Can non-contrast chest CT help screen for breast cancer alongside standard imaging
Official title: Artificial Intelligence-Assisted Opportunistic Screening for Breast Cancer Using Non-Contrast Chest CT: A Comparative Study With Mammography and/or Breast MRI
Run by Fudan University · NCT07557654 · Data updated 2026-11-12
This study looks at whether non-contrast chest CT done for other reasons can help detect breast cancer and how its results compare with mammography or breast MRI.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | Women only |
| Enrollment | 5000 (estimated) |
| Sponsor | Fudan University Academic / other |
| Drugs / interventions | chemotherapy, immunotherapy |
| Locations | 1 site (Shanghai) |
| Status | Recruiting |
| Started | May 6, 2026 |
| Main results expected | May 1, 2028 |
| Study ends | May 1, 2029 |
| Registry record updated | October 29, 2026 |
| Trial ID | NCT07557654 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Women who have undergone non-contrast chest CT and for whom at least one comparator breast imaging modality (mammography or breast MRI) has been performed.
✕Probably not a fit
Patients without detectable lesions on both non-contrast chest CT and comparator imaging, or those with incomplete data, may not experience a screening benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study evaluates the feasibility and accuracy of using non-contrast chest CT scans to opportunistically screen for breast cancer. Researchers will use AI-assisted analysis of chest CTs obtained for other indications to identify suspicious breast lesions and compare diagnostic performance with conventional imaging modalities such as mammography and breast MRI. The study will measure sensitivity, specificity, and overall accuracy, and will examine how non-contrast CT findings align with pathology or long-term clinical follow-up. By leveraging existing imaging, the study aims to determine whether chest CT could add value to breast cancer screening without requiring additional scans. The investigation involves multiple institutions in China and relies on retrospective data with defined quality and timing criteria.
Why it matters
Potential benefit: If successful, this approach could facilitate earlier detection of breast cancer without extra imaging burden for patients undergoing chest CT for other reasons.
How similar studies have gone: Prior work suggests imaging features on chest CT can correlate with breast findings, but using CT for opportunistic breast screening with AI is a novel approach with mixed prior evidence.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Female patients who have undergone non-contrast chest CT examination; 2. Participants included in the comparative analysis must have undergone at least one comparator imaging modality (mammography and/or breast MRI); 3. If a breast lesion is detected, it must be confirmed by pathology or clinical follow-up at least 12 months; 4. No prior systemic or local therapy before imaging examinations; 5. Imaging data are complete and of sufficient quality for analysis. Exclusion Criteria: 1. History of other malignancies with potential impact on breast imaging interpretation; 2. Participants with suspected malignant breast lesions but no confirmation; 3. Prior radiotherapy, chemotherapy, or immunotherapy before imaging examinations; 4. Imaging data that are incomplete, of poor quality, or contain significant artifacts preventing reliable analysis; 5. Time interval between non-contrast chest CT and comparator imaging modalities exceeding three months, or with clinical events occurring between examinations that may alter lesion status.
Where it's running
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Fudan University Shanghai Cancer Center
Shanghai, China Recruiting
Study contacts
- Principal investigator: Yajia Gu, MD — Fudan University
- Study coordinator: Chao You, MD
- Email: youchao@fudan.edu.cn
- Phone: +86-021-15800780035
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.