ArticleNature communications2025
Artificial intelligence driven 3D reconstruction for enhanced lung surgery planning.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Artificial Intelligence and the Ethical Foundations of Cardiothoracic Surgery: Evidence, Accountability, and the Limits of Delegated Judgment.Medical sciences (Basel, Switzerland) · 2026Review
- Decision-centered artificial intelligence for perioperative care outside the operating room: a practical review for surgeons.Journal of minimally invasive surgery · 2026Review
- From the Thoracoscope to the Robot: The Evolving Landscape of Minimally Invasive Pulmonary Surgery.Cancers · 2026Review
- ASO Authors Reflections: Artificial Intelligence-Driven Three-Dimensional Reconstruction System-From Plan to Procedure.Annals of surgical oncology · 2026Article
- Artificial Intelligence-Driven Three-Dimensional Reconstruction System Reduced Unexpected Procedural Changes in Thoracic Surgery.Annals of surgical oncology · 2026Article
- Three-Dimensional Bronchovascular Modelling in Sublobar Pulmonary Resection: A Tool for Personalised Thoracic Surgery.Journal of personalized medicine · 2026Review
- Artificial intelligence in thoracic surgery: a narrative review of clinical advances and applications in 2025.Journal of thoracic disease · 2026Review
- Artificial intelligence-based density proportion analysis in predicting the invasiveness of neoplastic ground-glass nodules.Translational lung cancer research · 2026Article
- The intersection of artificial intelligence and lung nodule research: current applications and future prospects.International journal of surgery (London, England) · 2026Article
- Impact of patient-specific three-dimensional reconstruction on surgical planning and perioperative outcomes in early-stage lung cancer: a randomised clinical trial.Frontiers in oncology · 2026Article
- Short-term quantitative CT changes in synchronous ground-glass nodules during immune checkpoint inhibitor therapy in patients with lung cancer.Frontiers in immunology · 2026Article
- Emerging technologies in thoracic surgery: artificial intelligence, robotic-assisted surgery, and telesurgery.Frontiers in surgery · 2026Review
- Optimizing Ridge Augmentation With AI-Generated Models: A Case Report With Technical Note.Clinical case reports · 2025Article
- Artificial Intelligence in Radiology: Advancing Precision, Accuracy, and Early Detection in Cancer Diagnosis.Cureus · 2025Review
- Efficiency of Artificial Intelligence in Three-Dimensional Reconstruction of Medical Imaging.Cureus · 2025Review
- Advances in the Application of Three-Dimensional Reconstruction in Thoracic Surgery: A Comprehensive Review.Thoracic cancer · 2025Review
- Review
- 3D Printing Today, AI Tomorrow: Rethinking Apert Syndrome Surgery in Low-Resource Settings.Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
35 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing complexity of lung surgeries necessitates the need for enhanced imaging support to improve the precision and efficiency of preoperative planning. Despite the promise of 3D reconstruction, clinical adoption remains limited due to time constraints and insufficient validation. To address this, we evaluate an artificial intelligence-driven 3D reconstruction system for pulmonary vessels and bronchi in a retrospective, multi-center multi-reader multi-case study. Using a two-stage crossover design, ten thoracic surgeons assess 140 cases with and without the system's assistance. The system significantly improves the accuracy of anatomical variant identification by 8% (p < 0.01), reducing errors by 41%. Improvements in secondary endpoints are also observed. Operation procedure selection accuracy is improved by 8%, with a 35% decrease in errors. Preoperative planning time is decreased by 25%, and user satisfaction is high at 99%. These benefits are consistent across surgeons of varying experience. In conclusion, the artificial intelligence-driven 3D reconstruction system significantly improves the identification of anatomical variants, addressing a critical need in preoperative planning for thoracic surgery.
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Registered trials
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