A Brief Review of Artificial Intelligence in Genitourinary Oncological Imaging.

Journal: Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Published Date:

Abstract

Genitourinary (GU) system is among the most commonly involved malignancy sites in the human body. Imaging plays a crucial role not only in diagnosis of cancer but also in disease management and its prognosis. However, interpretation of conventional imaging methods such as CT or MR imaging (MRI) usually demonstrates variability across different readers and institutions. Artificial intelligence (AI) has emerged as a promising technology that could improve the patient care by providing helpful input to human readers through lesion detection algorithms and lesion classification systems. Moreover, the robustness of these models may be valuable in automating time-consuming tasks such as organ and lesion segmentations. Herein, we review the current state of imaging and existing challenges in GU malignancies, particularly for cancers of prostate, kidney and bladder; and briefly summarize the recent AI-based solutions to these challenges.

Authors

  • Enis C Yilmaz
    Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Mason J Belue
    Medical Research Scholars Program Fellow, Artificial Intelligence Resource, Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
  • Baris Turkbey
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Caroline Reinhold
    Department of Radiology, McGill University Health Center, Montréal, Québec, Canada.
  • Peter L Choyke
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.