predictors among radiomics features for poor prognosis in aneurysmal subarachnoid hemorrhage (aSAH), develop models for prediction, and verify their predictive power.

Methods

In total, 252 patients with aSAH were included in this study and categorized into favorable and poor outcome groups based on the modified Rankin Scale score 3 months after event. Radiomics features of the ruptured intracranial aneurysm extracted from computed tomography angiography images were selected using least absolute shrinkage and selection operator regression and 10-fold cross-validation. A radiomics score was created by selecting the optimal features. Other risk factors for a poor prognosis were screened using multivariate regression analysis. Three models (clinical, aneurysm, and clinical-aneurysm combined models) were developed. The performance of the models was assessed using receiver operating characteristic (ROC) curves. A clinical-aneurysm combined nomogram was constructed to forecast the risk of poor prognosis in patients with aSAH.

Results

A total of three clinical variables and six radiomics features were shown to have a significant association with poor prognosis in patients with aSAH. In the training cohort, the clinical, aneurysm, and clinical-aneurysm combined models had areas under the ROC curves of 0.846, 0.762, and 0.893, respectively. In the testing cohort, these models had areas under the ROC curves of 0.848, 0.753, and 0.869, respectively.

Conclusion

The radiomics characteristics of ruptured intracranial aneurysms are valuable to predict prognosis after aSAH. The clinical-aneurysm combined model exhibited the best among the three models. The clinical-aneurysm combined nomogram is a reliable and effective tool for predicting poor prognosis in patients with aSAH.

Enhancing Outcome Prediction in Intracerebral Hemorrhage Through Deep Learning: A Retrospective Multicenter Study

RATIONALE AND OBJECTIVES

This study aimed to employ deep learning techniques to analyze and validate an automatic prognostic biomarker for predicting outcomes following intracerebral hemorrhage (ICH).

MATERIALS AND METHODS

This study included patients with ICH whose onset-to-imaging time (OIT) was less than 6 h. Patients were randomly divided into training and test sets at a 7:3 ratio. Using the Resnet50 deep learning method, we extracted features from the hematoma and perihematomal edema (PHE) areas and constructed a 90-day prognosis prediction model using logistic regression. To evaluate predictive efficacy and clinical significance, we employed logistic regression to train three models: Clinical, Deep Score, and the combined Clinical-Deep Learning (Merge).

RESULTS

Our study comprised 1098 patients (652 male, 446 female), with a mean Glasgow Coma Scale (GCS) score of 10. Univariate and multivariate analyses identified age, intraventricular hemorrhage (IVH), hematoma and PHE volume, and admission GCS score as independent prognostic factors. Additionally, 15 deep learning features were retained through LASSO regression. In the training set, the AUC values for the three models were as follows: Clinical model (0.88), Deep Score (0.91), and Merge model (0.94). In the test set, the Merge model exhibited a significantly higher AUC value than the other models. Calibration curves revealed satisfactory calibration of the Merge model nomogram in both training and test sets.

CONCLUSION

Our Merge model nomogram is an objective and effective prognostic tool, offering personalized risk assessments for 90-day functional outcomes in patients with ICH.

The relationship between perihematomal edema and hematoma expansion in acute spontaneous intracerebral hemorrhage: an exploratory radiomics analysis study

Background

The relationship between early perihematomal edema (PHE) and hematoma expansion (HE) is unclear. We investigated this relationship in patients with acute spontaneous intracerebral hemorrhage (ICH), using radiomics.

Methods

In this multicenter retrospective study, we analyzed 490 patients with spontaneous ICH who underwent non-contrast computed tomography within 6 h of symptom onset, with follow-up imaging at 24 h. We performed HE and PHE image segmentation, and feature extraction and selection to identify HE-associated optimal radiomics features. We calculated radiomics scores of hematoma (Radscores_HEA) and PHE (Radscores_PHE) and constructed a combined model (Radscore_HEA_PHE). Relationships of the PHE radiomics features or Radscores_PHE with clinical variables, hematoma imaging signs, Radscores_HEA, and HE were assessed by univariate, correlation, and multivariate analyses. We compared predictive performances in the training (n = 296) and validation (n = 194) cohorts.

Results

Shape_VoxelVolume and Shape_MinorAxisLength of PHE were identified as optimal radiomics features associated with HE. Radscore_PHE (odds ratio = 1.039, p = 0.032) was an independent HE risk factor after adjusting for the ICH onset time, Glasgow Coma Scale score, baseline hematoma volume, hematoma shape, hematoma density, midline shift, and Radscore_HEA. The areas under the receiver operating characteristic curve of Radscore_PHE in the training and validation cohorts were 0.808 and 0.739, respectively. After incorporating Radscore_PHE, the integrated discrimination improvements of Radscore_HEA_PHE in the training and validation cohorts were 0.009 (p = 0.086) and -0.011 (p < 0.001), respectively.

Conclusion

Radscore_PHE, based on Shape_VoxelVolume and Shape_MinorAxisLength of PHE, independently predicts HE, while Radscore_PHE did not add significant incremental value to Radscore_HEA.

