Background Parenchimal EnhancementBD/BPE_CEMNCT06836089
Reproducibility of Breast Density and Background Parenchymal Enhancement Grading on Contrast-Enhanced Mammography With AI Support: A Retrospective Single-Centre Study
An observational study of Background Parenchimal Enhancement and Breast Density, run by Graziella di Grezia at 1 site in Italy.
Trial summary
Retrospective single-centre observational study in women who underwent contrast-enhanced mammography (CEM). It assesses the reproducibility of breast density (BD) and background parenchymal enhancement (BPE) grading by five radiologists with and without AI support, develops linear regression and deep neural network… Read more about this study
- Who is it for?
- Ages 28 to 80 years, women only
- Conditions the study is for
- Background Parenchimal Enhancement, Breast Density, Contrast Enhanced Mammography
- What is being tested?
- Contrast Enhanced Mammography
- How many people
- 213 participants
- Where
- 1 siteItaly
- Study dates
- 1 Jan 2022to 31 Dec 2023
- Phase
- Observational
- 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 28 to 80 years
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: From 314 women who underwent CEM between January 2022 and December 2023 at P.O. "A. Perrino", Brindisi, 213 met the eligibility criteria.
Inclusion Criteria: women aged 28-80 years referred for CEM for diagnostic work-up; histopathology available for BI-RADS 4/5 findings; inclusion not restricted to malignant cases.
Exclusion Criteria: previous history of malignancy; breast biopsy within three weeks before imaging; contraindications to iodinated contrast medium; incomplete imaging records.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Beyond Cancer Detection: An AI Framework for Multidimensional Risk Profiling on Contrast-Enhanced Mammography Acronym: AI-CEM-RISK
Retrospective single-centre observational study in women who underwent contrast-enhanced mammography (CEM). It assesses the reproducibility of breast density (BD) and background parenchymal enhancement (BPE) grading by five radiologists with and without AI support, develops linear regression and deep neural network (DNN) models to predict BD and BPE, tests BD prediction on an external public dataset, and explores a multi-output DNN as a proof of concept for proxy estimates of bone mineral density and systolic blood pressure. This is a secondary analysis of the cohort also described in NCT06838117 and NCT06838130.
Read the detailed description
Women referred for diagnostic CEM at the Interventional Breast Unit of P.O. "A. Perrino", Brindisi, were analyzed. Five breast radiologists independently graded BD (BI-RADS A-D) and BPE (minimal to marked) and consensus served as ground truth. Linear regression and a DNN were compared with a simple linear baseline. Inter-reader agreement was measured with Fleiss' kappa. The external validation used 500 BI-RADS C/D cases from VinDr-Mammo and was restricted to density endpoints. The multi-output analysis was hypothesis-generating; bone density and blood pressure outputs are proxy estimates, not measured values.
- Being tested
- Contrast Enhanced Mammography
- Keywords
- CEM, breast density, background parenchimal enhancement
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Contrast Enhanced MammographyDiagnostic test
Diagnostic Test: contrast-enhanced mammography (Senographe Pristina, GE Healthcare), performed as routine care. Other: AI-assisted grading of breast density and BPE (linear regression and deep neural network).
| Study group | Role | What they receive |
|---|---|---|
| Women undergoing CEM for diagnostic work-up | Women aged 28-80 years referred for CEM at the Interventional Breast Unit, P.O. "A. Perrino", Brindisi. Histopathology was available for BI-RADS 4/5 findings. Receives: Diagnostic Test: Contrast Enhanced Mammography |
What is being measured
The primary outcome is the main question the study is designed to answer.
Inter-reader agreement for breast density and BPE grading, without and with AI support
Fleiss' kappa among five radiologists for BD and for BPE, baseline versus AI-assisted reading.
Measured: Retrospective reading sessions on examinations performed between January 2022 and December 2023
Secondary outcomes (3)
Prediction error (mean squared error) of linear regression and DNN versus a simple linear baseline, for BD and BPE
Measured: Retrospective reading sessions on examinations performed between January 2022 and December 2023
Classification performance (AUC, precision, recall, F1-score) of the models
Measured: Retrospective reading sessions on examinations performed between January 2022 and December 2023
External validation on 500 VinDr-Mammo BI-RADS C/D cases: MSE, R² and AUC for breast density
Measured: Retrospective reading sessions on examinations performed between January 2022 and December 2023
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Feb 2025
- Study start1 Jan 2022
- Primary completion31 Dec 2023
- Study completion31 Dec 2023
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 Background Parenchimal EnhancementStudies of the same condition, open and under way.
- 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
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 213 participants (actual)
Sponsor and investigators
- Lead sponsor
- Graziella di Grezia
- Sponsor type
- University, hospital or other
- Collaborators
- Link Campus University, University of Campania Luigi Vanvitelli
- Responsible party
- Sponsor-investigator, Graziella di Grezia, Link Campus University
- Investigators
- Graziella Di Grezia, medicine and surgery, Principal investigator, Link Campus UniversityGianluca Gatta, medicine and surgery, Study chair, University of Campania Luigi Vanvitelli
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06836089
- Sponsor's protocol ID
- T_3_2025
- Acronym
- BD/BPE_CEM
- Status last verified
- Oct 2026
- First submitted
- 15 Feb 2025
- Last updated
- 3 Nov 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Data are available upon request from the corresponding author
Publications
Di Grezia G, Nazzaro A, Cisternino E, Galiano A, Marinelli L, Mercogliano S, Cuccurullo V, Gatta G. Beyond Cancer Detection: An AI Framework for Multidimensional Risk Profiling on Contrast-Enhanced Mammography. Diagnostics (Basel). 2025 Nov 4;15(21):2788. doi: 10.3390/diagnostics15212788.
