ReviewThoracic cancer2025
Advances in the Application of Three-Dimensional Reconstruction in Thoracic Surgery: A Comprehensive Review.
Review in Thoracic cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Three-Dimensional Bronchovascular Modelling in Sublobar Pulmonary Resection: A Tool for Personalised Thoracic Surgery.Journal of personalized medicine · 2026Review
- Comparative analysis of short-term outcomes, inflammatory markers, and complications in robotic-assistedJournal of thoracic disease · 2026Article
- Utilizing 3D Slicer for pulmonary bronchovascular anatomy reconstruction: a practical workflow and case examples.Journal of thoracic disease · 2026Article
- Artificial Intelligence in Adult Cardiovascular Medicine and Surgery: Real-World Deployments and Outcomes.Journal of personalized medicine · 2026Review
- 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
- Advances in the Application of Three-Dimensional Reconstruction in Thoracic Surgery: A Comprehensive Review.Thoracic cancer · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
This review presents a comprehensive overview of recent advancements and clinical applications of three-dimensional (3D) reconstruction technology in thoracic surgery, with a focus on lung cancer surgery. The widespread adoption of chest computed tomography (CT) screening has increased the detection rates of early-stage lung cancers, facilitating a transition from traditional lobectomy to parenchymal-sparing sublobar resections, such as segmentectomy, which demand higher anatomical precision. 3D reconstruction technology significantly improves tumor localization, as well as vascular and bronchial visualization, thereby enhancing surgical accuracy and safety. Its key applications encompass preoperative planning, intraoperative navigation, real-time localization, vascular and airway visualization, and postoperative pulmonary function assessment, collectively contributing to improved surgical outcomes and patient prognosis. Recent innovations in artificial intelligence have streamlined and automated the reconstruction process, leading to reduced operative times and increased accuracy. However, challenges persist, including image quality limitations, algorithm robustness, and limited high-quality clinical evidence. Future integration with emerging technologies such as virtual reality and augmented reality holds promise for achieving personalized, intelligent thoracic surgical procedures. This review aims to systematically evaluate the clinical value of 3D reconstruction technology and explore its future development directions.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.