Cranial midline shift is a predictor of the clinical prognosis of acute cerebral infarction patients undergoing emergency endovascular treatment

Endovascular treatment is widely used in acute cerebral infarction (ACI), but patient prognosis varies greatly. We aimed to investigate the predictive value of midline shift (MLS) threshold for the clinical prognosis of patients with ACI who undergo emergency endovascular treatment. We prospectively enrolled patients with ACI who received endovascular treatment within 24 h of onset. Cranial images were collected within 24 h after endovascular treatment. We assessed MLS at the level of the midbrain, pineal calcification, septum pellucida, and falx cerebri and noted the maximum MLS (MLS[max]) among these locations. Functional outcomes were assessed at 90 days using the modified Rankin Scale. Receiver operating characteristic curves and optimal cutoff points were used to analyze the predictive value of MLS. We enrolled 82 patients, including 46 with poor outcomes. Although the MLS values at all levels were significantly different between the poor and favorable outcome groups (p < 0.01), the MLS(max) tended to be a better marker for 90-day poor outcome. To predict poor outcome, the optimal cutoff values for MLS(max) within 24 and 48 h after intervention were 0.45 and 2.35 mm, respectively. MLS(max) has predictive value for patient prognosis.

Fecal microbial transplantation limits neural injury severity and functional deficits in a pediatric piglet traumatic brain injury model

Pediatric traumatic brain injury (TBI) is a leading cause of death and disability in children. Due to bidirectional communication between the brain and gut microbial population, introduction of key gut bacteria may mitigate critical TBI-induced secondary injury cascades, thus lessening neural damage and improving functional outcomes. The objective of this study was to determine the efficacy of a daily fecal microbial transplant (FMT) to alleviate neural injury severity, prevent gut dysbiosis, and improve functional recovery post TBI in a translational pediatric piglet model. Male piglets at 4-weeks of age were randomly assigned to Sham + saline, TBI + saline, or TBI + FMT treatment groups. A moderate/severe TBI was induced by controlled cortical impact and Sham pigs underwent craniectomy surgery only. FMT or saline were administered by oral gavage daily for 7 days. MRI was performed 1 day (1D) and 7 days (7D) post TBI. Fecal and cecal samples were collected for 16S rRNA gene sequencing. Ipsilateral brain and ileum tissue samples were collected for histological assessment. Gait and behavior testing were conducted at multiple timepoints. MRI showed that FMT treated animals demonstrated decreased lesion volume and hemorrhage volume at 7D post TBI as compared to 1D post TBI. Histological analysis revealed improved neuron and oligodendrocyte survival and restored ileum tissue morphology at 7D post TBI in FMT treated animals. Microbiome analysis indicated decreased dysbiosis in FMT treated animals with an increase in multiple probiotic Lactobacilli species, associated with anti-inflammatory therapeutic effects, in the cecum of the FMT treated animals, while non-treated TBI animals showed an increase in pathogenic bacteria, associated with inflammation and disease such in feces. FMT mediated enhanced cellular and tissue recovery resulted in improved motor function including stride and step length and voluntary motor activity in FMT treated animals. Here we report for the first time in a highly translatable pediatric piglet TBI model, the potential of FMT treatment to significantly limit cellular and tissue damage leading to improved functional outcomes following a TBI.

Perihematomal edema-based CT-radiomics model to predict functional outcome in patients with intracerebral hemorrhage

PURPOSE

The purpose of this study was to identify possible association between noncontrast computed tomography (NCCT)-based radiomics features of perihematomal edema (PHE) and poor functional outcome at 90 days after intracerebral hemorrhage (ICH) and to develop a NCCT-based radiomics-clinical nomogram to predict 90-day functional outcomes in patients with ICH.

MATERIALS AND METHODS

In this multicenter retrospective study, 107 radiomics features were extracted from 1098 NCCT examinations obtained in 1098 patients with ICH. There were 652 men and 446 women with a mean age of 60 ± 12 (SD) years (range: 23-95 years). After harmonized and univariable and multivariable screening, seven of these radiomics features were closely associated with the 90-day functional outcome of patients with ICH. The radiomics score (Rad-score) was calculated based on the seven radiomics features. A clinical-radiomics nomogram was developed and validated in three cohorts. The model performance was evaluated using area under the curve analysis and decision and calibration curves.

RESULTS

Of the 1098 patients with ICH, 395 had a good outcome at 90 days. Hematoma hypodensity sign and intraventricular and subarachnoid hemorrhages were identified as risk factors for poor outcomes (P < 0.001). Age, Glasgow coma scale score, and Rad-score were independently associated with outcome. The clinical-radiomics nomogram showed good predictive performance with AUCs of 0.882 (95% CI: 0.859-0.905), 0.834 (95% CI: 0.776-0.891) and 0.905 (95% CI: 0.839-0.970) in the three cohorts and clinical applicability.

CONCLUSION

NCCT-based radiomics features from PHE are highly correlated with outcome. When combined with Rad-score, radiomics features from PHE can improve the predictive performance for 90-day poor outcome in patients with ICH.

Thrombolysis Outcomes in Acute Ischaemic Stroke Patients with Pre-Existing Cognitive Impairment

BACKGROUND

Thrombolysis treatment for ischaemic stroke in patients with pre-existing disabilities, including cognitive impairment, remains controversial. Previous studies have suggested functional outcomes post-thrombolysis are worse in patients with cognitive impairment. This study aimed to compare and explore factors contributing to thrombolysis outcomes, including haemorrhagic complications, in cognitively and non-cognitively impaired patients with ischaemic stroke.

