Application of 3-dimensional reconstruction via modified pulmonary artery computed tomography angiography in anatomic pulmonary segmentectomy

Application of 3-dimensional reconstruction via modified pulmonary artery computed tomography angiography in anatomic pulmonary segmentectomy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Application of 3-dimensional reconstruction via modified pulmonary artery computed tomography angiography in anatomic pulmonary segmentectomy Weiwei Min, jianbin zhang, Yilv Zhu, Lili Jin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5337984/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Jun, 2025 Read the published version in Journal of Cardiothoracic Surgery → Version 1 posted 8 You are reading this latest preprint version Abstract Background This retrospective study aimed to summarize the application of 3 - dimensional(3D) reconstruction via modified pulmonary artery computed tomography angiography(CTA), as well as to compare the surgical outcomes of 3D versus high resolution CT(HRCT) in anatomic pulmonary segmentectomy(APS). Methods A total of 93 patients who underwent thoracoscopic APS were enrolled in the study. They were divided into 3D group (n = 30) and HRCT group (n = 63), and than matched at 1:1 ratio using the propensity score matching (PSM) method. Clinical characteristics, surgical status, and postoperative recovery were compared between two groups, additionally, variations of segmental structures were summarized. Results 60 cases were matched by PSM with 30 cases in each group. There were no significant differences between two groups in clinical characteristics, intraoperative blood loss and postoperative recovery (including total chest drainage, length of postoperative hospital stay)( P > 0.05 for all). 8(26.7%) patients in 3D group manifesting unique variations of segmental structures underwent anatomical segmentectomy accurately. Despite the 3D group exhibited higher anatomic variations compared to the HRCT group, it demonstrated shorter operation times and lower incidence of pulmonary infection. ( P < 0.05 for all). Conclusion Preoperative 3D reconstruction has advantages in APS, particularly for patients with complex anatomic variations. Reconstruction via modified pulmonary artery CTA is also feasible for preoperative planning and intraoperative navigation in thoracoscopic APS. Three-dimensional (3D) Reconstruction Thoracoscopic Pulmonary segmentectomy Figures Figure 1 Figure 2 Introduction The prevalence of physical examination has led to a rise in the identification of early lung cancer(ELC), thereby advancing the development of pulmonary segmentectomy[1–3]. It is crucial to grasp the anatomical structure before surgery due to the common anatomical variations. The utilization of 3D imaging softwares, such as Minics [4] , IQQA [5] , and DeepInsight [6] , have bean reported to provide precise anatomic details of pulmonary segments. However, surgeons may encounter challenges in effectively employing these softwares. Since 2020, we have conducted 3DCT of pulmonary segments via modified pulmonary artery CTA, which can also provide the 3D imaging of segmental structures with satisfactory outcome. Previously, we have reported two cases with unique anatomical variations detected by this technique [7][8] . This study aimed to summarize the application of this technique in thoracoscopic APS. Methods Patients 93 patients who underwent thoracoscopic APS for ELC were enrolled from January 2021 to July 2023 in our department. The inclusion and exclusion criteria are shown in Table 1 . The patients were categorized into 3D group (n=30) and HRCT group (n=63). Furthermore, they were divided into general subgroup (RS1, RS2, LS1+2, R/LS6, and LS4+S5), moderate subgroup (RS7, R/LS8, and R/LS3), and complex subgroup (R/LS9, R/LS10, R/LS9+10 and combined-subsegmental resection). The clinical data including age, sex, smoking history, forced expiratory volume (FEV1%), chronic obstructive pulmonary disease (COPD), tumor size, surgical type, operation time, intraoperative blood loss, postoperative recovery (total chest drainage, postoperative hospital stay, postoperative complications), and anatomic variations were compared between two groups. All patients underwent two-portal thoracoscopic surgery which were performed by a single surgeon. 3D reconstruction via modified pulmonary artery CTA (1) Instrument: Toshiba aquillion one 320-row Dual-source CT, vitrea extend 6.7 graphic analysis system. (2) Scanning scheme: The contrast agent was injected through the cubital vein mass with the rate 3.5-4.0ml/s, the scanning layer thickness was 1mm, the image matrix was 512*512, the trigger technology was adopted, the trigger point was set in the main pulmonary artery, the domain value was set to 110HU. Pulmonary artery and venous were scanned in two phases. (3) Segmental reconstruct: The maximum intensity projection (MinIP) technique was performed to reconstruct the 3D images of segmental bronchi. The 3D images of pulmonary vessels were reconstructed via software post-processing, which could well display segmental and subsegmental vessel branches ( Figure 1A-C ). Surgical technique Operations were performed under general anesthesia with one-lung ventilation. The patient assumed a supine position. during the procedure, with the surgeon positioned ventrally and the assistant positioned dorsally. The observation port was created in the seventh intercostal space of the posterior axillary line, while the operation port was established in the fourth intercostal space of the anterior axillary line. The segmental structures were dissected separately based on the preoperative planning, and then, the lung was reventilated with pure oxygen via double-lung ventilation. Approximately 10 to 15 minutes after transiting to single-lung ventilation, the intersegmental plane was clear, and it was subsequently divided using endostaplers. The dissection of mediastinal lymph node (MLN) was performed established by the fast-frozen pathological analysis. Statistical analyses All statistical analyses were conducted using SPSS 23.0 (IBM Corp, Armonk, NY, USA). Mean ± standard deviation (SD) was used to represent continuous distributed data, and the t-test was utilized to compare differences between two groups. Categorical variables were presented as absolute frequencies and proportions (%), and the χ 2 test was employed to compare categorical variables. P <0.05 was deemed statistically significant for all analyses. Results General characteristics This study encompassed a total of 93 cases with 30 in 3D group and 63 in HRCT group. 