Skip to main content
OpenTrials
Not Yet Recruiting

NCT Number: NCT07280559

Evaluation of AI-assisted LDCT Screening in Lung Cancer

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.

Not Yet Recruiting

Trial opening soon.

Get Notified

Key information

Conditions

Lung Cancer Lung Diseases Lung Neoplasms Neoplasms Neoplasms by Site Respiratory Tract Diseases Respiratory Tract Neoplasms Thoracic Neoplasms

Age range

40 year–74 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Taipei Veterans General Hospital

Taipei, Taiwan, 112

Location contact

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

CONTACT

[email protected]

+886-2-28712121 ext 85322

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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.
  • Heavy Smoking History: Ages 50-74 with ≥20 pack-years smoking history, currently smoking or quit <15 years ago.
  • General Screening Participants: Adults aged 40 years or older attending routine health check-ups.

Exclusion criteria

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

Treatment and study plan

AI-assisted Low-Dose CT Interpretation

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.

Primary outcomes

  1. Lung Cancer Incidence

    Time frame: From baseline to 12 months, 36 months, and 60 months.

    The proportion of newly diagnosed lung cancer cases identified within the specified follow-up period among all individuals who underwent LDCT screening.

  2. False Positive Rate

    Time frame: Within 6 months following LDCT screening.

    The proportion of LDCT screening results interpreted as positive that are subsequently confirmed as non-lung cancer based on further diagnostic imaging or pathological examination.

Secondary outcomes

  1. Lung Cancer Mortality

    Time frame: From baseline to 12 months, 36 months, and 60 months.

    The proportion of participants who die from lung cancer within the specified follow-up period after undergoing LDCT screening.

  2. Lung Cancer Recurrence Rate

    Time frame: From baseline to 12 months, 36 months, and 60 months.

    The proportion of patients previously diagnosed and treated for lung cancer who experience disease recurrence during the follow-up period.

  3. All-Cause Mortality

    Time frame: From baseline to 12 months, 36 months, and 60 months.

    The proportion of deaths from any cause among all individuals who underwent LDCT screening during the study period.

  4. Time to Diagnosis

    Time frame: At the 12-month, 36-month, and 60-month follow-up assessments after LDCT screening.

    The time interval from LDCT screening to the date of confirmed lung cancer diagnosis, reported at the 12-month, 36-month, and 60-month follow-up time points.

  5. Time to Treatment Initiation

    Time frame: At the 12-month, 36-month, and 60-month follow-up assessments after lung cancer diagnosis.

    The time interval from the date of confirmed lung cancer diagnosis to the initiation of treatment, reported at the 12-month, 36-month, and 60-month follow-up time points.

  6. Follow-up Completion Rate

    Time frame: Up to 12 months post-screening.

    The proportion of individuals who completed the scheduled follow-up examinations or clinical evaluations within the designated follow-up period after undergoing LDCT screening.

  7. Smoking Cessation Rate

    Time frame: Assessed at 3 months, 6 months, and 12 months after baseline screening.

    The proportion of individuals who successfully quit smoking within the follow-up period after LDCT screening

Study contacts

Contact information is provided by the study sponsor or research team.

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

CONTACT

[email protected]

+886-2-28712121 ext 85322

Sponsors and collaborators

Lead sponsor

Taipei Veterans General Hospital, Taiwan

Other Gov

Collaborators

  • Da Chien General Hospital
  • Far Eastern Memorial Hospital
  • Kinmen Hospital, Ministry of Health and Welfare
  • Ministry of Health and Welfare, Taiwan
  • Taipei Municipal Guandu Hospital

Registry information

Official study title

Evaluation of AI Medical Software-assisted LDCT Interpretation in Lung Cancer Screening and Prognosis: a Randomized Controlled Trial

Important dates

Study start
2025
Primary completion
2027
Study completion
2031
First posted
Dec 12, 2025
Registry last updated
Dec 12, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Related clinical trials

Published trials that share one or more normalized conditions with this study.