MATERIALS AND METHODS

A retrospective analysis of 428 ischaemic stroke patients who were thrombolysed between January 2016 and February 2021 was performed. Cognitive impairment was defined as a diagnosis of dementia, mild cognitive impairment, or clinical evidence of the condition. The outcome measures included morbidity (using NIHSS and mRS), haemorrhagic complications, and mortality, and were analysed using multivariable logistic regression models.

RESULTS

The analysis of the cohort revealed that 62 patients were cognitively impaired. When compared to those without cognitive impairment, this group showed worse functional status at discharge (mRS 4 vs. 3, p < 0.001) and a higher probability of dying within 90 days (OR 3.34, 95% CI 1.85-6.01, p < 0.001). A higher risk of a fatal ICH post-thrombolysis was observed in the cognitively impaired patients, and, after controlling for covariates, cognitive impairment remained a significant predictor of a fatal haemorrhage (OR 4.79, 95% CI 1.24-18.45, p = 0.023).

CONCLUSIONS

Cognitively impaired ischaemic stroke patients experience increased morbidity, mortality, and haemorrhagic complications following thrombolytic therapy. However cognitive status is not independently predictive of most outcome measures. Further work is required to elucidate contributing factors to the poor outcomes observed in these patients and help guide thrombolysis decision-making in clinical practice.

Outcome Prediction of Spontaneous Supratentorial Intracerebral Hemorrhage after Surgical Treatment Based on Non-Contrast Computed Tomography: A Multicenter Study

This study aims to explore the value of a machine learning (ML) model based on radiomics features and clinical features in predicting the outcome of spontaneous supratentorial intracerebral hemorrhage (sICH) 90 days after surgery. A total of 348 patients with sICH underwent craniotomy evacuation of hematoma from three medical centers. One hundred and eight radiomics features were extracted from sICH lesions on baseline CT. Radiomics features were screened using 12 feature selection algorithms. Clinical features included age, gender, admission Glasgow Coma Scale (GCS), intraventricular hemorrhage (IVH), midline shift (MLS), and deep ICH. Nine ML models were constructed based on clinical feature, and clinical features + radiomics features, respectively. Grid search was performed on different combinations of feature selection and ML model for parameter tuning. The averaged receiver operating characteristics (ROC) area under curve (AUC) was calculated and the model with the largest AUC was selected. It was then tested using multicenter data. The combination of lasso regression feature selection and logistic regression model based on clinical features + radiomics features had the best performance (AUC: 0.87). The best model predicted an AUC of 0.85 (95%CI, 0.75-0.94) on the internal test set and 0.81 (95%CI, 0.64-0.99) and 0.83 (95%CI, 0.68-0.97) on the two external test sets, respectively. Twenty-two radiomics features were selected by lasso regression. The second-order feature gray level non-uniformity normalized was the most important radiomics feature. Age is the feature with the greatest contribution to prediction. The combination of clinical features and radiomics features using logistic regression models can improve the outcome prediction of patients with sICH 90 days after surgery.

Comparative outcome of endovascular embolization with microsurgery in managing acute spontaneous cerebral hemorrhage in pediatric patients, an institutional experience

OBJECTIVES

A few previous studies have reported the role of embolization with curative intent in the treatment of the early phase of a spontaneous cerebral hemorrhage in pediatric patients, and its efficacy needs to be compared with surgery at the same time risk factors for hemorrhage following early embolization in such patients need to be evaluated.

METHODS

From a pool of 80 pediatric (< 18 years) who had undergone treatment for ruptured AVM with hemorrhage at our center between July 2018 and July 2022, we identified 36 patients with spontaneous bleeding due to AVM. Out of which, 20 were treated solely by embolization (group 1), while the remaining patients were treated surgically (with and without adjuvant embolization) (group 2).

RESULT

Spetzler-Martin's grading of the lesion suggested seven lesions < 3 and 13 lesions ≥ 3 in the embolization group. Similarly, seven lesions were < 3 and nine ≥ 3 Spetzler-Martin grade in the surgery group. Incomplete embolization was associated with hemorrhage in two patients treated with curative intent and four patients treated with embolization as adjuvant in the surgery group (p = 0.01). On follow-up, 18 patients in the embolization group and 12 in the surgery group had Glasgow outcome scores ≥ 4 (p = 0.273).

CONCLUSION

In the pediatric age group, incomplete embolization is the significant risk factor for hemorrhage in AVMs treated after a hemorrhagic stroke. Embolization with curative intent is as effective as surgery in treating such lesions as adjuvant embolization with careful patient selection.

