Recent advances in the application of three dimensional reconstruction techniques in surgical treatment of early lung cancer_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

LONG Tao ¹ , REN Zhengbing ¹ , SHAO Aizhong ¹ , HE Zhicheng ² ,  WU Weibing ²

1. Department of Cardiothoracic Surgery, Affiliated People’s Hospital of Jiangsu University, Zhenjiang, 212000, Jiangsu, P. R. China;
2. Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, P. R. China;

Corresponding author：

WU Weibing, Email: wuweibing95@163.com

Keywords：

Three-dimensional reconstruction; lung cancer; ground-glass opacity; video-assisted thoracic surgery; sublobar resection; artificial intelligence; review

DOI：

10.7507/1007-4848.202307015

Video：

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Lung cancer is the leading cause of death worldwide. With the prevalence of CT screening and early diagnosis and treatment of lung cancer in China, more and more patients with early-stage lung cancer characterized with ground-glass opacity are discovered and urgently require treatment, which poses a significant challenge to surgeons. As an emerging technology, three dimensional reconstruction technology plays a crucial auxiliary role in clinical work. This review aims to briefly introduce this technology, focusing on its latest advances in surgical applications in early lung cancer screening, malignant risk assessment, and perioperative period application and medical education.

Citation： LONG Tao, REN Zhengbing, SHAO Aizhong, HE Zhicheng, WU Weibing. Recent advances in the application of three dimensional reconstruction techniques in surgical treatment of early lung cancer. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2025, 32(1): 121-128. doi: 10.7507/1007-4848.202307015 Copy

1.	Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2021, 71(3): 209-249.
2.	中华医学会肿瘤学分会, 中华医学会杂志社. 中华医学会肺癌临床诊疗指南(2023版). 中华肿瘤杂志, 2023, 45(7): 539-574.Chinese Medical Association Oncology Branch, Chinese Medical Association Journal. Clinical diagnosis and treatment guidelines for lung cancer (2023 edition). Chin J Oncol, 2023, 45(7): 539-574.
3.	中华医学会呼吸病学分会. 早期肺癌诊断中国专家共识(2023年版). 中华结核和呼吸杂志, 2023, 46(1): 1-18.Chinese Medical Association Respiratory Disease Branch. Early lung cancer diagnosis chinese expert consensus (2023 edition). Chin J Tuberc Respir Dis, 2023, 46(1): 1-18.
4.	中国肺癌早诊早治专家组, 中国西部肺癌研究协作中心. 中国肺癌低剂量CT筛查指南(2023年版). 中国肺癌杂志, 2023, 26(1): 1-9.Expert Group for Early Diagnosis and Treatment of Lung Cancer in China, Western China Lung Cancer Research Collaborative Center. Guidelines for low-dose CT screening for lung cancer in China (2023 edition). Chin J Lung Cancer, 2023, 26(1): 1-9.
5.	Saji 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. Lancet, 2022, 399(10335): 1607-1617.
6.	Altorki N, Wang X, Kozono D, et al. Lobar or sublobar resection for peripheral stage ⅠA non-small-cell lung cancer. N Engl J Med, 2023, 388(6): 489-498.
7.	Aokage K, Suzuki K, Saji H, et al. Segmentectomy for ground-glass-dominant lung cancer with a tumour diameter of 3 cm or less including ground-glass opacity (JCOG1211): A multicentre, single-arm, confirmatory, phase 3 trial. Lancet Respir Med, 2023, 11(6): 540-549.
8.	Yotsukura M, Asamura H, Motoi N, et al. Long-term prognosis of patients with resected adenocarcinoma in situ and minimally invasive adenocarcinoma of the lung. J Thorac Oncol, 2021, 16(8): 1312-1320.
9.	Li D, Deng C, Wang S, et al. Ten-year follow-up of lung cancer patients with resected adenocarcinoma in situ or minimally invasive adenocarcinoma: Wedge resection is curative. J Thorac Cardiovasc Surg, 2022, 164(6): 1614-1622.
10.	Wu Z, Huang Z, Qin Y, et al. Progress in three-dimensional computed tomography reconstruction in anatomic pulmonary segmentectomy. Thorac Cancer, 2022, 13(13): 1881-1887.
11.	Radermacher K, Portheine F, Anton M, et al. Computer assisted orthopaedic surgery with image based individual templates. Clin Orthop Relat Res, 1998(354): 28-38.
12.	Levesque JN, Shah A, Ekhtiari S, et al. Three-dimensional printing in orthopaedic surgery: A scoping review. EFORT Open Rev, 2020, 5(7): 430-441.
13.	Skelley NW, Smith MJ, Ma R, et al. Three-dimensional printing technology in orthopaedics. J Am Acad Orthop Surg, 2019, 27(24): 918-925.
14.	Lopez-Lopez V, Gomez-Perez B, de Vicente E, et al. Next-generation three-dimensional modelling software for personalized surgery decision-making in perihilar cholangiocarcinoma: Multicentre study. Br J Surg, 2021, 108(12): e394-e395.
15.	Felli E, Boleslawski E, Sommacale D, et al. Paradigm shift: Should preoperative 3D reconstruction models become mandatory before hepatectomy for hepatocellular carcinoma (HCC)? Results of a multicenter prospective trial. HPB (Oxford), 2023, 25(3): 293-300.
