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

Predefined and data driven CT densitometric features predict critical illness and hospital length of stay in COVID-19 patients

The aim of this study was to compare whole lung CT density histograms to predict critical illness outcome and hospital length of stay in a cohort of 80 COVID-19 patients. CT chest images on segmented lungs were retrospectively analyzed. Functional Principal Component Analysis (FPCA) was used to find the main modes of variations on CT density histograms. CT density features, the CT severity score, the COVID-GRAM score and the patient clinical data were assessed for predicting the patient outcome using logistic regression models and survival analysis. ROC analysis predictors of critically ill status: 87.5th percentile CT density (Q875)—AUC 0.88 95% CI (0.79 0.94), F1-CT—AUC 0.87 (0.77 0.93) Standard Deviation (SD-CT)—AUC 0.86 (0.73, 0.93). Multivariate models combining CT-density predictors and Neutrophil–Lymphocyte Ratio showed the highest accuracy. SD-CT, Q875 and F1 score were significant predictors of hospital length of stay (LOS) while controlling for hospital death using competing risks models. Moreover, two multivariate Fine-Gray regression models combining the clinical variables: age, NLR, Contrast CT factor with either Q875 or F1 CT-density predictors revealed significant effects for the prediction of LOS incidence in presence of a competing risk (death) and acceptable predictive performances (Bootstrapped C-index 0.74 [0.70 0.78]).

The Patterns of Morphological Change During Intracerebral Hemorrhage Expansion: A Multicenter Retrospective Cohort Study

Objectives: Hemorrhage expansion (HE) is a common and serious condition in patients with intracerebral hemorrhage (ICH). In contrast to the volume changes, little is known about the morphological changes that occur during HE. We developed a novel method to explore the patterns of morphological change and investigate the clinical significance of this change in ICH patients. Methods: The morphological changes in the hematomas of ICH patients with available paired non-contrast CT data were described in quantitative terms, including the diameters of each hematoma in three dimensions, the longitudinal axis type, the surface regularity (SR) index, the length and direction changes of the diameters, and the distance and direction of movement of the center of the hematoma. The patterns were explored by descriptive analysis and difference analysis in subgroups. We also established a prognostic nomogram model for poor outcomes in ICH patients using both morphological changes and clinical parameters. Results: A total of 1,094 eligible patients from four medical centers met the inclusion criteria. In 266 (24.3%) cases, the hematomas enlarged; the median absolute increase in volume was 14.0 [interquartile range (IQR), 17.9] mL. The initial hematomas tended to have a more irregular shape, reflected by a larger surface regularity index, than the developed hematomas. In subtentorial and deep supratentorial hematomas, the center moved in the direction of gravity. The distance of center movement and the length changes of the diameters were small, with median values of less than 4 mm. The most common longitudinal axis type was anterior-posterior (64.7%), and the axis type did not change between initial and repeat imaging in most patients (95.2%). A prognostic nomogram model including lateral expansion, a parameter of morphological change, showed good performance in predicting poor clinical outcomes in ICH patients. Conclusions: The present study provides a morphological perspective on HE using a novel automatic approach. We identified certain patterns of morphological change in HE, and we believe that some morphological change parameters could help physicians predict the prognosis of ICH patients.

Glycemic Gap Predicts in-Hospital Mortality in Diabetic Patients with Intracerebral Hemorrhage

BACKGROUND AND PURPOSE

The relationship between admission hyperglycemia and intracerebral hemorrhage (ICH) outcome remains controversial. Glycemic gap (GG) is a superior indicator of glucose homeostatic response to physical stress compared to admission glucose levels. We aimed to evaluate the association between GG and in-hospital mortality in ICH.

METHODS

We retrospectively identified consecutive patients hospitalized for spontaneous ICH at the 2 healthcare systems in the Twin Cities area, MN, between January 2008 and December 2017. Patients without glycosylated hemoglobin (HbA1c) test or those admitted beyond 24 hours post-ICH were excluded. Demographics, medical history, admission tests, and computed tomography data were recorded. GG was computed using admission glucose level minus HbA1c-derived average glucose. The association between GG and time to in-hospital mortality was evaluated by Cox regression analysis. Receiver operating characteristic (ROC) analysis with the DeLong test was used to evaluate the ability of GG to predict in-hospital death.

