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The Impact of Total Variation Regularized Expectation Maximization Reconstruction on (68)Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor

OBJECTIVE: The aim of this study was to investigate the effects of the total variation regularized expectation maximization (TVREM) reconstruction on improving (68)Ga-DOTA-TATE PET/CT images compared to the ordered subset expectation maximization (OSEM) reconstruction. METHOD: A total of 17 patients...

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Autores principales: Liu, Lin, Liu, Hanxiang, Xu, Shijie, Zhang, Shumao, Tao, Yi, Mok, Greta S. P., Chen, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963366/
https://www.ncbi.nlm.nih.gov/pubmed/35360749
http://dx.doi.org/10.3389/fmed.2022.845806
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author Liu, Lin
Liu, Hanxiang
Xu, Shijie
Zhang, Shumao
Tao, Yi
Mok, Greta S. P.
Chen, Yue
author_facet Liu, Lin
Liu, Hanxiang
Xu, Shijie
Zhang, Shumao
Tao, Yi
Mok, Greta S. P.
Chen, Yue
author_sort Liu, Lin
collection PubMed
description OBJECTIVE: The aim of this study was to investigate the effects of the total variation regularized expectation maximization (TVREM) reconstruction on improving (68)Ga-DOTA-TATE PET/CT images compared to the ordered subset expectation maximization (OSEM) reconstruction. METHOD: A total of 17 patients with neuroendocrine tumors who underwent clinical (68)Ga-DOTA-TATE PET/CT were involved in this study retrospectively. The PET images were acquired with either 3 min-per-bed (min/bed) acquisition time and reconstructed with OSEM (2 iterations, 20 subsets, and a 3.2-mm Gaussian filter) and TVREM (seven penalization factors = 0.01, 0.07, 0.14, 0.21, 0.28, 0.35, and 0.42) for 2 and 3 min-per-bed (min/bed) acquisition time using list-mode. The SUV(mean) of the liver, background variability (BV), signal-to-noise ratios (SNR), SUV(max) of the lesions and tumor-to-background ratios (TBR) were measured. The mean percentage difference in the SNR and TBR between TVREM with difference penalization factors and OSEM was calculated. Qualitative image quality was evaluated by two experienced radiologists using a 5-point score scale (5-excellent, 1-poor). RESULTS: In total, 63 lesions were analyzed in this study. The SUV(mean) of the liver did not differ significantly between TVREM and OSEM. The BV of all TVREM groups was lower than OSEM groups (all p < 0.05), and the BV of TVREM 2 min/bed group with penalization factor of 0.21 was considered comparable to OSEM 3 min/bed group (p = 0.010 and 0.006). The SNR, SUV(max) and TBR were higher for all TVREM groups compared to OSEM groups (all p < 0.05). The mean percentage difference in the SNR and TBR was larger for small lesions (<10 mm) than that for medium (≥10 mm but < 20 mm) and large lesions (≥20 mm). The highest image quality score was given to TVREM 2 min/bed group with penalization factor of 0.21 (3.77 ± 0.26) and TVREM 3 min/bed group with penalization factor of 0.35 (3.77 ± 0.26). CONCLUSION: TVREM could reduce image noise, improve the SNR, SUV(max) and TBR of the lesions, and has the potential to preserves the image quality with shorter acquisition time.
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spelling pubmed-89633662022-03-30 The Impact of Total Variation Regularized Expectation Maximization Reconstruction on (68)Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor Liu, Lin Liu, Hanxiang Xu, Shijie Zhang, Shumao Tao, Yi Mok, Greta S. P. Chen, Yue Front Med (Lausanne) Medicine OBJECTIVE: The aim of this study was to investigate the effects of the total variation regularized expectation maximization (TVREM) reconstruction on improving (68)Ga-DOTA-TATE PET/CT images compared to the ordered subset expectation maximization (OSEM) reconstruction. METHOD: A total of 17 patients with neuroendocrine tumors who underwent clinical (68)Ga-DOTA-TATE PET/CT were involved in this study retrospectively. The PET images were acquired with either 3 min-per-bed (min/bed) acquisition time and reconstructed with OSEM (2 iterations, 20 subsets, and a 3.2-mm Gaussian filter) and TVREM (seven penalization factors = 0.01, 0.07, 0.14, 0.21, 0.28, 0.35, and 0.42) for 2 and 3 min-per-bed (min/bed) acquisition time using list-mode. The SUV(mean) of the liver, background variability (BV), signal-to-noise ratios (SNR), SUV(max) of the lesions and tumor-to-background ratios (TBR) were measured. The mean percentage difference in the SNR and TBR between TVREM with difference penalization factors and OSEM was calculated. Qualitative image quality was evaluated by two experienced radiologists using a 5-point score scale (5-excellent, 1-poor). RESULTS: In total, 63 lesions were analyzed in this study. The SUV(mean) of the liver did not differ significantly between TVREM and OSEM. The BV of all TVREM groups was lower than OSEM groups (all p < 0.05), and the BV of TVREM 2 min/bed group with penalization factor of 0.21 was considered comparable to OSEM 3 min/bed group (p = 0.010 and 0.006). The SNR, SUV(max) and TBR were higher for all TVREM groups compared to OSEM groups (all p < 0.05). The mean percentage difference in the SNR and TBR was larger for small lesions (<10 mm) than that for medium (≥10 mm but < 20 mm) and large lesions (≥20 mm). The highest image quality score was given to TVREM 2 min/bed group with penalization factor of 0.21 (3.77 ± 0.26) and TVREM 3 min/bed group with penalization factor of 0.35 (3.77 ± 0.26). CONCLUSION: TVREM could reduce image noise, improve the SNR, SUV(max) and TBR of the lesions, and has the potential to preserves the image quality with shorter acquisition time. Frontiers Media S.A. 2022-03-11 /pmc/articles/PMC8963366/ /pubmed/35360749 http://dx.doi.org/10.3389/fmed.2022.845806 Text en Copyright © 2022 Liu, Liu, Xu, Zhang, Tao, Mok and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Liu, Lin
Liu, Hanxiang
Xu, Shijie
Zhang, Shumao
Tao, Yi
Mok, Greta S. P.
Chen, Yue
The Impact of Total Variation Regularized Expectation Maximization Reconstruction on (68)Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor
title The Impact of Total Variation Regularized Expectation Maximization Reconstruction on (68)Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor
title_full The Impact of Total Variation Regularized Expectation Maximization Reconstruction on (68)Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor
title_fullStr The Impact of Total Variation Regularized Expectation Maximization Reconstruction on (68)Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor
title_full_unstemmed The Impact of Total Variation Regularized Expectation Maximization Reconstruction on (68)Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor
title_short The Impact of Total Variation Regularized Expectation Maximization Reconstruction on (68)Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor
title_sort impact of total variation regularized expectation maximization reconstruction on (68)ga-dota-tate pet/ct images in patients with neuroendocrine tumor
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963366/
https://www.ncbi.nlm.nih.gov/pubmed/35360749
http://dx.doi.org/10.3389/fmed.2022.845806
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