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Optimization of [18F]PSMA-1007 PET-CT using regularized reconstruction in patients with prostate cancer

Trägårdh, Elin LU ; Minarik, David LU ; Brolin, Gustav LU ; Bitzén, Ulrika LU ; Olsson, Berit LU and Oddstig, Jenny LU (2020) In EJNMMI Physics 7(1).
Abstract

Background: Prostate-specific membrane antigen (PSMA) radiotracers such as [18F]PSMA-1007 used with positron emission tomography-computed tomography (PET-CT) is promising for initial staging and detection of recurrent disease in prostate cancer patients. The block-sequential regularization expectation maximization algorithm (BSREM) is a new PET reconstruction algorithm, which provides higher image contrast while also reducing noise. The aim of the present study was to evaluate the influence of different acquisition times and different noise-suppressing factors in BSREM (β values) in [18F]PSMA-1007 PET-CT regarding quantitative data as well as a visual image quality assessment. We included 35 patients referred for... (More)

Background: Prostate-specific membrane antigen (PSMA) radiotracers such as [18F]PSMA-1007 used with positron emission tomography-computed tomography (PET-CT) is promising for initial staging and detection of recurrent disease in prostate cancer patients. The block-sequential regularization expectation maximization algorithm (BSREM) is a new PET reconstruction algorithm, which provides higher image contrast while also reducing noise. The aim of the present study was to evaluate the influence of different acquisition times and different noise-suppressing factors in BSREM (β values) in [18F]PSMA-1007 PET-CT regarding quantitative data as well as a visual image quality assessment. We included 35 patients referred for clinical [18F]PSMA-1007 PET-CT. Four megabecquerels per kilogramme were administered and imaging was performed after 120 min. Eighty-four image series per patient were created with combinations of acquisition times of 1–4 min/bed position and β values of 300–1400. The noise level in normal tissue and the contrast-to-noise ratio (CNR) of pathological uptakes versus the local background were calculated. Image quality was assessed by experienced nuclear medicine physicians. Results: The noise level in the liver, spleen, and muscle was higher for low β values and low acquisition times (written as activity time products (ATs = administered activity × acquisition time)) and was minimized at maximum AT (16 MBq/kg min) and maximum β (1400). There was only a small decrease above AT 10. The median CNR increased slowly with AT from approximately 6 to 12 and was substantially lower at AT 4 and higher at AT 14–16. At AT 4–6, many images were regarded as being of unacceptable quality. For AT 8, β values of 700–900 were considered of acceptable quality. Conclusions: An AT of 8 (for example as in our study, 4 MB/kg with an acquisition time of 2 min) with a β value of 700 performs well regarding noise level, CNR, and visual image quality assessment.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Block-sequential regularized expectation maximization, Image quality, PET-CT, PSMA, Q.Clear, [18F]PSMA-1007
in
EJNMMI Physics
volume
7
issue
1
article number
31
publisher
Springer
external identifiers
  • pmid:32399664
  • scopus:85084459675
ISSN
2197-7364
DOI
10.1186/s40658-020-00298-8
language
English
LU publication?
yes
id
35c385de-4449-465d-b181-8d8a8d89db90
date added to LUP
2020-05-27 14:29:06
date last changed
2024-08-07 19:07:17
@article{35c385de-4449-465d-b181-8d8a8d89db90,
  abstract     = {{<p>Background: Prostate-specific membrane antigen (PSMA) radiotracers such as [<sup>18</sup>F]PSMA-1007 used with positron emission tomography-computed tomography (PET-CT) is promising for initial staging and detection of recurrent disease in prostate cancer patients. The block-sequential regularization expectation maximization algorithm (BSREM) is a new PET reconstruction algorithm, which provides higher image contrast while also reducing noise. The aim of the present study was to evaluate the influence of different acquisition times and different noise-suppressing factors in BSREM (β values) in [<sup>18</sup>F]PSMA-1007 PET-CT regarding quantitative data as well as a visual image quality assessment. We included 35 patients referred for clinical [<sup>18</sup>F]PSMA-1007 PET-CT. Four megabecquerels per kilogramme were administered and imaging was performed after 120 min. Eighty-four image series per patient were created with combinations of acquisition times of 1–4 min/bed position and β values of 300–1400. The noise level in normal tissue and the contrast-to-noise ratio (CNR) of pathological uptakes versus the local background were calculated. Image quality was assessed by experienced nuclear medicine physicians. Results: The noise level in the liver, spleen, and muscle was higher for low β values and low acquisition times (written as activity time products (ATs = administered activity × acquisition time)) and was minimized at maximum AT (16 MBq/kg min) and maximum β (1400). There was only a small decrease above AT 10. The median CNR increased slowly with AT from approximately 6 to 12 and was substantially lower at AT 4 and higher at AT 14–16. At AT 4–6, many images were regarded as being of unacceptable quality. For AT 8, β values of 700–900 were considered of acceptable quality. Conclusions: An AT of 8 (for example as in our study, 4 MB/kg with an acquisition time of 2 min) with a β value of 700 performs well regarding noise level, CNR, and visual image quality assessment.</p>}},
  author       = {{Trägårdh, Elin and Minarik, David and Brolin, Gustav and Bitzén, Ulrika and Olsson, Berit and Oddstig, Jenny}},
  issn         = {{2197-7364}},
  keywords     = {{Block-sequential regularized expectation maximization; Image quality; PET-CT; PSMA; Q.Clear; [18F]PSMA-1007}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{Springer}},
  series       = {{EJNMMI Physics}},
  title        = {{Optimization of [<sup>18</sup>F]PSMA-1007 PET-CT using regularized reconstruction in patients with prostate cancer}},
  url          = {{http://dx.doi.org/10.1186/s40658-020-00298-8}},
  doi          = {{10.1186/s40658-020-00298-8}},
  volume       = {{7}},
  year         = {{2020}},
}