RESULTS

Among 345 included subjects, 63 (25.7%) died during the hospital stay. Compared with survivors, non-survivors presented with a lower Glasgow coma scale score, larger hematoma volume, and higher white blood cells count, glucose, and GG levels at admission (p<0.001). GG remained an independent predictor of in-hospital mortality after adjusting for known ICH outcome predictors and potential confounders [adjusted hazard ratio: 1.09, 95% confidence interval (CI): 1.02-1.18, p = 0.018]. GG showed a good discriminative power (area under the ROC curve: 0.75, 95% CI: 0.68-0.82) in predicting in-hospital death and performed better than admission glucose levels in diabetic patients (p = 0.030 for DeLong test).

CONCLUSIONS

Admission GG is associated with the risk of in-hospital mortality and can potentially represent a useful prognostic biomarker for ICH patients with diabetes.

Revised intracerebral hemorrhage expansion definitions: Relationship with care limitations

BACKGROUND

Hematoma expansion is an important therapeutic target in intracerebral hemorrhage. Recently proposed hematoma expansion definitions have not been validated, and no previous definition has accounted for withdrawal of care.

AIMS

To externally validate revised definitions of hematoma expansion that incorporate intraventricular hemorrhage, and to test their validity in the context of withdrawal of care.

METHODS

We analyzed data from the Antihypertensive Treatment of Acute Cerebral Hemorrhage II trial, comparing revised definitions of hematoma expansion incorporating intraventricular hemorrhage expansion to the conventional definition of "≥6 mL or ≥33%." Primary outcome was modified Rankin Scale of 4-6 at 90 days. We calculated the incidence, sensitivity, specificity, positive and negative predictive values, and c-statistic for all definitions of hematoma expansion. Definitions were compared using nonparametric methods. Secondary analyses were performed after removing patients with withdrawal of care.

RESULTS

Primary analysis included 948 patients. Using the conventional definition, the sensitivity was 37.1% and specificity was 83.2% for the primary outcome. Sensitivity improved with all three revised definitions (53.3%, 48.7%, and 45.3%, respectively), with minimal change to specificity (78.4%, 80.5%, and 81.0%, respectively). The greatest improvement was seen with the definition "≥6 mL or ≥33% or any intraventricular hemorrhage," with increased c-statistic from 60.2% to 65.9% (p < 0.001). Secondary analysis excluded 46 participants who experienced withdrawal of care. The revised definitions similarly outperformed the conventional definition in this population, with the greatest improvement in c-statistic using "≥6 mL or ≥33% or any intraventricular hemorrhage" (58.1% vs. 64.1%, p < 0.001).

CONCLUSIONS

Revised hematoma expansion definitions incorporating intraventricular hemorrhage expansion outperformed conventional definitions for predicting poor outcome, even after accounting for care limitations.

Assessing invasiveness of subsolid lung adenocarcinomas with combined attenuation and geometric feature models

The aim of this study was to develop and test multiclass predictive models for assessing the invasiveness of individual lung adenocarcinomas presenting as subsolid nodules on computed tomography (CT). 227 lung adenocarcinomas were included: 31 atypical adenomatous hyperplasia and adenocarcinomas in situ (class H1), 64 minimally invasive adenocarcinomas (class H2) and 132 invasive adenocarcinomas (class H3). Nodules were segmented, and geometric and CT attenuation features including functional principal component analysis features (FPC1 and FPC2) were extracted. After a feature selection step, two predictive models were built with ordinal regression: Model 1 based on volume (log) (logarithm of the nodule volume) and FPC1, and Model 2 based on volume (log) and Q.875 (CT attenuation value at the 87.5% percentile). Using the 200-repeats Monte-Carlo cross-validation method, these models provided a multiclass classification of invasiveness with discriminative power AUCs of 0.83 to 0.87 and predicted the class probabilities with less than a 10% average error. The predictive modelling approach adopted in this paper provides a detailed insight on how the value of the main predictors contribute to the probability of nodule invasiveness and underlines the role of nodule CT attenuation features in the nodule invasiveness classification.