60 cases were matched by PSM at ratio of 1:1 with 30 cases in each group. Logistic regression analysis was conducted on the baseline data of two groups( Table 2 ) . The summarized data included sex, age, preoperative smoking, COPD, pulmonary function, maximum lesion diameter, anatomic variations and surgical types. No statistically significant differences were observed between two groups ( P >0.05 for all) ( Table 3 ). Surgical outcomes No instances of death related to surgery were reported in either group during hospitalization. There were no significant disparities between two groups in terms of intraoperative blood loss and postoperative recovery including total chest drainage and length of postoperative hospital stay ( P >0.05 for all). Although the 3D group exhibited a higher prevalence of anatomic variations compared to HRCT group (26.7% vs. 20%, P >0.05), it demonstrated shorter operation times and lower incidence of pulmonary infection( P <0.05 for all) ( Table 4 ). 8(26.7%) individuals in 3D group exhibited segmental variations. Among this subset of patients, 3 displayed a solitary variation( Figure 2A ), 4 exhibited combined variations( Figure 2B ), and 1 presented an uncommon multiple anatomic variations( Figure 2C ). Discussion Currently, lung cancer has the highest rates of morbidity and mortality of all malignant tumors worldwide [9,10] . Pulmonary lobectomy is the standard surgical procedure for early-stage lung cancer, which was supported in 1995 by the Lung Cancer Study Group's randomized trial [11] . Recently, with the increasing popularity of chest CT examinations, the detection rate of ELC has been rising. Studies have reconmend that pulmonary segmentectomy should be considered as a preferred treatment option for some ELC [12–14] . Meanwhile, pulmonary segmentectomy has been demonstrated equally efficacious to lobectomy, with additional advantages such as minimal damage, expedited recovery, and lung function protection [15–17] . However, the anatomic variation of pulmonary segments poses a main obstacle for surgeons in APS. Consequently, a precise understanding of the segmental structures is crucial for achieving successful APS [18] . The utilization of 3DCT-bronchography and angiography (3D-CTBA) has gradually gained traction since the 1990s [19,20] . In this technology, a transformation from 2D image into 3D model accurately depict the complex segmental structures. Studies have demonstrated that the preoperative 3D-CTBA to assess segmental bronchi and vascular patterns can improve the safety and efficacy of APS [21,22] . There are many reconstructive softwares presenting the opportunity to obtain precise anatomic details of pulmonary segments. In this study, we performed 3D-CTBA via modified pulmonary artery CTA technique to reconstruct the segmental structures. The quality of reconstruction was comparable to that of other softwares. 8 cases with complex anatomic variations were detected by 3D reconstruction, including a rare case of multiple variations in the right upper lobe, which were consistent with what we detected intraoperatively. Compared to the HRCT group, the 3D group might have potential advantages in terms of shortening operation time and decreaing postoperative pulmonary infection, which was consistent with findings from previous studies [22–24] . Furthermore, the preoperative 3D-CTBA via this technology offers several advantages for APS. Firstly, it enhances the visualization of nodules and lung structures, thereby enabling more efficient surgical procedures. Secondly, it facilitates the treatment of vessels and bronchus during surgery, resulting in safer and expedited operations. Lastly, it allows for preoperative simulated surgery, thereby minimizing the necessity for exploration of redundant lung tissue [25–27] . There are several factors that should be taken into consideration in this context. Firstly, it is crucial to emphasize the necessity of close collaboration between thoracic surgeons and radiologists. Secondly, the correction of the intersection position of the pulmonary artery and vein might be a perplexing task. Thirdly, the accuracy of 3D-CTBA results can be influenced by the presence of underlying lung diseases, such as emphysema and pulmonary fibrosis. Declarations Authors' contributions All authors read and approved final manuscripts. JZ performed the surgery. WM was the major contributor in writing. YZ performed the 3D-CTBA. LJ provided the language polishing. Conflict interest statement The author declares that they have no conflicts of interest in the research presented in this manuscript. Ethics statement The article was reviewed and approved by the by the research ethics committee of Huzhou Central Hospital, Affiliated Central Hospital of HuZhou University. Written informed consent was signed by all participants. Funding This work was supported by grants from the medical and health research project of Zhejiang province (2022RC261). 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Application of the IQQA-3D imaging interpretation and analysis system in uniportal video-assisted thoracoscopic anatomical segmentectomy: a series study. J Thorac Dis. 2019; 11(5): 2058-2066. Wu WB, Xu xf, Wen W, etal. Three-dimensional computed tomography bronchography and angiography in the preoperative evaluation of thoracoscopic segmentectomy and subsegmentectomy. J Thorac Dis . 2016; 8( 9): S710-S715. Zhang JB, Li HW, Yu CH, etal. Thoracoscopic Segmentectomy for Right Upper Lobe With Unique Anatomic Variation.Ann Thorac Surg. 2022;114: e201-e203. Zhang JB, Zhu YL, Li HW, etal. VATS right posterior segmentectomy with anomalous bronchi and pulmonary vessels: a case report and literature review. Journal of Cardiothoracic Surgery. 2021; 16:60. Feng RM, Zong YN, Cao SM, etal. Current cancer situation in China: good or bad news from the 2018 Global Cancer Statistics?. Cancer Commun (Lond) . 2019 ; 39(1): 22. Chen W , Zheng R , Baade P D,et al. Cancer statistics in China, 2015[J]. 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Segmentectomy versus lobectomy in small-sized peripheral non-small-cell lung cancer (JCOG0802/WJOG4607L): a multicentre, open-label, phase 3, randomised, controlled, non-inferiority trial[J]. The Lancet , 2022(10335): 399. Wang P, Wang S, Liu Z, et al. Segmentectomy and Wedge Resection for Elderly Patients with Stage I Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis[J]. Journal of clinical medicine . 2022;11(2): 294. Lin, Huang, Bin, et al. To Explore Clinical Value of Single-port Video-assisted Thoracoscopic Surgery ?in Elderly Patients with Non-small Cell Lung Cancer: Lobectomy, Segmentectomy ? and Lobectomy vs Segmentectomy[J]. Chinese Journal of Lung Cancer. 