A Nomogram Based on CT Radiomics and Clinical Risk Factors for Prediction of Prognosis of Hypertensive Intracerebral Hemorrhage

Purpose. To develop and validate a clinical-radiomics nomogram based on clinical risk factors and CT radiomics feature to predict hypertensive intracerebral hemorrhage (HICH) prognosis. Methods. A total of 195 patients with HICH treated in our hospital from January 2018 to January 2022 were retrospectively enrolled and randomly divided into two cohorts for training (n = 138) and validation (n = 57) according to the ratio of 7 : 3. All CT radiomics features were extracted from intrahematomal, perihematomal, and combined intra- and perihematomal regions by using free open-source software called 3D slicer. The least absolute shrinkage and selection operator method was used to select the optimal radiomics features, and the radiomics score (Rad-score) was calculated. The relationship between Rad-score, clinical risk factors, and the HICH prognosis was analyzed by univariate and multivariate logistic regression analyses, and the clinical-radiomics nomogram was built. The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to evaluate the performance of the clinical-radiomics nomogram in predicting the prognosis of HICH. Results. A total of 1702 radiomics features were extracted from the CT images of each patient for analysis. By univariate and stepwise multivariate logistic regression analyses, age, sex, RBC, serum glucose, D-dimer level, hematoma volume, and midline shift were clinical risk factors for the prognosis of HICH. Rad-score and clinical risk factors developed the clinical-radiomics nomogram. The nomogram showed the highest predictive efficiency in the training cohort (AUC = 0.95, 95% confidence interval (CI), 0.92 to 0.98) and the validation cohort (AUC = 0.90, 95% CI, 0.82 to 0.98). The calibration curve indicated that the clinical-radiomics nomogram had good calibration. DCA showed that the nomogram had high applicability in clinical practice. Conclusions. The clinical-radiomics nomogram incorporated with the radiomics features and clinical risk factors has good potential in predicting the prognosis of HICH.

Radiomics for prediction of intracerebral hemorrhage outcomes: A retrospective multicenter study

BACKGROUND

Accurate risk stratification of patients with intracerebral hemorrhage (ICH) could help refine adjuvant therapy selection and better understand the clinical course. We aimed to evaluate the value of radiomics features from hematomal and perihematomal edema areas for prognosis prediction and to develop a model combining clinical and radiomic features for accurate outcome prediction of patients with ICH.

METHODS

This multicenter study enrolled patients with ICH from January 2016 to November 2021. Their outcomes at 3 months were recorded based on the modified Rankin Scale (good, 0-3; poor, 4-6). Independent clinical and radiomic risk factors for poor outcome were identified through multivariate logistic regression analysis, and predictive models were developed. Model performance and clinical utility were evaluated in both internal and external cohorts.

RESULTS

Among the 1098 ICH patients evaluated (mean age, 60 ± 13 years), 703 (64 %) had poor outcomes. Age, hemorrhage volume and location, and Glasgow Coma Scale (GCS) were independently associated with outcomes. The area under the receiver operating characteristic curve (AUC) of the clinical model was 0.881 in the external validation cohort. Addition of the Rad-score (combined hematoma and perihematomal edema area) improved predictive accuracy and model performance (AUC, 0.893), net reclassification improvement, 0.140 (P < 0.001), and integrated discrimination improvement, 0.050 (P < 0.001).

CONCLUSIONS

The radiomics features of hematomal and perihematomal edema area have additional value in prognostic prediction; moreover, addition of radiomic features significantly improves model accuracy.

Reduction of Midline Shift and Short-Term Mortality Following Minimal Invasive Surgery for Spontaneous Supratentorial Intracerebral Hemorrhage: A Retrospective and Case-Control Series

OBJECTIVE

Currently, the treatment of spontaneous intracerebral hemorrhage (sICH) is limiting, especially in patients with midline shift and supratentorial hemorrhage. Here, we investigated the clinical value of minimally invasive surgery (MIS) in patients with midline shift and supratentorial sICH by observing the consciousness state, midline shift, and short-term mortality.

METHODS

A total of 124 supratentorial sICH patients with midline shift, hematoma volume >30 mL and <150 mL were included in this study. Based on treatment methods, the enrolled patients were divided into minimally invasive surgical (MIS) (group 1, n = 61) and conservative (group 2, n = 63) treatment groups. Measurements of midline shift and state of consciousness using the Glasgow Coma Scale (GCS) score were performed on day 2 following treatment. Additionally, mortality, adverse events, and neurologic recovery (modified Rankin Scale score) in each group were observed after 1 month.

RESULTS

On postoperative day 2, the recovery rates of midline shift and consciousness state in group 1 patients were 59.02% and 50.82%, respectively, significantly higher than group 2, 26.98% and 25.40% (P < 0.01). By comparing death, adverse events, and neurologic function recovery of the 2 groups within 1 month postoperative, we observed a significantly lower fatality rate in group 1 (16.39%; 10 cases) than group 2 (33.33%; 21 cases) (P < 0.05). No significant difference of the adverse event rates was observed between groups 1 and 2 (19.67% [12 cases] vs. 19.05% [12 cases]). In addition, neurologic function recovery also had no significant difference between the 2 groups (P > 0.05).

CONCLUSIONS

MIS could reduce early-stage midline shift, improve consciousness state and reduce short-term mortality in patients with supratentorial sICH.

