Hematoma heterogeneity prediction of intracranial hematoma enlargement and establishment of predictive scoring system / 中国脑血管病杂志

ABSTRACT

Objective To investigate the influence of hematoma heterogeneity for the enlargement of primary supratentorial intracerebral hemorrhage and established predictive scoring model of hematoma enlargement. Methods From June 2015 to December 2017, a total of 208 patients with primary cerebral hemorrhage treated first at the First Affiliated Hospital of Jishou University were analyzed retrospectively. 3D software was used to conduct hematoma imaging and calculate hematoma volume and surface area. The patients were divided into enlarged hematoma group (n =44) and non-enlarged hematoma group (n = 164) according to whether the hematomas were enlarged or not. The standard deviation of CT value (CTSD) of hematoma and irregular ratio (IR) of hematoma morphology were used to reflect the heterogeneity of hematoma. Univariate analysis and Multivariate Logistic regression analysis were used to analyze the Influencing factors of hematoma enlargement with SPSS 22. 0 software,and the predictive value of predictive scoring model to hematoma enlargement was evaluated with receiver operating characteristic (ROC) curve. Results The incidence of hematoma enlargement in primary cerebral hemorrhage was 21. 2% (44/208). Compared with the non-enlarged hematoma group,the increased volume of hematoma in the enlarged hematoma group increased significantly (15 ± 11 ml vs. 4 ± 6 ml ,t =45. 568,P 2. 0 and CTSD was 10. 85, the heterogeneity of hematomas increased. Multivariate analysis showed that CCS 10 score at admission (OR, 4. 141,95% CI 1. 526 - 11. 237,/'=0. 005) ,CTSDs5 10. 85 (OR, 3. 593,95% CI 1.354 - 9.540, P =0.010), and IR5s2.0 (OR, 93. 487,95%CI 27. 656 -316.012,P<0.01) were the independent risk factors for hematoma enlargement, and based on this,a predictive scoring model of CIG (CTSD,IR,and GCS) was established ROC curve analysis showed that the sensitivity and specificity of CIG score model predicting the hematoma enlargement were 86. 9% and 95. 1% , respectively when the predictive score was 9. 5 score. Conclusion The heterogeneity of hematoma was first quantified by the density heterogeneity and morphological irregularity of hematoma through individualized imaging processing, and a scoring model of hematoma enlargement was established based on this,which provided a new idea for clinical identification of hematoma enlargement.