2018; 21(4):287-295. Subotich D, Mandarich D, Milisavljevich M, et al.Variations of pulmonary vessels: Some practical implications for lung resections[J]. Clinical Anatomy . 2019;22(6):698-705. Nagashima T, Shimizu K, Ohtaki Y, et al．Analysis of variation in bronchovascular pattern of the right middle and lower lobes of the lung using three-dimensional CT angiography and bronchography[J]. Gen Thorac Cardiovasc Surg . 2017; 65( 6) : 343-349． Yutaka Y, Sato T, Matsushita K, et al. Three-dimensional Navigation for Thoracoscopic Sublobar Resection Using a Novel Wireless Marking System. Semin Thorac Cardiovasc Surg . 2018;30(2):230-237. Hagiwara M, Shimada Y, Kato Y, et al. High-quality 3-dimensional image simulation for pulmonary lobectomy and segmentectomy: results of preoperative assessment of pulmonary vessels and short-term surgical outcomes in consecutive patients undergoing video-assisted thoracic surgery[J]. Eur J Cardiothorac Surg . 2014; 46(6): e120. Fourdrain A, De Dominicis F, Blanchard C, et al. Three-dimensional CT angiography of anatomic variations in the pulmonary arterial tree. Surg Radiol Anat . 2018 ;40(1):45-53. PEYMAN SARDARI NIA, JULES R. OLSTHOORN, SAMUEL HEUTS, et al. Interactive 3D Reconstruction of Pulmonary Anatomy for Preoperative Planning, Virtual Simulation, and Intraoperative Guiding in Video-Assisted Thoracoscopic Lung Surgery[J]. Innovations: technology and techniques in cardiothoracic and vascular surgery . 2019; 14(1):17-26. Hu W, Zhang K, Han X, et al. Three-dimensional computed tomography angiography and bronchography combined with three-dimensional printing for thoracoscopic pulmonary segmentectomy in stage IA non-small cell lung cancer. J Thorac Dis . 2021;13(2):1187-1195. Hironobu Wada, Takayoshi Yamamoto, Junichi Morimoto, etal. Pulmonary Segmentectomy After Endobronchial Indocyanine Green Injection[J]. Ann Thorac Surg . 2020;109(2):396-403. Kong XL, Lu J, Li PJ, etal. Technical aspects and early results of uniportal video-assisted thoracoscopic complex segmentectomy: a 30 case-series study. J Cardiothorac Surg . 2022;17(1):63. Bouabdallah I, Pauly V, Viprey M, etal. Unplanned readmission and survival after video-assisted thoracic surgery and open thoracotomy in patients with non-small-cell lung cancer: a 12-month nationwide cohort study. Eur J Cardiothorac Surg . 2021;59(5):987-995. Tables Table 1 Inclusion and exclusion criteria Inclusion criteria (I) Patients with early stage lung cancer who underwent anatomic segmentectomy. (II)Types of surgery including thoracoscopic anatomic segmentectomy and combined segmentectomy. Meanwhile, the mediastinal lymph node sampling was performed. (Ⅲ) All surgeries were performed by a single surgeon under two-portal thoracoscopic surgery. Exclusion criteria (I) Severe adhesions or calcification of lymph nodes in the chest. (II) Segmentectomy in different lobes at the same time. (III) Previous history of surgery for lung cancer. (IV)Incomplete data. Table 2 Logistic regression analysis of baseline data of 3D and HRCT groups Variable Coef td. err z P>z 95% CI Sex 1.333 0.777 1.72 0.086 -0.189 to 2.856 Age 0.009 0.021 0.45 0.655 -0.031 to 0.05 COPD 0.378 0.785 0.48 0.63 -1.16 to 1.916 Smoke -1.503 0.952 -1.58 0.114 -3.368 to 0.363 FEV1 0.194 0.678 0.29 0.775 -1.136 to 1.523 FEV1/FVC -0.015 0.02 -0.75 0.453 -0.053 to 0.024 Tumor size (cm) -0.681 0.645 -1.06 0.291 -1.946 to 0.584 operation type -0.506 0.364 -1.39 0.165 -1.22 to 0.208 _cons 1.042 2.61 0.4 0.69 -4.074 to 6.158 COPD, Chronic Obstructive Pulmonary Disease; FEV1, Forced Expiratory Volume in the first second; FVC, Forced Vital Capacity. Table 3 Comparative status of the baseline data of two groups (n=30) Variable 3D group HRCT group P Sex, male (%) 13(43.3) 11(36.7) 0.056 Age(years) 51.4±10.7 53.2±13.4 0.355 COPD (%) 20.0 16.7 0.632 Smoke (%) 23.3 26.7 0.074 FEV1(L) 2.27±0.69 2.13±1.26 0.375 FEV1/FVC(%) 93.5±11.8 96.2±14.2 0.553 Tumor size (cm) 1.05±0.37 0.97±0.45 0.081 Anatomic variations (%) 26.7 20.0 0.062 Operation type (%) general moderate complex 53.3 30.0 16.7 56.7 26.7 16.6 0.079 0.562 0.184 COPD, Chronic Obstructive Pulmonary Disease; FEV1, Forced Expiratory Volume in the first second; FVC, Forced Vital Capacity. Table 4 Surgical characteristics and postoperative recovery between two groups Variable 3D group HRCT group P operation time(min) 123.5±15.2 168.7±22.5 0.046 intraoperative blood loss(ml) 54.3±18.2 62.4±15.7 0.355 total chest drainage(ml) 223.9±105.3 245.2±97.6 0.632 postoperative hospital stay (d) 5.9±2.6 5.4±1.8 0.174 postoperative complications (%) Pulmonary infection Pulmonary leakage (>7 days) Postoperative hemothorax 3.3 6.7 0 6.7 6.7 3.3 0.035 0.762 0.082 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Jun, 2025 Read the published version in Journal of Cardiothoracic Surgery → Version 1 posted Editorial decision: Revision requested 30 Nov, 2024 Reviewers agreed at journal 23 Nov, 2024 Reviews received at journal 21 Nov, 2024 Reviewers agreed at journal 20 Nov, 2024 Reviewers invited by journal 18 Nov, 2024 Editor assigned by journal 30 Oct, 2024 Submission checks completed at journal 30 Oct, 2024 First submitted to journal 26 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5337984","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":372021392,"identity":"67206d6c-0cce-4d5d-9fc5-099dc235024a","order_by":0,"name":"Weiwei Min","email":"","orcid":"","institution":"Huzhou Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Min","suffix":""},{"id":372021395,"identity":"bb3b80fd-9791-4e7a-867f-3dabb3ea27de","order_by":1,"name":"jianbin zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIie3QsQrCMBCA4ZNCshzqmKLUJxAChbpI+yoGB1dHBy2WQvpG4hgp2MWHaJbOXd1MqXsyCuZfstxHuAPw+X4wWgKBHQASWhS6dyFYj2Q5xbqMmRNRhpi2ETvIOToRSrtW3y9IQi2BQRqtrzYS4IaLV4NkIWR7hH2cKAvJAiRMyOdAKs5AiZuNYEC7kYQPydCNQGLI2fw1cSY4EIUEhTkyd9gFZ00XvmWerapG6/6URlbyrf6+3G18KHcf9fl8vv/rA7+aOOyBmeHVAAAAAElFTkSuQmCC","orcid":"","institution":"Huzhou Central Hospital","correspondingAuthor":true,"prefix":"","firstName":"jianbin","middleName":"","lastName":"zhang","suffix":""},{"id":372021398,"identity":"9a9e27cb-32ea-475d-8189-22e4e2ee530c","order_by":2,"name":"Yilv Zhu","email":"","orcid":"","institution":"Huzhou Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yilv","middleName":"","lastName":"Zhu","suffix":""},{"id":372021400,"identity":"08eb96a1-1434-406a-b4b6-1eb2c53384fc","order_by":3,"name":"Lili Jin","email":"","orcid":"","institution":"Huzhou Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Jin","suffix":""}],"badges":[],"createdAt":"2024-10-26 14:38:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5337984/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5337984/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13019-025-03515-6","type":"published","date":"2025-06-24T15:57:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":69912214,"identity":"ac3a354c-4501-4d5a-aba4-fddbd6b72992","added_by":"auto","created_at":"2024-11-26 14:01:15","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":259578,"visible":true,"origin":"","legend":"\u003cp\u003eExampled for reconstructed images in 3DCT group. The 3D imagings of the lesion,\u003c/p\u003e\n\u003cp\u003epulmonary vein , artery and bronchi which were reconstructed via modified pulmonary artery CTA.