Lung Cancer, Peripheral Pulmonary Nodules
Conditions
Keywords
Lung cancer, peripheral pulmonary nodules, AI-constructed airway tree navigation system, diagnosis, effectiveness and safety
Brief summary
To verify the clinical effectiveness and safety of the airway tree navigation system constructed by artificial intelligence (AI) in the navigation diagnosis of peripheral pulmonary nodules (PPLs).
Detailed description
Early diagnosis and treatment of lung cancer is of great significance, in which navigated tracheoscopic biopsy is an important tool for confirming the diagnosis of early lung cancer. Conventional navigation software realizes airway reconstruction and guides biopsy by recognizing differences in HU values on computed tomography scans. It is difficult for conventional navigation software to recognize the reconstruction due to the special characteristics of small airways that are susceptible to interference and collapse. Therefore, an AI deep learning approach can realize accurate construction of small airways and guide accurate biopsy. This study intends to validate the clinical effectiveness and safety of the AI-constructed airway tree navigation system in the navigational diagnosis of peripheral pulmonary nodules (PPLs).
Interventions
DIAGNOSTIC_TESTPreoperative navigation path planning using the SARS-pro navigation system
The SARS-pro navigation system was used for preoperative navigation path planning for tracheoscopic biopsies in the new navigation system group (patients with suspected lung cancer).
DIAGNOSTIC_TESTPreoperative navigation path planning using the VBN navigation system
The VBN navigation system was used for preoperative navigation path planning for tracheoscopic biopsies in the old navigation system group (patients with suspected lung cancer).
Sponsors
Jisong Zhang
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Subject)
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No
Inclusion criteria
1. Aged 18 years or above. 2. Patients with one or more peripheral lung nodules suspected to be lung cancer or poorly absorbing lesions on conventional anti-infective therapy. 3. Patients with nodule diameters ≤30 mm (diameters mentioned in the text are the average of the maximum and minimum diameters). 4. The nodules were pure ground glass nodules, partially solid nodules, or solid nodules. 5. The nodule is surrounded by lung parenchyma and is not visible in the bronchial lumen above the segment.
Exclusion criteria
1. Preoperative judgment that it is difficult for the patient to benefit from bronchoscopic biopsy (e.g., high risk of bleeding due to perivascular encasement of the lesion, difficulty in reaching the airway adjacent to the lesion due to previous lung surgery, etc.). 2. Those with incomplete clinical data. 3. Those with missing visits after biopsy.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic positive yield | One month after the patients were enrolled | After biopsy by navigational bronchoscopy, the biopsy tissue was tested for lung cancer pathology. A positive diagnosis was defined when the pathology report was a neoplastic lesion (benign or malignant tumor). A positive diagnosis was also made if the pathology report was a granulomatous lesion (with tuberculosis or fungus). If the pathology was reported as an inflammatory cell infiltration or other non-specific inflammation in the lungs, the subject underwent another pathology biopsy after at least 3 months of follow-up to rule out false-positive results due to a change in the site of the lesion. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Adverse events | 3 days after navigational tracheoscopic biopsy | Patients underwent a follow-up period of 3 days after navigational tracheoscopic biopsy, and subjects were followed for adverse events such as hemoptysis, pneumothorax, and mediastinal emphysema. |
Countries
China
Outcome results
None listed