Robust evaluation of tissue-specific radiomic features for classifying breast tissue density grades.

Journal: Journal of medical imaging (Bellingham, Wash.)
Published Date: May 29, 2025

Abstract

PURPOSE: Breast cancer risk depends on an accurate assessment of breast density due to lesion masking. Although governed by standardized guidelines, radiologist assessment of breast density is still highly variable. Automated breast density assessment tools leverage deep learning but are limited by model robustness and interpretability.

Authors

  • Vincent Dong
    University of Pennsylvania, Department of Bioengineering, Philadelphia, Pennsylvania, United States.
  • Walter Mankowski
    Columbia University, Department of Radiology, New York, United States.
  • Telmo M Silva Filho
    Universidade Federal de Pernambuco, Centro de Informática, Av. Jornalista Aníbal Fernandes, s/n, 50.740-560 Recife (PE), Brazil. Electronic address: tmsf@cin.ufpe.br.
  • Anne Marie McCarthy
    University of Pennsylvania, Department of Biostatistics, Epidemiology and Informatics, Philadelphia, Pennsylvania, United States.
  • Despina Kontos
    Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States.
  • Andrew D A Maidment
    Department of Radiology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA.
  • Bruno Barufaldi
    Department of Radiology, University of Pennsylvania, 3400 Spruce Str., Philadelphia, PA 19104, USA.

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