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5337984/v1/9baff578c6d5dc69d1d32f5f.jpg"},{"id":69912215,"identity":"82566753-3a8f-4130-ae8b-0fb02d0103b3","added_by":"auto","created_at":"2024-11-26 14:01:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":450908,"visible":true,"origin":"","legend":"\u003cp\u003eExampled for anatomic variations discovered by 3D reconstruction. (A) Variation of pulmonary artery in the RUL: The A1, A2 and A3 shared a trunk. (B) Combined variation of bronchus and pulmonary vein in the RUL: (1)The B2a and B2b originated from the B1 and B3 respectively, (2)the V1a and V2a shared a trunk presenting the right upper hilum. (C) Uncommon multiple anatomic variations in the RUL: (1)The B2 originated from the B1 and B3 respectively, (2)The A3 shared a trunk with A2, (3)the central vein crossed between the bronchus of RUL and A1. RUL, right upper lobe; B, bronchus; A, artery; V, vein.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5337984/v1/c4ff351d69b1525756d9789c.png"},{"id":85686149,"identity":"ab4dc38e-3e23-40a2-a0f7-7b7f9c11cdcd","added_by":"auto","created_at":"2025-06-30 16:03:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1254306,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5337984/v1/bf4f1847-6915-4998-b986-11cc1632d239.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Application of 3-dimensional reconstruction via modified pulmonary artery computed tomography angiography in anatomic pulmonary segmentectomy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe prevalence of physical examination has led to a rise in the identification of early lung cancer(ELC), thereby advancing the development of pulmonary segmentectomy[1\u0026ndash;3]. It is crucial to grasp the anatomical structure before surgery due to the common anatomical variations. The utilization of 3D imaging softwares, such as Minics\u003csup\u003e[4]\u003c/sup\u003e, IQQA\u003csup\u003e[5]\u003c/sup\u003e, and DeepInsight\u003csup\u003e[6]\u003c/sup\u003e, have bean reported to provide precise anatomic details of pulmonary segments. However, surgeons may encounter challenges in effectively employing these softwares. Since 2020, we have conducted 3DCT of pulmonary segments via modified pulmonary artery CTA, which can also provide the 3D imaging of segmental structures with satisfactory outcome. Previously, we have reported two cases with unique anatomical variations detected by this technique\u003csup\u003e[7][8]\u003c/sup\u003e. This study aimed to summarize the application of this technique in thoracoscopic APS.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e93 patients who underwent\u0026nbsp;thoracoscopic\u0026nbsp;APS\u0026nbsp;for\u0026nbsp;ELC\u0026nbsp;were\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eenrolled from January 2021 to July 2023 in our department. The inclusion and exclusion\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003ecriteria are shown in \u003cem\u003eTable 1\u003c/em\u003e. The patients were categorized into 3D group (n=30) and HRCT group (n=63). Furthermore, they were divided into general subgroup (RS1, RS2, LS1+2, R/LS6, and LS4+S5), moderate subgroup (RS7, R/LS8, and R/LS3), and complex subgroup (R/LS9, R/LS10, R/LS9+10 and combined-subsegmental resection). The clinical data including age, sex, smoking history, forced expiratory volume (FEV1%), chronic obstructive pulmonary disease (COPD), tumor size, surgical type, operation time, intraoperative blood loss, postoperative recovery (total chest drainage, postoperative hospital stay, postoperative complications), and anatomic variations were compared between two groups. All patients underwent two-portal thoracoscopic surgery which were performed by a single surgeon.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3D reconstruction via modified pulmonary artery CTA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(1) Instrument: Toshiba aquillion one 320-row Dual-source CT, vitrea extend 6.7 graphic\u0026nbsp;analysis\u0026nbsp;system.\u003c/p\u003e\n\u003cp\u003e(2) Scanning scheme: The contrast agent was injected through the cubital vein mass with the rate 3.5-4.0ml/s, the scanning layer thickness was 1mm, the image matrix was 512*512, the trigger technology was adopted, the trigger point was set in the main pulmonary artery, the domain value was set to 110HU. Pulmonary artery and venous were scanned in two phases.\u003c/p\u003e\n\u003cp\u003e(3) Segmental reconstruct: The\u0026nbsp;maximum intensity projection\u0026nbsp;(MinIP) technique was performed to reconstruct the 3D images of segmental bronchi. The 3D images of pulmonary vessels were reconstructed via software post-processing, which could well display segmental and subsegmental vessel branches\u0026nbsp;(\u003cem\u003eFigure 1A-C\u003c/em\u003e).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurgical technique\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOperations were performed under general anesthesia with one-lung ventilation. The patient assumed a supine position. during the procedure, with the surgeon positioned ventrally and the assistant positioned dorsally. The observation port was created in the seventh intercostal space of the posterior axillary line, while the operation port was established in the fourth intercostal space of the anterior axillary line. The segmental structures were dissected separately based on the preoperative planning, and then, the lung was reventilated with pure oxygen via double-lung ventilation. Approximately 10 to 15 minutes after transiting to single-lung ventilation, the intersegmental plane was clear, and it was subsequently divided using endostaplers. The dissection of mediastinal lymph node (MLN) was performed established by the fast-frozen pathological analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using SPSS 23.0 (IBM Corp, Armonk, NY, USA). Mean \u0026plusmn; standard deviation (SD) was used to represent continuous distributed data, and the t-test was utilized to compare differences between two groups. Categorical variables were presented as absolute frequencies and proportions (%), and the\u0026nbsp;\u0026chi;\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003csup\u003e2\u003c/sup\u003e test was employed\u0026nbsp;to compare categorical variables. \u003cem\u003eP\u003c/em\u003e \u0026lt;0.05 was deemed statistically significant for all analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eGeneral characteristics\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study encompassed a total of 93 cases with 30 in 3D group and 63 in HRCT group.