Computed tomography–based radial endobronchial ultrasound image simulation of peripheral pulmonary lesions using deep learning

IF 4.4 1区 医学 Q1 GASTROENTEROLOGY & HEPATOLOGY
Chunxi Zhang, Yongzheng Zhou, Chuanqi Sun, Jilei Zhang, Junxiang Chen, Xiaoxuan Zheng, Ying Li, Xiaoyao Liu, Weiping Liu, Jiayuan Sun
{"title":"Computed tomography–based radial endobronchial ultrasound image simulation of peripheral pulmonary lesions using deep learning","authors":"Chunxi Zhang, Yongzheng Zhou, Chuanqi Sun, Jilei Zhang, Junxiang Chen, Xiaoxuan Zheng, Ying Li, Xiaoyao Liu, Weiping Liu, Jiayuan Sun","doi":"10.1097/eus.0000000000000079","DOIUrl":null,"url":null,"abstract":"<h3>Background and Objectives </h3>\n<p>Radial endobronchial ultrasound (R-EBUS) plays an important role during transbronchial sampling of peripheral pulmonary lesions (PPLs). However, existing navigational bronchoscopy systems provide no guidance for R-EBUS. To guide intraoperative R-EBUS probe manipulation, we aimed to simulate R-EBUS images of PPLs from preoperative computed tomography (CT) data using deep learning.</p>\n<h3>Materials and Methods </h3>\n<p>Preoperative CT and intraoperative ultrasound data of PPLs in 250 patients who underwent R-EBUS–guided transbronchial lung biopsy were retrospectively collected. Two-dimensional CT sections perpendicular to the biopsy path were transformed into ultrasonic reflection and transmission images using an ultrasound propagation model to obtain the initial simulated R-EBUS images. A cycle generative adversarial network was trained to improve the realism of initial simulated images. Objective and subjective indicators were used to evaluate the similarity between real and simulated images.</p>\n<h3>Results </h3>\n<p>Wasserstein distances showed that utilizing the cycle generative adversarial network significantly improved the similarity between real and simulated R-EBUS images. There was no statistically significant difference in the long axis, short axis, and area between real and simulated lesions (all <em xmlns:mrws=\"http://webservices.ovid.com/mrws/1.0\">P</em> &gt; 0.05). Based on the experts’ evaluation, a median similarity score of ≥4 on a 5-point scale was obtained for lesion size, shape, margin, internal echoes, and overall similarity.</p>\n<h3>Conclusions </h3>\n<p>Simulated R-EBUS images of PPLs generated by our method can closely mimic the corresponding real images, demonstrating the potential of our method to provide guidance for intraoperative R-EBUS probe manipulation.</p>","PeriodicalId":11577,"journal":{"name":"Endoscopic Ultrasound","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endoscopic Ultrasound","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/eus.0000000000000079","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background and Objectives 

Radial endobronchial ultrasound (R-EBUS) plays an important role during transbronchial sampling of peripheral pulmonary lesions (PPLs). However, existing navigational bronchoscopy systems provide no guidance for R-EBUS. To guide intraoperative R-EBUS probe manipulation, we aimed to simulate R-EBUS images of PPLs from preoperative computed tomography (CT) data using deep learning.

Materials and Methods 

Preoperative CT and intraoperative ultrasound data of PPLs in 250 patients who underwent R-EBUS–guided transbronchial lung biopsy were retrospectively collected. Two-dimensional CT sections perpendicular to the biopsy path were transformed into ultrasonic reflection and transmission images using an ultrasound propagation model to obtain the initial simulated R-EBUS images. A cycle generative adversarial network was trained to improve the realism of initial simulated images. Objective and subjective indicators were used to evaluate the similarity between real and simulated images.

Results 

Wasserstein distances showed that utilizing the cycle generative adversarial network significantly improved the similarity between real and simulated R-EBUS images. There was no statistically significant difference in the long axis, short axis, and area between real and simulated lesions (all P > 0.05). Based on the experts’ evaluation, a median similarity score of ≥4 on a 5-point scale was obtained for lesion size, shape, margin, internal echoes, and overall similarity.

Conclusions 

Simulated R-EBUS images of PPLs generated by our method can closely mimic the corresponding real images, demonstrating the potential of our method to provide guidance for intraoperative R-EBUS probe manipulation.

利用深度学习对基于计算机断层扫描的径向支气管内超声周边肺部病变进行图像模拟
背景和目的 径向支气管内超声(R-EBUS)在经支气管取样检查周围肺部病变(PPL)时发挥着重要作用。然而,现有的导航支气管镜系统无法为 R-EBUS 提供指导。为了指导术中的 R-EBUS 探头操作,我们旨在利用深度学习从术前计算机断层扫描(CT)数据中模拟 PPLs 的 R-EBUS 图像。利用超声传播模型将垂直于活检路径的二维 CT 切片转换为超声反射和透射图像,从而获得初始模拟 R-EBUS 图像。对循环生成对抗网络进行了训练,以提高初始模拟图像的逼真度。结果 Wasserstein 距离显示,利用循环生成对抗网络显著提高了真实和模拟 R-EBUS 图像之间的相似度。真实病变与模拟病变在长轴、短轴和面积上的差异无统计学意义(均为 P > 0.05)。结论 用我们的方法生成的 PPLs 仿真 R-EBUS 图像可以近似模拟相应的真实图像,这表明我们的方法具有为术中 R-EBUS 探头操作提供指导的潜力。
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 求助全文
来源期刊
Endoscopic Ultrasound
Endoscopic Ultrasound GASTROENTEROLOGY & HEPATOLOGY-
CiteScore
6.20
自引率
11.10%
发文量
144
期刊介绍: Endoscopic Ultrasound, a publication of Euro-EUS Scientific Committee, Asia-Pacific EUS Task Force and Latin American Chapter of EUS, is a peer-reviewed online journal with Quarterly print on demand compilation of issues published. The journal’s full text is available online at http://www.eusjournal.com. The journal allows free access (Open Access) to its contents and permits authors to self-archive final accepted version of the articles on any OAI-compliant institutional / subject-based repository. The journal does not charge for submission, processing or publication of manuscripts and even for color reproduction of photographs.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信