Quantification of uptake in pelvis F-18 FLT PET-CT images using a 3D localization and segmentation CNN.

Journal: Medical physics
Published Date: Mar 1, 2022

Abstract

PURPOSE: The purpose of this work was to develop and validate a deep convolutional neural network (CNN) approach for the automated pelvis segmentation in computed tomography (CT) scans to enable the quantification of active pelvic bone marrow by means of Fluorothymidine F-18 (FLT) tracer uptake measurement in positron emission tomography (PET) scans. This quantification is a critical step in calculating bone marrow dose for radiopharmaceutical therapy clinical applications as well as external beam radiation doses.

Authors

  • Xiaofan Xiong
    Department of Biomedical Engineering, The University of Iowa, Iowa City, IA, 52242, USA.
  • Brian J Smith
    Department of Biostatistics, University of Iowa, 145 N. Riverside Drive, 100 CPHB, Iowa City, IA, 52242, USA.
  • Stephen A Graves
    Department of Radiology, The University of Iowa, Iowa City, Iowa, USA.
  • John J Sunderland
    Department of Radiology, The University of Iowa, Iowa City, IA, 52242, USA.
  • Michael M Graham
    Department of Radiology, The University of Iowa, Iowa City, IA, 52242, USA.
  • Brandie A Gross
    Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA.
  • John M Buatti
    Department of Radiation Oncology, Carver College of Medicine, University of Iowa Carver College of Medicine, LL-W Pomerantz Family Pavilion, 200 Hawkins Drive, Iowa City, IA, 52242-1089, USA.
  • Reinhard R Beichel
    Iowa Institute for Biomedical Imaging, Department of Electrical and Computer Engineering, Department of Internal Medicine, The University of Iowa, Iowa City, 52242, IA, USA.

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