Jiang Yan-Wei, Xu Xiong-Jei, Wang Rui, Chen Chun-Mei
Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
Front Oncol. 2023 Jan 10;12:973104. doi: 10.3389/fonc.2022.973104. eCollection 2022.
This meta-analysis aimed to assess the efficacy of radiomics using non-enhanced computed tomography (NCCT) for predicting hematoma expansion in patients with spontaneous intracerebral hemorrhage.
Throughout the inception of the project to April 11, 2022, a comprehensive search was conducted on PubMed, Embase, and Cochrane Central Register of Controlled Trials. The methodological quality of studies in this analysis was assessed by the radiomics quality scoring system (RQS). A meta-analysis of radiomic studies based on NCCT for predicting hematoma expansion in patients with intracerebral hemorrhage was performed. The efficacy of the radiomics approach and non-contrast CT markers was compared using network meta-analysis (NMA).
Ten articles comprising a total of 1525 patients were quantitatively analyzed for hematoma expansion after cerebral hemorrhage using radiomics. Based on the included studies, the mean RQS was 14.4. The AUC value (95% confidence interval) of the radiomics model was 0.80 (0.76-0.83). Five articles comprising 846 patients were included in the NMA. The results synthesized according to Bayesian NMA revealed that the predictive ability of the radiomics model outperformed most of the NCCT biomarkers.
The NCCT-based radiomics approach has the potential to predict hematoma expansion. Compared to NCCT biomarkers, we recommend a radiomics approach. Standardization of the radiomics approach is required for further clinical implementation.
https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=324034, identifier [CRD42022324034].
本荟萃分析旨在评估使用非增强计算机断层扫描(NCCT)的放射组学预测自发性脑出血患者血肿扩大的疗效。
从项目启动至2022年4月11日,对PubMed、Embase和Cochrane对照试验中央注册库进行了全面检索。本分析中研究的方法学质量通过放射组学质量评分系统(RQS)进行评估。对基于NCCT预测脑出血患者血肿扩大的放射组学研究进行了荟萃分析。使用网络荟萃分析(NMA)比较了放射组学方法和非增强CT标志物的疗效。
对10篇共包含1525例患者的文章进行了放射组学定量分析,以评估脑出血后的血肿扩大情况。根据纳入的研究,平均RQS为14.4。放射组学模型的AUC值(95%置信区间)为0.80(0.76 - 0.83)。NMA纳入了5篇共846例患者的文章。根据贝叶斯NMA综合的结果显示,放射组学模型的预测能力优于大多数NCCT生物标志物。
基于NCCT的放射组学方法有预测血肿扩大的潜力。与NCCT生物标志物相比,我们推荐放射组学方法。放射组学方法的标准化对于进一步临床应用是必要的。
https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=324034,标识符[CRD42022324034]