Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
Eur J Radiol. 2024 Sep;178:111652. doi: 10.1016/j.ejrad.2024.111652. Epub 2024 Jul 26.
We conducted a systematic review and meta-analysis of current publications on the potential role of non-contrast-enhanced computed tomography (NCCT) radiomics as a prognostic indicator in patients with intracerebral hemorrhage (ICH).
We systematically searched PubMed, EMBASE, and the Web of Science from inception until January 8, 2024. Studies with NCCT-based radiomics features for predicting the prognostic outcomes of ICH patients were included. We calculated the pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under curve (AUC) values. The radiomics quality score (RQS), METhodological RadiomICs Score (METRICS), and the quality assessment of diagnostic accuracy studies (QUADAS-2) were used for quality assessment.
Twenty-two studies were included. The pooled sensitivity, specificity, DOR, and AUC of radiomics models were 0.73, 0.78, 10.03, and 0.83, respectively, while on the combined radiomics models with other non-radiomics features were 0.80, 0.80, 16.28, and 0.86. Subgroup analysis showed that studies with the following covariates have a higher accuracy: single center, modified Rankin Scale (mRS) criteria for the ICH outcomes assessment, following patients for evaluation of ICH outcomes for more than a month, automatic segmentation, capturing the radiomics feature from the only intra-hematomal region, using PyRadiomic tool for features extraction, and using non-logistic regression for modeling. The quality of literature using QUADAS-2 and METRICS tools was good and was under-average using the RQS tool. No publication bias was detected.
Radiomics features showed moderate to high accuracy for predicting ICH prognostic outcomes. Although the QUADAS-2 and METRICS assessments indicated good quality, the radiomics pipeline quality was under-average.
NCCT-based radiomics features can provide information about the prognostic outcomes of ICH patients after patient admission. This study exploits the value of current evidence on NCCT-based radiomics methodology in the prediction of ICH prognosis.
我们对当前关于非增强 CT（NCCT）放射组学作为脑出血（ICH）患者预后指标的潜在作用的出版物进行了系统回顾和荟萃分析。
我们系统地检索了 PubMed、EMBASE 和 Web of Science，检索时间截至 2024 年 1 月 8 日。纳入基于 NCCT 放射组学特征预测 ICH 患者预后结局的研究。我们计算了汇总的敏感性、特异性、诊断比值比（DOR）和曲线下面积（AUC）值。使用放射组学质量评分（RQS）、方法学放射组学评分（METRICS）和诊断准确性研究的质量评估（QUADAS-2）进行质量评估。
共纳入 22 项研究。放射组学模型的汇总敏感性、特异性、DOR 和 AUC 值分别为 0.73、0.78、10.03 和 0.83，而在结合放射组学模型和其他非放射组学特征的模型中则分别为 0.80、0.80、16.28 和 0.86。亚组分析显示，具有以下协变量的研究具有更高的准确性：单中心、ICH 结局评估的改良 Rankin 量表（mRS）标准、对 ICH 结局进行评估的随访时间超过 1 个月、自动分割、仅从血肿内区域捕获放射组学特征、使用 PyRadiomic 工具提取特征以及使用非逻辑回归进行建模。使用 QUADAS-2 和 METRICS 工具的文献质量良好，而使用 RQS 工具的质量则处于中下水平。未发现发表偏倚。
放射组学特征对预测 ICH 预后结局具有中等至高度准确性。尽管 QUADAS-2 和 METRICS 评估表明质量良好，但放射组学流程质量处于中下水平。
NCCT 基于放射组学特征可提供患者入院后 ICH 患者预后结局的信息。本研究利用了当前关于 NCCT 基于放射组学方法在预测 ICH 预后方面的证据价值。