Development and Validation of a Clinical-Based Signature to Predict the 90-Day Functional Outcome for Spontaneous Intracerebral Hemorrhage

We aimed to develop and validate an objective and easy-to-use model for identifying patients with spontaneous intracerebral hemorrhage (ICH) who have a poor 90-day prognosis. This three-center retrospective study included a large cohort of 1,122 patients with ICH who presented within 6 h of symptom onset [training cohort, n = 835; internal validation cohort, n = 201; external validation cohort (center 2 and 3), n = 86]. We collected the patients’ baseline clinical, radiological, and laboratory data as well as the 90-day functional outcomes. Independent risk factors for prognosis were identified through univariate analysis and multivariate logistic regression analysis. A nomogram was developed to visualize the model results while a calibration curve was used to verify whether the predictive performance was satisfactorily consistent with the ideal curve. Finally, we used decision curves to assess the clinical utility of the model. At 90 days, 714 (63.6%) patients had a poor prognosis. Factors associated with prognosis included age, midline shift, intraventricular hemorrhage (IVH), subarachnoid hemorrhage (SAH), hypodensities, ICH volume, perihematomal edema (PHE) volume, temperature, systolic blood pressure, Glasgow Coma Scale (GCS) score, white blood cell (WBC), neutrophil, and neutrophil-lymphocyte ratio (NLR) (p < 0.05). Moreover, age, ICH volume, and GCS were identified as independent risk factors for prognosis. For identifying patients with poor prognosis, the model showed an area under the receiver operating characteristic curve of 0.874, 0.822, and 0.868 in the training cohort, internal validation, and external validation cohorts, respectively. The calibration curve revealed that the nomogram showed satisfactory calibration in the training and validation cohorts. Decision curve analysis showed the clinical utility of the nomogram. Taken together, the nomogram developed in this study could facilitate the individualized outcome prediction in patients with ICH.

Risk factor guided early discharge and potential resource allocation benefits in patients with traumatic subarachnoid hemorrhage

OBJECTIVES

We sought to develop screening criteria predicting the lack of poor neurological outcomes in patients presenting with traumatic subarachnoid hemorrhage (tSAH), while evaluating their potential to improve resource-allocation in these cases.

METHODS

We retrospectively reviewed patients presenting with tSAH to the emergency department (ED) of a tertiary care institution from 2016-2018. We defined good neurological outcomes as patients with stable/improving neurological status, did not require neurosurgical intervention, no expanding bleed, and no hospital readmission. Univariate and multivariate models were generated to predict risk factors inversely associated with good neurological outcome.

RESULTS

167 patients presented with tSAH from 2016-2018. The presence of depressed skull fracture, concomitant spinal fracture, low GCS, cranial nerve palsies, disorientation, concomitant hemorrhages, midline shift (MLS), elevated INR, and emergent medical intervention were inversely correlated with likelihood of good neurological outcome upon univariate analysis. Multivariate regression demonstrated that midline shift [OR=0.22 (0.05-0.89), p=0.04], GCS <13 [OR=0.22 (0.05-0.99), p=0.05], elevated INR [OR=0.18 (0.03-0.85), p=0.04], and emergent medical intervention [OR=0.18 (0.04-0.63), p=0.01] were independently associated with lower likelihood of good neurological outcome. 46 patients without any factors had good outcomes but were held in the ED or admitted to the hospital. These patients - if instead discharged directly - translated to a potential cost savings of $179,172.

CONCLUSIONS

In our study we found multiple risk factors inversely associated with good neurological outcome, namely low GCS, midline shift, emergent medical intervention, and INR ≥ 1.4. Our findings may aid clinicians in determining which tSAH patients are candidates for safe early discharge.

A Robust, Fully Automatic Detection Method and Calculation Technique of Midline Shift in Intracranial Hemorrhage and Its Clinical Application

A midline shift (MLS) is an important clinical indicator for intracranial hemorrhage. In this study, we proposed a robust, fully automatic neural network-based model for the detection of MLS and compared it with MLSs drawn by clinicians; we also evaluated the clinical applications of the fully automatic model. We recruited 300 consecutive non-contrast CT scans consisting of 7269 slices in this study. Six different types of hemorrhage were included. The automatic detection of MLS was based on modified Keypoint R-CNN with keypoint detection followed by training on the ResNet-FPN-50 backbone. The results were further compared with manually drawn outcomes and manually defined keypoint calculations. Clinical parameters, including Glasgow coma scale (GCS), Glasgow outcome scale (GOS), and 30-day mortality, were also analyzed. The mean absolute error for the automatic detection of an MLS was 0.936 mm compared with the ground truth. The interclass correlation was 0.9899 between the automatic method and MLS drawn by different clinicians. There was high sensitivity and specificity in the detection of MLS at 2 mm (91.7%, 80%) and 5 mm (87.5%, 96.7%) and MLSs greater than 10 mm (85.7%, 97.7%). MLS showed a significant association with initial poor GCS and GCS on day 7 and was inversely correlated with poor 30-day GOS (p < 0.001). In conclusion, automatic detection and calculation of MLS can provide an accurate, robust method for MLS measurement that is clinically comparable to the manually drawn method.

Bedside detection of intracranial midline shift using portable magnetic resonance imaging

Neuroimaging is crucial for assessing mass effect in brain-injured patients. Transport to an imaging suite, however, is challenging for critically ill patients. We evaluated the use of a low magnetic field, portable MRI (pMRI) for assessing midline shift (MLS). In this observational study, 0.064 T pMRI exams were performed on stroke patients admitted to the neuroscience intensive care unit at Yale New Haven Hospital. Dichotomous (present or absent) and continuous MLS measurements were obtained on pMRI exams and locally available and accessible standard-of-care imaging exams (CT or MRI). We evaluated the agreement between pMRI and standard-of-care measurements. Additionally, we assessed the relationship between pMRI-based MLS and functional outcome (modified Rankin Scale). A total of 102 patients were included in the final study (48 ischemic stroke; 54 intracranial hemorrhage). There was significant concordance between pMRI and standard-of-care measurements (dichotomous, κ = 0.87; continuous, ICC = 0.94). Low-field pMRI identified MLS with a sensitivity of 0.93 and specificity of 0.96. Moreover, pMRI MLS assessments predicted poor clinical outcome at discharge (dichotomous: adjusted OR 7.98, 95% CI 2.07–40.04, p = 0.005; continuous: adjusted OR 1.59, 95% CI 1.11–2.49, p = 0.021). Low-field pMRI may serve as a valuable bedside tool for detecting mass effect.