\u0026nbsp;60 cases were matched by PSM at ratio of 1:1 with 30 cases in each group. Logistic regression analysis was conducted on the baseline data of two groups(\u003cem\u003eTable 2\u003c/em\u003e)\u003cem\u003e.\u0026nbsp;\u003c/em\u003eThe summarized data included\u0026nbsp;sex, age, preoperative smoking, COPD,\u0026nbsp;pulmonary function,\u0026nbsp;maximum lesion diameter,\u0026nbsp;anatomic variations\u0026nbsp;and\u0026nbsp;surgical\u0026nbsp;types.\u0026nbsp;No statistically significant differences were observed between\u0026nbsp;two\u0026nbsp;groups\u0026nbsp;(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05 for all) ( \u003cem\u003eTable\u0026nbsp;\u003c/em\u003e\u003cem\u003e3\u003c/em\u003e).\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurgical outcomes\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo instances of death related to surgery were reported in either group during hospitalization.\u0026nbsp;There were no significant disparities between two groups in terms of\u0026nbsp;intraoperative blood loss and postoperative recovery including total chest drainage\u0026nbsp;and\u0026nbsp;length of postoperative hospital stay\u0026nbsp;(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05 for all). Although the 3D group exhibited a higher prevalence of anatomic variations compared to HRCT group (26.7% \u003cem\u003evs.\u003c/em\u003e 20%, \u003cem\u003eP\u003c/em\u003e\u0026gt;0.05), it\u0026nbsp;demonstrated shorter operation times and lower incidence of\u0026nbsp;pulmonary\u0026nbsp;infection(\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 for all)\u0026nbsp;(\u003cem\u003eTable 4\u003c/em\u003e). 8(26.7%) individuals in 3D group exhibited segmental variations. Among this subset of patients, 3 displayed a solitary\u0026nbsp;variation(\u003cem\u003eFigure 2A\u003c/em\u003e),\u0026nbsp;4\u0026nbsp;exhibited\u0026nbsp;combined\u0026nbsp;variations(\u003cem\u003eFigure 2B\u003c/em\u003e), and\u0026nbsp;1\u0026nbsp;presented\u0026nbsp;an\u0026nbsp;uncommon\u0026nbsp;multiple\u0026nbsp;anatomic variations(\u003cem\u003eFigure 2C\u003c/em\u003e). \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCurrently, lung cancer has the highest rates of morbidity and mortality of all malignant tumors worldwide\u003csup\u003e[9,10]\u003c/sup\u003e. Pulmonary lobectomy is the standard surgical procedure for early-stage lung cancer, which was supported in 1995 by the Lung Cancer Study Group's randomized trial\u003csup\u003e[11]\u003c/sup\u003e. Recently, with the increasing popularity of chest CT examinations, the detection rate of ELC has been rising. Studies have reconmend that pulmonary segmentectomy should be considered as a preferred treatment option for some ELC\u003csup\u003e[12\u0026ndash;14]\u003c/sup\u003e. Meanwhile, pulmonary segmentectomy has been demonstrated equally efficacious to lobectomy, with additional advantages such as minimal damage, expedited recovery, and lung function protection\u003csup\u003e[15\u0026ndash;17]\u003c/sup\u003e. However, the anatomic variation of pulmonary segments poses a main obstacle for surgeons in APS. Consequently, a precise understanding of the segmental structures is crucial for achieving successful APS \u003csup\u003e[18]\u003c/sup\u003e. The utilization of 3DCT-bronchography and angiography (3D-CTBA) has gradually gained traction since the 1990s\u003csup\u003e[19,20]\u003c/sup\u003e. In this technology, a transformation from 2D image into 3D model accurately depict the complex segmental structures. Studies have demonstrated that the preoperative 3D-CTBA to assess segmental bronchi and vascular patterns can improve the safety and efficacy of APS \u003csup\u003e[21,22]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere are many reconstructive softwares presenting the opportunity to obtain precise anatomic details of pulmonary segments. In this study, we performed 3D-CTBA via modified pulmonary artery CTA technique to reconstruct the segmental structures. The quality of reconstruction was comparable to that of other softwares. 8 cases with complex anatomic variations were detected by 3D reconstruction, including a rare case of multiple variations in the right upper lobe, which were consistent with what we detected intraoperatively. Compared to the HRCT group, the 3D group might have potential advantages in terms of shortening operation time and decreaing postoperative pulmonary infection, which was consistent with findings from previous studies\u003csup\u003e[22\u0026ndash;24]\u003c/sup\u003e. Furthermore, the preoperative 3D-CTBA via this technology offers several advantages for APS. Firstly, it enhances the visualization of nodules and lung structures, thereby enabling more efficient surgical procedures. Secondly, it facilitates the treatment of vessels and bronchus during surgery, resulting in safer and expedited operations. Lastly, it allows for preoperative simulated surgery, thereby minimizing the necessity for exploration of redundant lung tissue \u003csup\u003e[25\u0026ndash;27]\u003c/sup\u003e. There are several factors that should be taken into consideration in this context. Firstly, it is crucial to emphasize the necessity of close collaboration between thoracic surgeons and radiologists. Secondly, the correction of the intersection position of the pulmonary artery and vein might be a perplexing task. Thirdly, the accuracy of 3D-CTBA results can be influenced by the presence of underlying lung diseases, such as emphysema and pulmonary fibrosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors read and approved final manuscripts. JZ performed the surgery. WM was the major contributor in writing. YZ performed the\u0026nbsp;3D-CTBA. LJ\u0026nbsp;provided the language polishing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict interest statement\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe author declares that they have no conflicts of interest in the research presented in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003estatement\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe article was reviewed and approved by the by the research ethics committee of\u0026nbsp;Huzhou\u0026nbsp;Central\u0026nbsp;Hospital, Affiliated\u0026nbsp;Central\u0026nbsp;Hospital\u0026nbsp;of\u0026nbsp;HuZhou University. Written informed consent was signed by all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the medical and health research project of Zhejiang province (2022RC261).