AI-Enhanced Analysis of Breast Density and Background Parenchymal Enhancement (BPE)

NCT06838130 | Enrolling By Invitation

• 1 other identifier: T_6_2025
• Study Type: observational
• Target: 213
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Breast Parenchimal Enhancement; Artificial Intelligence (AI)

Outcome Measures

Primary Outcomes (1)

• 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.

  Data analysis within 12 months of study completion.

Secondary Outcomes (3)

• AI-based optimization of breast density and BPE classification

  Within 12 months of study completion

• Comparative performance of multiple linear regression vs. AI models.

  Within 12 months of study completion.

• Mean Squared Error (MSE) and explained variance in predictive models

  Within 12 months of study completion

Study Arms (1)

patiens underwent CEM

Eligibility Criteria

• Age: 18 Years+
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

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.

You may not qualify if:

• Patients with prior breast cancer treatment that could alter BPE.
• Incomplete imaging or missing classification data.
• Contraindications to contrast-enhanced imaging.

Sponsors & Collaborators

• Link Campus University: lead
• University of Campania Luigi Vanvitelli: collaborator

Study Sites (1)

University of Campania Luigi Vanvitelli

Naples, 80138, Italy

Location

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: February 15, 2025
• First Posted: February 20, 2025
• Study Start: May 1, 2022
• Primary Completion: June 30, 2023
• Study Completion: February 1, 2025
• Last Updated: February 20, 2025

Record last verified: 2025-02

Data Sharing

• IPD Sharing: Will not share

Locations

IT (1)