16.	Liu Y, Meng S, Wei M, et al. Reconstruction of three-dimensional models for complex female pelvic tumors. Int J Gynaecol Obstet, 2022, 157(3): 747-749.
17.	Porpiglia F, Checcucci E, Amparore D, et al. Three-dimensional augmented reality robot-assisted partial nephrectomy in case of complex tumours (PADUA≥10): A new intraoperative tool overcoming the ultrasound guidance. Eur Urol, 2020, 78(2): 229-238.
18.	Porpiglia F, Checcucci E, Amparore D, et al. Three-dimensional elastic augmented-reality robot-assisted radical prostatectomy using hyperaccuracy three-dimensional reconstruction technology: A step further in the identification of capsular involvement. Eur Urol, 2019, 76(4): 505-514.
19.	Matsumoto T, Kanzaki M, Amiki M, et al. Comparison of three software programs for three-dimensional graphic imaging as contrasted with operative findings. Eur J Cardiothorac Surg, 2012, 41(5): 1098-1103.
20.	Li X, Zhang S, Luo X, et al. Accuracy and efficiency of an artificial intelligence-based pulmonary broncho-vascular three-dimensional reconstruction system supporting thoracic surgery: Retrospective and prospective validation study. EBioMedicine, 2023, 87: 104422.
21.	Ardila D, Kiraly AP, Bharadwaj S, et al. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med, 2019, 25(6): 954-961.
22.	Luo ZH, Brubaker MA, Brudno M. Size and texture-based classification of lung tumors with 3D CNNs. 2017 IEEE winter conference on applications of computer vision (WACV). IEEE, 2017: 806-814.
23.	Kalchiem-Dekel O, Connolly JG, Lin IH, et al. Shape-sensing robotic-assisted bronchoscopy in the diagnosis of pulmonary parenchymal lesions. Chest, 2022, 161(2): 572-582.
24.	Li C, Zheng B, Yu Q, et al. Augmented reality and 3-dimensional printing technologies for guiding complex thoracoscopic surgery. Ann Thorac Surg, 2021, 112(5): 1624-1631.
25.	Sadeghi AH, Maat APWM, Taverne YJHJ, et al. Virtual reality and artificial intelligence for 3-dimensional planning of lung segmentectomies. JTCVS Tech, 2021, 7: 309-321.
26.	Furumoto H, Shimada Y, Imai K, et al. Prognostic impact of the integration of volumetric quantification of the solid part of the tumor on 3DCT and FDG-PET imaging in clinical stage ⅠA adenocarcinoma of the lung. Lung Cancer, 2018, 121: 91-96.
27.	陈勇, 吴俊, 陆世春, 等. 18F-FDG PET/CT联合CT三维重建在肺结节良恶性鉴别中的应用. 中国胸心血管外科临床杂志, 2024, 31(3): 357-363.Chen Y, Wu J, Lu SC, et al. A retrospective cohort study on the differentiation of benign and malignant pulmonary nodules using 18F-FDG PET/CT combined with CT three-dimensional reconstruction. Chin J Clin Thorac Cardiovasc Surg, 2024, 31(3): 357-363.
28.	Kudo Y, Shimada Y, Matsubayashi J, et al. Artificial intelligence analysis of three-dimensional imaging data derives factors associated with postoperative recurrence in patients with radiologically solid-predominant small-sized lung cancers. Eur J Cardiothorac Surg, 2022, 61(4): 751-760.
29.	Kamiya S, Iwano S, Umakoshi H, et al. Computer-aided volumetry of part-solid lung cancers by using CT: Solid component size predicts prognosis. Radiology, 2018, 287(3): 1030-1040.
30.	Sun Y, Li C, Jin L, et al. Radiomics for lung adenocarcinoma manifesting as pure ground-glass nodules: Invasive prediction. Eur Radiol, 2020, 30(7): 3650-3659.
31.	Mehta AC, Hood KL, Schwarz Y, et al. The evolutional history of electromagnetic navigation bronchoscopy: State of the art. Chest, 2018, 154(4): 935-947.
32.	Folch EE, Pritchett MA, Nead MA, et al. Electromagnetic navigation bronchoscopy for peripheral pulmonary lesions: One-year results of the prospective, multicenter NAVIGATE study. J Thorac Oncol, 2019, 14(3): 445-458.
33.	Folch EE, Bowling MR, Pritchett MA, et al. NAVIGATE 24-month results: Electromagnetic navigation bronchoscopy for pulmonary lesions at 37 centers in Europe and the United States. J Thorac Oncol, 2022, 17(4): 519-531.
34.	Chen AC, Pastis NJ, Mahajan AK, et al. Robotic bronchoscopy for peripheral pulmonary lesions: A multicenter pilot and feasibility study (BENEFIT). Chest, 2021, 159(2): 845-852.
35.	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. Eur J Cardiothorac Surg, 2014, 46(6): e120-e126.
36.	Gossot D, Lutz JA, Grigoroiu M, et al. Unplanned procedures during thoracoscopic segmentectomies. Ann Thorac Surg, 2017, 104(5): 1710-1717.
