Breast CancerScreenTrustMRINCT04832594
Using AI to Select Women for Supplemental MRI in Breast Cancer Screening
A study testing AI selection for supplemental breast MRI in people with Breast Cancer, run by Karolinska University Hospital at 1 site in Sweden.
Trial summary
This is a prospective clinical trial aiming to determine the ability of an AI pipeline to identify women who would benefit from supplemental MRI in terms of decreasing the number of cancers having a significantly delayed detection Read more about this study
- Who is it for?
- Ages 40 to 74 years, women only
- Conditions the study is for
- Breast Cancer
- What is being tested?
- AI selection for supplemental breast MRI
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 2,500 participants
- Where
- 1 siteSweden
- Study dates
- 1 Apr 2021to 1 Jul 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 40 to 74 years
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Complete four-view screening mammography examination
Who cannot join
- Women in surveillance program referred from the hereditary cancer unit
- Breast implants
- Prior breast cancer
- Breast feeding
- MRI contraindication requiring radiologist assessment
- AI Tool unable to process mammograms due to technical reason
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Image Analysis With Artificial Intelligence to Increase Precision in Breast Cancer Screening - the ScreenTrust MRI Substudy: a Prospective Trial of AI to Select Women for Supplemental Screening MRI
This is a prospective clinical trial aiming to determine the ability of an AI pipeline to identify women who would benefit from supplemental MRI in terms of decreasing the number of cancers having a significantly delayed detection
Read the detailed description
All women attending mammography screening at Karolinska University Hospital will have their mammograms analyzed by AI (Figure 1). The specific AI-implementation (AI tool) in this study is a result of AI predictions from three equally weighted component AI models analyzing mammograms: (i) masking predictor, (ii) risk predictor and (iii) cancer signs predictor (by one commercial CAD model and one in-house academic CAD model); the age of the woman is also taken into account by multiplying the score with (110-age)/70. The purpose of the age factor is to attain a relatively similar proportion of MRI exams in the lower and higher age groups. The aim of the AI tool is to identify women with the highest probability of having a delay in cancer detection, i.e., having had a false negative screening mammogram.
An AI-based framework has been developed by researchers at Karolinska Institute (led by Dr. Fredrik Strand) and Royal Institute of Technology (led by Dr: Kevin Smith). The specific AI-implementation (AI tool) in this study is a result of AI predictions from three equally weighted component AI models analyzing mammograms: (i) masking predictor, (ii) risk predictor and (iii) cancer signs predictor (by one commercial CAD model and one in-house academic CAD model); the age of the woman is also taken into account by multiplying the score with (110-age)/70. The purpose of the age factor is to attain a relatively similar proportion of MRI exams in the lower and higher age groups. The aim of the AI tool is to identify women with the highest probability of having a delay in cancer detection, i.e., having had a false negative screening mammogram. The specific AI tool and its settings will remain the same during the study. For each examination, the AI tool will produce an AI Joint Score and an AI Masking Score. The AI Masking Score cut-off point was defined by the median of examinations collected during the initial period of March 1 to March 24, 2021. The cut-off point of the AI Joint Score was defined by the 92nd percentile of the initial population. Women meeting these criteria will be invited to the study, and randomized to MRI or no-MRI (standard-of-care).
A Signa Premier 3T MRI scanner from GE Healthcare will be used. The MRI protocol will contain a T2-weighted Dixon sequence and a T1-weighted dynamic contrast enhanced series, and will remain the same through the course of the study. All MRI exams will be assessed by two radiologists, where the second reader will have access to the assessment of the first reader. In case of disagreement, a consensus discussion between two radiologists will be held. The MRI exams will be assessed according to BI-RADS, and follow-up will depend on the BI-RADS category (Figure 2). Women with BI-RADS 1-2 will have no further diagnostics and will be sent a 'healthy letter'. Women with BI-RADS 3 to 5 will be recalled for 2nd look ultrasound. Women with BI-RADS 4-5 will be included in the regular process for established cancer suspicion and be discussed in a multidisciplinary team conference. For women with BI-RADS 3, the follow-up will be handled within the breast radiology unit.
