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A new automated method to evaluate 2D mammographic breast density according to BI-RADS® Atlas Fifth Edition recommendations

  • Breast
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Abstract

Objectives

Radiologists’ visual assessment of breast mammographic density (BMD) is subject to inter-observer variability. We aimed to develop and validate a new automated software tool mimicking expert radiologists’ consensus assessments of 2D BMD, as per BI-RADS V recommendations.

Methods

The software algorithm was developed using a concept of Manhattan distance to compare a patient’s mammographic image to reference mammograms with an assigned BMD category. Reference databases were built from a total of 2289 pairs (cranio-caudal and medio-lateral oblique views) of 2D full-field digital mammography (FFDM). Each image was independently assessed for BMD by a consensus of radiologists specialized in breast imaging. A validation set of additional 800 image pairs was evaluated for BMD both by the software and seven blinded radiologists specialized in breast imaging. The median score was used for consensus. Software reproducibility was assessed using FFDM image pairs from 214 patients in the validation set to compare BMD assessment between left and right breasts.

Results

The software showed a substantial agreement with the radiologists’ consensus (unweighted κ = 0.68, 95% CI 0.64–0.72) when considering the four breast density categories, and an almost perfect agreement (unweighted κ = 0.84, 95% CI 0.80–0.88) when considering clinically significant non-dense (A-B) and dense (C-D) categories. Correlation between left and right breasts was high (rs = 0.87; 95% CI 0.84–0.90).

Conclusions

BMD assessment by the software was strongly correlated to radiologists’ consensus assessments of BMD. Its performance should be compared to other methods, and its clinical utility evaluated in a risk assessment model.

Key Points

• A new software tool assesses breast density in a standardized way.

• The tool mimics radiologists’ clinical assessment of breast density.

• It may be incorporated in a breast cancer risk assessment model.

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Abbreviations

BI-RADS:

Breast Imaging Reporting and Data System

BMD:

Breast mammographic density

CC:

Cranio-caudal

DBT:

Digital breast tomosynthesis

Md:

Manhattan distance

MLO:

Medio-lateral oblique

MQSA:

Mammography Quality Standards Act

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Acknowledgments

The authors would like to thank Sylvie Phung (Predlife, France) for her technical support and Sandra Canale (Gustave Roussy, France) for her clinical support.

Funding

This study has received funding by Fondation ARC pour la Recherche.

Author information

Authors and Affiliations

  1. Imaging Department, Gustave Roussy, 114 rue Edouard Vaillant, 94800, Villejuif, France

    Corinne Balleyguier, Julia Arfi-Rouche, Bruno Boyer, Ara Loshkajian & Suzette Delaloge

  2. Predlife, Espace Maurice Tubiana, 39 rue Camille Desmoulins, 94800, Villejuif, France

    Emilien Gauthier, Valerie Helin & Stephane Ragusa

Authors
  1. Corinne Balleyguier
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  2. Julia Arfi-Rouche
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  3. Bruno Boyer
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  4. Emilien Gauthier
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  5. Valerie Helin
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  6. Ara Loshkajian
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  7. Stephane Ragusa
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  8. Suzette Delaloge
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Corresponding author

Correspondence to Corinne Balleyguier.

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Guarantor

The scientific guarantor of this publication is Dr. Corinne Balleyguier.

Conflict of interest

Emilien Gauthier, Valerie Helin, and Stephane Ragusa, authors of this manuscript, declare relationships with Predlife (Villejuif, France). Predlife, which developed the DenSeeMammo algorithm, did not support the study, but provided their software tool for the study. Non-employee authors had complete control of the data and information that might present a conflict of interest to the authors who are employees of Predlife.

Statistics and biometry

One of the authors has significant statistical expertise.

Informed consent

Written informed consent was not required for this study because it is a retrospective analysis of imaging datasets.

Ethical approval

Institutional review board approval was obtained.

Methodology

• retrospective

• observational

• multicenter study

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Balleyguier, C., Arfi-Rouche, J., Boyer, B. et al. A new automated method to evaluate 2D mammographic breast density according to BI-RADS® Atlas Fifth Edition recommendations. Eur Radiol 29, 3830–3838 (2019). https://doi.org/10.1007/s00330-019-06016-y

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  • DOI: https://doi.org/10.1007/s00330-019-06016-y

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