Liao Zhongfan, Luo Dashuang, Tang Xiaoyan, Huang Fasheng, Zhang Xuhui
Department of Oncology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Front Oncol. 2025 Mar 10;15:1550838. doi: 10.3389/fonc.2025.1550838. eCollection 2025.
To evaluate the value of MRI-based radiomics for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced rectal cancer (LARC) through a systematic review and meta-analysis.
A systematic literature search was conducted in PubMed, Embase, Proquest, Cochrane Library, and Web of Science databases, covering studies up to July 1st, 2024, on the diagnostic accuracy of MRI radiomics for predicting pCR in LARC patients following NCRT. Two researchers independently evaluated and selected studies using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and the Radiomics Quality Score (RQS) tool. A random-effects model was employed to calculate the pooled sensitivity, specificity, and diagnostic odds ratio (DOR) for MRI radiomics in predicting pCR. Meta-regression and subgroup analyses were performed to explore potential sources of heterogeneity. Statistical analyses were performed using RevMan 5.4, Stata 17.0, and Meta-Disc 1.4.
A total of 35 studies involving 9,696 LARC patients were included in this meta-analysis. The average RQS score of the included studies was 13.91 (range 9.00-24.00), accounting for 38.64% of the total score. According to QUADAS-2, there were risks of bias in patient selection and flow and timing domain, though the overall quality of the studies was acceptable. MRI-based radiomics showed no significant threshold effect in predicting pCR (Spearman correlation coefficient=0.119, P=0.498) but exhibited high heterogeneity (I≥50%). The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and DOR were 0.83, 0.82, 5.1, 0.23 and 27.22 respectively, with an area under the summary receiver operating characteristic (sROC) curve of 0.91. According to joint model analysis, publication year, country, multi-magnetic field strength, multi-MRI sequence, ROI structure, contour consistency, feature extraction software, and feature quantity after feature dimensionality reduction were potential sources of heterogeneity. Deeks' funnel plot suggested no significant publication bias (P=0.69).
MRI-based radiomics demonstrates high efficacy for predicting pCR in LARC patients following NCRT, holding significant promise for informing clinical decision-making processes and advancing individualized treatment in rectal cancer patients.
https://www.crd.york.ac.uk/prospero/, identifier CRD42024611733.
通过系统评价和荟萃分析，评估基于磁共振成像（MRI）的影像组学在预测局部晚期直肠癌（LARC）患者新辅助放化疗（NCRT）后病理完全缓解（pCR）方面的价值。
在PubMed、Embase、Proquest、Cochrane图书馆和Web of Science数据库中进行系统文献检索，涵盖截至2024年7月1日关于MRI影像组学预测LARC患者NCRT后pCR诊断准确性的研究。两名研究人员使用诊断准确性研究质量评估2（QUADAS-2）工具和影像组学质量评分（RQS）工具独立评估和选择研究。采用随机效应模型计算MRI影像组学预测pCR的合并敏感性、特异性和诊断比值比（DOR）。进行Meta回归和亚组分析以探索异质性的潜在来源。使用RevMan 5.4、Stata 17.0和Meta-Disc 1.4进行统计分析。
本荟萃分析共纳入35项研究，涉及9696例LARC患者。纳入研究的平均RQS评分为13.91（范围9.00 - 24.00），占总分的38.64%。根据QUADAS-2，尽管研究的总体质量可接受，但在患者选择、流程和时间领域存在偏倚风险。基于MRI的影像组学在预测pCR方面未显示出显著的阈值效应（Spearman相关系数 = 0.119，P = 0.498），但表现出高度异质性（I²≥50%）。合并敏感性、特异性、阳性似然比、阴性似然比和DOR分别为0.83、0.82、5.1、0.23和27.22，汇总受试者工作特征（sROC）曲线下面积为0.91。根据联合模型分析，发表年份、国家、多磁场强度、多MRI序列、感兴趣区（ROI）结构、轮廓一致性、特征提取软件和特征降维后的特征数量是异质性的潜在来源。Deeks漏斗图表明无显著发表偏倚（P = 0.69）。
基于MRI的影像组学在预测LARC患者NCRT后pCR方面显示出高效能，在为直肠癌患者的临床决策过程提供信息和推进个体化治疗方面具有重大前景。
