Clinical trial · Interventional
Lung Cancer Screening in HIgh Risk nonsmokErs by Artificial inteLligence Device
A Prospective Study on Artificial Intelligence Guided Lung Cancer Screening for High-risk Never Smokers in Hong Kong
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Lung cancer screening is currently not recommended in non-smokers due to paucity of evidence. Emerging evidence suggests that first-degree family history is a strong risk factor for lung cancer in Asian non-smokers. In Asia, lack of resource is a major challenge in successful implementation of lung cancer screening. Artificial intelligence (AI) is a promising tool to overcome this resource. In this study, we aim to study the clinical utility and demonstrate the feasibility of using an AI assisted programme for lung cancer screening in Asian non-smokers with a positive family history. This is a single-arm non-randomized lung cancer screening study. 3000 non-smokers, age 50 to 75 year old, with a first-degree family history of lung cancer, will be enrolled. Participants will undergo low does computed tomography (LDCT) of thorax and blood taking at enrolment. LDCT films will be interpreted by AI softwares for presence of lung nodules. Participants with lung nodules will be further investigated and followed up according to the risk of malignancy. The primary endpoint is the prevalence of early-staged lung cancer detected by first-round LDCT thorax in this population.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Lung-SIGHT | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- type
- OTHER
- label
- Artificial intelligence-based programme (Lung-SIGHT)
- description
- Artificial intelligence (AI) algorithms have been demonstrated to function well and complement radiologists as second or concurrent readers in pulmonary nodule detection. AI Lung nodule detection and quantification solution are now widely used in the hospitals in the United Kingdom and at least eight other European countries. The sensitivity of nodule detection by radiologists increased from 72% to 80% with the aid of the AI programme. A clinical trial in Taiwan showed that using AI programme alone achieved an overall sensitivity of 95.6% in nodule detection, and superior performance in detecting nodule sized 4-5 mm comparing to radiologists. Overall, application of AI in CT analysis and lung nodule detection may significantly reduce the cost and workload of radiologist.
- interventionNames
- Device: Lung-SIGHT
Primary outcomes (1)
- measure
- Sensitivity, specificity, positive predictive value and negative predictive value of AI-assisted programme in lung nodule (≥5mm) detection and monitoring compared to radiologist assessment
- timeFrame
- 2 years
Secondary outcomes (6)
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 50 Years
- Maximum age
- 75 Years
Show eligibility criteria text
Inclusion Criteria: Patients are eligible to be included in the study only if all of the following criteria apply: 1. Age 50-75 years old 2. Non-smoker (defined as less than 100 cigarettes in lifetime) 3. Having a first-degree family history of lung cancer 4. Physically fit for curative treatment if early-staged lung cancer is found 5. Able to provide written informed consent 6. Consent to follow up visits and follow up CT scan if indicated 7. Consent to blood taking for translational research Exclusion Criteria: Patients who meet any of the following exclusion criteria at screening are not eligible to be enrolled in this study: 1. History of malignancy 2. Smoking history (defined as more than 100 cigarettes in lifetime) 3. Clinical symptoms suspicious for lung cancer e.g. haemoptysis, chest pain, weight loss 4. Medical comorbidities that preclude curative treatment (surgery) for lung cancer, such as severe heart disease, acute or chronic respiratory failure, home oxygen therapy, bleeding disorder 5. Pregnant ladies or ladies planning for conception 6. History of tuberculosis or interstitial lung disease 7. Pneumonia requiring antibiotic treatment within the last 12 weeks 8. CT thorax or chest performed within 2 years (including LDCT, PET-CT, MRI thorax or suspicious of lung cancer) 9. Unable or unwilling to provide written informed consent
References
Publications (0)
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