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSuzuki K, Watanabe SI, Wakabayashi M, etal. West Japan Oncology Group and Japan Clinical Oncology Group. A single-arm study of sublobar resection for ground-glass opacity dominant peripheral lung cancer. J \u003cem\u003eThorac Cardiovasc Surg\u003c/em\u003e. 2022;163(1):289-301\u003c/li\u003e\n\u003cli\u003eNational Comprehensive Cancer Network. Non-small cell lung cancer. Clinical practice guidelines in oncology. \u003cem\u003eJ Natl Compr Canc Netw\u003c/em\u003e. 2004 ; 2(2):94-123. \u003c/li\u003e\n\u003cli\u003eZHONG RB, WANG YY, HAN BH, etal. Chinese Medical Association guideline for clinical diagnosis and treatment of lung cancer (2022 edition): An interpretation. \u003cem\u003eChinese Journal of Clinical Thoracic and Cardiovascular Surgery\u003c/em\u003e. 2022;29(11): 1402-1406.\u003c/li\u003e\n\u003cli\u003eYou Y H , Zhao D , Huang Q B ,et al. Application of Mimics Medical 21.0 software in thoracoscopic anatomical sublobectomy[J]. \u003cem\u003eMinerva Surg\u003c/em\u003e. 2022; 77(3): 221-228.\u003c/li\u003e\n\u003cli\u003eXu GB, Chen C, Zheng W, etal. Application of the IQQA-3D imaging interpretation and analysis system in uniportal video-assisted thoracoscopic anatomical segmentectomy: a series study. \u003cem\u003eJ Thorac Dis. \u003c/em\u003e2019; 11(5): 2058-2066.\u003c/li\u003e\n\u003cli\u003eWu WB, Xu xf, Wen W, etal. Three-dimensional computed tomography bronchography and angiography in the preoperative evaluation of thoracoscopic segmentectomy and subsegmentectomy. \u003cem\u003eJ Thorac Dis\u003c/em\u003e. 2016; 8( 9): S710-S715.\u003c/li\u003e\n\u003cli\u003eZhang JB, Li HW, Yu CH, etal. Thoracoscopic Segmentectomy for Right Upper Lobe With Unique Anatomic Variation.Ann Thorac Surg. 2022;114: e201-e203.\u003c/li\u003e\n\u003cli\u003eZhang JB, Zhu YL, Li HW, etal. VATS right posterior segmentectomy with anomalous bronchi and pulmonary vessels: a case report and literature review. Journal of Cardiothoracic Surgery. 2021; 16:60.\u003c/li\u003e\n\u003cli\u003eFeng RM, Zong YN, Cao SM, etal. Current cancer situation in China: good or bad news from the 2018 Global Cancer Statistics?. \u003cem\u003eCancer Commun (Lond)\u003c/em\u003e. 2019 ; 39(1): 22. \u003c/li\u003e\n\u003cli\u003eChen W , Zheng R , Baade P D,et al. Cancer statistics in China, 2015[J]. \u003cem\u003eCA: A Cancer Journal for Clinicians\u003c/em\u003e. 2016; 66.\u003c/li\u003e\n\u003cli\u003eGinsberg RJ, Rubinstein LV. Randomized trial of lobectomy versus limited resection for T1 N0 non-small cell lung cancer. Lung Cancer Study Group. \u003cem\u003eAnn Thorac Surg\u003c/em\u003e. 1995;60(3):615-22; \u003c/li\u003e\n\u003cli\u003eParada SA, Eichinger JK, Dumont GD, et al. Paper #27 Accuracy and Reliability of a Simple Calculation for Measuring Glenoid Bone Loss on 3D Computer Tomography Scans[J]. \u003cem\u003eArthroscopy The Journal of Arthroscopic and Related Surgery\u003c/em\u003e. 2017; 34(4):e134.\u003c/li\u003e\n\u003cli\u003eEttinger DS, Wood DE, Aisner DL, et al. Non-small cell lung cancer, version 5 .2017, NCCN clinical practice guidelines in oncology[J]. \u003cem\u003eJ Natl Compr Canc Netw.\u003c/em\u003e 2017; 15(4): 504-535.\u003c/li\u003e\n\u003cli\u003eWu L , Zhao W , Chen T ,et al. Surgical choice for patients with stage I non-small-cell lung cancer \u0026le;2 cm: an analysis from surveillance, epidemiology, and end results database[J]. \u003cem\u003eJournal of Cardiothoracic Surgery.\u003c/em\u003e 2021;16(1):191.\u003c/li\u003e\n\u003cli\u003eSaji H, Okada M, Tsuboi M, et al. Segmentectomy versus lobectomy in small-sized peripheral non-small-cell lung cancer (JCOG0802/WJOG4607L): a multicentre, open-label, phase 3, randomised, controlled, non-inferiority trial[J]. \u003cem\u003eThe Lancet\u003c/em\u003e, 2022(10335): 399.\u003c/li\u003e\n\u003cli\u003eWang P, Wang S, Liu Z, et al. Segmentectomy and Wedge Resection for Elderly Patients with Stage I Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis[J]. \u003cem\u003eJournal of clinical medicine\u003c/em\u003e. 2022;11(2): 294.\u003c/li\u003e\n\u003cli\u003eLin, Huang, Bin, et al. To Explore Clinical Value of Single-port Video-assisted Thoracoscopic Surgery ?in Elderly Patients with Non-small Cell Lung Cancer: Lobectomy, Segmentectomy ? and Lobectomy vs Segmentectomy[J].\u003cem\u003e Chinese Journal of Lung Cancer.\u003c/em\u003e 2018; 21(4):287-295.\u003c/li\u003e\n\u003cli\u003eSubotich D, Mandarich D, Milisavljevich M, et al.Variations of pulmonary vessels: Some practical implications for lung resections[J]. \u003cem\u003eClinical Anatomy\u003c/em\u003e. 2019;22(6):698-705.\u003c/li\u003e\n\u003cli\u003eNagashima T, Shimizu K, Ohtaki Y, et al．Analysis of variation in bronchovascular pattern of the right middle and lower lobes of the lung using three-dimensional CT angiography and bronchography[J]. \u003cem\u003eGen Thorac Cardiovasc Surg\u003c/em\u003e. 2017; 65( 6) : 343-349．\u003c/li\u003e\n\u003cli\u003eYutaka Y, Sato T, Matsushita K, et al. Three-dimensional Navigation for Thoracoscopic Sublobar Resection Using a Novel Wireless Marking System. \u003cem\u003eSemin Thorac Cardiovasc Surg\u003c/em\u003e. 2018;30(2):230-237. \u003c/li\u003e\n\u003cli\u003eHagiwara M, Shimada Y, Kato Y, et al. High-quality 3-dimensional image simulation for pulmonary lobectomy and segmentectomy: results of preoperative assessment of pulmonary vessels and short-term surgical outcomes in consecutive patients undergoing video-assisted thoracic surgery[J]. \u003cem\u003eEur J Cardiothorac Surg\u003c/em\u003e. 2014; 46(6): e120.