- Conditions
- Breast Cancer
- Being tested
- AI selection for supplemental breast MRI
- Keywords
- Artificial Intelligence
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI selection for supplemental breast MRIOther
An AI tool will generate scores used to determine eligibility. Women randomized to MRI will be examined in an MRI scanner.
| Study group | Role | What they receive |
|---|---|---|
| Supplemental MRI | Experimental | Women randomized to MRI will be examined using a shortened MRI protocol on a Signa Premier 3T MRI scanner. The MRI examination will be reviewed by two radiologists and assigned BI-RADS score. Appropriate clinical work-up will follow according to the BI-RADS score. BI-RADS 3 or higher at initial MRI will be recalled for a second look ultrasound. Receives: Other: AI selection for supplemental breast MRI |
| No MRI (standard-of-care) | No intervention | Standard-of-care. Both arms will have had a regular screening mammography examination prior to randomization. The "No MRI" arm will have no further intervention. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Significantly Delayed Breast Cancer Detection per 1000 women
Composite end-point defined by either: 1. Interval Cancer, 2. Cancer with lymph node metastasis, 3. Cancer with invasive component larger than 15 mm
Measured: Until 27 months from study inclusion (includes cancer detected at subsequent screening within this time frame). Cancer detected at the initial screening mammography or MRI shall not be included.
Secondary outcomes (11)
MRI-detected breast cancer
Breast cancer detected at the initial screening MRI for women in the Intervention arm of the study
Measured: Diagnosis during work-up within 2 months of the initial screening MRI
Invasiveness
In situ and/or Invasive cancer
Measured: All diagnosed breast cancer within 27 months of study inclusion
Histology
Ductal, Lobular, Mucinous, Tubular, Other
Measured: All diagnosed breast cancer within 27 months of study inclusion
Lymph node metastasis
0 nodes, 1-3 nodes, 4 or more nodes
Measured: All diagnosed breast cancer within 27 months of study inclusion
Tumor size
Size (in millimetre) for the invasive and the in situ component
Measured: All diagnosed breast cancer within 27 months of study inclusion
Receptor status
ER positive/negative, PR positive/negative, HER2 positive/negative
Measured: All diagnosed breast cancer within 27 months of study inclusion
Age
Age of the woman
Measured: At study inclusion
Distribution of AI scores
Histogram, mean, median and dispersion measures for the AI Scores
Measured: At study inclusion
BI-RADS codes
For each MRI examination, the BI-RADS code for fibroglandular volume, background enhancement and breast lesions
Measured: At study inclusion and until end of 27 month follow-up
Biopsy result
Pathology assessment of biopsy: normal tissue, benign lesion, cancer in situ, invasive cancer
Measured: Diagnosis during work-up within 2 months of the MRI examination
Participant questionnaire
Participant questionnaire replies for MRI contraindications and for Breast cancer-related history
Measured: At study inclusion
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Apr 2021
- Study start1 Apr 2021
- Primary completion1 Apr 2023
- Study completion1 Jul 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Breast CancerStudies of the same condition, open and under way.
- More trials run by Karolinska University HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
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
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- For each screening mammography examination, the AI tool will produce an AI Joint Score and an AI Masking Score. Women having an AI Masking Score above the threshold and an AI Joint Score above the threshold will be invited to the study unless they met exclusion criteria. Women who decide to participate, will be randomized to MRI or no-MRI (standard-of-care).
- Masking
- None (open label)
- Enrolment
- 2,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Karolinska University Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- KTH Royal Institute of Technology, Region Stockholm, Bröstcancerförbundet
- Responsible party
- Principal investigator, Fredrik Strand, Karolinska University Hospital
- Investigators
- Fredrik Strand, MDPhD, Principal investigator, Karolinska University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04832594
- Sponsor's protocol ID
- KSRAD001
- Acronym
- ScreenTrustMRI
- Status last verified
- Oct 2023
- First submitted
- 31 Mar 2021
- Last updated
- 5 Oct 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The final trial dataset will be available for the research team of the principal investigator. Pseudonymized data can be made available for external research audit. Anonymous data may be shared with academic researchers.