37.	Chen-Yoshikawa TF, Date H. Update on three-dimensional image reconstruction for preoperative simulation in thoracic surgery. J Thorac Dis, 2016, 8(Suppl 3): S295-S301.
38.	姜宗来, 于伟勇, 张炎, 主编. 胸心外科临床解剖学. 济南: 山东科学技术出版社, 2010. 118-124.Jiang ZL, Yu WY, Zhang Y, chief editor. Clinical Anatomy of Thoracic Surgery. Jinan: Shandong Science and Technology Press, 2010. 118-124.
39.	Xu H, Zhao H, Jin J, et al. An atlas of anatomical variants of subsegmental pulmonary arteries and recognition error analysis. Front Oncol, 2023, 13: 1127138.
40.	陈亮, 主编. 全胸腔镜解剖性肺段切除手术图谱. 东南大学出版社东南大学电子音像出版社. 2015.Chen L, chief editor. Atlas of Totally Thoracoscopic Anatomical Lung Segment Resection. Southeast University Press, Southeast University Audio-Visual Publishing House. 2015.
41.	陈亮, 主编. 胸腔镜解剖性肺亚段切除手术图谱. 东南大学出版社. 2021.Chen L, chief editor. Atlas of Thoracoscopic Anatomical Pulmonary Sub-segmentectomy. Southeast University Press. 2021.
42.	张银萍, 吴菲, 余慧, 等. 肺内血管的影像解剖学在肺段切除术的临床应用. 解剖学报, 2022, 53(2): 217-224.Zhang YP, Wu F, Yu H, et al. The imaging anatomy of pulmonary vessels in the clinical application of pulmonary segmentectomy. Acta Anatomica Sinica, 2022, 53(2): 217-224.
43.	张振龙, 潘小杰, 欧德彬. 胸腔镜肺叶切除术中血管损伤出血的原因及处理. 中国微创外科杂志, 2019, 19(2): 111-114.Zhang ZL, Pan XJ, Ou DB. Causes and management of vascular injury and bleeding during thoracoscopic lobectomy. Chin J Min Inv Surg, 2019, 19(2): 111-114.
44.	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.
45.	He H, Chen P, Chen X, et al. Analysis of anatomical variations of the lingular artery of the left upper lobe using 3D computed tomography angiography and bronchography. J Thorac Dis, 2021, 13(8): 5035-5041.
46.	Lewis RJ, Caccavale RJ, Sisler GE, et al. Video-assisted thoracic surgical resection of malignant lung tumors. J Thorac Cardiovasc Surg, 1992, 104(6): 1679-1687.
47.	Oizumi H, Kanauchi N, Kato H, et al. Anatomic thoracoscopic pulmonary segmentectomy under 3-dimensional multidetector computed tomography simulation: A report of 52 consecutive cases. J Thorac Cardiovasc Surg, 2011, 141(3): 678-682.
48.	吴卫兵, 夏阳, 许晶, 等. 3D导航胸腔镜联合肺亚段切除术治疗肺段间结节的对比研究. 南京医科大学学报(自然科学版), 2018, 38(10): 1424-1427.Wu WB, Xia Y, Xu J, et al. Comparative study of 3D navigation thoracoscopic surgery combined with pulmonary subsegmentectomy for the treatment of intersegmental nodules. J Nanjing Med Univ (Natural Science Edition), 2018, 38(10): 1424-1427.
49.	李响, 朱燚宁, 吴卫兵, 等. 肺结节三维空间位置判定方法及临床意义. 中国胸心血管外科临床杂志, 2021, 28(3): 305-310.Li X, Zhu YN, Wu WB, et al. Method for determining the three-dimensional spatial position of pulmonary nodules and its clinical significance. Chin J Clin Thorac Cardiovasc Surg, 2021, 28(3): 305-310.
50.	胡硕, 王琦, 魏海星, 等. 三维导航免穿刺和穿刺定位行解剖性肺段切除术治疗肺结节的回顾性队列研究. 中国胸心血管外科临床杂志, 2021, 28(10): 1202-1206.Hu S, Wang Q, Wei HX, et al. A retrospective cohort study on three-dimensional navigation for non-invasive and invasive localization in anatomical segmentectomy for lung nodules. Chin J Clin Thorac Cardiovasc Surg, 2021, 28(10): 1202-1206.
51.	Chu XP, Chen ZH, Lin SM, et al. Watershed analysis of the target pulmonary artery for real-time localization of non-palpable pulmonary nodules. Transl Lung Cancer Res, 2021, 10(4): 1711-1719.
52.	陈星, 林铿强, 马晨晖, 等. 3D-CTBA联合3D打印技术在早期非小细胞肺癌胸腔镜解剖性肺段切除术中的应用研究. 微创医学, 2022, 17(1): 16-22.Chen X, Lin KQ, Ma CH, et al. Application of 3D-CTBA combined with 3D printing technology in early non-small cell lung cancer thoracoscopic anatomical lung segment resection. J Minim Invasive Med, 2022, 17(1): 16-22.
53.	张楼乾, 蒋峰, 李明, 等. 无创三维重建在肺部亚厘米结节定位中应用. 南京医科大学学报(自然科学版), 2019, 39(10): 1491-1493.Zhang LQ, Jiang F, Li M, et al. Application of non-invasive three-dimensional reconstruction in the localization of sub-centimeter pulmonary nodules. J Nanjing Med Univ (Natural Science Edition), 2019, 39(10): 1491-1493.
