AzTrials
AzTrials

Breast Cancer ScreeningAI-BCSQNCT07075679

Screening Mammography: Single Reading by One Radiologist With AI vs. Double Reading by Two Radiologists (AI-BCSQ)

A study testing Group with AI iCAD version 3 and Group without AI in people with Breast Cancer Screening and Artificial Intelligence (AI), run by University Hospital Olomouc at 1 site in Czechia.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts
Official record
Search all trials

Trial summary

A randomized prospective study comparing the evaluation of mammography images in a breast cancer screening programme by a single radiologist with AI support versus standard double reading by two radiologists without AI support. Read more about this study

Who is it for?
Ages 45 to 69 years, women onlyHealthy volunteers can take part
What is being tested?
Group with AI iCAD version 3 and Group without AI
Could I receive a placebo?
No, everyone receives an active treatment
How many people
8,000 participants
Where
1 siteCzechia
Study dates
6 Oct 2025to 5 Oct 2028
Phase
Interventional
Are there results?
Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 45 to 69 years
  • Women only
  • Healthy volunteers accepted
  • Adult, Older adult

Who may be able to join

  • age 45-69, asymptomatic woman participating in breast cancer screening programme

Who cannot join

  • clinical signs of breast disease - indication for diagnostic mammography

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

Lucia Veverkova, MD contact

+420603181913

lucia.veverkova@fnol.cz

Czechia1 site, 1 recruiting

  • University Hospital Olomouc

    Olomouc

    Recruiting

Other trials in Czechia

About this study

Official title: Use of Artificial Intelligence in Breast Cancer Screening: Impact of AI-Assisted Single Reading by One Radiologist on Screening Quality Indicators Compared to Standard Double Reading by Two Radiologists Without AI

A randomized prospective study comparing the evaluation of mammography images in a breast cancer screening programme by a single radiologist with AI support versus standard double reading by two radiologists without AI support.

Read the detailed description

In the intervention group, the first reading of the screening mammogram will be performed by one radiologist with AI support. After this AI-assisted first reading is completed and recorded for the study, a standard second reading will be carried out by another radiologist. This ensures that the legal requirement for double reading in the breast cancer screening program is maintained.

In the control group, mammograms will be evaluated according to the current standard practice - that is, independently by two radiologists without AI support.

Participants will be divided to the two groups based on a randomization scheme that determines specific days for evaluation with AI (Group 1) and without AI (Group 2). The randomization ensures equal distribution of weekdays between the two groups to minimize bias due to variability in daily workflow, diagnostic/screening ratios, or other operational factors.

Being tested
Group with AI iCAD version 3, Group without AI
Keywords
breast cancer, screening, artificial intelligence
Medical subject headings
Disease, Breast Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • Group with AI iCAD version 3Diagnostic test

    Reading mammograms by one radiologist with AI support

  • Group without AIDiagnostic test

    Standard double reading by two radiologists without AI.

Study groups in NCT07075679
Study groupRoleWhat they receive
Group with AIExperimentalAsymptomatic women aged 45-69 participating in breast cancer screening programme, reading of mammograms by one radiologist with AI support.
Receives: Diagnostic Test: Group with AI iCAD version 3
Group without AIOtherAsymptomatic women aged 45-69 participating in breast cancer screening programme, reading of mammograms by two radiologists without AI (current practice).
Receives: Diagnostic Test: Group without AI

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Further assessment rate

    The proportion of women udergoing follow-up examinations within 0-190 days after screening mammography.

    Measured: up to 190 days after screening mammmography

Secondary outcomes (2)

  1. Cancer Detection Rate

    The number of cancers detected per 1,000 women screened.

    Measured: up to 1 year after screening mammography

  2. Recall Rate

    The proportion of women recalled for follow-up examinations withing 1-190 days after screening mammography.

    Measured: up to 190 days after screening mammography

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted20 Jul 2025
  2. Study start6 Oct 2025
  3. Primary completion5 Oct 2028 (estimated)
  4. Study completion5 Oct 2028 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Interventional
Phase
Phase N/A
Primary purpose
Diagnosis
Allocation
Randomised
Intervention model
Parallel groups
Masking
None (open label)
Enrolment
8,000 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT07075679
Sponsor's protocol ID
03062025
Other IDs
IGA_LF_2024_022
Acronym
AI-BCSQ
Status last verified
Apr 2026
First submitted
9 Jul 2025
Last updated
2 Apr 2026
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Publications

  • Larsen M, Olstad CF, Lee CI, Hovda T, Hoff SR, Martiniussen MA, Mikalsen KO, Lund-Hanssen H, Solli HS, Silberhorn M, Sulheim AO, Auensen S, Nygard JF, Hofvind S. Performance of an Artificial Intelligence System for Breast Cancer Detection on Screening Mammograms from BreastScreen Norway. Radiol Artif Intell. 2024 May;6(3):e230375. doi: 10.1148/ryai.230375.

