Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance.

Journal: La Radiologia medica
Published Date: Mar 23, 2022

Abstract

PURPOSE: To evaluate stability and machine learning-based classification performance of radiomic features of spine bone tumors using diffusion- and T2-weighted magnetic resonance imaging (MRI).

Authors

  • Salvatore Gitto
    Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milano, Italy. Electronic address: sal.gitto@gmail.com.
  • Marco Bologna
    Department of Electronics, Information and Bioengineering (DEIB), Politecnico Di Milano, Via Golgi 39, 20133, Milan, Italy. marco.bologna@polimi.it.
  • Valentina D A Corino
    Department of Electronics, Information and Bioengineering (DEIB), Politecnico Di Milano, Via Golgi 39, 20133, Milan, Italy.
  • Ilaria Emili
    Scuola Di Specializzazione in Radiodiagnostica, Università Degli Studi Di Milano, 20122, Milan, Italy.
  • Domenico Albano
    IRCCS Istituto Ortopedico Galeazzi, Milano, Italy; Sezione di Scienze Radiologiche, Dipartimento di Biomedicina, Neuroscienze e Diagnostica Avanzata, Università degli Studi di Palermo, Palermo, Italy.
  • Carmelo Messina
    Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milano, Italy; IRCCS Istituto Ortopedico Galeazzi, Milano, Italy.
  • Elisabetta Armiraglio
    Pathology Department, ASST Pini-CTO, 20122, Milan, Italy.
  • Antonina Parafioriti
    Pathology Department, ASST Pini-CTO, Milano, Italy.
  • Alessandro Luzzati
    IRCCS Istituto Ortopedico Galeazzi, Milano, Italy.
  • Luca Mainardi
    Department of ElectronicsInformation and BioengineeringPolitecnico di Milano 20133 Milan Italy.
  • Luca Maria Sconfienza
    Unit of Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.

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