\u003c/li\u003e\n\u003cli\u003eFourdrain A, De Dominicis F, Blanchard C, et al. Three-dimensional CT angiography of anatomic variations in the pulmonary arterial tree. \u003cem\u003eSurg Radiol Anat\u003c/em\u003e. 2018 ;40(1):45-53. \u003c/li\u003e\n\u003cli\u003ePEYMAN SARDARI NIA, JULES R. OLSTHOORN, SAMUEL HEUTS, et al. Interactive 3D Reconstruction of Pulmonary Anatomy for Preoperative Planning, Virtual Simulation, and Intraoperative Guiding in Video-Assisted Thoracoscopic Lung Surgery[J]. \u003cem\u003eInnovations: technology and techniques in cardiothoracic and vascular surgery\u003c/em\u003e. 2019; 14(1):17-26. \u003c/li\u003e\n\u003cli\u003eHu W, Zhang K, Han X, et al. Three-dimensional computed tomography angiography and bronchography combined with three-dimensional printing for thoracoscopic pulmonary segmentectomy in stage IA non-small cell lung cancer. \u003cem\u003eJ Thorac Dis\u003c/em\u003e. 2021;13(2):1187-1195. \u003c/li\u003e\n\u003cli\u003eHironobu Wada, Takayoshi Yamamoto, Junichi Morimoto, etal. Pulmonary Segmentectomy After Endobronchial Indocyanine Green Injection[J]. \u003cem\u003eAnn Thorac Surg\u003c/em\u003e. 2020;109(2):396-403.\u003c/li\u003e\n\u003cli\u003eKong XL, Lu J, Li PJ, etal. Technical aspects and early results of uniportal video-assisted thoracoscopic complex segmentectomy: a 30 case-series study.\u003cem\u003e J Cardiothorac Surg\u003c/em\u003e. 2022;17(1):63.\u003c/li\u003e\n\u003cli\u003eBouabdallah I, Pauly V, Viprey M, etal. Unplanned readmission and survival after video-assisted thoracic surgery and open thoracotomy in patients with non-small-cell lung cancer: a 12-month nationwide cohort study. \u003cem\u003eEur J Cardiothorac Surg\u003c/em\u003e. 2021;59(5):987-995. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Inclusion and exclusion criteria\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003eInclusion criteria\u003c/p\u003e\n \u003cp\u003e(I) Patients with early stage lung cancer who underwent anatomic segmentectomy.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(II)Types of surgery including thoracoscopic anatomic segmentectomy and combined\u0026nbsp;\u003c/p\u003e\n \u003cp\u003esegmentectomy. Meanwhile, the mediastinal lymph node sampling was performed.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(Ⅲ) All surgeries were performed by a single surgeon\u0026nbsp;under two-portal thoracoscopic\u0026nbsp;surgery.\u003c/p\u003e\n \u003cp\u003eExclusion criteria\u003c/p\u003e\n \u003cp\u003e(I) Severe adhesions or calcification of lymph nodes in the chest.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(II) Segmentectomy in different lobes at the same time.\u003c/p\u003e\n \u003cp\u003e(III) Previous history of surgery for lung cancer.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(IV)Incomplete data.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Logistic regression analysis of baseline data of 3D and HRCT groups\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"551\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003eCoef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003etd. err\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003ez\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003eP\u0026gt;z\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e1.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-0.189 to 2.856\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-0.031 to 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-1.16 to 1.916\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eSmoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e-1.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e-1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-3.368 to 0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eFEV1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-1.136 to 1.523\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eFEV1/FVC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e-0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-0.053 to 0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eTumor size (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e-0.681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e-1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-1.946 to 0.584\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003eoperation type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e-0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-1.22 to 0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 22.1416%;\"\u003e\n \u003cp\u003e_cons\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.7042%;\"\u003e\n \u003cp\u003e1.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.882%;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5082%;\"\u003e\n \u003cp\u003e-4.074 to 6.158\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCOPD, \u003cem\u003eChronic Obstructive Pulmonary Disease;\u0026nbsp;\u003c/em\u003eFEV1, Forced Expiratory Volume in the first second; FVC, Forced Vital Capacity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Comparative status of the baseline data of two groups (n=30)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"553\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e3D group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003eHRCT group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eSex, male (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e13(43.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e11(36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e51.4\u0026plusmn;10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e53.2\u0026plusmn;13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eCOPD\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e16.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eSmoke\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eFEV1(L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e2.27\u0026plusmn;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e2.13\u0026plusmn;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eFEV1/FVC(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e93.5\u0026plusmn;11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e96.2\u0026plusmn;14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eTumor size (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e1.05\u0026plusmn;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.97\u0026plusmn;0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eAnatomic variations (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.7414%;\"\u003e\n \u003cp\u003eOperation type\u0026nbsp;(%)\u003c/p\u003e\n \u003cp\u003egeneral\u003c/p\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003cp\u003ecomplex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3273%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53.3\u003c/p\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003cp\u003e16.