MRI-based prostate cancer classification using 3D efficient capsule network.

Journal: Medical physics
Published Date: Feb 12, 2024

Abstract

BACKGROUND: Prostate cancer (PCa) is the most common cancer in men and the second leading cause of male cancer-related death. Gleason score (GS) is the primary driver of PCa risk-stratification and medical decision-making, but can only be assessed at present via biopsy under anesthesia. Magnetic resonance imaging (MRI) is a promising non-invasive method to further characterize PCa, providing additional anatomical and functional information. Meanwhile, the diagnostic power of MRI is limited by qualitative or, at best, semi-quantitative interpretation criteria, leading to inter-reader variability.

Authors

  • Yuheng Li
    Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Jacob Wynne
    Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Jing Wang
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Justin Roper
    Radiology Oncology, Emory University, 1365 Clifton Road, Department of Radiation Oncology, Atlanta, Atlanta, Georgia, 30322, UNITED STATES.
  • Chih-Wei Chang
    Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30308, United States of America.
  • Ashish B Patel
    Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, United States of America.
  • Joseph Shelton
    Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA, United States of America.
  • Tian Liu
    Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA.
  • Hui Mao
  • Xiaofeng Yang
    Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA.

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