54.	赵肖, 卢恒孝, 张振江. CT三维重建联合术中肺自然萎陷定位在胸腔镜肺段切除术中的初步探讨. 中国肺癌杂志, 2021, 24(10): 683-689.Zhao X, Lu HX, Zhang ZJ. Preliminary exploration of CT three-dimensional reconstruction combined with intraoperative lung natural collapse localization in thoracoscopic lung segment resection. Chin J Lung Cancer, 2021, 24(10): 683-689.
55.	Kato H, Oizumi H, Suzuki J, et al. Thoracoscopic anatomical lung segmentectomy using 3D computed tomography simulation without tumour markings for non-palpable and non-visualized small lung nodules. Interact Cardiovasc Thorac Surg, 2017, 25(3): 434-441.
56.	Sawabata N, Ohta M, Matsumura A, et al. Optimal distance of malignant negative margin in excision of nonsmall cell lung cancer: A multicenter prospective study. Ann Thorac Surg, 2004, 77(2): 415-420.
57.	Schuchert MJ, Pettiford BL, Keeley S, et al. Anatomic segmentectomy in the treatment of stageⅠ non-small cell lung cancer. Ann Thorac Surg, 2007, 84(3): 926-932.
58.	Li Z, Xu W, Wang J, et al. Three-dimensional guided cone-shaped segmentectomy versus lobectomy for small-sized non-small cell lung cancer in the middle third of the lung field. Ann Surg Oncol, 2023, 30(11): 6684-6692.
59.	Akamine T, Yotsukura M, Yoshida Y, et al. Feasibility and effectiveness of segmentectomy versus wedge resection for clinical stage Ⅰnon-small-cell lung cancer. Eur J Cardiothorac Surg, 2023, 63(3): ezad018.
60.	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.
61.	卞承禹, 黄晶晶, 慕广, 等. 上肺特异侧枝静脉的三维影像研究及其临床意义. 中国胸心血管外科临床杂志, 2022, 29(7): 859-866.Bian CY, Huang JJ, Mu G, et al. Three-dimensional imaging study of specific collateral veins in the upper lung and its clinical significance. Chin J Clin Thorac Cardiovasc Surg, 2022, 29(7): 859-866.
62.	Handa Y, Tsutani Y, Mimae T, et al. Oncologic outcomes of complex segmentectomy: A multicenter propensity score-matched analysis. Ann Thorac Surg, 2021, 111(3): 1044-1051.
63.	陆佳昊, 谢骏, 唐佳, 等. 单孔胸腔镜复杂肺段切除术在直径≤2 cm磨玻璃结节中的应用. 中国微创外科杂志, 2023, 23(2): 103-107.Lu JH, Xie J, Tang J, et al. Application of single-port thoracoscopic complex pulmonary segmentectomy in ground-glass nodules with a diameter of ≤2 cm. Chin J Min Inv Surg, 2023, 23(2): 103-107.
64.	Wu WB, Xu XF, Wen W, et al. Thoracoscopic pulmonary sub-subsegmentectomy based on three-dimensional images. Ann Thorac Surg, 2016, 102(5): e389-e391.
65.	Kato H, Oizumi H, Suzuki J, et al. Roles and outcomes of thoracoscopic anatomic lung subsegmentectomy for lung cancer. Interact Cardiovasc Thorac Surg, 2022, 34(1): 81-90.
66.	Hong R, Chen C, Zheng W, et al. "Split" combined subsegmentectomy: A case series. Thorac Cancer, 2022, 13(3): 423-429.
67.	Takamori S, Oizumi H, Suzuki J, et al. Combined basilar subsegmentectomy for intralobar sequestration via uniportal VATS: A case report. Surg Case Rep, 2023, 9(1): 14.
68.	Bakhuis W, Sadeghi AH, Moes I, et al. Essential surgical plan modifications after virtual reality planning in 50 consecutive segmentectomies. Ann Thorac Surg, 2023, 115(5): 1247-1255.
69.	Zilverschoon M, Custers EJ, Ten Cate O, et al. Support for using a three-dimensional anatomy application over anatomical atlases in a randomized comparison. Anat Sci Educ, 2022, 15(1): 178-186.
70.	Sun Z. Clinical applications of patient-specific 3D printed models in cardiovascular disease: Current status and future directions. Biomolecules, 2020, 10(11): 1577.
71.	Miao H, Ding J, Gong X, et al. Application of 3D-printed pulmonary segment specimens in experimental teaching of sectional anatomy. BMC Surg, 2023, 23(1): 109.
72.	Tokuno J, Chen-Yoshikawa TF, Nakao M, et al. Creation of a video library for education and virtual simulation of anatomical lung resection. Interact Cardiovasc Thorac Surg, 2022, 34(5): 808-813.
73.	Nakazawa S, Hanawa R, Nagashima T, et al. Segmentectomy guided by 3-dimensional images reconstructed from nonenhanced computed tomographic data. Ann Thorac Surg, 2021, 111(4): e301-e304.
