Evaluation of AI-assisted LDCT Screening in Lung Cancer

NCT ID: NCT07280559

Last Updated: 2025-12-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

1120 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-12-11

Study Completion Date

2031-12-31

Brief Summary

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This multicenter pragmatic randomized controlled trial evaluates whether AI-assisted interpretation of low-dose CT (LDCT) improves lung cancer screening performance compared with standard reading. Eligible participants are randomized to AI-assisted or conventional interpretation. The study assesses diagnostic accuracy, efficiency, lung cancer incidence, mortality, recurrence, and smoking cessation outcomes. Results will inform the clinical utility and potential implementation of AI-assisted LDCT in routine screening practice.

Detailed Description

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Lung cancer is a leading cause of cancer-related mortality worldwide, and early detection is essential for improving survival. Low-dose computed tomography (LDCT) has been shown to reduce lung cancer mortality in high-risk populations, but image interpretation is time-consuming and may lead to overdiagnosis. Artificial intelligence (AI)-assisted diagnostic tools offer the potential to improve accuracy and efficiency in LDCT-based lung cancer screening, though challenges related to model adaptability, data heterogeneity, user trust, and regulatory compliance remain.

This multicenter pragmatic randomized controlled trial evaluates the effectiveness of AI-assisted LDCT interpretation compared with standard interpretation. Eligible participants will be randomized to an AI-assisted arm or a standard-reading arm. Outcomes include diagnostic accuracy, efficiency, lung cancer incidence, lung cancer mortality, recurrence, and smoking cessation.

The findings will provide evidence on the clinical utility of AI-assisted LDCT screening and support future implementation in routine practice and policy development.

Conditions

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Lung Cancer

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SCREENING

Blinding Strategy

SINGLE

Participants

Study Groups

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AI-assisted LDCT Interpretation

Group Type EXPERIMENTAL

AI-assisted Low-Dose CT Interpretation

Intervention Type DIAGNOSTIC_TEST

Participants undergo low-dose computed tomography (LDCT) lung cancer screening. The images are first interpreted by AI-assisted software, which highlights suspicious nodules. Radiologists then review the AI outputs and generate the final report.

Standard Radiologist LDCT Interpretation

Participants undergo low-dose computed tomography (LDCT) lung cancer screening. Images are interpreted solely by radiologists without AI assistance.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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AI-assisted Low-Dose CT Interpretation

Participants undergo low-dose computed tomography (LDCT) lung cancer screening. The images are first interpreted by AI-assisted software, which highlights suspicious nodules. Radiologists then review the AI outputs and generate the final report.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

1. Family History of Lung Cancer: Males aged 45-74 or females aged 40-74 with first-degree relatives (parents, siblings, or children) diagnosed with lung cancer.
2. Heavy Smoking History: Ages 50-74 with ≥20 pack-years smoking history, currently smoking or quit \<15 years ago.
3. General Screening Participants: Adults aged 40 years or older attending routine health check-ups.

Exclusion Criteria

1. Pregnant women.
2. Chest CT or other higher-radiation chest imaging within the past 12 months.
3. Individuals holding a major illness certificate for lung cancer.
4. Inability to undergo thoracic puncture or surgery.
5. Inability to hold breath or otherwise complete the scanning procedure.
6. Hemoptysis of unknown cause within the past month.
7. Chest X-ray within the past month showing suspicious lung lesions.
8. Unexplained weight loss \>6 kg within the past year.
9. History of lung cancer within the past three years.
10. Presence of other severe diseases with an expected life expectancy \<5 years.
Minimum Eligible Age

40 Years

Maximum Eligible Age

74 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Far Eastern Memorial Hospital

OTHER

Sponsor Role collaborator

Taipei Municipal Guandu Hospital

UNKNOWN

Sponsor Role collaborator

Da Chien General Hospital

OTHER

Sponsor Role collaborator

Kinmen Hospital, Ministry of Health and Welfare

UNKNOWN

Sponsor Role collaborator

Ministry of Health and Welfare, Taiwan

OTHER_GOV

Sponsor Role collaborator

Taipei Veterans General Hospital, Taiwan

OTHER_GOV

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Taipei Veterans General Hospital

Taipei, Taiwan, Taiwan

Site Status

Countries

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Taiwan

Central Contacts

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Hao-Min Cheng, M.D., Ph.D

Role: CONTACT

+886-2-28712121 ext 85322

Facility Contacts

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Hao-Min Cheng, M.D., Ph.D.

Role: primary

+886-2-28712121 ext 85322

Other Identifiers

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2025-11-002AU-3AI

Identifier Type: -

Identifier Source: org_study_id

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