---
title: AI-Enhanced Analysis of Breast Density and Background Parenchymal Enhancement (BPE)
nct_id: NCT06838130
overall_status: ENROLLING_BY_INVITATION
sponsor: Link Campus University
study_type: OBSERVATIONAL
primary_condition: Breast Parenchimal Enhancement
countries: Italy
canonical_url: "https://parkinsonspathways.com/agent/trials/NCT06838130.md"
clinicaltrials_gov: "https://clinicaltrials.gov/study/NCT06838130"
ct_last_update_post_date: 2025-02-20
last_seen_at: "2026-05-12T07:17:27.713Z"
source: ClinicalTrials.gov (mirrored, no enrichment)
---
# AI-Enhanced Analysis of Breast Density and Background Parenchymal Enhancement (BPE)

**NCT ID:** [NCT06838130](https://clinicaltrials.gov/study/NCT06838130)

## Key Facts

- **Status:** ENROLLING_BY_INVITATION
- **Study Type:** OBSERVATIONAL
- **Target Enrollment:** 213
- **Lead Sponsor:** Link Campus University
- **Collaborators:** University of Campania Luigi Vanvitelli
- **Conditions:** Breast Parenchimal Enhancement, Artificial Intelligence (AI)
- **Start Date:** 2022-05-01
- **Completion Date:** 2025-02
- **CT.gov Last Update:** 2025-02-20

## 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.

## Eligibility

- **Minimum age:** 18 Years
- **Sex:** FEMALE
- **Healthy Volunteers:** No

```
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.
```

## Arms

- **patiens underwent CEM**

## Primary Outcomes

- **Correlation between breast density, BPE, and age using AI-driven analysis.** _(time frame: Data analysis within 12 months of study completion.)_ — Evaluating whether AI models, including neural networks, can enhance prediction accuracy for BPE assessment compared to conventional multiple linear regression.

## Secondary Outcomes

- **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)_

## Locations (1)

- University of Campania Luigi Vanvitelli, Naples, Italy

## Recent Field Changes (last 30 days)

- `design.enrollmentCount` — added _(2026-05-12)_
- `status.overallStatus` — added _(2026-05-12)_
- `status.primaryCompletionDate` — added _(2026-05-12)_
- `status.completionDate` — added _(2026-05-12)_
- `status.lastUpdatePostDate` — added _(2026-05-12)_
- `eligibility.criteria` — added _(2026-05-12)_
- `eligibility.minAge` — added _(2026-05-12)_
- `eligibility.sex` — added _(2026-05-12)_
- `outcomes.primary` — added _(2026-05-12)_
- `outcomes.secondary` — added _(2026-05-12)_
- `armsInterventions.arms` — added _(2026-05-12)_
- `sponsor.lead` — added _(2026-05-12)_
- `sponsor.collaborators` — added _(2026-05-12)_
- `results.hasResults` — added _(2026-05-12)_
- `locations.university of campania luigi vanvitelli|naples||italy` — added _(2026-05-12)_

---

*Canonical: https://parkinsonspathways.com/agent/trials/NCT06838130.md*  
*Source data (authoritative): https://clinicaltrials.gov/study/NCT06838130*  
*This page is a raw mirror with no AI summary, no editorial enrichment, and no Parkinson's-specific filtering.*