Exploring the Relationship Between Objective Pupillometry Metrics and Midline Shift

ABSTRACT

BACKGROUND: Pupillary examinations provide early subtle signs of worsening intracranial pathology. Objective pupillomtery assessment, although not yet the standard of care, is considered best practice. However, inconsistent findings from objective pupillometry studies have caused a lack of consensus among clinicians; as such, no clinical guidelines are available to guide clinical use of objective pupillometer devices. To add to the body of evidence, the purpose of this project was to explore the relationship between objective pupillometry metrics and midline shift (MLS). METHODS: A retrospective chart review of pupillometer data was conducted. Midline shift was correlated with objective pupillometry metrics including Neurological Pupil Index (NPi), pupil size, and anisocoria. Midline shift was measured for the patient's initial neuroimaging and with any defined neurological change. Spearman ρ was used for statistical analysis of correlations between pupillometer metrics and MLS measured at both the septum pellucidum and pineal gland. RESULTS: A total of 41 patients were included in the analysis; most were White (58.5%) and male (58.5%), with a mean (SD) age of 58.49 (16.92) years. Spearman ρ revealed statistically significant positive correlations between right pupil NPi and anisocoria with MLS, and significant negative correlations between left pupil NPi and pupil size with MLS. CONCLUSIONS: Results from this project are consistent with previous studies. Objective pupillometry continues to be a valuable component of a comprehensive neurological examination, because it has the ability to discern early and subtle changes in a patient's neurological status, leading to lifesaving interventions.

Risk factors for poor outcomes of spontaneous supratentorial cerebral hemorrhage after surgery

OBJECTIVE

This study aimed to explore the factors affecting the outcomes of spontaneous supratentorial cerebral hemorrhage 90 days after surgery.

METHODS

A total of 256 patients with spontaneous supratentorial intracerebral hemorrhage underwent craniotomy evacuation of hematoma. The control group included 120 patients who received conservative treatment. The patients were divided into two subgroups based on a bifurcation of the modified Rankin Scale (mRS) 90 days after clinical therapeutics: good outcome (mRS score 0-3) and poor outcome (mRS score 4-6). The differences in clinical and imaging data between the two subgroups were analyzed. Based on difference analysis results, a binary logistic regression model was constructed to analyze the influencing factors related to poor outcomes.

RESULTS

The difference analysis results in the surgery group showed statistically significant differences in age, sex, Glasgow Coma Score (GCS) on admission, coronary atherosclerosis, smoking, stroke history, blood glucose, D-dimer, hematoma size, deep cerebral hemorrhage, midline shift, hematoma burst into the ventricle, vortex sign, island sign, and black hole sign. Binary logistic regression analysis showed that deep cerebral hemorrhage, midline shift, and age > 58 years independently correlated with the poor outcomes of patients after surgery. The binary logistic regression results of the control group showed that age > 58 years and GCS ≤ 8 independently correlated with the poor outcomes of patients.

CONCLUSIONS

Deep cerebral hemorrhage, midline shift, and age > 58 years significantly increased the risk of adverse prognosis in patients after surgery. The findings might help select the clinical treatment plan and evaluate the postoperative prognosis of patients.

A Novel CT-based Radiomics-Clinical Nomogram for the Prediction of Short-Term Prognosis in Deep Intracerebral Hemorrhage

OBJECTIVE

To develop and validate a radiomics-clinical nomogram for the prediction of short-term prognosis in patients with deep intracerebral hemorrhage (DICH) on admission.

METHODS

A total of 326 patients with DICH (development cohort = 187; testing cohort = 81; validation cohort = 58) were retrospectively included. Radiomics features were extracted from computed tomography (CT) images and optimal features were selected using least absolute shrinkage and selection operator regression. A radiomics score (R-score) was developed using the optimal features. Univariate and multivariate analyses were used to determine independent risk factors for poor outcomes at 30 days. A radiomics-clinical (R-C) nomogram was developed and validated in the three cohorts. Receiver operating characteristic curve (ROC), calibration curve and decision curve analyses were conducted to evaluate the performances of the R-C nomogram.

RESULTS

Only 4 of 396 radiomics features were selected to develop R-scores. Age, onset-to-CT time, Glasgow Coma Scale score, midline shift, and R-score were detected as independent predictors of poor prognosis of DICH. The R-C nomogram was developed by the independent predictors and showed acceptable discrimination with areas under ROCs of 0.80, 0.79, and 0.70 in the development, testing and validation cohorts, respectively. The R-C nomogram showed good agreement between the predicted probability and the actual probability (all P > 0.05) and clinical applicability in each cohort.

CONCLUSIONS

The R-C nomogram is a stable and effective tool for predicting the short-term prognosis of DICH, which may help clinicians perform individual risk assessments and make decisions for patients with DICH.