74.	Nakao M, Omura K, Hashimoto K, et al. Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data. Gen Thorac Cardiovasc Surg, 2022, 70(3): 312-314.
75.	Zhang W, Chen L, Wang J, et al. A study on the authenticity of preoperative pulmonary bronchial angiography by DeepInsight software. Zhongguo Fei Ai Za Zhi, 2021, 24(2): 88-93.
76.	Kadry S. Three-dimensional reconstruction system in pulmonary broncho vascular surgery using AI. EBioMedicine, 2023, 89: 104495.
77.	Chen X, Wang X, Zhang K, et al. Recent advances and clinical applications of deep learning in medical image analysis. Med Image Anal, 2022, 79: 102444.
78.	Egger J, Gsaxner C, Pepe A, et al. Medical deep learning—A systematic meta-review. Comput Methods Programs Biomed, 2022, 221: 106874.

1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2021, 71(3): 209-249.
2. 中华医学会肿瘤学分会, 中华医学会杂志社. 中华医学会肺癌临床诊疗指南(2023版). 中华肿瘤杂志, 2023, 45(7): 539-574.Chinese Medical Association Oncology Branch, Chinese Medical Association Journal. Clinical diagnosis and treatment guidelines for lung cancer (2023 edition). Chin J Oncol, 2023, 45(7): 539-574.
3. 中华医学会呼吸病学分会. 早期肺癌诊断中国专家共识(2023年版). 中华结核和呼吸杂志, 2023, 46(1): 1-18.Chinese Medical Association Respiratory Disease Branch. Early lung cancer diagnosis chinese expert consensus (2023 edition). Chin J Tuberc Respir Dis, 2023, 46(1): 1-18.
4. 中国肺癌早诊早治专家组, 中国西部肺癌研究协作中心. 中国肺癌低剂量CT筛查指南(2023年版). 中国肺癌杂志, 2023, 26(1): 1-9.Expert Group for Early Diagnosis and Treatment of Lung Cancer in China, Western China Lung Cancer Research Collaborative Center. Guidelines for low-dose CT screening for lung cancer in China (2023 edition). Chin J Lung Cancer, 2023, 26(1): 1-9.
5. Saji 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. Lancet, 2022, 399(10335): 1607-1617.
6. Altorki N, Wang X, Kozono D, et al. Lobar or sublobar resection for peripheral stage ⅠA non-small-cell lung cancer. N Engl J Med, 2023, 388(6): 489-498.
7. Aokage K, Suzuki K, Saji H, et al. Segmentectomy for ground-glass-dominant lung cancer with a tumour diameter of 3 cm or less including ground-glass opacity (JCOG1211): A multicentre, single-arm, confirmatory, phase 3 trial. Lancet Respir Med, 2023, 11(6): 540-549.
8. Yotsukura M, Asamura H, Motoi N, et al. Long-term prognosis of patients with resected adenocarcinoma in situ and minimally invasive adenocarcinoma of the lung. J Thorac Oncol, 2021, 16(8): 1312-1320.
9. Li D, Deng C, Wang S, et al. Ten-year follow-up of lung cancer patients with resected adenocarcinoma in situ or minimally invasive adenocarcinoma: Wedge resection is curative. J Thorac Cardiovasc Surg, 2022, 164(6): 1614-1622.
10. Wu Z, Huang Z, Qin Y, et al. Progress in three-dimensional computed tomography reconstruction in anatomic pulmonary segmentectomy. Thorac Cancer, 2022, 13(13): 1881-1887.
11. Radermacher K, Portheine F, Anton M, et al. Computer assisted orthopaedic surgery with image based individual templates. Clin Orthop Relat Res, 1998(354): 28-38.
12. Levesque JN, Shah A, Ekhtiari S, et al. Three-dimensional printing in orthopaedic surgery: A scoping review. EFORT Open Rev, 2020, 5(7): 430-441.
13. Skelley NW, Smith MJ, Ma R, et al. Three-dimensional printing technology in orthopaedics. J Am Acad Orthop Surg, 2019, 27(24): 918-925.
14. Lopez-Lopez V, Gomez-Perez B, de Vicente E, et al. Next-generation three-dimensional modelling software for personalized surgery decision-making in perihilar cholangiocarcinoma: Multicentre study. Br J Surg, 2021, 108(12): e394-e395.
15. Felli E, Boleslawski E, Sommacale D, et al. Paradigm shift: Should preoperative 3D reconstruction models become mandatory before hepatectomy for hepatocellular carcinoma (HCC)? Results of a multicenter prospective trial. HPB (Oxford), 2023, 25(3): 293-300.
16. Liu Y, Meng S, Wei M, et al. Reconstruction of three-dimensional models for complex female pelvic tumors. Int J Gynaecol Obstet, 2022, 157(3): 747-749.
17. Porpiglia F, Checcucci E, Amparore D, et al. Three-dimensional augmented reality robot-assisted partial nephrectomy in case of complex tumours (PADUA≥10): A new intraoperative tool overcoming the ultrasound guidance. Eur Urol, 2020, 78(2): 229-238.
18. Porpiglia F, Checcucci E, Amparore D, et al. Three-dimensional elastic augmented-reality robot-assisted radical prostatectomy using hyperaccuracy three-dimensional reconstruction technology: A step further in the identification of capsular involvement. Eur Urol, 2019, 76(4): 505-514.
