Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Molecular residual disease-based novel modality of postoperative management for non-small-cell lung cancer (REMODEL): Protocol for a prospective multicenter study.

Journal of translational internal medicine·2026
Same author

Locus-Specific Human Endogenous Retrovirus ERVK18 Expression Indicates an Inflamed Microenvironment and Favorable Immunotherapy Outcome in Small Cell Lung Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research·2026
Same author

The Evolution of Spatial Omics Technologies Introduces A Novel Avenue for Lung Cancer Research.

Genomics, proteomics & bioinformatics·2026
Same author

Dual-modality theranostics probes: sintegrative strategies for precision management of oncologic malignancies.

Life medicine·2026
Same author

Protocol for Chinese lung cancer evolution and microenvironment tracking under therapy study.

Journal of translational internal medicine·2025
Same author

Mediating role of basophils in the triacylglycerol-asthma link: a Mendelian randomization study.

3 Biotech·2025

Related Experiment Video

Updated: May 14, 2025

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.3K

Artificial intelligence driven 3D reconstruction for enhanced lung surgery planning.

Xiuyuan Chen1,2,3,4,5, Chenyang Dai6, Muyun Peng7

  • 1Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China.

Nature Communications
|May 1, 2025
PubMed
Summary

An AI-powered 3D reconstruction system enhances lung surgery planning by improving anatomical variant identification and reducing errors. This AI tool significantly decreases preoperative planning time, boosting surgeon confidence and efficiency.

More Related Videos

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

391
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.7K

Related Experiment Videos

Last Updated: May 14, 2025

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.3K
Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

391
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.7K

Area of Science:

  • Thoracic Surgery
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Complex lung surgeries require precise preoperative planning.
  • Current 3D reconstruction methods face adoption barriers like time and validation.
  • Enhanced imaging support is crucial for improving surgical outcomes.

Purpose of the Study:

  • To evaluate an AI-driven 3D reconstruction system for pulmonary vessels and bronchi.
  • To assess the system's impact on anatomical variant identification and preoperative planning efficiency.
  • To determine the system's utility in thoracic surgery planning.

Main Methods:

  • Retrospective, multi-center, multi-reader, multi-case study.
  • Ten thoracic surgeons assessed 140 cases with and without AI system assistance.
  • Two-stage crossover design evaluating system's impact on accuracy and time.

Main Results:

  • AI system improved anatomical variant identification accuracy by 8% (p<0.01), reducing errors by 41%.
  • Operation procedure selection accuracy improved by 8%, with a 35% decrease in errors.
  • Preoperative planning time decreased by 25%; user satisfaction was 99%.

Conclusions:

  • AI-driven 3D reconstruction significantly enhances anatomical variant identification in thoracic surgery.
  • The system addresses critical needs in preoperative planning, improving accuracy and efficiency.
  • Benefits were consistent across surgeons of varying experience levels.