Achieving accurate prostate auto-segmentation on CT in the absence of MR imaging.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PMID: 39419353

Abstract

BACKGROUND: Magnetic resonance imaging (MRI) is considered the gold standard for prostate segmentation. Computed tomography (CT)-based segmentation is prone to observer bias, potentially overestimating the prostate volume by ∼ 30 % compared to MRI. However, MRI accessibility is challenging for patients with contraindications or in rural areas globally with limited clinical resources.

Authors

  • Jingwei Duan
    Department of Radiation Medicine, University of Kentucky, Lexington, Kentucky, USA.
  • Riley C Tegtmeier
    Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
  • Carlos E Vargas
    Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
  • Nathan Y Yu
    Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ (Y.H., J.H., S.H.P., N.Y.Y., W.L.); Cornell University, Ithaca, NY (Y.H.); Department of Electric Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA (Y.H.); and Department of Radiation Oncology, Mayo Clinic, Rochester, MN (A.B., E.L.M., D.K.E., D.M.R., S.S., C.L.H., B.E.B., M.W.).
  • Brady S Laughlin
    Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
  • Jean-Claude M Rwigema
    Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
  • Justin D Anderson
    Mayo Clinic Arizona, Phoenix, AZ, United States.
  • Libing Zhu
    Mayo Clinic Arizona, Phoenix, AZ, United States.
  • Quan Chen
    Management School, Zhongshan Institute, University of Electronic Science and Technology of China, Guangdong, 528402, China.
  • Yi Rong
    Department of Radiation Oncology, University of California Davis Medical Center, Sacramento, CA, United States.

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