AI-Enhanced Analysis of Breast Density and Background Parenchymal Enhancement (BPE)
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Breast Parenchimal Enhancement, Artificial Intelligence (AI). Basic parameters: from 18 years · Female.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Italy
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Overview
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.
Primary outcome measures
- Correlation between breast density, BPE, and age using AI-driven analysis. [Time frame: Data analysis within 12 months of study completion.]
Secondary outcome measures (3)
- AI-based optimization of breast density and BPE classification [Time frame: Within 12 months of study completion]
- Comparative performance of multiple linear regression vs. AI models. [Time frame: Within 12 months of study completion.]
- Mean Squared Error (MSE) and explained variance in predictive models [Time frame: Within 12 months of study completion]
Eligibility criteria
Patients who underwent CEM, mammography, and ultrasound between May 2022 and June 2023.
Availability of BPE assessment, BI-RADS density classification, and age data.
Complete dataset available for statistical and AI-based analysis.
Exclusion criteria
Patients with prior breast cancer treatment that could alter BPE.
Incomplete imaging or missing classification data.
Contraindications to contrast-enhanced imaging.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
Italy · 1 center
- University of Campania Luigi Vanvitelli — Naples
Identifiers
NCT: NCT06838130 · T_6_2025