Development and clinical implementation of an MRI-only planning workflow featuring deep learning-based synthetic CT for prostate cancer external beam radiotherapy.

Journal: Journal of applied clinical medical physics
Published Date: Sep 1, 2025

Abstract

BACKGROUND: In external beam radiation therapy (EBRT) for prostate cancer, both MRI and CT are typically used-CT provides electron density for dose calculation and visualization of bony anatomy and fiducial markers, while MRI offers superior soft tissue contrast. With recent advances in deep learning, synthetic CT (sCT) images can now be generated from MRI, potentially eliminating the need for separate CT scans.

Authors

  • Jie Deng
    Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, 1653 W. Congress Pkwy, Chicago, IL 60612, USA. Electronic address: Jie_deng@rush.edu.
  • Xiao Liang
    Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agricultural University, Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, Beijing Laboratory for Food Quality and Safety, Beijing, 100193, People's Republic of China; College of Veterinary Medicine, Qingdao Agricultural University, Qingdao, 266109, People's Republic of China.
  • Viktor Iakovenko
    Department of Radiation Oncology, University of Texas Southwestern Medical Center, Texas, USA.
  • Boyu Meng
    Department of Radiation Medicine & Applied Sciences, Medical Physics Division, University of California San Diego, La Jolla, California, USA.
  • Junjie Wu
  • Weiguo Lu
    Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America.
  • Raquibul Hannan
    Medical Artificial Intelligence and Automation Laboratory and Department of Radiation Oncology,University of Texas Southwestern Medical Center, Dallas, Texas, United States.
  • Neil Desai
    Medical Artificial Intelligence and Automation Laboratory and Department of Radiation Oncology,University of Texas Southwestern Medical Center, Dallas, Texas, United States.
  • Daniel Yang
    Kaiser Permanente, Oakland, CA, USA.
  • Aurelie Garant
    Medical Artificial Intelligence and Automation Laboratory and Department of Radiation Oncology,University of Texas Southwestern Medical Center, Dallas, Texas, United States.
  • Yang Kyun Park
    Department of Radiation Oncology, University of Texas Southwestern Medical Center, Texas, USA.
  • Mu-Han Lin
    Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas.
  • Steve Jiang
  • Andrew Godley
    Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas.

Keywords

External Resources

Popular Topics
Recent Journals