19. Matsumoto T, Kanzaki M, Amiki M, et al. Comparison of three software programs for three-dimensional graphic imaging as contrasted with operative findings. Eur J Cardiothorac Surg, 2012, 41(5): 1098-1103.
20. Li X, Zhang S, Luo X, et al. Accuracy and efficiency of an artificial intelligence-based pulmonary broncho-vascular three-dimensional reconstruction system supporting thoracic surgery: Retrospective and prospective validation study. EBioMedicine, 2023, 87: 104422.
21. Ardila D, Kiraly AP, Bharadwaj S, et al. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med, 2019, 25(6): 954-961.
22. Luo ZH, Brubaker MA, Brudno M. Size and texture-based classification of lung tumors with 3D CNNs. 2017 IEEE winter conference on applications of computer vision (WACV). IEEE, 2017: 806-814.
23. Kalchiem-Dekel O, Connolly JG, Lin IH, et al. Shape-sensing robotic-assisted bronchoscopy in the diagnosis of pulmonary parenchymal lesions. Chest, 2022, 161(2): 572-582.
24. Li C, Zheng B, Yu Q, et al. Augmented reality and 3-dimensional printing technologies for guiding complex thoracoscopic surgery. Ann Thorac Surg, 2021, 112(5): 1624-1631.
25. Sadeghi AH, Maat APWM, Taverne YJHJ, et al. Virtual reality and artificial intelligence for 3-dimensional planning of lung segmentectomies. JTCVS Tech, 2021, 7: 309-321.
26. Furumoto H, Shimada Y, Imai K, et al. Prognostic impact of the integration of volumetric quantification of the solid part of the tumor on 3DCT and FDG-PET imaging in clinical stage ⅠA adenocarcinoma of the lung. Lung Cancer, 2018, 121: 91-96.
27. 陈勇, 吴俊, 陆世春, 等. 18F-FDG PET/CT联合CT三维重建在肺结节良恶性鉴别中的应用. 中国胸心血管外科临床杂志, 2024, 31(3): 357-363.Chen Y, Wu J, Lu SC, et al. A retrospective cohort study on the differentiation of benign and malignant pulmonary nodules using 18F-FDG PET/CT combined with CT three-dimensional reconstruction. Chin J Clin Thorac Cardiovasc Surg, 2024, 31(3): 357-363.
28. Kudo Y, Shimada Y, Matsubayashi J, et al. Artificial intelligence analysis of three-dimensional imaging data derives factors associated with postoperative recurrence in patients with radiologically solid-predominant small-sized lung cancers. Eur J Cardiothorac Surg, 2022, 61(4): 751-760.
29. Kamiya S, Iwano S, Umakoshi H, et al. Computer-aided volumetry of part-solid lung cancers by using CT: Solid component size predicts prognosis. Radiology, 2018, 287(3): 1030-1040.
30. Sun Y, Li C, Jin L, et al. Radiomics for lung adenocarcinoma manifesting as pure ground-glass nodules: Invasive prediction. Eur Radiol, 2020, 30(7): 3650-3659.
31. Mehta AC, Hood KL, Schwarz Y, et al. The evolutional history of electromagnetic navigation bronchoscopy: State of the art. Chest, 2018, 154(4): 935-947.
32. Folch EE, Pritchett MA, Nead MA, et al. Electromagnetic navigation bronchoscopy for peripheral pulmonary lesions: One-year results of the prospective, multicenter NAVIGATE study. J Thorac Oncol, 2019, 14(3): 445-458.
33. Folch EE, Bowling MR, Pritchett MA, et al. NAVIGATE 24-month results: Electromagnetic navigation bronchoscopy for pulmonary lesions at 37 centers in Europe and the United States. J Thorac Oncol, 2022, 17(4): 519-531.
34. Chen AC, Pastis NJ, Mahajan AK, et al. Robotic bronchoscopy for peripheral pulmonary lesions: A multicenter pilot and feasibility study (BENEFIT). Chest, 2021, 159(2): 845-852.
35. 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. Eur J Cardiothorac Surg, 2014, 46(6): e120-e126.
36. Gossot D, Lutz JA, Grigoroiu M, et al. Unplanned procedures during thoracoscopic segmentectomies. Ann Thorac Surg, 2017, 104(5): 1710-1717.
37. Chen-Yoshikawa TF, Date H. Update on three-dimensional image reconstruction for preoperative simulation in thoracic surgery. J Thorac Dis, 2016, 8(Suppl 3): S295-S301.
38. 姜宗来, 于伟勇, 张炎, 主编. 胸心外科临床解剖学. 济南: 山东科学技术出版社, 2010. 118-124.Jiang ZL, Yu WY, Zhang Y, chief editor. Clinical Anatomy of Thoracic Surgery. Jinan: Shandong Science and Technology Press, 2010. 118-124.
39. Xu H, Zhao H, Jin J, et al. An atlas of anatomical variants of subsegmental pulmonary arteries and recognition error analysis. Front Oncol, 2023, 13: 1127138.
