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特定位置的放射组学评分:预测深部和脑叶自发性脑出血不良预后的新型影像标志物。

Location-Specific Radiomics Score: Novel Imaging Marker for Predicting Poor Outcome of Deep and Lobar Spontaneous Intracerebral Hemorrhage.

作者信息

Zhou Zhiming, Zhou Hongli, Song Zuhua, Chen Yuanyuan, Guo Dajing, Cai Jinhua

机构信息

Department of Radiology, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.

Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, China.

出版信息

Front Neurosci. 2021 Nov 25;15:766228. doi: 10.3389/fnins.2021.766228. eCollection 2021.

Abstract

To derive and validate a location-specific radiomics score (Rad-score) based on noncontrast computed tomography for predicting poor deep and lobar spontaneous intracerebral hemorrhage (SICH) outcome. In total, 494 SICH patients from multiple centers were retrospectively reviewed. Poor outcome was considered mRS 3-6 at 6 months. The Rad-score was derived using optimal radiomics features. The optimal location-specific Rad-score cut-offs for poor deep and lobar SICH outcomes were identified using receiver operating characteristic curve analysis. Univariable and multivariable analyses were used to determine independent poor outcome predictors. The combined models for deep and lobar SICH were constructed using independent predictors of poor outcomes, including dichotomized Rad-score in the derivation cohort, which was validated in the validation cohort. Of 494 SICH patients, 392 (79%) had deep SICH, and 373 (76%) had poor outcomes. The Glasgow Coma Scale score, haematoma enlargement, haematoma location, haematoma volume and Rad-score were independent predictors of poor outcomes (all < 0.05). Cut-offs of Rad-score, 82.90 (AUC = 0.794) in deep SICH and 80.77 (AUC = 0.823) in lobar SICH, were identified for predicting poor outcomes. For deep SICH, the AUCs of the combined model were 0.856 and 0.831 in the derivation and validation cohorts, respectively. For lobar SICH, the combined model AUCs were 0.866 and 0.843 in the derivation and validation cohorts, respectively. Location-specific Rad-scores and combined models can identify subjects at high risk of poor deep and lobar SICH outcomes, which could improve clinical trial design by screening target patients.

摘要

基于非增强计算机断层扫描得出并验证特定部位的放射组学评分(Rad评分),以预测深部和脑叶自发性脑出血(SICH)的不良预后。总共对来自多个中心的494例SICH患者进行了回顾性研究。不良预后定义为6个月时改良Rankin量表(mRS)评分为3 - 6分。使用最佳放射组学特征得出Rad评分。通过受试者工作特征曲线分析确定深部和脑叶SICH不良预后的最佳特定部位Rad评分临界值。采用单变量和多变量分析来确定独立的不良预后预测因素。使用不良预后的独立预测因素构建深部和脑叶SICH的联合模型,包括在推导队列中二分的Rad评分,并在验证队列中进行验证。在494例SICH患者中,392例(79%)为深部SICH,373例(76%)预后不良。格拉斯哥昏迷量表评分、血肿扩大、血肿位置、血肿体积和Rad评分是不良预后的独立预测因素(均P<0.05)。确定深部SICH的Rad评分临界值为82.90(AUC = 0.794),脑叶SICH为80.77(AUC = 0.823),用于预测不良预后。对于深部SICH,联合模型在推导队列和验证队列中的AUC分别为0.856和0.831。对于脑叶SICH,联合模型在推导队列和验证队列中的AUC分别为0.866和0.843。特定部位的Rad评分和联合模型可以识别深部和脑叶SICH不良预后的高危患者,这可以通过筛选目标患者来改进临床试验设计。

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