Radiomics based on MRI in predicting lymphovascular space invasion of cervical cancer: a meta-analysis

作者：Chongshuang Yang, Min Wu, Jiancheng Zhang, Hongwei Qian, Xiangyang Fu, Jing Yang, Yingbin Luo, Zhihong Qin, Tianliang Shi · 发表于：Frontiers in Oncology · 年份：2024 · DOI：10.3389/fonc.2024.1425078 · 被引用次数：3 · 研究领域：Endometrial and Cervical Cancer Treatments、Radiomics and Machine Learning in Medical Imaging、MRI in cancer diagnosis

Objective The objective of this meta-analysis is to assess the efficacy of radiomics techniques utilizing magnetic resonance imaging (MRI) for predicting lymphovascular space invasion (LVSI) in patients with cervical cancer (CC). Methods A comprehensive literature search was conducted in databases including PubMed, Embase, Cochrane Library, Medline, Scopus, CNKI, and Wanfang, with studies published up to 08/04/2024, being considered for inclusion. The meta-analysis was performed using Stata 15 and Review Manager 5.4. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies 2 and Radiomics Quality Score tools. The analysis encompassed the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). Summary ROC curves were constructed, and the AUC was calculated. Heterogeneity was investigated using meta-regression. Statistical significance was set at p ≤ 0.05. Results There were 13 studies involving a total of 2,245 patients that were included in the meta-analysis. The overall sensitivity and specificity of the MRI-based model in the Training set were 83% (95% CI: 77%–87%) and 72% (95% CI: 74%–88%), respectively. The AUC, DOR, PLR, and NLR of the MRI-based model in the Training set were 0.89 (95% CI: 0.86–0.91), 22 (95% CI: 12–40), 4.6 (95% CI: 3.1–7.0), and 0.21 (95% CI: 0.16–0.29), respectively. Subgroup analysis revealed that the AUC of the model combi...