40. 陈亮, 主编. 全胸腔镜解剖性肺段切除手术图谱. 东南大学出版社东南大学电子音像出版社. 2015.Chen L, chief editor. Atlas of Totally Thoracoscopic Anatomical Lung Segment Resection. Southeast University Press, Southeast University Audio-Visual Publishing House. 2015.
41. 陈亮, 主编. 胸腔镜解剖性肺亚段切除手术图谱. 东南大学出版社. 2021.Chen L, chief editor. Atlas of Thoracoscopic Anatomical Pulmonary Sub-segmentectomy. Southeast University Press. 2021.
42. 张银萍, 吴菲, 余慧, 等. 肺内血管的影像解剖学在肺段切除术的临床应用. 解剖学报, 2022, 53(2): 217-224.Zhang YP, Wu F, Yu H, et al. The imaging anatomy of pulmonary vessels in the clinical application of pulmonary segmentectomy. Acta Anatomica Sinica, 2022, 53(2): 217-224.
43. 张振龙, 潘小杰, 欧德彬. 胸腔镜肺叶切除术中血管损伤出血的原因及处理. 中国微创外科杂志, 2019, 19(2): 111-114.Zhang ZL, Pan XJ, Ou DB. Causes and management of vascular injury and bleeding during thoracoscopic lobectomy. Chin J Min Inv Surg, 2019, 19(2): 111-114.
44. 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.
45. He H, Chen P, Chen X, et al. Analysis of anatomical variations of the lingular artery of the left upper lobe using 3D computed tomography angiography and bronchography. J Thorac Dis, 2021, 13(8): 5035-5041.
46. Lewis RJ, Caccavale RJ, Sisler GE, et al. Video-assisted thoracic surgical resection of malignant lung tumors. J Thorac Cardiovasc Surg, 1992, 104(6): 1679-1687.
47. Oizumi H, Kanauchi N, Kato H, et al. Anatomic thoracoscopic pulmonary segmentectomy under 3-dimensional multidetector computed tomography simulation: A report of 52 consecutive cases. J Thorac Cardiovasc Surg, 2011, 141(3): 678-682.
48. 吴卫兵, 夏阳, 许晶, 等. 3D导航胸腔镜联合肺亚段切除术治疗肺段间结节的对比研究. 南京医科大学学报(自然科学版), 2018, 38(10): 1424-1427.Wu WB, Xia Y, Xu J, et al. Comparative study of 3D navigation thoracoscopic surgery combined with pulmonary subsegmentectomy for the treatment of intersegmental nodules. J Nanjing Med Univ (Natural Science Edition), 2018, 38(10): 1424-1427.
49. 李响, 朱燚宁, 吴卫兵, 等. 肺结节三维空间位置判定方法及临床意义. 中国胸心血管外科临床杂志, 2021, 28(3): 305-310.Li X, Zhu YN, Wu WB, et al. Method for determining the three-dimensional spatial position of pulmonary nodules and its clinical significance. Chin J Clin Thorac Cardiovasc Surg, 2021, 28(3): 305-310.
50. 胡硕, 王琦, 魏海星, 等. 三维导航免穿刺和穿刺定位行解剖性肺段切除术治疗肺结节的回顾性队列研究. 中国胸心血管外科临床杂志, 2021, 28(10): 1202-1206.Hu S, Wang Q, Wei HX, et al. A retrospective cohort study on three-dimensional navigation for non-invasive and invasive localization in anatomical segmentectomy for lung nodules. Chin J Clin Thorac Cardiovasc Surg, 2021, 28(10): 1202-1206.
51. Chu XP, Chen ZH, Lin SM, et al. Watershed analysis of the target pulmonary artery for real-time localization of non-palpable pulmonary nodules. Transl Lung Cancer Res, 2021, 10(4): 1711-1719.
52. 陈星, 林铿强, 马晨晖, 等. 3D-CTBA联合3D打印技术在早期非小细胞肺癌胸腔镜解剖性肺段切除术中的应用研究. 微创医学, 2022, 17(1): 16-22.Chen X, Lin KQ, Ma CH, et al. Application of 3D-CTBA combined with 3D printing technology in early non-small cell lung cancer thoracoscopic anatomical lung segment resection. J Minim Invasive Med, 2022, 17(1): 16-22.
53. 张楼乾, 蒋峰, 李明, 等. 无创三维重建在肺部亚厘米结节定位中应用. 南京医科大学学报(自然科学版), 2019, 39(10): 1491-1493.Zhang LQ, Jiang F, Li M, et al. Application of non-invasive three-dimensional reconstruction in the localization of sub-centimeter pulmonary nodules. J Nanjing Med Univ (Natural Science Edition), 2019, 39(10): 1491-1493.
54. 赵肖, 卢恒孝, 张振江. CT三维重建联合术中肺自然萎陷定位在胸腔镜肺段切除术中的初步探讨. 中国肺癌杂志, 2021, 24(10): 683-689.Zhao X, Lu HX, Zhang ZJ. Preliminary exploration of CT three-dimensional reconstruction combined with intraoperative lung natural collapse localization in thoracoscopic lung segment resection. Chin J Lung Cancer, 2021, 24(10): 683-689.
55. Kato H, Oizumi H, Suzuki J, et al. Thoracoscopic anatomical lung segmentectomy using 3D computed tomography simulation without tumour markings for non-palpable and non-visualized small lung nodules. Interact Cardiovasc Thorac Surg, 2017, 25(3): 434-441.
