Skip to main content
OpenTrials
Not yet recruiting

NCT Number: NCT07809698

CT-AI Breast Cancer Opportunistic Screening Health Examination Study

This study evaluates the clinical utility of a locked chest CT artificial intelligence model for opportunistic breast cancer screening among women undergoing health examinations. The study includes a retrospective validation phase and a prospective single-arm implementation phase. AI analyzes existing non-contrast chest CT images without additional CT examinations. Clinical physicians make further evaluation decisions based on AI outputs, imaging findings, ultrasound results and clinical information.

Not yet recruiting

Trial opening soon.

Get Notified

Key information

Conditions

Breast Neoplasms Breast Diseases Neoplasms Neoplasms by Site Skin Diseases Skin and Connective Tissue Diseases

Age range

18 year–80 year

Sex eligibility

Female

Study type

Interventional

Phase

Not applicable

About this study

Retrospective phase: Historical health examination data will be used for offline validation of the locked CT-AI model.

Prospective phase: Eligible women undergoing routine health examination will be consecutively enrolled. Participants receive routine chest CT and breast ultrasound. After routine reports are completed and locked, AI analysis is performed. Cases exceeding predefined thresholds are reviewed by clinicians who determine recall decisions. The study evaluates incremental detection value, recall workflow, safety and feasibility.

Who can participate

Healthy volunteers accepted: Yes

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

Inclusion criteria

  • Female participants aged 18 to 80 years.
  • Undergoing routine health examination.
  • For the prospective phase, no clear ongoing breast-related symptoms at baseline.
  • Availability of complete non-contrast chest CT images. In the prospective phase, chest CT must have been scheduled as part of the routine health examination or for another established clinical purpose and must not be performed solely for this study.
  • Availability of a contemporaneous routine breast ultrasound report and relevant clinical information.
  • Chest CT image quality adequate for AI analysis.
  • Availability of an appropriate follow-up pathway through hospital records, pathology systems, cancer registry data, or approved follow-up methods.
  • For the prospective phase, study information has been provided through an ethics-approved process and the participant has not actively opted out.

Exclusion criteria

  • Previous diagnosis of breast cancer, prior treatment for breast malignancy, or breast malignancy already confirmed before baseline.
  • Pregnancy or breastfeeding.
  • Incomplete breast coverage on chest CT, severe image artifacts, missing images, or other conditions that prevent valid AI analysis.
  • Critical baseline or outcome data are substantially incomplete and cannot reasonably be recovered.
  • No effective follow-up pathway can be established.
  • For the prospective phase, the participant actively opts out before AI analysis or explicitly declines use of imaging and clinical data for this study.

Treatment and study plan

CT-AI-assisted breast cancer screening

Device

A fixed artificial intelligence model is applied to existing non-contrast chest CT images obtained during routine health examinations to identify and localize suspicious breast lesions and generate a breast cancer risk score and risk category. No additional CT examination is performed for study purposes. Participants meeting predefined AI review criteria are evaluated by trained physicians, who review the original CT images together with the AI output and make the final decision regarding whether additional breast evaluation is recommended. The AI system does not independently diagnose breast cancer or automatically recall participants. Subsequent imaging, biopsy, or treatment is determined according to routine clinical practice and participant preference.

Primary outcomes

  1. Incremental Breast Cancer Detection Rate of CT-AI

    Time frame: Within 3 months after the index health examination

  2. Sensitivity of CT-AI for Breast Cancer Detection in the Retrospective Cohort

    Time frame: Up to 12 months of retrospective outcome ascertainment

  3. Overall Breast Cancer Detection Rate of Combined CT-AI and Breast Ultrasound Screening

    Time frame: Within 3 months after the index health examination

Secondary outcomes

  1. Specificity of CT-AI

    Time frame: Up to 24 months after the index health examination

    Specificity of the fixed CT-AI model for breast cancer detection, using final breast cancer status based on pathology and/or clinical follow-up as the reference standard. Unit of measure: percentage (%).

  2. Positive Predictive Value of CT-AI-Assisted Recall

    Time frame: Within 3 months after the index health examination

    Proportion of participants recalled following CT-AI-assisted physician review who are subsequently confirmed to have breast cancer. Unit of measure: percentage (%).

  3. Proportion of Early-Stage Breast Cancers Detected

    Time frame: Within 3 months after the index health examination

  4. Physician Recall Rate

    Time frame: Within 3 months after the index health examination

    Proportion of participants for whom the reviewing physician recommends additional breast evaluation after CT-AI-assisted review. Unit of measure: percentage (%).

  5. Breast Biopsy Rate

    Time frame: Within 3 months after the index health examination

    Proportion of participants who undergo breast biopsy following the index screening episode. Unit of measure: percentage (%).

  6. 24-Month Interval Breast Cancer Rate

    Time frame: Up to 24 months after the index health examination

    Number of breast cancers diagnosed during follow-up after the index screening episode among participants without breast cancer detected at the initial screening assessment, reported per 1,000 participants.

Study contacts

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

Ge Ma, doctor

CONTACT

[email protected]

+8618262632870

Sponsors and collaborators

Lead sponsor

The First Affiliated Hospital with Nanjing Medical University

Other

Registry information

Official study title

AI-Assisted Opportunistic Breast Cancer Screening Using Non-contrast Chest CT in Women Undergoing Health Examination: A Retrospective Validation and Prospective Single-Arm Interventional Study

Important dates

Study start
2026
Primary completion
2028
Study completion
2030
First posted
Sep 9, 2026
Registry last updated
Sep 9, 2026

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.