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Attenuation Correction and Quantitative PET Analysis

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Hybrid PET/MR Neuroimaging

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Abstract

The nature of PET is quantitative which allows it to measure precise physiology across various systems in the human body. In order to produce these quantitatively accurate PET images for in-depth analysis, several corrections are needed to get quantitatively accurate PET images including attenuation, scatter, random, dead time, decay, and crystal sensitivity corrections. While approaches to quantitatively correct stand-alone PET and PET/MR are mostly similar, attenuation correction is vastly different between these scanners. In this chapter, we first review various MR-based attenuation corrections for PET/MR and then discuss quantitative analysis techniques. These quantitative PET analysis techniques, from static to dynamic acquisition analysis, enable physicians and researchers to measure activity concentration in organs/tissues of a molecular process of a biochemical and functional system.

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Notes

  1. 1.

    Dixon MRI is a method of obtaining great separation between fat and water due to the intrinsic chemical shift response between the two mediums. This chemical shift between fat and water allows the two molecules to process at different frequencies, thus creating two images wherein the fat and water signals are “in-phase” and “out-of-phase.” Dixon is usually considered to be a method for “fat suppression” as the “in-phase” and “out-of-phase images” can be used to create “water-only” and “fat-only” images.

  2. 2.

    Deep learning-based approaches can also be generalized and considered to be atlas-based approaches since they typically are trained on either a CT- or transmission-based atlas. Nevertheless, deep learning-based approaches omit the step of spatially registering the input image to the atlas.

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Author information

Authors and Affiliations

  1. Department of Radiology, Stony Brook Medicine, Stony Brook, NY, USA

    Mario Serrano-Sosa

  2. Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, The Feinstein Institutes for Medical Research, Manhasset, NY, USA

    Ana M. Franceschi

  3. Division of Neuroradiology, Department of Radiology, Lenox Hill Hospital, Northwell Health, New York, NY, USA

    Ana M. Franceschi

  4. Department of Psychiatry and Behavioral Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA

    Chuan Huang

  5. Department of Radiology, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA

    Chuan Huang

Authors
  1. Mario Serrano-Sosa
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  2. Ana M. Franceschi
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  3. Chuan Huang
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Correspondence to Chuan Huang .

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Editors and Affiliations

  1. Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, The Feinstein Institutes for Medical Research, Manhasset, NY, USA

    Ana M. Franceschi

  2. Stony Brook University Hospital, Stony Brook, NY, USA

    Dinko Franceschi

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Serrano-Sosa, M., Franceschi, A.M., Huang, C. (2022). Attenuation Correction and Quantitative PET Analysis. In: Franceschi, A.M., Franceschi, D. (eds) Hybrid PET/MR Neuroimaging. Springer, Cham. https://doi.org/10.1007/978-3-030-82367-2_3

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  • DOI: https://doi.org/10.1007/978-3-030-82367-2_3

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  • Print ISBN: 978-3-030-82366-5

  • Online ISBN: 978-3-030-82367-2

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