The Attenuation Value Within the Non-hypodense Region on Non-contrast Computed Tomography of Spontaneous Cerebral Hemorrhage: A Long-Neglected Predictor of Hematoma Expansion

Abstract

Background and PurposeThe ability of attenuation value of the non-hypodense region of hematoma in non-contrast computed tomography (NCCT) for predicting hematoma expansion (HE) remains unclear. Our purpose is to explore this relationship.MethodsTwo cohorts of patients were collected for analysis. The region where we measured hematoma attenuation values was limited to the non-hypodense region that was not adjacent to the normal brain tissue on NCCT. The critical attenuation value was derived via receiver operating characteristic (ROC) curve analysis in the derivation cohort and its predictive ability was validated in the validation cohort. Independent relationships between predictors, such as critical attenuation value of the non-hypodense region and HE were analyzed using the least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic analysis.ResultsThe results showed that the attenuation value <64 Hounsfield units (HU) was independently associated with HE [odds ratio (OR), 4.118; 95% confidential interval (CI), 1.897–9.129, p < 0.001] and the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the curve (AUC) for predicting HE were 36.11%, 81.71%, 1.97, 0.78, 44.8%, 75.7%, and 0.589, respectively.ConclusionsOur research explored and validated the relationship between the attenuation value of the non-hypodense region of hematoma and HE. The attenuation value < 64 HU was an appropriate indicator of early HE.

Prediction of Basal Ganglia Hematoma Expansion Based on Radiomics and Clinical Characteristics: A Novel Multivariate Predictive Nomogram

“…Concurrently, the follow-up NCCT within the initial 24 hours of admission was examined to delineate between HE and non-HE cases. Our findings confirmed that m-CTD is an independent risk factor for HE prediction (P < 0:001), corroborating previous studies [20,21]. When amalgamated with other factors, the predictive accuracy was enhanced, underscoring m-CTD's ability to independently anticipate HE occurrence and, when utilized as a contributing factor, augmenting the precision of the predictive model.…”