Machine learning-based discrimination of benign and malignant breast lesions on US: The contribution of shear-wave elastography.

Journal: European journal of radiology
PMID: 39442348

Abstract

PURPOSE: To build and validate a combined radiomics and machine learning (ML) approach using B-mode US and SWE images to differentiate benign from malignant solid breast lesions (BLs) and compare its performance with that of an expert radiologist.

Authors

  • Ludovica Rita La Rocca
    Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.
  • Martina Caruso
    Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via S. Pansini 5, 80131, Naples, Italy.
  • Arnaldo Stanzione
    Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
  • Nicola Rocco
    G.RE.T.A. Group for Reconstructive and Therapeutic Advancements, Catania, Italy.
  • Tommaso Pellegrino
    Azienda Ospedaliera Universitaria Federico II, Naples, Italy.
  • Daniela Russo
    Dipartimento di Scienze, Università degli Studi della Basilicata, via dell'Ateneo Lucano, 10-85100, Potenza, Italy.
  • Maria Salatiello
    Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.
  • Andrea de Giorgio
    Artificial Engineering, Naples, Italy.
  • Roberta Pastore
    Azienda Ospedaliera Universitaria Federico II, Naples, Italy.
  • Simone Maurea
    Department of Advanced Biomedical Sciences, University of Naples "Federico II,", Naples, Italy.
  • Arturo Brunetti
    Department of Advanced Biomedical Sciences, University of Naples "Federico II,", Naples, Italy.
  • Renato Cuocolo
    Department of Medicine, Surgery and Dentistry, University of Salerno, Baronissi, Italy.
  • Valeria Romeo
    Department of Advanced Biomedical Sciences, University of Naples "Federico II,", Naples, Italy.

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