Dilated Optic Nerve Sheath Diameter Predicts Poor Outcome in Acute Spontaneous Intracerebral Hemorrhage

BACKGROUND AND PURPOSE

Optic nerve sheath diameter (ONSD) enlargement occurs in patients with intracerebral hemorrhage (ICH). However, the relationship between ONSD and prognosis of ICH is uncertain. This study aimed to investigate the predictive value of ONSD on poor outcome of patients with acute spontaneous ICH.

METHODS

We studied 529 consecutive patients with acute spontaneous ICH who underwent initial CT within 6 h of symptom onset between October 2016 and February 2019. The ONSDs were measured 3 mm behind the eyeball on initial CT images. Poor outcome was defined as having a Glasgow Outcome Scale (GOS) score of 1-3, and favorable outcome was defined as having a GOS score of 4-5 at discharge.

RESULTS

The ONSD of the poor outcome group was significantly greater than that of the favorable outcome group (5.87 ± 0.86 vs. 5.21 ± 0.69 mm, p < 0.001). ONSD was related to hematoma volume (r = 0.475, p < 0.001). Adjusting other meaningful predictors, ONSD (OR: 2.83; 95% CI: 1.94-4.15) was associated with poor functional outcome by multivariable logistic regression analysis. Receiver operating characteristic curve showed that the ONSD improved the accuracy of ultraearly hematoma growth in the prediction of poor outcome (AUC: 0.790 vs. 0.755, p = 0.016). The multivariable logistic regression model with all the meaningful predictors showed a better predictive performance than the model without ONSD (AUC: 0.862 vs. 0.831, p = 0.001).

CONCLUSIONS

The dilated ONSD measured on initial CT indicated elevated intracranial pressure and poor outcome, so appropriate intervention should be taken in time.

Lateral Brain Displacement and Cerebral Autoregulation in Acutely Comatose Patients

OBJECTIVES

Lateral displacement and impaired cerebral autoregulation are associated with worse outcomes following acute brain injury, but their effect on long-term clinical outcomes remains unclear. We assessed the relationship between lateral displacement, disturbances to cerebral autoregulation, and clinical outcomes in acutely comatose patients.

DESIGN

Retrospective analysis of prospectively collected data.

SETTING

Neurocritical care unit of the Johns Hopkins Hospital.

PATIENTS

Acutely comatose patients (Glasgow Coma Score ≤ 8).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Cerebral oximetry index, derived from near-infrared spectroscopy multimodal monitoring, was used to evaluate cerebral autoregulation. Associations between lateral brain displacement, global cerebral autoregulation, and interhemispheric cerebral autoregulation asymmetry were assessed using mixed random effects models with random intercept. Patients were grouped by functional outcome, determined by the modified Rankin Scale. Associations between outcome group, lateral displacement, and cerebral oximetry index were assessed using multivariate linear regression. Increasing lateral brain displacement was associated with worsening global cerebral autoregulation (p = 0.01 septum; p = 0.05 pineal) and cerebral autoregulation asymmetry (both p < 0.001). Maximum lateral displacement during the first 3 days of coma was significantly different between functional outcome groups at hospital discharge (p = 0.019 pineal; p = 0.008 septum), 3 months (p = 0.026; p = 0.007), 6 months (p = 0.018; p = 0.010), and 12 months (p = 0.022; p = 0.012). Global cerebral oximetry index was associated with functional outcomes at 3 months (p = 0.019) and 6 months (p = 0.013).

CONCLUSIONS

During the first 3 days of acute coma, increasing lateral brain displacement is associated with worsening global cerebral autoregulation and cerebral autoregulation asymmetry, and poor long-term clinical outcomes in acutely comatose patients. The impact of acute interventions on outcome needs to be explored.

A clinical-radiomics nomogram may provide a personalized 90-day functional outcome assessment for spontaneous intracerebral hemorrhage

OBJECTIVES

To develop and validate a noncontrast computed tomography (NCCT)-based clinical-radiomics nomogram to identify spontaneous intracerebral hemorrhage (sICH) patients with a poor 90-day prognosis on admission.

METHODS

In this double-center retrospective study, data from 435 patients with sICH (training cohort: n = 244; internal validation cohort: n = 104; external validation cohort: n = 87) were reviewed. The radiomics score (Rad-score) was calculated based on the coefficients of the selected radiomics features. A clinical-radiomics nomogram was developed by using independent predictors of poor outcome at 90 days through multivariate logistic regression analysis in the training cohort and was validated in the internal and external cohorts.

RESULTS

At 90 days, 200 of 435 (46.0%) patients had a poor prognosis. The clinical-radiomics nomogram was developed by six independent predictors namely midline shift, NCCT time from sICH onset, Glasgow Coma Scale score, serum glucose, uric acid, and Rad-score. In identifying patients with poor prognosis, the clinical-radiomics nomogram showed an area under the receiver operating characteristic curve (AUC) of 0.81 in the training cohort, an AUC of 0.78 in the internal validation cohort, and an AUC of 0.73 in the external validation cohort. The calibration curve revealed that the clinical-radiomics nomogram showed satisfactory calibration in the training and internal validation cohorts (both p > 0.05), but slightly poor agreement in the external validation cohort (p < 0.05).

CONCLUSIONS

The clinical-radiomics nomogram is a valid computer-aided tool that may provide personalized risk assessment of 90-day functional outcome for sICH patients.

