Development of a CT image-based virtual atelectasis simulation model and noninvasive lung nodule localization system.

IF 2.1 3区 医学 Q3 RESPIRATORY SYSTEM
Journal of thoracic disease Pub Date : 2024-11-30 Epub Date: 2024-11-21 DOI:10.21037/jtd-24-903
Intae Hwang, Sungwon Ham, Chohee Kim, Seong-Hak Lee, Cherry Kim, Jinwook Hwang
{"title":"Development of a CT image-based virtual atelectasis simulation model and noninvasive lung nodule localization system.","authors":"Intae Hwang, Sungwon Ham, Chohee Kim, Seong-Hak Lee, Cherry Kim, Jinwook Hwang","doi":"10.21037/jtd-24-903","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>In the process of video-assisted thoracoscopic surgery (VATS) for lung nodule resection, lung is leaded to atelectasis. However, preoperative computed tomography (CT) images are taken during inspiration, which means they differ significantly from the lung status observed during surgery. Consequently, this discrepancy can make the localization of small or subsolid nodules challenging during the operation. This study aimed to develop a CT-based virtual atelectasis simulation system for noninvasive lung nodule localization. By accurately simulating atelectasis, this study aimed to improve the precision of presurgical planning from lung nodule resections.</p><p><strong>Methods: </strong>This study retrospectively examined 20 patients who had either subsolid nodules or small nodules less than 3 cm in size, selected from a cohort of 279 patients who underwent VATS surgery for lung nodules in Korea University Ansan Hospital between June 28, 2021, and January 22, 2024. Chest CT images of the lungs of 20 patients were acquired, and image data were converted three-dimensional models. The mesh points extracted from these lung models were manipulated to simulate the effects of gravity, by adjusting the lung shapes and nodule locations to align with the respective surgical postures of the patients. Subsequently, we assessed the similarity of the simulation by comparing the resulting deformed lung shapes and nodule locations with the corresponding perspectives observed in the surgical videos.</p><p><strong>Results: </strong>The average volume of the entire lung among the patients was 2,336 cm<sup>3</sup> (±588). After atelectasis simulation, the average lung shrinkage rate was 48.6% (±12.9%). Evaluations of an average of 15 pairs of images per case revealed significant conformity between atelectasis simulation images and surgical video snapshots, with average Dice and Jaccard similarity coefficient values of 90.27 and 88.25, respectively. Furthermore, the alignment of nodule locations between the simulations and surgical anticipation demonstrated notable accuracy, with an average Hausdorff distance of 6.39 mm.</p><p><strong>Conclusions: </strong>We successfully developed a simulation of lung atelectasis based on preoperative CT scans that closely resembled actual surgical videos. The integration of this presurgical atelectasis simulation is anticipated to enhance the accuracy of nodule locations, thus contributing to more efficient and precise surgical planning.</p>","PeriodicalId":17542,"journal":{"name":"Journal of thoracic disease","volume":"16 11","pages":"7651-7662"},"PeriodicalIF":2.1000,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11635236/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of thoracic disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/jtd-24-903","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/21 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0

Abstract

Background: In the process of video-assisted thoracoscopic surgery (VATS) for lung nodule resection, lung is leaded to atelectasis. However, preoperative computed tomography (CT) images are taken during inspiration, which means they differ significantly from the lung status observed during surgery. Consequently, this discrepancy can make the localization of small or subsolid nodules challenging during the operation. This study aimed to develop a CT-based virtual atelectasis simulation system for noninvasive lung nodule localization. By accurately simulating atelectasis, this study aimed to improve the precision of presurgical planning from lung nodule resections.

Methods: This study retrospectively examined 20 patients who had either subsolid nodules or small nodules less than 3 cm in size, selected from a cohort of 279 patients who underwent VATS surgery for lung nodules in Korea University Ansan Hospital between June 28, 2021, and January 22, 2024. Chest CT images of the lungs of 20 patients were acquired, and image data were converted three-dimensional models. The mesh points extracted from these lung models were manipulated to simulate the effects of gravity, by adjusting the lung shapes and nodule locations to align with the respective surgical postures of the patients. Subsequently, we assessed the similarity of the simulation by comparing the resulting deformed lung shapes and nodule locations with the corresponding perspectives observed in the surgical videos.