Publications
Salim M, Liu Y, Sorkhei M, Ntoula D, Foukakis T, Fredriksson I, Wang Y, Eklund M, Azizpour H, Smith K, Strand F. AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trial. Nat Med. 2024 Sep;30(9):2623-2630. doi: 10.1038/s41591-024-03093-5. Epub 2024 Jul 8.
PubMed 38977914
Study at a glance
From the registry record, last updated by the sponsor on 5 Oct 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Image Analysis With Artificial Intelligence to Increase Precision in Breast Cancer Screening - the ScreenTrust MRI Substudy: a Prospective Trial of AI to Select Women for Supplemental Screening MRI
- ClinicalTrials.gov ID
- NCT04832594
- Acronym / sponsor ID
- ScreenTrustMRI / KSRAD001
- Conditions
- Breast Cancer
- Keywords
- Artificial Intelligence
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 2,500 participants (estimated)
- Lead sponsor
- Karolinska University HospitalUniversity, hospital or other
- Collaborators
- KTH Royal Institute of Technology, Region Stockholm, Bröstcancerförbundet
- Study start
- 1 Apr 2021 (actual)
- Primary completion
- 1 Apr 2023 (actual)
- Study completion
- 1 Jul 2025 (estimated)
- First posted
- 6 Apr 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is a prospective clinical trial aiming to determine the ability of an AI pipeline to identify women who would benefit from supplemental MRI in terms of decreasing the number of cancers having a significantly delayed detection
Detailed description
All women attending mammography screening at Karolinska University Hospital will have their mammograms analyzed by AI (Figure 1). The specific AI-implementation (AI tool) in this study is a result of AI predictions from three equally weighted component AI models analyzing mammograms: (i) masking predictor, (ii) risk predictor and (iii) cancer signs predictor (by one commercial CAD model and one in-house academic CAD model); the age of the woman is also taken into account by multiplying the score with (110-age)/70. The purpose of the age factor is to attain a relatively similar proportion of MRI exams in the lower and higher age groups. The aim of the AI tool is to identify women with the highest probability of having a delay in cancer detection, i.e., having had a false negative screening mammogram.
An AI-based framework has been developed by researchers at Karolinska Institute (led by Dr. Fredrik Strand) and Royal Institute of Technology (led by Dr: Kevin Smith). The specific AI-implementation (AI tool) in this study is a result of AI predictions from three equally weighted component AI models analyzing mammograms: (i) masking predictor, (ii) risk predictor and (iii) cancer signs predictor (by one commercial CAD model and one in-house academic CAD model); the age of the woman is also taken into account by multiplying the score with (110-age)/70. The purpose of the age factor is to attain a relatively similar proportion of MRI exams in the lower and higher age groups. The aim of the AI tool is to identify women with the highest probability of having a delay in cancer detection, i.e., having had a false negative screening mammogram. The specific AI tool and its settings will remain the same during the study. For each examination, the AI tool will produce an AI Joint Score and an AI Masking Score. The AI Masking Score cut-off point was defined by the median of examinations collected during the initial period of March 1 to March 24, 2021. The cut-off point of the AI Joint Score was defined by the 92nd percentile of the initial population. Women meeting these criteria will be invited to the study, and randomized to MRI or no-MRI (standard-of-care).
A Signa Premier 3T MRI scanner from GE Healthcare will be used. The MRI protocol will contain a T2-weighted Dixon sequence and a T1-weighted dynamic contrast enhanced series, and will remain the same through the course of the study. All MRI exams will be assessed by two radiologists, where the second reader will have access to the assessment of the first reader. In case of disagreement, a consensus discussion between two radiologists will be held. The MRI exams will be assessed according to BI-RADS, and follow-up will depend on the BI-RADS category (Figure 2). Women with BI-RADS 1-2 will have no further diagnostics and will be sent a 'healthy letter'. Women with BI-RADS 3 to 5 will be recalled for 2nd look ultrasound. Women with BI-RADS 4-5 will be included in the regular process for established cancer suspicion and be discussed in a multidisciplinary team conference. For women with BI-RADS 3, the follow-up will be handled within the breast radiology unit.