    PubMed 38597784

  • Lambin P, Leijenaar RTH, Deist TM, Peerlings J, de Jong EEC, van Timmeren J, Sanduleanu S, Larue RTHM, Even AJG, Jochems A, van Wijk Y, Woodruff H, van Soest J, Lustberg T, Roelofs E, van Elmpt W, Dekker A, Mottaghy FM, Wildberger JE, Walsh S. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 2017 Dec;14(12):749-762. doi: 10.1038/nrclinonc.2017.141. Epub 2017 Oct 4.

    PubMed 28975929

  • Tudos Z, Veverkova L, Baxa J, Hartmann I, Ctvrtlik F. The current and upcoming era of radiomics in phaeochromocytoma and paraganglioma. Best Pract Res Clin Endocrinol Metab. 2025 Jan;39(1):101923. doi: 10.1016/j.beem.2024.101923. Epub 2024 Aug 23.

    PubMed 39227277

  • McDonald ES, Conant EF. Can AI Reduce the Harms of Screening Mammography? Radiol Artif Intell. 2023 Oct 25;5(6):e230304. doi: 10.1148/ryai.230304. eCollection 2023 Nov. No abstract available.

    PubMed 38074781

  • Letter H, Peratikos M, Toledano A, Hoffmeister J, Nishikawa R, Conant E, Shisler J, Maimone S, Diaz de Villegas H. Use of Artificial Intelligence for Digital Breast Tomosynthesis Screening: A Preliminary Real-world Experience. J Breast Imaging. 2023 May 22;5(3):258-266. doi: 10.1093/jbi/wbad015.

    PubMed 38416890

  • Dahlblom V, Dustler M, Tingberg A, Zackrisson S. Breast cancer screening with digital breast tomosynthesis: comparison of different reading strategies implementing artificial intelligence. Eur Radiol. 2023 May;33(5):3754-3765. doi: 10.1007/s00330-022-09316-y. Epub 2022 Dec 11.

    PubMed 36502459

  • Eisemann N, Bunk S, Mukama T, Baltus H, Elsner SA, Gomille T, Hecht G, Heywang-Kobrunner S, Rathmann R, Siegmann-Luz K, Tollner T, Vomweg TW, Leibig C, Katalinic A. Nationwide real-world implementation of AI for cancer detection in population-based mammography screening. Nat Med. 2025 Mar;31(3):917-924. doi: 10.1038/s41591-024-03408-6. Epub 2025 Jan 7.

    PubMed 39775040

  • Diaz O, Rodriguez-Ruiz A, Sechopoulos I. Artificial Intelligence for breast cancer detection: Technology, challenges, and prospects. Eur J Radiol. 2024 Jun;175:111457. doi: 10.1016/j.ejrad.2024.111457. Epub 2024 Apr 16.

    PubMed 38640824

  • Lang K, Dustler M, Dahlblom V, Akesson A, Andersson I, Zackrisson S. Identifying normal mammograms in a large screening population using artificial intelligence. Eur Radiol. 2021 Mar;31(3):1687-1692. doi: 10.1007/s00330-020-07165-1. Epub 2020 Sep 2.

    PubMed 32876835

  • Lang K, Josefsson V, Larsson AM, Larsson S, Hogberg C, Sartor H, Hofvind S, Andersson I, Rosso A. Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study. Lancet Oncol. 2023 Aug;24(8):936-944. doi: 10.1016/S1470-2045(23)00298-X.

    PubMed 37541274

  • Dembrower 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.

    PubMed 37690911

  • Chang YW, Ryu JK, An JK, Choi N, Park YM, Ko KH, Han K. Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study. Nat Commun. 2025 Mar 6;16(1):2248. doi: 10.1038/s41467-025-57469-3.

    PubMed 40050619

Questions about this trial

What is this clinical trial studying?

A study testing Group with AI iCAD version 3 and Group without AI in people with Breast Cancer Screening and Artificial Intelligence (AI), run by University Hospital Olomouc at 1 site in Czechia.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: looking for participants now, as of the sponsor's last update on 2 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in Czechia. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Contact Lucia Veverkova, MD (+420603181913, lucia.veverkova@fnol.cz), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Further assessment rate (time frame: up to 190 days after screening mammmography). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT07075679, which also lists 12 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 2 Apr 2026.

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