ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2023
[Application Value of Artificial Intelligence-assisted Three-dimensional Reconstruction in Planning Thoracoscopic Segmentectomy].
Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 2 citations in OpenAlex.
- Comparative analysis of two-dimensional and three-dimensional machine learning models for predicting the degree of invasion in lung non-mucinous adenocarcinomas presenting as subsolid nodules.Frontiers in oncology · 2026Article
- Artificial intelligence-assisted surgical simulation system based on non-enhanced computed tomography images in thoracoscopic pulmonary segmentectomies.Journal of thoracic disease · 2025Article
- Research progress in medical imaging for intracranial aneurysms: technological advances in diagnosis, management, and clinical integration.Frontiers in neurology · 2025Review
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Authors and funding
9 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsA 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.
resultsAll 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).
conclusionsIt is accurate and safe to use artificial intelligence 3D reconstruction to assist planning thoracoscopic segmentectomy.
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