56. Sawabata N, Ohta M, Matsumura A, et al. Optimal distance of malignant negative margin in excision of nonsmall cell lung cancer: A multicenter prospective study. Ann Thorac Surg, 2004, 77(2): 415-420.
57. Schuchert MJ, Pettiford BL, Keeley S, et al. Anatomic segmentectomy in the treatment of stageⅠ non-small cell lung cancer. Ann Thorac Surg, 2007, 84(3): 926-932.
58. Li Z, Xu W, Wang J, et al. Three-dimensional guided cone-shaped segmentectomy versus lobectomy for small-sized non-small cell lung cancer in the middle third of the lung field. Ann Surg Oncol, 2023, 30(11): 6684-6692.
59. Akamine T, Yotsukura M, Yoshida Y, et al. Feasibility and effectiveness of segmentectomy versus wedge resection for clinical stage Ⅰnon-small-cell lung cancer. Eur J Cardiothorac Surg, 2023, 63(3): ezad018.
60. 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.
61. 卞承禹, 黄晶晶, 慕广, 等. 上肺特异侧枝静脉的三维影像研究及其临床意义. 中国胸心血管外科临床杂志, 2022, 29(7): 859-866.Bian CY, Huang JJ, Mu G, et al. Three-dimensional imaging study of specific collateral veins in the upper lung and its clinical significance. Chin J Clin Thorac Cardiovasc Surg, 2022, 29(7): 859-866.
62. Handa Y, Tsutani Y, Mimae T, et al. Oncologic outcomes of complex segmentectomy: A multicenter propensity score-matched analysis. Ann Thorac Surg, 2021, 111(3): 1044-1051.
63. 陆佳昊, 谢骏, 唐佳, 等. 单孔胸腔镜复杂肺段切除术在直径≤2 cm磨玻璃结节中的应用. 中国微创外科杂志, 2023, 23(2): 103-107.Lu JH, Xie J, Tang J, et al. Application of single-port thoracoscopic complex pulmonary segmentectomy in ground-glass nodules with a diameter of ≤2 cm. Chin J Min Inv Surg, 2023, 23(2): 103-107.
64. Wu WB, Xu XF, Wen W, et al. Thoracoscopic pulmonary sub-subsegmentectomy based on three-dimensional images. Ann Thorac Surg, 2016, 102(5): e389-e391.
65. Kato H, Oizumi H, Suzuki J, et al. Roles and outcomes of thoracoscopic anatomic lung subsegmentectomy for lung cancer. Interact Cardiovasc Thorac Surg, 2022, 34(1): 81-90.
66. Hong R, Chen C, Zheng W, et al. "Split" combined subsegmentectomy: A case series. Thorac Cancer, 2022, 13(3): 423-429.
67. Takamori S, Oizumi H, Suzuki J, et al. Combined basilar subsegmentectomy for intralobar sequestration via uniportal VATS: A case report. Surg Case Rep, 2023, 9(1): 14.
68. Bakhuis W, Sadeghi AH, Moes I, et al. Essential surgical plan modifications after virtual reality planning in 50 consecutive segmentectomies. Ann Thorac Surg, 2023, 115(5): 1247-1255.
69. Zilverschoon M, Custers EJ, Ten Cate O, et al. Support for using a three-dimensional anatomy application over anatomical atlases in a randomized comparison. Anat Sci Educ, 2022, 15(1): 178-186.
70. Sun Z. Clinical applications of patient-specific 3D printed models in cardiovascular disease: Current status and future directions. Biomolecules, 2020, 10(11): 1577.
71. Miao H, Ding J, Gong X, et al. Application of 3D-printed pulmonary segment specimens in experimental teaching of sectional anatomy. BMC Surg, 2023, 23(1): 109.
72. Tokuno J, Chen-Yoshikawa TF, Nakao M, et al. Creation of a video library for education and virtual simulation of anatomical lung resection. Interact Cardiovasc Thorac Surg, 2022, 34(5): 808-813.
73. Nakazawa S, Hanawa R, Nagashima T, et al. Segmentectomy guided by 3-dimensional images reconstructed from nonenhanced computed tomographic data. Ann Thorac Surg, 2021, 111(4): e301-e304.
74. Nakao M, Omura K, Hashimoto K, et al. Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data. Gen Thorac Cardiovasc Surg, 2022, 70(3): 312-314.
75. Zhang W, Chen L, Wang J, et al. A study on the authenticity of preoperative pulmonary bronchial angiography by DeepInsight software. Zhongguo Fei Ai Za Zhi, 2021, 24(2): 88-93.
76. Kadry S. Three-dimensional reconstruction system in pulmonary broncho vascular surgery using AI. EBioMedicine, 2023, 89: 104495.
77. Chen X, Wang X, Zhang K, et al. Recent advances and clinical applications of deep learning in medical image analysis. Med Image Anal, 2022, 79: 102444.
78. Egger J, Gsaxner C, Pepe A, et al. Medical deep learning—A systematic meta-review. Comput Methods Programs Biomed, 2022, 221: 106874.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Recent advances in the application of three dimensional reconstruction techniques in surgical treatment of early lung cancer

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