Established the prediction model of early-stage non-small cell lung cancer spread through air spaces (STAS) by radiomics and genomics features.

IF 1.4 4区医学 Q4 ONCOLOGY Asia-Pacific journal of clinical oncology Pub Date : 2024-07-01 DOI:10.1111/ajco.14099

Yimin Wang, Chuling Li, Zhaofeng Wang, Ranpu Wu, Huijuan Li, Yunchang Meng, Hongbing Liu, Yong Song

{"title":"Established the prediction model of early-stage non-small cell lung cancer spread through air spaces (STAS) by radiomics and genomics features.","authors":"Yimin Wang, Chuling Li, Zhaofeng Wang, Ranpu Wu, Huijuan Li, Yunchang Meng, Hongbing Liu, Yong Song","doi":"10.1111/ajco.14099","DOIUrl":null,"url":null,"abstract":"Background: This study was aimed to establish a prediction model for spread through air spaces (STAS) in early-stage non-small cell lung cancer based on imaging and genomic features.Methods: We retrospectively collected 204 patients (47 STAS+ and 157 STAS-) with non-small cell lung cancer who underwent surgical treatment in the Jinling Hospital from January 2021 to December 2021. Their preoperative CT images, genetic testing data (including next-generation sequencing data from other hospitals), and clinical data were collected. Patients were randomly divided into training and testing cohorts (7:3).Results: The study included a total of 204 eligible patients. STAS were found in 47 (23.0%) patients, and no STAS were found in 157 (77.0%) patients. The receiver operating characteristic curve showed that radiomics model, clinical genomics model, and mixed model had good predictive performance (area under the curve [AUC] = 0.85; AUC = 0.70; AUC = 0.85).Conclusions: The prediction model based on radiomics and genomics features has a good prediction performance for STAS.","PeriodicalId":8633,"journal":{"name":"Asia-Pacific journal of clinical oncology","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia-Pacific journal of clinical oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/ajco.14099","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Background: This study was aimed to establish a prediction model for spread through air spaces (STAS) in early-stage non-small cell lung cancer based on imaging and genomic features.

Methods: We retrospectively collected 204 patients (47 STAS+ and 157 STAS-) with non-small cell lung cancer who underwent surgical treatment in the Jinling Hospital from January 2021 to December 2021. Their preoperative CT images, genetic testing data (including next-generation sequencing data from other hospitals), and clinical data were collected. Patients were randomly divided into training and testing cohorts (7:3).

Results: The study included a total of 204 eligible patients. STAS were found in 47 (23.0%) patients, and no STAS were found in 157 (77.0%) patients. The receiver operating characteristic curve showed that radiomics model, clinical genomics model, and mixed model had good predictive performance (area under the curve [AUC] = 0.85; AUC = 0.70; AUC = 0.85).

Conclusions: The prediction model based on radiomics and genomics features has a good prediction performance for STAS.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

通过放射组学和基因组学特征，建立早期非小细胞肺癌气隙扩散（STAS）预测模型。

背景：本研究旨在根据影像学特征建立早期非小细胞肺癌气隙扩散（STAS）预测模型：本研究旨在根据影像学和基因组学特征建立早期非小细胞肺癌气隙播散（STAS）预测模型：我们回顾性地收集了 204 例（47 例 STAS+ 和 157 例 STAS-）于 2021 年 1 月至 2021 年 12 月在金陵医院接受手术治疗的非小细胞肺癌患者。研究人员收集了他们的术前 CT 图像、基因检测数据（包括其他医院的新一代测序数据）和临床数据。患者被随机分为训练组和测试组（7:3）：研究共纳入了 204 名符合条件的患者。47例（23.0%）患者发现STAS，157例（77.0%）患者未发现STAS。接受者操作特征曲线显示，放射组学模型、临床基因组学模型和混合模型具有良好的预测性能（曲线下面积 [AUC] = 0.85；AUC = 0.70；AUC = 0.85）：结论：基于放射组学和基因组学特征的预测模型对 STAS 具有良好的预测效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Asia-Pacific journal of clinical oncology 医学-肿瘤学

CiteScore

3.40

自引率

0.00%

发文量

175

审稿时长

6-12 weeks

期刊介绍： Asia–Pacific Journal of Clinical Oncology is a multidisciplinary journal of oncology that aims to be a forum for facilitating collaboration and exchanging information on what is happening in different countries of the Asia–Pacific region in relation to cancer treatment and care. The Journal is ideally positioned to receive publications that deal with diversity in cancer behavior, management and outcome related to ethnic, cultural, economic and other differences between populations. In addition to original articles, the Journal publishes reviews, editorials, letters to the Editor and short communications. Case reports are generally not considered for publication, only exceptional papers in which Editors find extraordinary oncological value may be considered for review. The Journal encourages clinical studies, particularly prospectively designed clinical trials.