Shulman Julie G, Jara Hernan, Qureshi Muhammad M, Lau Helena, Finn Brandon, Abbas Saleh, Cervantes-Arslanian Anna M, Mercado Melissa, Greer David, Chapman Margaret, Mian Asim Z, Takahashi Courtney E
Boston University School of Medicine.
Department of Neurology.
Medicine (Baltimore). 2020 Jul 10;99(28):e20951. doi: 10.1097/MD.0000000000020951.
Perihematomal edema (PHE) surrounding intracerebral hemorrhage (ICH) may contribute to disease-associated morbidity. Before quantifying PHE's effects on morbidity, a fast, accurate, and reproducible method for measuring PHE volume is needed. The aim of this study is to demonstrate the use of a semiautomated dual clustering segmentation algorithm to generate PHE volumetrics on noncontrast computed tomography (CT) of the head and compare this technique to physicians' manual calculations.This is a single-center, retrospective imaging study that included head CTs performed from January 2008 to December 2014 on 154 patients with ICH. Subjects ≥ 18 years old who were admitted to the hospital with spontaneous ICH were included. Included subjects had head CTs performed upon admission and within 6 to 24 hours. Two neurologists, 2 neuroradiologists, and a computer program all calculated hemorrhage and PHE volumes. Inter-rater correlation was evaluated using 2 statistical methods: intraclass correlations (ICCs) and limits of agreement (LOA). Additionally, correlation between volumes was separately evaluated using Pearson correlation coefficient.There was an excellent correlation between measurements performed by neurologists and neuroradiologists using ABC/2 for ICH (0.93) and PHE (0.78). There was a good correlation between measurements performed by neurologists using ABC/2 and the volume measurements generated by the algorithm for ICH (0.69) and PHE (0.70). There was a fair correlation between measurements performed by neuroradiologists using ABC/2 and volume measurements generated by the algorithm for ICH (0.47) and good correlation for PHE (0.73).Although the ABC/2 method for measuring PHE is quick and practical, algorithms that do not assume ellipsoidal shape may be more accurate.
脑出血（ICH）周围的血肿周围水肿（PHE）可能导致与疾病相关的发病率。在量化PHE对发病率的影响之前，需要一种快速、准确且可重复的测量PHE体积的方法。本研究的目的是演示使用半自动双聚类分割算法在头部非增强计算机断层扫描（CT）上生成PHE体积测量值，并将该技术与医生的手动计算结果进行比较。
这是一项单中心回顾性影像学研究，纳入了2008年1月至2014年12月期间对154例ICH患者进行的头部CT检查。纳入的受试者为≥18岁因自发性ICH入院的患者。纳入的受试者在入院时及6至24小时内进行了头部CT检查。两名神经科医生、两名神经放射科医生和一个计算机程序都计算了出血和PHE体积。使用两种统计方法评估评分者间的相关性：组内相关性（ICC）和一致性界限（LOA）。此外，使用Pearson相关系数分别评估体积之间的相关性。
神经科医生和神经放射科医生使用ABC/2法测量ICH（0.93）和PHE（0.78）的测量结果之间具有极好的相关性。神经科医生使用ABC/2法的测量结果与算法生成的ICH（0.69）和PHE（0.70）体积测量结果之间具有良好的相关性。神经放射科医生使用ABC/2法的测量结果与算法生成的ICH（0.47）体积测量结果之间具有中等相关性，与PHE（0.73）具有良好相关性。
虽然ABC/2法测量PHE快速实用，但不假设为椭球体形状的算法可能更准确。
