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Postoperative Pulmonary Function Assessment Based on Deep Learning Study
NCT07256457 · Chinese University of Hong Kong · Updated 21 Oct 2026
- What is being tested
- Segmentectomy; Lobectomy; Bronchoscopic Ablation
- For
- Lung Cancer (NSCLC)
- Kind of study
- Tests a treatment or device on volunteers. No drug phase (a device or procedure study).
- Who can join
- Ages 18 years and older. About 192 people. The full rules are on the registry page.
- Where
- Hong Kong
- When
- Starts or started 1 Nov 2026, ends 31 Dec 2029. Registered 1 Dec 2025.
- Results
- None posted yet.
In the researchers' words
Improvements in low-dose CT screening have led to an increase in early-stage NSCLC diagnoses, with surgical resection-usually lobectomy or segmentectomy-remaining the primary curative option. In Hong Kong, however, patients frequently present with comorbidities such as chronic respiratory disease or cardiovascular issues, making the preservation of healthy lung tissue crucial for their long-term quality of life. Traditional surgical resection, such as lobectomy or segmentectomy, has certain limitations in terms of functional preservation. In contrast, robotic/navigational bronchoscopic ablation has emerged in recent years as a novel minimally invasive endoscopic treatment strategy. This approach has been implemented in select centers and demonstrates potential advantages, including faster postoperative recovery, reduced trauma, and improved preservation of pulmonary function. By leveraging advanced navigation systems, bronchoscopic ablation enables precise localization and ablation of pulmonary nodules, avoiding the extensive resection of healthy lung tissue required in traditional surgery. These benefits hold promise for enhancing patients' long-term quality of life and survival rates. Moreover, conventional pulmonary function tests like FEV₁ and diffusing capacity of the lung for carbon monoxide provide only a global assessment of respiratory capacity, which may not fully…
Sites
- Prince of Wales HospitalShatin, Hong Kong
