An interventional study of CT-AI-assisted breast cancer screening in Breast Neoplasms, sponsored by The First Affiliated Hospital with Nanjing Medical University. Not yet recruiting. Open to female participants aged 18 Years to 80 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-09-09.
Sponsored by The First Affiliated Hospital with Nanjing Medical University · Not applicable, Interventional, and Screening
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.
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.
Exclusion Criteria:
Participants undergo routine health examination, including breast ultrasound and non-contrast chest CT when clinically scheduled. No additional chest CT is performed for study purposes. After routine breast ultrasound and chest CT reports are completed and locked, a fixed CT-AI model analyzes the existing chest CT images. Participants meeting predefined AI criteria are reviewed by trained physicians, who make the final decision regarding whether additional breast evaluation is recommended. Further imaging, biopsy, or treatment is determined according to routine clinical practice and participant preference.
Device: CT-AI-assisted breast cancer screening
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.
Incremental Breast Cancer Detection Rate of CT-AI
Time frame: Within 3 months after the index health examination
Sensitivity of CT-AI for Breast Cancer Detection in the Retrospective Cohort
Time frame: Up to 12 months of retrospective outcome ascertainment
Overall Breast Cancer Detection Rate of Combined CT-AI and Breast Ultrasound Screening
Time frame: Within 3 months after the index health examination
Specificity of CT-AI
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 (%).
Time frame: Up to 24 months after the index health examination
Positive Predictive Value of CT-AI-Assisted Recall
Proportion of participants recalled following CT-AI-assisted physician review who are subsequently confirmed to have breast cancer. Unit of measure: percentage (%).
Time frame: Within 3 months after the index health examination
Proportion of Early-Stage Breast Cancers Detected
Time frame: Within 3 months after the index health examination
Physician Recall Rate
Proportion of participants for whom the reviewing physician recommends additional breast evaluation after CT-AI-assisted review. Unit of measure: percentage (%).
Time frame: Within 3 months after the index health examination
Breast Biopsy Rate
Proportion of participants who undergo breast biopsy following the index screening episode. Unit of measure: percentage (%).
Time frame: Within 3 months after the index health examination
24-Month Interval Breast Cancer Rate
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.
Time frame: Up to 24 months after the index health examination
No study locations are listed for this record.
Plan to share: No
This study is not yet recruiting, as verified in Aug 2026. You cannot join it, but the record below documents what was studied.
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The First Affiliated Hospital with Nanjing Medical University