预测急性缺血性脑卒中患者预后的影像组学研究现状与质量：一项系统评价和Meta分析
Current status and quality of radiomics studies for predicting outcome in acute ischemic stroke patients: a systematic review and meta-analysis.
作者信息
Kong Jinfen, Zhang Danfen
机构信息
Department of Radiology, Yuhuan Second People's Hospital, Yuhuan, Taizhou, Zhejiang, China.
出版信息
Front Neurol. 2024 Jan 2;14:1335851. doi: 10.3389/fneur.2023.1335851. eCollection 2023.
BACKGROUND
Pre-treatment prediction of reperfusion and long-term prognosis in acute ischemic stroke (AIS) patients is crucial for effective treatment and decision-making. Recent studies have demonstrated that the inclusion of radiomics data can improve the performance of predictive models. This paper reviews published studies focused on radiomics-based prediction of reperfusion and long-term prognosis in AIS patients.
METHODS
We systematically searched PubMed, Web of Science, and Cochrane databases up to September 9, 2023, for studies on radiomics-based prediction of AIS patient outcomes. The methodological quality of the included studies was evaluated using the phase classification criteria, the radiomics quality scoring (RQS) tool, and the Prediction model Risk Of Bias Assessment Tool (PROBAST). Two separate meta-analyses were performed of these studies that predict long-term prognosis and reperfusion in AIS patients.
RESULTS
Sixteen studies with sample sizes ranging from 67 to 3,001 were identified. Ten studies were classified as phase II, and the remaining were categorized as phase 0 ( = 2), phase I ( = 1), and phase III ( = 3). The mean RQS score of all studies was 39.41%, ranging from 5.56 to 75%. Most studies (87.5%, 14/16) were at high risk of bias due to their retrospective design. The remaining two studies were categorized as low risk and unclear risk, respectively. The pooled area under the curve (AUC) was 0.88 [95% confidence interval (CI) 0.84-0.92] for predicting the long-term prognosis and 0.80 (95% CI 0.74-0.86) for predicting reperfusion in AIS.
CONCLUSION
Radiomics has the potential to predict immediate reperfusion and long-term outcomes in AIS patients. Further external validation and evaluation within the clinical workflow can facilitate personalized treatment for AIS patients. This systematic review provides valuable insights for optimizing radiomics prediction systems for both reperfusion and long-term outcomes in AIS patients.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023461671, identifier CRD42023461671.
背景
急性缺血性卒中（AIS）患者再灌注及长期预后的治疗前预测对于有效治疗和决策至关重要。近期研究表明，纳入放射组学数据可提高预测模型的性能。本文综述了已发表的关于基于放射组学预测AIS患者再灌注及长期预后的研究。
方法
我们系统检索了截至2023年9月9日的PubMed、Web of Science和Cochrane数据库，以查找基于放射组学预测AIS患者预后的研究。使用阶段分类标准、放射组学质量评分（RQS）工具和预测模型偏倚风险评估工具（PROBAST）对纳入研究的方法学质量进行评估。对这些预测AIS患者长期预后和再灌注的研究进行了两项独立的荟萃分析。
结果
共纳入16项研究，样本量从67至3001不等。10项研究被归类为II期，其余分别归类为0期（=2）、I期（=1）和III期（=3）。所有研究的平均RQS评分为39.41%，范围为5.56%至75%。由于其回顾性设计，大多数研究（87.5%，14/16）存在高偏倚风险。其余两项研究分别归类为低风险和风险不明确。预测AIS长期预后的合并曲线下面积（AUC）为0.88 [95%置信区间（CI）0.84 - 0.92]，预测再灌注的AUC为0.80（95%CI 0.74 - 0.86）。
结论
放射组学有潜力预测AIS患者的即刻再灌注和长期预后。在临床工作流程中进行进一步的外部验证和评估可促进AIS患者的个性化治疗。本系统评价为优化AIS患者再灌注和长期预后的放射组学预测系统提供了有价值的见解。
系统评价注册
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023461671，标识符CRD42023461671。
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