Anticoagulation use and Hemorrhagic Stroke in SARS-CoV-2 Patients Treated at a New York Healthcare System

BACKGROUND AND PURPOSE

While the thrombotic complications of COVID-19 have been well described, there are limited data on clinically significant bleeding complications including hemorrhagic stroke. The clinical characteristics, underlying stroke mechanism, and outcomes in this particular subset of patients are especially salient as therapeutic anticoagulation becomes increasingly common in the treatment and prevention of thrombotic complications of COVID-19.

METHODS

We conducted a retrospective cohort study of patients with hemorrhagic stroke (both non-traumatic intracerebral hemorrhage and spontaneous non-aneurysmal subarachnoid hemorrhage) who were hospitalized between March 1, 2020, and May 15, 2020, within a major healthcare system in New York, during the coronavirus pandemic. Patients with hemorrhagic stroke on admission and who developed hemorrhage during hospitalization were both included. We compared the clinical characteristics of patients with hemorrhagic stroke and COVID-19 to those without COVID-19 admitted to our hospital system between March 1, 2020, and May 15, 2020 (contemporary controls), and March 1, 2019, and May 15, 2019 (historical controls). Demographic variables and clinical characteristics between the individual groups were compared using Fischer's exact test for categorical variables and nonparametric test for continuous variables. We adjusted for multiple comparisons using the Bonferroni method.

RESULTS

During the study period in 2020, out of 4071 patients who were hospitalized with COVID-19, we identified 19 (0.5%) with hemorrhagic stroke. Of all COVID-19 with hemorrhagic stroke, only three had isolated non-aneurysmal SAH with no associated intraparenchymal hemorrhage. Among hemorrhagic stroke in patients with COVID-19, coagulopathy was the most common etiology (73.7%); empiric anticoagulation was started in 89.5% of these patients versus 4.2% in contemporary controls (p ≤ .001) and 10.0% in historical controls (p ≤ .001). Compared to contemporary and historical controls, patients with COVID-19 had higher initial NIHSS scores, INR, PTT, and fibrinogen levels. Patients with COVID-19 also had higher rates of in-hospital mortality (84.6% vs. 4.6%, p ≤ 0.001). Sensitivity analyses excluding patients with strictly subarachnoid hemorrhage yielded similar results.

CONCLUSION

We observed an overall low rate of imaging-confirmed hemorrhagic stroke among patients hospitalized with COVID-19. Most hemorrhages in patients with COVID-19 infection occurred in the setting of therapeutic anticoagulation and were associated with increased mortality. Further studies are needed to evaluate the safety and efficacy of therapeutic anticoagulation in patients with COVID-19.

Matrix Metalloproteinases in Acute Intracerebral Hemorrhage

Spontaneous intracerebral hemorrhage (ICH) accounts for 10-30% of all strokes and affects more than one million people every year worldwide, and it is the stroke subtype associated with the highest rates of mortality and residual disability. So far, clinical trials have mainly targeted primary cerebral injury and have substantially failed to improve clinical outcomes. The understanding of the pathophysiology of early and delayed injury after ICH is, hence, of paramount importance to identify potential targets of intervention and develop effective therapeutic strategies. Matrix metalloproteinases (MMPs) represent a ubiquitous superfamily of structurally related zinc-dependent endopeptidases able to degrade any component of the extracellular matrix. They are upregulated after ICH, in which different cell types, including leukocytes, activated microglia, neurons, and endothelial cells, are involved in their synthesis and secretion. The aim of this review is to summarize the available experimental and clinical evidence about the role of MMPs in brain injury following spontaneous ICH and provide critical insights into the underlying mechanisms.