PubMed 41226080
Study at a glance
From the registry record, last updated by the sponsor on 3 Nov 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Beyond Cancer Detection: An AI Framework for Multidimensional Risk Profiling on Contrast-Enhanced Mammography Acronym: AI-CEM-RISK
- ClinicalTrials.gov ID
- NCT06836089
- Acronym / sponsor ID
- BD/BPE_CEM / T_3_2025
- Keywords
- CEM, breast density, background parenchimal enhancement
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 213 participants (actual)
- Lead sponsor
- Graziella di GreziaUniversity, hospital or other
- Collaborators
- Link Campus University, University of Campania Luigi Vanvitelli
- Study start
- 1 Jan 2022 (actual)
- Primary completion
- 31 Dec 2023 (actual)
- Study completion
- 31 Dec 2023 (actual)
- First posted
- 20 Feb 2025 (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.
Retrospective single-centre observational study in women who underwent contrast-enhanced mammography (CEM). It assesses the reproducibility of breast density (BD) and background parenchymal enhancement (BPE) grading by five radiologists with and without AI support, develops linear regression and deep neural network (DNN) models to predict BD and BPE, tests BD prediction on an external public dataset, and explores a multi-output DNN as a proof of concept for proxy estimates of bone mineral density and systolic blood pressure. This is a secondary analysis of the cohort also described in NCT06838117 and NCT06838130.
Detailed description
Women referred for diagnostic CEM at the Interventional Breast Unit of P.O. "A. Perrino", Brindisi, were analyzed. Five breast radiologists independently graded BD (BI-RADS A-D) and BPE (minimal to marked) and consensus served as ground truth. Linear regression and a DNN were compared with a simple linear baseline. Inter-reader agreement was measured with Fleiss' kappa. The external validation used 500 BI-RADS C/D cases from VinDr-Mammo and was restricted to density endpoints. The multi-output analysis was hypothesis-generating; bone density and blood pressure outputs are proxy estimates, not measured values.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Women undergoing CEM for diagnostic work-up | – | Diagnostic Test: Contrast Enhanced MammographyWomen aged 28-80 years referred for CEM at the Interventional Breast Unit, P.O. "A. Perrino", Brindisi. Histopathology was available for BI-RADS 4/5 findings. |
Who may qualify
- Ages
- 28 to 80 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- From 314 women who underwent CEM between January 2022 and December 2023 at P.O. "A. Perrino", Brindisi, 213 met the eligibility criteria.
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 |
|---|---|---|
| Contrast Enhanced MammographyDiagnostic Test: contrast-enhanced mammography (Senographe Pristina, GE Healthcare), performed as routine care. Other: AI-assisted grading of breast density and BPE (linear regression and deep neural network). | Diagnostic test | Women undergoing CEM for diagnostic work-up |
Primary outcome
Inter-reader agreement for breast density and BPE grading, without and with AI support
Time frame: Retrospective reading sessions on examinations performed between January 2022 and December 2023
Fleiss' kappa among five radiologists for BD and for BPE, baseline versus AI-assisted reading.
3 secondary outcomes
Prediction error (mean squared error) of linear regression and DNN versus a simple linear baseline, for BD and BPE
Time frame: Retrospective reading sessions on examinations performed between January 2022 and December 2023
Classification performance (AUC, precision, recall, F1-score) of the models
Time frame: Retrospective reading sessions on examinations performed between January 2022 and December 2023
External validation on 500 VinDr-Mammo BI-RADS C/D cases: MSE, R² and AUC for breast density
Time frame: Retrospective reading sessions on examinations performed between January 2022 and December 2023
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Nov 2026.
- Background: PubMed 41226080Di Grezia G, Nazzaro A, Cisternino E, Galiano A, Marinelli L, Mercogliano S, Cuccurullo V, Gatta G. Beyond Cancer Detection: An AI Framework for Multidimensional Risk Profiling on Contrast-Enhanced Mammography. Diagnostics (Basel). 2025 Nov 4;15(21):2788. doi: 10.3390/diagnostics15212788.
- Individual participant dataSharing planned: No. Data are available upon request from the corresponding author
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.
Graziella Di Grezia, medicine and surgery principal investigator
Link Campus University
Gianluca Gatta, medicine and surgery study chair
University of Campania Luigi Vanvitelli
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Background Parenchimal Enhancement and Breast Density, run by Graziella di Grezia at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
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: finished, as of the sponsor's last update on 3 Nov 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 Italy. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Inter-reader agreement for breast density and BPE grading, without and with AI support (time frame: Retrospective reading sessions on examinations performed between January 2022 and December 2023). 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 NCT06836089, 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 3 Nov 2026; AzTrials last refreshed its copy on 7 Nov 2026.