Abstract

Purpose

The image quality characteristics of two NEMA phantoms with yttrium-90 (90Y) were evaluated on a long axial field-of-view (AFOV) PET/CT. The purpose was to identify the optimized reconstruction setup for the imaging of patients with hepatocellular carcinoma after 90Y radioembolization.

Methods

Two NEMA phantoms were used, where one had a 1:10 sphere to background activity concentration ratio and the second had cold background. Reconstruction parameters used are as follows: iterations 2 to 8, Gaussian filter 2- to 6-mm full-width-at-half-maximum, reconstruction matrices 440 × 440 and 220 × 220, high sensitivity (HS), and ultra-high sensitivity (UHS) modes. 50-, 40-, 30-, 20-, 10-, and 5-min acquisitions were reconstructed. The measurements included recovery coefficients (RC), signal-to-noise ratio (SNR), background variability, and lung error which measures the residual error in the corrections. Patient data were reconstructed with 20-, 10-, 5-, and 1-min time frames and evaluated in terms of SNR.

Results

The RC for the hot phantom was 0.36, 0.45, 0.53, 0.63, 0.68, and 0.84 for the spheres with diameters of 10, 13, 17, 22, 28, and 37 mm, respectively, for UHS 2 iterations, a 220 × 220 matrix, and 50-min acquisition. The RC values did not differ with acquisition times down to 20 min. The SNR was the highest for 2 iterations, measured 11.7, 16.6, 17.6, 19.4, 21.9, and 27.7 while the background variability was the lowest (27.59, 27.08, 27.36, 26.44, 30.11, and 33.51%). The lung error was 18%. For the patient dataset, the SNR was 19%, 20%, 24%, and 31% higher for 2 iterations compared to 4 iterations for 20-, 10-, 5-, and 1-min time frames, respectively.

Conclusions

This study evaluates the NEMA image quality of a long AFOV PET/CT scanner with 90Y. It provides high RC for the smallest sphere compared to other standard AFOV scanners at shorter scan times. The maximum patient SNR was for 2 iterations, 20 min, while 5 min delivers images with acceptable SNR.

Details

Title
Phantom-based evaluation of yttrium-90 datasets using biograph vision quadra
Author
Zeimpekis, Konstantinos G. 1 ; Mercolli, Lorenzo 1   VIAFID ORCID Logo  ; Conti, Maurizio 2   VIAFID ORCID Logo  ; Sari, Hasan 3   VIAFID ORCID Logo  ; Prenosil, George 1   VIAFID ORCID Logo  ; Shi, Kuangyu 1   VIAFID ORCID Logo  ; Rominger, Axel 1   VIAFID ORCID Logo 

 Bern University Hospital, University of Bern, Department of Nuclear Medicine, Inselspital, Bern, Switzerland (GRID:grid.5734.5) (ISNI:0000 0001 0726 5157) 
 Siemens Healthineers, Molecular Imaging, Knoxville, USA (GRID:grid.415886.6) (ISNI:0000 0004 0546 1113) 
 Siemens Healthcare AG, Advanced Clinical Imaging Technology, Lausanne, Switzerland (GRID:grid.415886.6) 
Pages
1168-1182
Publication year
2023
Publication date
Mar 2023
Publisher
Springer Nature B.V.
ISSN
16197070
e-ISSN
16197089
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2776864569
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.