Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images

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Abstract

Objective evaluation of new and improved methods for PET imaging requires access to images with ground truth, as can be obtained through simulation studies. However, for these studies to be clinically relevant, it is important that the simulated images are clinically realistic. In this study, we develop a stochastic and physics-based method to generate realistic oncological two-dimensional (2-D) PET images, where the ground-truth tumor properties are known. The developed method extends upon a previously proposed approach. The approach captures the observed variabilities in tumor properties from actual patient population. Further, we extend that approach to model intra-tumor heterogeneity using a lumpy object model. To quantitatively evaluate the clinical realism of the simulated images, we conducted a human-observer study. This was a two-alternative forced-choice (2AFC) study with trained readers (five PET physicians and one PET physicist). Our results showed that the readers had an average of ∼50% accuracy in the 2AFC study. Further, the developed simulation method was able to generate wide varieties of clinically observed tumor types. These results provide evidence for the application of this method to 2-D PET imaging applications, and motivate development of this method to generate 3-D PET images.

Original languageEnglish
Title of host publicationMedical Imaging 2021
Subtitle of host publicationImage Perception, Observer Performance, and Technology Assessment
EditorsFrank W. Samuelson, Sian Taylor-Phillips
PublisherSPIE
ISBN (Electronic)9781510640276
DOIs
StatePublished - 2021
EventMedical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment - Virtual, Online
Duration: Feb 15 2021Feb 19 2021

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11599
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment
CityVirtual, Online
Period02/15/2102/19/21

Keywords

  • image quality assessment
  • lung cancer
  • observer study
  • positron emission tomography
  • simulation

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