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This preliminary study aimed to differentiate malignant from benign enhancing foci on breast MRI using radiomic signature. Forty-five patients were included in the study, with 12 malignant lesions and 33 benign lesions. The study showed how feasible a radiomic approach was in the characterization of enhancing foci on breast MRI.

Key points

  • Radiomic signature could distinguish malignant from benign enhancing foci on magnetic resonance imaging of the breast.
  • In this study, we applied a “training with input selection and testing “machine learning algorithm on 45 foci, using 8 confirmed benign lesions and 15 confirmed malignant lesions as reference cases.
  • Over 200 radiomic features were extracted.
  • Overall, a k-nearest neighbour classifier based on 35 selected features showed an over 90% accuracy.

Article: A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI

Authors: Natascha C. D’Amico, Enzo Grossi, Giovanni Valbusa, Francesca Rigiroli, Bernardo Colombo, Massimo Buscema, Deborah Fazzini, Marco Ali, Ala Malasevschi, Gianpaolo Cornalba & Sergio Papa

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