Breast Parenchimal EnhancementNCT06838130
AI-Enhanced Analysis of Breast Density and Background Parenchymal Enhancement (BPE)
An observational study of Breast Parenchimal Enhancement and Artificial Intelligence (AI), run by Link Campus University at 1 site in Italy.
Trial summary
This study expands upon previous research investigating the correlation between breast density, Background Parenchymal Enhancement (BPE), and age in contrast-enhanced mammography (CEM). Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Breast Parenchimal Enhancement, Artificial Intelligence (AI)
- How many people
- 213 participants
- Where
- 1 siteItaly
- Study dates
- 1 May 2022to Feb 2025
- Phase
- Observational
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 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: Women aged 18 years and older who underwent CEM for diagnostic or surveillance purposes. Patients with recorded BPE levels and BI-RADS breast density classification. Relational database containing structured data for correlation matrix analysis and AI model training.
Who may be able to join
None listed.
Who cannot join
- Patients with prior breast cancer treatment that could alter BPE.
- Incomplete imaging or missing classification data.
- Contraindications to contrast-enhanced imaging.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
About this study
This study expands upon previous research investigating the correlation between breast density, Background Parenchymal Enhancement (BPE), and age in contrast-enhanced mammography (CEM). By integrating Artificial Intelligence (AI) methodologies, including Artificial Neural Networks (ANNs) and deep learning models, the study aims to optimize the accuracy of predictions and validate prior findings obtained through multiple linear regression.
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| patiens underwent CEM | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Correlation between breast density, BPE, and age using AI-driven analysis.
Evaluating whether AI models, including neural networks, can enhance prediction accuracy for BPE assessment compared to conventional multiple linear regression.
Measured: Data analysis within 12 months of study completion.
Secondary outcomes (3)
AI-based optimization of breast density and BPE classification
Evaluating the performance of neural networks in predicting BPE levels across different breast density categories.
Measured: Within 12 months of study completion
Comparative performance of multiple linear regression vs. AI models.
Assessing the accuracy of traditional statistical methods versus ANN-based predictions in explaining variance in BPE values.
Measured: Within 12 months of study completion.
Mean Squared Error (MSE) and explained variance in predictive models
Analyzing the error rates and variance explained by different AI models compared to multiple linear regression.
Measured: Within 12 months of study completion
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 May 2022
- Primary completion30 Jun 2023
- Study completionFeb 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast 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 (estimated)
Sponsor and investigators
- Lead sponsor
- Link Campus University
- Sponsor type
- University, hospital or other
- Collaborators
- University of Campania Luigi Vanvitelli
- Responsible party
- Principal investigator, Graziella di Grezia, Link Campus University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06838130
- Sponsor's protocol ID
- T_6_2025
- Status last verified
- Feb 2025
- First submitted
- 15 Feb 2025
- Last updated
- 20 Feb 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No