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Endoscopic Studies I: Bronchoscopy and Thoracoscopy01:30

Endoscopic Studies I: Bronchoscopy and Thoracoscopy

Endoscopy is a non-surgical medical technique used to examine a person's internal organs and vessels. This lesson will focus on two types of endoscopic studies: bronchoscopy and thoracoscopy.
Bronchoscopy
Description
Bronchoscopy is a procedure that involves direct visualization of the larynx, trachea, and bronchi for diagnostic and therapeutic purposes. A flexible fiber optic or rigid bronchoscope is used to carry out the procedure. The fiber-optic bronchoscope is more frequently used due to...

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Related Experiment Video

Updated: Jul 6, 2026

Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery
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Patients-specific virtual surgical navigation for lung segmentectomy: a prospective multicenter study.

Chang Young Lee1, Woo Sik Yu2, Young Ho Yang1

  • 1Department of Thoracic and Cardiovascular Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.

Frontiers in Oncology
|March 27, 2026
PubMed
Summary

A patient-specific virtual navigation system enhances anatomical segmentectomy for non-small cell lung cancer (NSCLC). This AI-driven tool improves tumor localization and reduces surgeon workload, leading to better surgical outcomes.

Keywords:
non-small cell lung cancerpreoperative planningsegmentectomysurgeon workloadthree-dimensional simulation

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Area of Science:

  • Thoracic Surgery
  • Medical Imaging
  • Artificial Intelligence in Medicine

Background:

  • Anatomical segmentectomy is a standard treatment for early-stage non-small cell lung cancer (NSCLC).
  • The technical complexity of segmentectomy requires precise preoperative planning.
  • Conventional 2D CT planning may have limitations in visualizing complex 3D anatomy.

Purpose of the Study:

  • To evaluate the feasibility and clinical utility of a patient-specific virtual surgical navigation system for preoperative planning in anatomical segmentectomy and subsegmentectomy.
  • To compare the accuracy and efficiency of AI-driven 3D virtual navigation with conventional 2D CT planning.
  • To assess the impact of the navigation system on surgeon workload and perioperative outcomes.

Main Methods:

  • Prospective multicenter observational study of 34 patients undergoing anatomical segmentectomy or subsegmentectomy.
  • Preoperative planning using conventional 2D CT and an AI-driven 3D virtual surgical navigation system.
  • Comparison of tumor localization, segment prediction, and bronchovascular anatomy accuracy against intraoperative findings.
  • Assessment of surgeon workload using NASA-TLX and comparison of perioperative outcomes with historical cohorts.

Main Results:

  • The AI-driven 3D navigation system achieved high accuracy (κ = 0.96-1.00) in tumor localization and segment prediction, outperforming 2D CT.
  • Surgeon workload was significantly reduced with the navigation system (NASA-TLX score: 52.5 vs. 76.1, p < 0.001).
  • Navigation system planning was associated with shorter operative time, reduced blood loss, and fewer resected subsegments compared to 2D and conventional 3D CT planning.

Conclusions:

  • Patient-specific virtual surgical navigation is a feasible and effective tool for preoperative planning in lung segmentectomy.
  • The system enhances anatomical prediction accuracy and reduces surgeon workload, proving valuable for complex lung-sparing surgeries.
  • This AI-driven approach supports improved perioperative performance in early-stage NSCLC treatment.