دورية أكاديمية

Application Value of Artificial Intelligence-assisted Three-dimensional Reconstruction in Planning Thoracoscopic Segmentectomy

التفاصيل البيبلوغرافية
العنوان: Application Value of Artificial Intelligence-assisted Three-dimensional Reconstruction in Planning Thoracoscopic Segmentectomy
المؤلفون: Zhizhong ZHENG, Meiyu REN, Bin LI, Jianbao YANG, Xiaoping WEI, Tieniu SONG, Yuqi MENG, Yuzhen CHEN, Qing LIU
المصدر: Chinese Journal of Lung Cancer, Vol 26, Iss 7, Pp 515-522 (2023)
بيانات النشر: Chinese Anti-Cancer Association; Chinese Antituberculosis Association, 2023.
سنة النشر: 2023
المجموعة: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
مصطلحات موضوعية: artificial intelligence, three-dimensional reconstruction, ground-glass nodule, segmentectomy, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
الوصف: Background and objective 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. Methods 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. Results 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). Conclusion It is accurate and safe to use artificial intelligence 3D reconstruction to assist planning thoracoscopic segmentectomy.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: Chinese
تدمد: 1009-3419
1999-6187
Relation: https://doaj.org/toc/1009-3419; https://doaj.org/toc/1999-6187
DOI: 10.3779/j.issn.1009-3419.2023.102.28
URL الوصول: https://doaj.org/article/ab9a538fe1c5421396e3b08c151f9bcd
رقم الأكسشن: edsdoj.b9a538fe1c5421396e3b08c151f9bcd
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:10093419
19996187
DOI:10.3779/j.issn.1009-3419.2023.102.28