Zheng Zhizhong, Ren Meiyu, Li Bin, Yang Jianbao, Wei Xiaoping, Song Tieniu, Meng Yuqi, Chen Yuzhen, Liu Qing
Department of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, Lanzhou 730030, China.
Zhongguo Fei Ai Za Zhi. 2023 Jul 20;26(7):515-522. doi: 10.3779/j.issn.1009-3419.2023.102.28.
The three-dimensional (3D) can assist in planning lung segmentectomy. 3D reconstruction software based on artificial intelligence algorithm is gradually applied in clinic. The aim of this study was to evaluate the accuracy and safety of 3D reconstruction assisted planning of thoracoscopic segmentectomy.
A total of 90 patients admitted to Department of Thoracic Surgery of Lanzhou University Second Hospital were evaluated for thoracoscopic segmentectomy. Before operation, artificial intelligence 3D reconstruction software was used to make 3D lung images and conduct preoperative planning. Surgical videos were saved during the operation and perioperative data were recorded. Video recordings of 38 patients were selected to explore the effectiveness of artificial intelligence 3D reconstruction for surgical planning. The results of artificial intelligence 3D reconstruction and Mimics 21 software reconstruction were compared with the actual results in the operation, and the detection and classification ability of bronchus and blood vessels of the two reconstruction methods were compared.
All the 90 patients underwent artificial intelligence 3D reconstruction planning, including 57 patients (63.3%) with single lung segmentectomy and 33 patients (36.7%) with combined sub-segmentectomy. The accuracy of artificial intelligence 3D reconstruction for lesion localization was 100.0%, and the accuracy of computed tomography (CT) was 94.4% (85/90). The detection accuracy of artificial intelligence 3D reconstruction and Mimics 21 software was 92.1% (35/38) and 89.5% (34/38), and the anatomic typing accuracy was 89.5% (34/38) and 84.2% (32/38), and the total accuracy was 76.3% (29/38) and 71.1% (27/38). In the comparative observation of 38 surgical videos and reconstructed images, the consistent rates of target segment planning, surgical approach, artery dissection, vein dissection and bronchial dissection for preoperative planning using artificial intelligence 3D reconstruction were 92.1% (35/38), 92.1% (35/38), 89.5% (34/38), 86.8% (33/38) and 94.7% (36/38). The overall planning operational consistency rate was 68.4% (26/38).
It is accurate and safe to use artificial intelligence 3D reconstruction to assist planning thoracoscopic segmentectomy.
三维（3D）技术有助于肺段切除术的规划。基于人工智能算法的3D重建软件正逐渐应用于临床。本研究旨在评估3D重建辅助胸腔镜肺段切除术规划的准确性和安全性。
对兰州大学第二医院胸外科收治的90例患者进行胸腔镜肺段切除术评估。术前，使用人工智能3D重建软件制作3D肺图像并进行术前规划。术中保存手术视频并记录围手术期数据。选取38例患者的视频记录，探讨人工智能3D重建用于手术规划的有效性。将人工智能3D重建和Mimics 21软件重建的结果与手术中的实际结果进行比较，并比较两种重建方法对支气管和血管的检测及分类能力。
90例患者均接受了人工智能3D重建规划，其中单肺段切除术57例（63.3%），联合亚段切除术33例（36.7%）。人工智能3D重建对病变定位的准确率为100.0%，计算机断层扫描（CT）的准确率为94.4%（85/90）。人工智能3D重建和Mimics 21软件的检测准确率分别为92.1%（35/38）和89.5%（34/38），解剖分型准确率分别为89.5%（34/38）和84.2%（32/38），总准确率分别为76.3%（29/38）和71.1%（27/38）。在38个手术视频与重建图像的对比观察中，使用人工智能3D重建进行术前规划的目标段规划、手术入路、动脉解剖、静脉解剖和支气管解剖的符合率分别为92.1%（35/38）、92.1%（35/38）、89.5%（34/38）、86.8%（33/38）和94.7%（36/38）。总体规划操作符合率为68.4%（26/38）。
使用人工智能3D重建辅助胸腔镜肺段切除术规划准确且安全。
