PET radiomics for histologic subtype classification of non-small cell lung cancer: a systematic review and meta-analysis.
Purpose: To systematically review the literature and perform a meta-analysis of PET radiomics for histologic subtype classification in non-small cell lung cancer (NSCLC). Methods: PubMed, Embase, Scopus, and Web of Science databases were systematically searched in English on human subjects for studi...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 52; no. 6; pp. 2212 - 2225 |
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| Autores principales: | , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=184671080&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 184671080 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: May2025 vid: 52 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 184671080 182140878 10.1007/s00259-025-07069-6 184671080 ppf: 2212 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: PET radiomics for histologic subtype classification of non-small cell lung cancer: a systematic review and meta-analysis. aug: au: Zhang, Jucheng Zhang, Xiaohui Zhong, Yan Wang, Jing Zhong, Chao Xiao, Meiling Chen, Yuhan Zhang, Hong affil: https://ror.org/059cjpv64 Department of Clinical Engineering, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, Zhejiang, China sug: ab: Purpose: To systematically review the literature and perform a meta-analysis of PET radiomics for histologic subtype classification in non-small cell lung cancer (NSCLC). Methods: 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 I2 value. Subgroup analyses were conducted to explore sources of heterogeneity. Results: 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 I2 of 92.20% (95% CI: 89.01–95.39) for sensitivity and 89.29% (95% CI: 84.48–94.10) for specificity. Conclusions: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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