KEY POINTS

• The proposed Rad-score was significantly associated with 90-day poor functional outcome in patients with sICH. • The clinical-radiomics nomogram showed satisfactory calibration and the most net benefit for discriminating 90-day poor outcome. • The clinical-radiomics nomogram may provide personalized risk assessment of 90-day functional outcome for sICH patients.

Exploration of Multiparameter Hematoma 3D Image Analysis for Predicting Outcome After Intracerebral Hemorrhage

BACKGROUND

Rapid diagnosis and proper management of intracerebral hemorrhage (ICH) play a crucial role in the outcome. Prediction of the outcome with a high degree of accuracy based on admission data including imaging information can potentially influence clinical decision-making practice.

METHODS

We conducted a retrospective multicenter study of consecutive ICH patients admitted between 2012-2017. Medical history, admission data, and initial head computed tomography (CT) scan were collected. CT scans were semiautomatically segmented for hematoma volume, hematoma density histograms, and sphericity index (SI). Discharge unfavorable outcomes were defined as death or severe disability (modified Rankin Scores 4-6). We compared (1) hematoma volume alone; (2) multiparameter imaging data including hematoma volume, location, density heterogeneity, SI, and midline shift; and (3) multiparameter imaging data with clinical information available on admission for ICH outcome prediction. Multivariate analysis and predictive modeling were used to determine the significance of hematoma characteristics on the outcome.

RESULTS

We included 430 subjects in this analysis. Models using automated hematoma segmentation showed incremental predictive accuracies for in-hospital mortality using hematoma volume only: area under the curve (AUC): 0.85 [0.76-0.93], multiparameter imaging data (hematoma volume, location, CT density, SI, and midline shift): AUC: 0.91 [0.86-0.97], and multiparameter imaging data plus clinical information on admission (Glasgow Coma Scale (GCS) score and age): AUC: 0.94 [0.89-0.99]. Similarly, severe disability predictive accuracy varied from AUC: 0.84 [0.76-0.93] for volume-only model to AUC: 0.88 [0.80-0.95] for imaging data models and AUC: 0.92 [0.86-0.98] for imaging plus clinical predictors.

CONCLUSIONS

Multiparameter models combining imaging and admission clinical data show high accuracy for predicting discharge unfavorable outcome after ICH.

Prognostic factors for adult patients with hemorrhagic moyamoya disease in the acute stage

OBJECTIVES

Hemorrhagic moyamoya disease (MMD) is one common subtype in adult patients. However, the study about outcome of hemorrhagic MMD patients in the acute stage is still lacking. This study is aimed to explore the short-term prognostic factors for adult patients with hemorrhagic MMD in the acute stage.

PATIENTS AND METHODS

Adult hemorrhagic MMD patients in the acute stage awere retrospectively analyzed. Both clinical and imaging data were collected. Unfavorable functional outcome at discharge was considered when modified Rankin Scale score ≥3. Multivariate logistic regression was used to investigate the prognostic factors in patients with hemorrhagic MMD in the acute stage.

RESULTS

A total of 107 patients were included in this study. Among these patients, 17 died and 59 had unfavorable functional outcome at 9.6 ± 7.8 days. In multivariate logistic regression, admission blood glucose (odds ratio (OR) = 1.457, 95% confidence interval (CI) 1.156-1.836, P = 0.001), midline shift >5 mm (OR = 24.268, 95%CI 4.324-136.191, P < 0.001), and subarachnoid hemorrhage (OR = 13.067, 95%CI 2.020-84.512, P = 0.007) were independently associated with death at discharge. Moreover, admission Glasgow Coma Scale (GCS) score (OR = 0.420, 95%CI 0.296-0.598, P < 0.001), midline shift >5 mm (OR = 6.685, 95%CI 1.226-36.455, P = 0.028), and intraparenchymal hemorrhage (OR = 4.790, 95%CI 1.184-19.381, P = 0.028) were independently associated with unfavorable functional outcome at discharge.

CONCLUSION

This study shows that admission blood glucose, midline shift >5 mm, and subarachnoid hemorrhage are independent predictors of short-term mortality in hemorrhagic MMD in the acute stage. In addition, admission GCS score, midline shift >5 mm, and intraparenchymal hemorrhage are independent predictors of short-term unfavorable functional outcome in hemorrhagic MMD in the acute stage.

Deep structural brain lesions associated with consciousness impairment early after hemorrhagic stroke

The purpose of this study was to determine the significance of deep structural lesions for impairment of consciousness following hemorrhagic stroke and recovery at ICU discharge. Our study focused on deep lesions that previously were implicated in studies of disorders of consciousness. We analyzed MRI measures obtained within the first week of the bleed and command following throughout the ICU stay. A machine learning approach was applied to identify MRI findings that best predicted the level consciousness. From 158 intracerebral hemorrhage patients that underwent MRI, one third was unconscious at the time of MRI and half of these patients recovered consciousness by ICU discharge. Deep structural lesions predicted both, impairment and recovery of consciousness, together with established measures of mass effect. Lesions in the midbrain peduncle and pontine tegmentum alongside the caudate nucleus were implicated as critical structures. Unconscious patients predicted to recover consciousness by ICU discharge had better long-term functional outcomes than those predicted to remain unconscious.