Zhang Jucheng, Zhang Xiaohui, Zhong Yan, Wang Jing, Zhong Chao, Xiao Meiling, Chen Yuhan, Zhang Hong
Department of Clinical Engineering, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China.
Department of Nuclear Medicine and Medical PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang, 310009, China.
Eur J Nucl Med Mol Imaging. 2025 May;52(6):2212-2224. doi: 10.1007/s00259-025-07069-6. Epub 2025 Jan 11.
To systematically review the literature and perform a meta-analysis of PET radiomics for histologic subtype classification in non-small cell lung cancer (NSCLC).
PubMed, Embase, Scopus, and Web of Science databases were systematically searched in English on human subjects for studies on distinguishing adenocarcinoma (ADC) from squamous cell carcinoma (SCC) using PET radiomics published from inception until November 2024. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and the Radiomics Quality Score (RQS) were utilized to assess the methodological quality of the included studies. The area under the receiver operating characteristic curves (AUC) was pooled to estimate predictive performance. An overall effect size was estimated using a random-effects model. Statistical heterogeneity was evaluated by the I value. Subgroup analyses were conducted to explore sources of heterogeneity.
Twelve studies were included in the analysis, yielding a pooled AUC of 0.92 (95% confidence interval [CI]: 0.89-0.94). Despite this promising result, the studies showed limitations in both study design and methodological quality, as evidenced by a median RQS of 11/36. A significant degree of heterogeneity was observed among the studies, with an I of 92.20% (95% CI: 89.01-95.39) for sensitivity and 89.29% (95% CI: 84.48-94.10) for specificity.
This meta-analysis highlights the potential utility of PET radiomics in distinguishing ADC from SCC. However, the observed high heterogeneity indicates substantial methodological variability across the included studies. Future research should focus on standardization, transparency, and multicenter collaborations to improve the reliability and clinical applicability of PET radiomics for histologic subtype classification in NSCLC.
系统回顾文献并对正电子发射断层扫描（PET）放射组学用于非小细胞肺癌（NSCLC）组织学亚型分类进行荟萃分析。
在PubMed、Embase、Scopus和Web of Science数据库中，以英文系统检索自数据库建立至2024年11月发表的关于使用PET放射组学区分腺癌（ADC）和鳞状细胞癌（SCC）的人体研究。采用诊断准确性研究质量评估2（QUADAS - 2）工具和放射组学质量评分（RQS）评估纳入研究的方法学质量。汇总受试者工作特征曲线（ROC）下面积（AUC）以估计预测性能。使用随机效应模型估计总体效应大小。通过I值评估统计异质性。进行亚组分析以探索异质性来源。
12项研究纳入分析，汇总AUC为0.92（95%置信区间[CI]：0.89 - 0.94）。尽管结果令人鼓舞，但研究在研究设计和方法学质量方面均存在局限性，RQS中位数为11/36即表明了这一点。研究间观察到显著程度的异质性，敏感性的I值为92.20%（95% CI：89.01 - 95.39），特异性的I值为89.29%（95% CI：84.48 - 94.10）。
这项荟萃分析突出了PET放射组学在区分ADC和SCC方面的潜在效用。然而，观察到的高异质性表明纳入研究在方法学上存在很大差异。未来研究应专注于标准化、透明度和多中心合作，以提高PET放射组学用于NSCLC组织学亚型分类的可靠性和临床适用性。
