Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics.

Journal: European radiology experimental
Published Date:

Abstract

In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds great promise for improving the quality of life of PCa patients, through managing and processing a vast amount of molecular imaging data and beyond, using a multi-omics approach and improving patients' risk-stratification for tailored medicine. Artificial intelligence (AI) and radiomics may allow clinicians to improve the overall efficiency and accuracy of using these "big data" in both the diagnostic and theragnostic field: from technical aspects (such as semi-automatization of tumor segmentation, image reconstruction, and interpretation) to clinical outcomes, improving a deeper understanding of the molecular environment of PCa, refining personalized treatment strategies, and increasing the ability to predict the outcome. This systematic review aims to describe the current literature on AI and radiomics applied to molecular imaging of prostate cancer.

Authors

  • Virginia Liberini
    Medical Physiopathology - A.O.U. Città della Salute e della Scienza di Torino, Division of Nuclear Medicine, Department of Medical Science, University of Torino, 10126, Torino, Italy. v.liberini@gmail.com.
  • Riccardo Laudicella
    Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, 98125 Messina, Italy.
  • Michele Balma
    Nuclear Medicine Department, S. Croce e Carle Hospital, 12100, Cuneo, Italy.
  • Daniele G Nicolotti
    Nuclear Medicine Department, S. Croce e Carle Hospital, 12100, Cuneo, Italy.
  • Ambra Buschiazzo
    Nuclear Medicine Department, S. Croce e Carle Hospital, 12100, Cuneo, Italy.
  • Serena Grimaldi
    Medical Physiopathology - A.O.U. Città della Salute e della Scienza di Torino, Division of Nuclear Medicine, Department of Medical Science, University of Torino, 10126, Torino, Italy.
  • Leda Lorenzon
    Medical Physics Department, Bolzano Hospital, 39100 Bolzano, Italy.
  • Andrea Bianchi
    Nuclear Medicine, Santa Croce e Carle Hospital, Cuneo, Italy.
  • Simona Peano
    Nuclear Medicine Department, S. Croce e Carle Hospital, 12100, Cuneo, Italy.
  • Tommaso Vincenzo Bartolotta
    Department of Radiology, Fondazione Istituto G. Giglio, Ct.da Pietrapollastra, Cefalù, Palermo, Italy.
  • Mohsen Farsad
    Nuclear Medicine, Central Hospital Bolzano, 39100, Bolzano, Italy.
  • Sergio Baldari
    Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, 98125 Messina, Italy.
  • Irene A Burger
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland.
  • Martin W Huellner
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland.
  • Alberto Papaleo
    Nuclear Medicine Department, S. Croce e Carle Hospital, 12100, Cuneo, Italy.
  • Désirée Deandreis
    Medical Physiopathology - A.O.U. Città della Salute e della Scienza di Torino, Division of Nuclear Medicine, Department of Medical Science, University of Torino, 10126, Torino, Italy.