Actively Recruiting

Age: 18Years - 80Years
All Genders
ID07436598

Preoperative 3-D Virtual Resection Predicts Lung Function After Anatomical Resection in NSCLC Patients: A Prospective Longitudinal Study

Led by National Taiwan University Hospital · Updated on 2026-05-13

60

Participants Needed

1

Research Sites

N/A

Total Duration

On this page

AI-Summary

What this Trial Is About

Researchers are evaluating a new preoperative method using three-dimensional CT scans and virtual resection simulation to predict lung function after surgery in patients with non-small cell lung cancer (NSCLC) undergoing Video-Assisted Thoracoscopic Surgery (VATS). This study aims to improve accuracy over traditional methods by accounting for differences in lung ventilation caused by tumors or emphysema. It is a prospective, multi-center, longitudinal cohort study involving 60 patients split evenly between those having lobectomy and segmentectomy. Participants will undergo detailed thin-slice chest CT scans and pulmonary function tests before surgery. Using Synapse 3-D software, doctors will create patient-specific 3-D lung models to simulate the planned lung tissue removal and calculate the fraction of ventilated lung to be resected. After surgery, patients will follow standard VATS procedures. The study includes long-term follow-up with pulmonary function tests at 3, 6, and 12 months and CT scans at 6 and 12 months to observe structural lung changes. During the study, participants will have preoperative assessments, surgery, and several postoperative visits for lung function tests and imaging. Researchers will measure how closely the predicted lung function matches actual results at 3 months, as well as longer-term accuracy at 6 and 12 months. They will also study how well the remaining lung compensates after surgery and the effect of any complications on recovery. The total participation spans about one year after surgery, allowing detailed evaluation of lung function and recovery.

CONDITIONS

Brief Title

3D Virtual Resection for Predicting Lung Function in VATS

Who Can Participate

Age: 18Years - 80Years
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Patients scheduled for video-assisted thoracoscopic lobectomy or segmentectomy at National Taiwan University Hospital or NTU Cancer Center
  • Age between 18 and 80 years
  • Patients who have signed the informed consent form agreeing to provide imaging data for 3D modeling
Not Eligible

You will not qualify if you...

  • Age younger than 18 or older than 80 years
  • Patients not scheduled for video-assisted thoracoscopic lobectomy or segmentectomy
  • Patients diagnosed with Chronic Obstructive Pulmonary Disease (COPD)
  • Patients unable or unwilling to sign the informed consent form
  • Vulnerable populations

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Your Study Journey

Screening

Duration - 2 to 4 weeks

Participants are screened for eligibility to participate in the trial.

1 visit (in-person)

Diagnostic Evaluation

Duration - Up to 30 days before surgery

Participants undergo preoperative assessments including high-resolution chest CT and pulmonary function tests within 30 days before surgery.

1 to 2 visits (in-person)

Surgery

Duration - Day of surgery

Participants undergo video-assisted thoracoscopic segmentectomy or lobectomy as clinically indicated.

1 visit (in-person)

Post-operative Follow-up

Duration - 12 months

Participants have pulmonary function tests and CT scans to assess lung function and structural remodeling after surgery.

3 pulmonary function test visits at 3, 6, and 12 months; 2 CT scan visits at 6 and 12 months

Trial Site Locations

Total: 1 location

1

National Taiwan University Cancer Center

Taipei, Taiwan

Actively Recruiting

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Research Team

C

Chih-Hsiang Chang, MD

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

2

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Published Research Related To This Trial

Quantitative computed tomography assessment of pulmonary function and compensation after lobectomy and segmentectomy in lung cancer patients.

Leqing Chen, Jinrong Yang, Chi Zhang...

https://pubmed.ncbi.nlm.nih.gov/39444877

Software-Based Assessment of Well-Aerated Lung at CT for Quantification of Predicted Pulmonary Function in Resected NSCLC.

Davide Colombi, Camilla Risoli, Rocco Delfanti...

https://pubmed.ncbi.nlm.nih.gov/36676147

Prediction of functional reserves after lung resection: comparison between quantitative computed tomography, scintigraphy, and anatomy.

Chris T Bolliger, Claudius Gückel, Hermann Engel...

https://pubmed.ncbi.nlm.nih.gov/12456999

Prediction of postoperative lung function in patients with lung cancer: comparison of quantitative CT with perfusion scintigraphy.

Ming-Ting Wu, Huay-Ben Pan, Ambrose A Chiang...

https://pubmed.ncbi.nlm.nih.gov/11856695

Quantitative computed tomography for the prediction of pulmonary function after lung cancer surgery: a simple method using simulation software.

Kazuhiro Ueda, Toshiki Tanaka, Tao-Sheng Li...

https://pubmed.ncbi.nlm.nih.gov/18485724

Prediction of postoperative lung function after major lung resection for lung cancer using volumetric computed tomography.

Lucía Fernández-Rodríguez, Isabel Torres, Delia Romera...

https://pubmed.ncbi.nlm.nih.gov/30195604