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56.7\u003c/p\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003cp\u003e16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9656%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003cp\u003e0.562\u003c/p\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCOPD, \u003cem\u003eChronic Obstructive Pulmonary Disease;\u0026nbsp;\u003c/em\u003eFEV1, Forced Expiratory Volume in the first second; FVC, Forced Vital Capacity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eSurgical\u0026nbsp;characteristics and postoperative recovery\u0026nbsp;between two groups\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"553\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5805%;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.0832%;\"\u003e\n \u003cp\u003e3D group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6257%;\"\u003e\n \u003cp\u003eHRCT group\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7107%;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5805%;\"\u003e\n \u003cp\u003eoperation time(min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.0832%;\"\u003e\n \u003cp\u003e123.5\u0026plusmn;15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6257%;\"\u003e\n \u003cp\u003e168.7\u0026plusmn;22.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7107%;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5805%;\"\u003e\n \u003cp\u003eintraoperative blood loss(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.0832%;\"\u003e\n \u003cp\u003e54.3\u0026plusmn;18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6257%;\"\u003e\n \u003cp\u003e62.4\u0026plusmn;15.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7107%;\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5805%;\"\u003e\n \u003cp\u003etotal chest drainage(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.0832%;\"\u003e\n \u003cp\u003e223.9\u0026plusmn;105.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6257%;\"\u003e\n \u003cp\u003e245.2\u0026plusmn;97.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7107%;\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 43.5805%;\"\u003e\n \u003cp\u003epostoperative hospital stay (d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.0832%;\"\u003e\n \u003cp\u003e5.9\u0026plusmn;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.6257%;\"\u003e\n \u003cp\u003e5.4\u0026plusmn;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.7107%;\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.5805%;\"\u003e\n \u003cp\u003epostoperative complications\u0026nbsp;(%)\u003c/p\u003e\n \u003cp\u003ePulmonary infection\u003c/p\u003e\n \u003cp\u003ePulmonary leakage (\u0026gt;7 days)\u003c/p\u003e\n \u003cp\u003ePostoperative hemothorax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0832%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.6257%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7107%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Three-dimensional (3D), Reconstruction, Thoracoscopic, Pulmonary segmentectomy","lastPublishedDoi":"10.21203/rs.3.rs-5337984/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5337984/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis retrospective study aimed to summarize the application of 3\u003cb\u003e-\u003c/b\u003edimensional(3D) reconstruction via modified pulmonary artery computed tomography angiography(CTA), as well as to compare the surgical outcomes of 3D versus high resolution CT(HRCT) in anatomic pulmonary segmentectomy(APS).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 93 patients who underwent thoracoscopic APS were enrolled in the study. They were divided into 3D group (n\u0026thinsp;=\u0026thinsp;30) and HRCT group (n\u0026thinsp;=\u0026thinsp;63), and than matched at 1:1 ratio using the propensity score matching (PSM) method. Clinical characteristics, surgical status, and postoperative recovery were compared between two groups, additionally, variations of segmental structures were summarized.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e60 cases were matched by PSM with 30 cases in each group. There were no significant differences between two groups in clinical characteristics, intraoperative blood loss and postoperative recovery (including total chest drainage, length of postoperative hospital stay)(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all). 8(26.7%) patients in 3D group manifesting unique variations of segmental structures underwent anatomical segmentectomy accurately. Despite the 3D group exhibited higher anatomic variations compared to the HRCT group, it demonstrated shorter operation times and lower incidence of pulmonary infection. (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePreoperative 3D reconstruction has advantages in APS, particularly for patients with complex anatomic variations. Reconstruction via modified pulmonary artery CTA is also feasible for preoperative planning and intraoperative navigation in thoracoscopic APS.\u003c/p\u003e","manuscriptTitle":"Application of 3-dimensional reconstruction via modified pulmonary artery computed tomography angiography in anatomic pulmonary segmentectomy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-26 14:01:11","doi":"10.21203/rs.3.rs-5337984/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-01T04:37:36+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"108465811214433805279109262073598411765","date":"2024-11-23T20:25:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-21T05:14:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74855152326707696171620246700865077586","date":"2024-11-21T00:20:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-18T12:33:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-30T04:22:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-30T04:19:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cardiothoracic Surgery","date":"2024-10-26T14:24:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ffe5315c-0209-4cdc-947f-618bab435eb8","owner":[],"postedDate":"November 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-30T15:59:30+00:00","versionOfRecord":{"articleIdentity":"rs-5337984","link":"https://doi.org/10.1186/s13019-025-03515-6","journal":{"identity":"journal-of-cardiothoracic-surgery","isVorOnly":false,"title":"Journal of Cardiothoracic Surgery"},"publishedOn":"2025-06-24 15:57:15","publishedOnDateReadable":"June 24th, 2025"},"versionCreatedAt":"2024-11-26 14:01:11","video":"","vorDoi":"10.1186/s13019-025-03515-6","vorDoiUrl":"https://doi.org/10.1186/s13019-025-03515-6","workflowStages":[]},"version":"v1","identity":"rs-5337984","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5337984","identity":"rs-5337984","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}