Clinical trial · Interventional
Artificial Intelligence in Large-scale Breast Cancer Screening
Artificial Intelligence in a Population-based Breast Cancer Screening - the Prospective Clinical Trial ScreenTrust CAD
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This is a prospective clinical trial following a paired screen-positive design, with the aims to assess the performance of an artificial intelligence (AI) computer-aided detection (CAD) algorithm as an independent reader, in addition to two radiologists, of screening mammograms in a true screening population. Since all decisions by individual readers will be recorded, it is possible to determine what the outcome would have been had one or two of the readers not been allowed to assess images, and to determine what the outcome would have been had the recall decision been performed by consensus decision (actual) compared to single reader arbitration of discordant cases.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Breast Neoplasm Female | Breast Neoplasm | ONTOLOGY_EXACT | 0.90 |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| AI CAD | Diagnostic Test | — | UNRESOLVED |
| Radiologist reading | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- ACTIVE_COMPARATOR
- label
- Standard of Care
- description
- Standard of Care means all examinations will receive a flagging decision by: first reader and second reader radiologist as usual. However, in this paired design all participants will belong to both arms.
- interventionNames
- Diagnostic Test: Radiologist reading
- type
- EXPERIMENTAL
- label
- AI CAD combination
- description
- AI CAD combination in the primary end-point means the combination of the flagging decision of the first reader and AI CAD; in the secondary end-points it means any combination of AI alone, or AI in combination with first, second and both readers.
- interventionNames
- Diagnostic Test: AI CAD
- Diagnostic Test: Radiologist reading
Primary outcomes (3)
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 40 Years
- Maximum age
- 74 Years
Show eligibility criteria text
Inclusion Criteria: * Participants in regular population-based breast cancer screening at Capio St Göran Hospital Exclusion Criteria: * Incomplete exam (complete exam: mediolateral oblique and craniocaudal images of Left and Right breast) * Breast implant * Complete mastectomy (excluded from screening positive group) * Participant in surveillance program for prior breast cancer
References
Publications (2)
- DERIVEDDembrower KE, Crippa A, Eklund M, Strand F. Human-AI Interaction in the ScreenTrustCAD Trial: Recall Proportion and Positive Predictive Value Related to Screening Mammograms Flagged by AI CAD versus a Human Reader. Radiology. 2025 Mar;314(3):e242566. doi: 10.1148/radiol.242566. PMID 40100021
- DERIVEDDembrower K, Crippa A, Colon E, Eklund M, Strand F; ScreenTrustCAD Trial Consortium. Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study. Lancet Digit Health. 2023 Oct;5(10):e703-e711. doi: 10.1016/S2589-7500(23)00153-X. Epub 2023 Sep 8. PMID 37690911