ROI-Based Quantitative Analysis in Contrast-Enhanced Mammography: A Feasibility Study for Reproducible Enhancement Assessment

Background/Objectives: Contrast-enhanced mammography (CEM) has demonstrated high diagnostic accuracy in breast lesion detection and characterization. However, interpretation of enhancement intensity remains largely qualitative and subject to interobserver variability. This study aimed to evaluate the feasibility and reproducibility of a standardized region-of-interest (ROI)-based quantitative approach for enhancement assessment in CEM. Methods: In this single-center prospective study, 22 women undergoing CEM for suspicious findings on conventional breast imaging were enrolled, yielding a total of 27 lesions. Quantitative analysis was performed on recombined mediolateral oblique images acquired in both the early and delayed post-contrast phases. Three radiologists with different levels of experience independently performed ROI measurements using two standardized ellipsoidal ROI sizes (0.1 cm2 and 0.2 cm2). ROIs were systematically positioned on the lesion, fibroglandular tissue, subcutaneous fat, and pectoralis major muscle. Relative ROI (rROI) metrics were calculated to reduce variability related to acquisition and post-processing factors. The primary normalized parameter was the lesion-to-parenchyma ratio (nROI). Histopathology served as the reference standard. Results: Of the 27 lesions, eight were benign (29.6%), eight were high-risk/B3 lesions (29.6%), and 11 were malignant (40.7%). Breast density categories were B in 11 lesions (40.7%), C in 13 lesions (48.1%), and D in three lesions (11.1%). Inter-reader reproducibility was good to excellent. Absolute lesion gray-scale values showed excellent agreement, with intraclass correlation coefficient (ICC) values ranging from 0.941 to 0.974, while nROI showed good reproducibility, with ICC values ranging from 0.861 to 0.894. No significant inter-reader differences were observed for normalized ratios. Comparison between ROI sizes showed small but statistically significant early phase differences for nROI, with median values of 1.009 for 0.1 cm2 ROIs and 1.005 for 0.2 cm2 ROIs (median paired difference −0.002; p = 0.002). Early phase nROI measured with the 0.1 cm2 ROI differed significantly across breast density categories, increasing from density B to D (0.996, 1.010, and 1.015, respectively; p = 0.026). Conclusions: Standardized ROI-based quantitative analysis in CEM is feasible, and normalized enhancement ratios showed good inter-reader agreement, suggesting their potential to reduce variability related to subjective visual assessment and technical acquisition factors. Consequently, the proposed method provides a reproducible methodological framework for future larger studies aimed at validating quantitative CEM metrics.

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Journal
Diagnostics
Published
2026-08-17
DOI
https://doi.org/10.3390/diagnostics16162602
Primary Topic
Digital Radiography and Breast Imaging
Type
article
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article

ROI-Based Quantitative Analysis in Contrast-Enhanced Mammography: A Feasibility Study for Reproducible Enhancement Assessment

Daniele Ugo Tari, Davide Raffaele De Lucia, M Sacco, Marika Santarsiere et al.
Diagnostics
Digital Radiography and Breast Imaging
article

ROI-Based Quantitative Analysis in Contrast-Enhanced Mammography: A Feasibility Study for Reproducible Enhancement Assessment

Daniele Ugo Tari, Davide Raffaele De Lucia, M Sacco, Marika Santarsiere, Rosalinda Santonastaso
article en

Abstract

Background/Objectives: Contrast-enhanced mammography (CEM) has demonstrated high diagnostic accuracy in breast lesion detection and characterization. However, interpretation of enhancement intensity remains largely qualitative and subject to interobserver variability. This study aimed to evaluate the feasibility and reproducibility of a standardized region-of-interest (ROI)-based quantitative approach for enhancement assessment in CEM. Methods: In this single-center prospective study, 22 women undergoing CEM for suspicious findings on conventional breast imaging were enrolled, yielding a total of 27 lesions. Quantitative analysis was performed on recombined mediolateral oblique images acquired in both the early and delayed post-contrast phases. Three radiologists with different levels of experience independently performed ROI measurements using two standardized ellipsoidal ROI sizes (0.1 cm2 and 0.2 cm2). ROIs were systematically positioned on the lesion, fibroglandular tissue, subcutaneous fat, and pectoralis major muscle. Relative ROI (rROI) metrics were calculated to reduce variability related to acquisition and post-processing factors. The primary normalized parameter was the lesion-to-parenchyma ratio (nROI). Histopathology served as the reference standard. Results: Of the 27 lesions, eight were benign (29.6%), eight were high-risk/B3 lesions (29.6%), and 11 were malignant (40.7%). Breast density categories were B in 11 lesions (40.7%), C in 13 lesions (48.1%), and D in three lesions (11.1%). Inter-reader reproducibility was good to excellent. Absolute lesion gray-scale values showed excellent agreement, with intraclass correlation coefficient (ICC) values ranging from 0.941 to 0.974, while nROI showed good reproducibility, with ICC values ranging from 0.861 to 0.894. No significant inter-reader differences were observed for normalized ratios. Comparison between ROI sizes showed small but statistically significant early phase differences for nROI, with median values of 1.009 for 0.1 cm2 ROIs and 1.005 for 0.2 cm2 ROIs (median paired difference −0.002; p = 0.002). Early phase nROI measured with the 0.1 cm2 ROI differed significantly across breast density categories, increasing from density B to D (0.996, 1.010, and 1.015, respectively; p = 0.026). Conclusions: Standardized ROI-based quantitative analysis in CEM is feasible, and normalized enhancement ratios showed good inter-reader agreement, suggesting their potential to reduce variability related to subjective visual assessment and technical acquisition factors. Consequently, the proposed method provides a reproducible methodological framework for future larger studies aimed at validating quantitative CEM metrics.

DiagnosticsVol. 16(16)
University of Campania "Luigi Vanvitelli" (IT), Regional Health (US)
Gender equality
Openalex Percentile: Top 10%
Digital Radiography and Breast Imaging
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