About this trial
This study aims to validate a novel preoperative assessment strategy using three-dimensional (3-D) computed tomography (CT) reconstruction and virtual resection simulation. The goal is to accurately predict postoperative pulmonary function in patients with non-small cell lung cancer (NSCLC) undergoing Video-Assisted Thoracoscopic Surgery (VATS) anatomical resection.
Accurate prediction of postoperative lung function is crucial for patient safety. Traditional methods, such as segment counting, often lack precision because they assume all lung segments contribute equally to function, ignoring variations caused by tumors or emphysema. This study utilizes 3-D "virtual resection" to quantify the "Planned Resected Ventilated Lung Volume Fraction" (pRVLVF) before surgery.
The study will recruit 60 participants divided into two groups: those undergoing lobectomy (n=30) and those undergoing segmentectomy (n=30). Participants will undergo standard thin-slice CT scans and pulmonary function tests (PFT) before surgery. Postoperatively, lung function and recovery will be tracked at 3, 6, and 12 months to develop a dynamic prediction model and evaluate the compensatory capacity of the residual lung.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Patients scheduled for video-assisted thoracoscopic (VATS) 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.
Disqualifiers
Age younger than 18 or older than 80 years.
Patients not scheduled for VATS lobectomy or segmentectomy.
Patients diagnosed with Chronic Obstructive Pulmonary Disease (COPD).
Patients unable or unwilling to sign the informed consent form.
Trial population
Patients with non-small cell lung cancer recruited from the thoracic surgery outpatient clinics and inpatient wards of National Taiwan University Hospital.
Trial design
Cohort
Prospective
Treatments tested in this trial
Not listed
Trial groups
Trial outcomes
Primary outcomes
Mean Absolute Error (MAE) of Predicted Postoperative FEV1
The accuracy of the preoperative 3D virtual resection model will be evaluated by calculating the Mean Absolute Error (MAE) between the predicted FEV1 and the actual measured FEV1. A lower MAE indicates higher prediction accuracy. The study targets an MAE of less than 180 mL.
Secondary outcomes
Long-term Prediction Error of FEV1 and FVC
Evaluation of the prediction model's accuracy at 6 and 12 months to assess stability over time.
Sponsors and contacts
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