Study design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- For each screening mammography examination, the AI tool will produce an AI Joint Score and an AI Masking Score. Women having an AI Masking Score above the threshold and an AI Joint Score above the threshold will be invited to the study unless they met exclusion criteria. Women who decide to participate, will be randomized to MRI or no-MRI (standard-of-care).
| Arm | Type | Receives |
|---|---|---|
| Supplemental MRI | Experimental | Other: AI selection for supplemental breast MRIWomen randomized to MRI will be examined using a shortened MRI protocol on a Signa Premier 3T MRI scanner. The MRI examination will be reviewed by two radiologists and assigned BI-RADS score. Appropriate clinical work-up will follow according to the BI-RADS score. BI-RADS 3 or higher at initial MRI will be recalled for a second look ultrasound. |
| No MRI (standard-of-care) | No intervention | –Standard-of-care. Both arms will have had a regular screening mammography examination prior to randomization. The "No MRI" arm will have no further intervention. |
Who may qualify
- Ages
- 40 to 74 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- Complete four-view screening mammography examination
Key exclusion criteria (6 listed)
- Women in surveillance program referred from the hereditary cancer unit
- Breast implants
- Prior breast cancer
- Breast feeding
- MRI contraindication requiring radiologist assessment
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI selection for supplemental breast MRIAn AI tool will generate scores used to determine eligibility. Women randomized to MRI will be examined in an MRI scanner. | Other | Supplemental MRI |
Primary outcome
Significantly Delayed Breast Cancer Detection per 1000 women
Time frame: Until 27 months from study inclusion (includes cancer detected at subsequent screening within this time frame). Cancer detected at the initial screening mammography or MRI shall not be included.
Composite end-point defined by either: 1. Interval Cancer, 2. Cancer with lymph node metastasis, 3. Cancer with invasive component larger than 15 mm
11 secondary outcomes
MRI-detected breast cancer
Time frame: Diagnosis during work-up within 2 months of the initial screening MRI
Invasiveness
Time frame: All diagnosed breast cancer within 27 months of study inclusion
Histology
Time frame: All diagnosed breast cancer within 27 months of study inclusion
Lymph node metastasis
Time frame: All diagnosed breast cancer within 27 months of study inclusion
Tumor size
Time frame: All diagnosed breast cancer within 27 months of study inclusion
Receptor status
Time frame: All diagnosed breast cancer within 27 months of study inclusion
Age
Time frame: At study inclusion
Distribution of AI scores
Time frame: At study inclusion
BI-RADS codes
Time frame: At study inclusion and until end of 27 month follow-up
Biopsy result
Time frame: Diagnosis during work-up within 2 months of the MRI examination
Participant questionnaire
Time frame: At study inclusion
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Oct 2023.
- Derived from this study: PubMed 38977914Salim M, Liu Y, Sorkhei M, Ntoula D, Foukakis T, Fredriksson I, Wang Y, Eklund M, Azizpour H, Smith K, Strand F. AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trial. Nat Med. 2024 Sep;30(9):2623-2630. doi: 10.1038/s41591-024-03093-5. Epub 2024 Jul 8.
- Individual participant dataSharing planned: Yes. The final trial dataset will be available for the research team of the principal investigator. Pseudonymized data can be made available for external research audit. Anonymous data may be shared with academic researchers.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Fredrik Strand, MDPhD principal investigator
Karolinska University Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI selection for supplemental breast MRI in people with Breast Cancer, run by Karolinska University Hospital at 1 site in Sweden.
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 6 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: status not confirmed, as of the sponsor's last update on 5 Oct 2023. 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 Sweden. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Significantly Delayed Breast Cancer Detection per 1000 women (time frame: Until 27 months from study inclusion (includes cancer detected at subsequent screening within this time frame). Cancer detected at the initial screening mammography or MRI shall not be included.). 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 NCT04832594, which also lists 1 linked publication.
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 5 Oct 2023.