From Variability to Standardization: The Impact of Breast Density on Background Parenchymal Enhancement in Contrast-Enhanced Mammography and the Need for a Structured Reporting System.

Simple Summary: Contrast-enhanced mammography (CEM) is increasingly used in breast cancer diagnostics, especially for women with dense breast tissue. However, interpreting background parenchymal enhancement (BPE)—a normal tissue reaction to contrast—is still subjective due to the lack of a standardi...

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Publicado en:Cancers Vol. 17; no. 15; pp. 2523 - 2535
Autores principales: Di Grezia, Graziella, Nazzaro, Antonio, Schiavone, Luigi, Elisa, Cisternino, Galiano, Alessandro, Gianluca, Gatta, Vincenzo, Cuccurullo, Scaglione, Mariano
Formato: research tables/charts Journal Article
Publicado: MDPI Aug2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2025
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      pub: MDPI
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        10.3390/cancers17152523
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        atl: From Variability to Standardization: The Impact of Breast Density on Background Parenchymal Enhancement in Contrast-Enhanced Mammography and the Need for a Structured Reporting System.
      aug:
        au:
          Di Grezia, Graziella
          Nazzaro, Antonio
          Schiavone, Luigi
          Elisa, Cisternino
          Galiano, Alessandro
          Gianluca, Gatta
          Vincenzo, Cuccurullo
          Scaglione, Mariano
        affil: Department of Radiology, Link Campus University, 00165 Rome, Italy
      sug:
        subj:
          Breast Neoplasms Diagnosis
          Breast Neoplasms Classification
          Cancer Screening Methods
          Breast Tissue Density
          Mammography
          Contrast Media
          Image Enhancement
          Image Interpretation, Computer Assisted
          Human
          Female
          Adult
          Middle Age
          Aged
          Aged, 80 and Over
          Italy
          Retrospective Design
          Record Review
          Scales
          Breast Ultrasonography
          Breast Radiography
          Database Management Software
          Descriptive Statistics
          Multiple Linear Regression
          kappa Statistic
          Analysis of Variance
          Breast Neoplasms Risk Factors
          Risk Assessment
          Artificial Intelligence
          Neural Networks (Computer)
          Confidence Intervals
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Aged, 80 & over
          Female
      ab: Simple Summary: Contrast-enhanced mammography (CEM) is increasingly used in breast cancer diagnostics, especially for women with dense breast tissue. However, interpreting background parenchymal enhancement (BPE)—a normal tissue reaction to contrast—is still subjective due to the lack of a standardized system. This study introduces the Breast Contrast Standard Scale (BCSS), a new four-level system designed specifically for CEM to assess BPE consistently. The results show that higher breast density is linked to stronger BPE, and the proposed scale demonstrated excellent agreement between different radiologists. Standardizing BPE assessment could improve diagnostic accuracy and support personalized screening strategies in clinical practice. Introduction: Breast density is a well-recognized factor in breast cancer risk assessment, with higher density linked to increased malignancy risk and reduced sensitivity of conventional mammography. Background parenchymal enhancement (BPE), observed in contrast-enhanced imaging, reflects physiological contrast uptake in non-pathologic breast tissue. While extensively characterized in breast MRI, the role of BPE in contrast-enhanced mammography (CEM) remains uncertain due to inconsistent findings regarding its correlation with breast density and cancer risk. Unlike breast density—standardized through the ACR BI-RADS lexicon—BPE lacks a uniform classification system in CEM, leading to variability in clinical interpretation and research outcomes. To address this gap, we introduce the BPE-CEM Standard Scale (BCSS), a structured four-tiered classification system specifically tailored to the two-dimensional characteristics of CEM, aiming to improve consistency and diagnostic alignment in BPE evaluation. Materials and Methods: In this retrospective single-center study, 213 patients who underwent mammography (MG), ultrasound (US), and contrast-enhanced mammography (CEM) between May 2022 and June 2023 at the "A. Perrino" Hospital in Brindisi were included. Breast density was classified according to ACR BI-RADS (categories A–D). BPE was categorized into four levels: Minimal (< 10% enhancement), Light (10–25%), Moderate (25–50%), and Marked (> 50%). Three radiologists independently assessed BPE in a subset of 50 randomly selected cases to evaluate inter-observer agreement using Cohen's kappa. Correlations between BPE, breast density, and age were examined through regression analysis. Results: BPE was Minimal in 57% of patients, Light in 31%, Moderate in 10%, and Marked in 2%. A significant positive association was found between higher breast density (BI-RADS C–D) and increased BPE (p < 0.05), whereas lower-density breasts (A–B) were predominantly associated with minimal or light BPE. Regression analysis confirmed a modest but statistically significant association between breast density and BPE (R2 = 0.144), while age showed no significant effect. Inter-observer agreement for BPE categorization using the BCSS was excellent (κ = 0.85; 95% CI: 0.78–0.92), supporting its reproducibility. Conclusions: Our findings indicate that breast density is a key determinant of BPE in CEM. The proposed BCSS offers a reproducible, four-level framework for standardized BPE assessment tailored to the imaging characteristics of CEM. By reducing variability in interpretation, the BCSS has the potential to improve diagnostic consistency and facilitate integration of BPE into personalized breast cancer risk models. Further prospective multicenter studies are needed to validate this classification and assess its clinical impact.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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