AUTHOR=Zhao Mingpei , Huang Wei , Huang Shuna , Lin Fuxin , He Qiu , Zheng Yan , Gao Zhuyu , Cai Lveming , Ye Gengzhao , Chen Renlong , Wu Siying , Fang Wenhua , Wang Dengliang , Lin Yuanxiang , Kang Dezhi , Yu Lianghong 

TITLE=Quantitative hematoma heterogeneity associated with hematoma growth in patients with early intracerebral hemorrhage

JOURNAL=Frontiers in Neurology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2022.999223

DOI=10.3389/fneur.2022.999223

ISSN=1664-2295

ABSTRACT=Background: Early hematoma growth is associated with poor functional outcomes in patients with intracerebral hemorrhage (ICH). We aim to see if quantitative hematoma heterogeneity in NCCT can predict early hematoma growth.
Methods: We used data contained in the risk stratification and minimally invasive surgery in acute intracerebral hemorrhage (Risa-MIS-ICH) patients. Our study included patients with ICH who had an onset to NCCT time of fewer than 12 hours and a follow-up CT duration of fewer than 72 hours. To get a Hounsfield unit histogram and the coefficient of variation (CV) of Hounsfield units (HU), the hematoma was segmented using software with an auto segmentation function. Quantitative hematoma heterogeneity is represented by the CV of hematoma HU. Multivariate logistic regression was utilized to determine hematoma growth parameters. The discriminant score's predictive value was assessed using the area under the ROC curve (AUC). The best cut-off was determined using ROC curves. Hematoma growth was defined as a follow-up CT hematoma volume increase of >6 mL or a hematoma volume increase of >1/3 as compared to the baseline NCCT.
Result: A total of 158 patients were enrolled in the study, with 31 of them (19.6%) suffering hematoma growth. The multivariate logistic regression analysis revealed that "heterogeneous" in density category [P=0.017, odds ratio (OR) 6.000, 95 % confidence interval (CI) 1.372-26.239] and CV of hematoma HU [P=0.018, odds ratio (OR) 1.128, 95 % confidence interval (CI) 1.043-1.576] were both independent predictors of hematoma growth. By evaluating the receiver operating characteristic curve, the CV of hematoma HU (AUC=0.750) has a superior predictive value for hematoma growth than heterogeneous (ACU=0.638). The CV of hematoma HU had an 18 percent cutoff, with an 81.9 % specificity and a 58.1 % sensitivity.
Conclusions:  The CV of hematoma HU is a quantitative hematoma heterogeneity index that predicts hematoma growth in early ICH patients independently.