Towards accurate

177Lu activity quantification Calibration factors Gamma camera calibration SPECT Sphere-to-background counts/voxel ratio

Journal

EJNMMI physics
ISSN: 2197-7364
Titre abrégé: EJNMMI Phys
Pays: Germany
ID NLM: 101658952

Informations de publication

Date de publication:
23 Jan 2023
Historique:
received: 12 09 2022
accepted: 11 01 2023
entrez: 23 1 2023
pubmed: 24 1 2023
medline: 24 1 2023
Statut: epublish

Résumé

Conventional calibration of the gamma camera consists of the calculation of calibration factors (CFs) (ratio of counts/cc and true concentration activity) as the function of the volume of interest (VOI). However, such method shows inconsistent results when the background activity varies. The aim of the present study was to propose a new calibration method by considering the sphere-to-background counts/voxel ratio (SBVR) in addition to the VOI for CFs calculation. A PET cylindrical flood phantom, a NEMA IQ body phantom, a Data spectrum Torso Phantom (ECT/TOR/P) and a LK-S Kyoto Liver/Kidney phantom were used. The NEMA IQ phantom was used to calibrate the camera and to produce CFs for the different spheres volumes and for varying sphere-to-background activity ratios. The spheres were filled with a uniform activity concentration of The relative errors in quantification using the NEMA IQ phantom with the new calibration method were 0.16%, 5.77%, 9.34% for the large, medium and small sphere, respectively, for a time per view of 30-s. The conventional calibration method gave errors of 3.65%, 6.65%, 30.28% for 30-s. The LK-S Kyoto Liver/Kidney Phantom resulted in quantification errors of 3.40%, 2.14%, 11.18% for the large, medium and small spheres, respectively, for 30-s; compared to 11.31%, 17.54%, 14.43% for 30-s, respectively, for the conventional method. Similar results were obtained for shorter acquisitions times with 20-s and 10-s time per view. These results suggest that SBVR allows to improve quantification accuracy. The shorter time-per-view acquisitions had similar relative differences compared to the full-time acquisition which allows shorter imaging times with

Sections du résumé

BACKGROUND BACKGROUND
Conventional calibration of the gamma camera consists of the calculation of calibration factors (CFs) (ratio of counts/cc and true concentration activity) as the function of the volume of interest (VOI). However, such method shows inconsistent results when the background activity varies. The aim of the present study was to propose a new calibration method by considering the sphere-to-background counts/voxel ratio (SBVR) in addition to the VOI for CFs calculation. A PET cylindrical flood phantom, a NEMA IQ body phantom, a Data spectrum Torso Phantom (ECT/TOR/P) and a LK-S Kyoto Liver/Kidney phantom were used. The NEMA IQ phantom was used to calibrate the camera and to produce CFs for the different spheres volumes and for varying sphere-to-background activity ratios. The spheres were filled with a uniform activity concentration of
RESULTS RESULTS
The relative errors in quantification using the NEMA IQ phantom with the new calibration method were 0.16%, 5.77%, 9.34% for the large, medium and small sphere, respectively, for a time per view of 30-s. The conventional calibration method gave errors of 3.65%, 6.65%, 30.28% for 30-s. The LK-S Kyoto Liver/Kidney Phantom resulted in quantification errors of 3.40%, 2.14%, 11.18% for the large, medium and small spheres, respectively, for 30-s; compared to 11.31%, 17.54%, 14.43% for 30-s, respectively, for the conventional method. Similar results were obtained for shorter acquisitions times with 20-s and 10-s time per view.
CONCLUSION CONCLUSIONS
These results suggest that SBVR allows to improve quantification accuracy. The shorter time-per-view acquisitions had similar relative differences compared to the full-time acquisition which allows shorter imaging times with

Identifiants

pubmed: 36689080
doi: 10.1186/s40658-023-00526-x
pii: 10.1186/s40658-023-00526-x
pmc: PMC9871126
doi:

Types de publication

Journal Article

Langues

eng

Pagination

5

Informations de copyright

© 2023. The Author(s).

Références

Appl Radiat Isot. 2016 Jun;112:156-64
pubmed: 27064195
EJNMMI Phys. 2021 Mar 18;8(1):27
pubmed: 33738605
Mol Imaging Biol. 2015 Aug;17(4):585-93
pubmed: 25475521
EJNMMI Phys. 2022 Mar 14;9(1):18
pubmed: 35286500
N Engl J Med. 2017 Jan 12;376(2):125-135
pubmed: 28076709
Acta Oncol. 2018 Apr;57(4):516-521
pubmed: 28920501
Nucl Med Commun. 2014 May;35(5):522-33
pubmed: 24525900
EJNMMI Phys. 2018 Dec 10;5(1):36
pubmed: 30535780
EJNMMI Phys. 2020 Jan 23;7(1):5
pubmed: 31975156
J Clin Oncol. 2008 May 1;26(13):2124-30
pubmed: 18445841
EJNMMI Phys. 2018 May 2;5(1):8
pubmed: 29717385
Cancer Imaging. 2011 Jun 15;11:56-66
pubmed: 21684829
Eur J Nucl Med Mol Imaging. 2012 Feb;39 Suppl 1:S103-12
pubmed: 22388631
J Med Phys. 2010 Oct;35(4):215-22
pubmed: 21170186
Eur J Nucl Med Mol Imaging. 2022 Sep;49(11):3830-3840
pubmed: 35451612
EJNMMI Phys. 2021 Jul 23;8(1):55
pubmed: 34297218
EJNMMI Phys. 2021 Aug 26;8(1):63
pubmed: 34436698

Auteurs

Stanislav Raskin (S)

Department of Physics, Ariel University, Ariel, Israel.
Department of Electrical and Electronics Engineering, Ariel University, 407000, Ariel, Israel.

Dan Gamliel (D)

Department of Physics, Ariel University, Ariel, Israel.

David Abookasis (D)

Department of Electrical and Electronics Engineering, Ariel University, 407000, Ariel, Israel.

Simona Ben-Haim (S)

Department of Nuclear Medicine and Biophysics, Hadassah Medical Organization and Faculty of Medicine, Hebrew University of Jerusalem, 91120, Jerusalem, Israel.
University College London, London, UK.

Alexandre Chicheportiche (A)

Department of Nuclear Medicine and Biophysics, Hadassah Medical Organization and Faculty of Medicine, Hebrew University of Jerusalem, 91120, Jerusalem, Israel. alexandre@hadassah.org.il.

Classifications MeSH