Results: The average volume of the entire lung among the patients was 2,336 cm3 (±588). After atelectasis simulation, the average lung shrinkage rate was 48.6% (±12.9%). Evaluations of an average of 15 pairs of images per case revealed significant conformity between atelectasis simulation images and surgical video snapshots, with average Dice and Jaccard similarity coefficient values of 90.27 and 88.25, respectively. Furthermore, the alignment of nodule locations between the simulations and surgical anticipation demonstrated notable accuracy, with an average Hausdorff distance of 6.39 mm.

Conclusions: We successfully developed a simulation of lung atelectasis based on preoperative CT scans that closely resembled actual surgical videos. The integration of this presurgical atelectasis simulation is anticipated to enhance the accuracy of nodule locations, thus contributing to more efficient and precise surgical planning.

开发基于 CT 图像的虚拟肺不张模拟模型和无创肺结节定位系统。
背景:在视频辅助胸腔镜手术(VATS)进行肺结节切除术的过程中,肺部会出现回流。然而,术前计算机断层扫描(CT)图像是在吸气时拍摄的,这意味着它们与手术中观察到的肺部状态有很大差异。因此,这种差异会使手术中对小结节或亚实结节的定位具有挑战性。本研究旨在开发一种基于 CT 的虚拟肺不张模拟系统,用于无创肺结节定位。通过精确模拟肺不张,本研究旨在提高肺结节切除术前规划的精确度:本研究从 2021 年 6 月 28 日至 2024 年 1 月 22 日期间在韩国大学安山医院接受 VATS 肺结节手术的 279 名患者中选取了 20 名患者进行回顾性研究,这些患者均患有实性下结节或小于 3 厘米的小结节。采集了 20 名患者肺部的胸部 CT 图像,并将图像数据转换为三维模型。我们对从这些肺部模型中提取的网格点进行了处理,通过调整肺部形状和结节位置来模拟重力的影响,使其与患者各自的手术姿势相一致。随后,我们通过比较变形后的肺部形状和结节位置与手术视频中观察到的相应视角来评估模拟的相似性:结果:患者整个肺的平均体积为 2,336 立方厘米(±588)。模拟肺不张后,肺的平均收缩率为 48.6%(±12.9%)。对每个病例平均 15 对图像进行评估后发现,脑偏流模拟图像与手术视频快照之间的一致性非常高,平均 Dice 和 Jaccard 相似性系数分别为 90.27 和 88.25。此外,模拟图像与手术预测图像之间的结节位置对齐也表现出显著的准确性,平均豪斯多夫距离为 6.39 毫米:结论:我们根据术前 CT 扫描成功开发了一种肺不张模拟,与实际手术视频非常相似。这种术前肺偏流模拟的整合有望提高结节位置的准确性,从而有助于更高效、更精确地制定手术计划。
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
Journal of thoracic disease
Journal of thoracic disease RESPIRATORY SYSTEM-
CiteScore
4.60
自引率
4.00%
发文量
254
期刊介绍: The Journal of Thoracic Disease (JTD, J Thorac Dis, pISSN: 2072-1439; eISSN: 2077-6624) was founded in Dec 2009, and indexed in PubMed in Dec 2011 and Science Citation Index SCI in Feb 2013. It is published quarterly (Dec 2009- Dec 2011), bimonthly (Jan 2012 - Dec 2013), monthly (Jan. 2014-) and openly distributed worldwide. JTD received its impact factor of 2.365 for the year 2016. JTD publishes manuscripts that describe new findings and provide current, practical information on the diagnosis and treatment of conditions related to thoracic disease. All the submission and reviewing are conducted electronically so that rapid review is assured.
×
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