A decision support system based on radiomics and machine learning to predict the risk of malignancy of ovarian masses from transvaginal ultrasonography and serum CA-125.

Journal: European radiology experimental
Published Date: Jul 26, 2021

Abstract

BACKGROUND: To evaluate the performance of a decision support system (DSS) based on radiomics and machine learning in predicting the risk of malignancy of ovarian masses (OMs) from transvaginal ultrasonography (TUS) and serum CA-125.

Authors

  • Valentina Chiappa
    Department of Gynecologic Oncology, IRCCS National Cancer Institute, Milan, Italy.
  • Matteo Interlenghi
    Institute of Biomedical Imaging and Physiology, National Research Council, 20090, Segrate, Milan, Italy.
  • Giorgio Bogani
    Department of Gynecologic Oncology, IRCCS National Cancer Institute, Milan, Italy. giorgiobogani@yahoo.it.
  • Christian Salvatore
  • Francesca Bertolina
    Department of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Via Venezian 1, 20133, Milan, Italy.
  • Giuseppe Sarpietro
    Department of Gynecologic Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Via Venezian 1, 20133, Milan, Italy.
  • Mauro Signorelli
    Department of Gynecologic Oncology.
  • Dominique Ronzulli
    Clinical Trial Center, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy.
  • Isabella Castiglioni
  • Francesco Raspagliesi
    Department of Gynecologic Oncology, IRCCS National Cancer Institute, Milan, Italy.

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