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Framing protocol optimization in oncological Patlak parametric imaging with uKinetics
PURPOSE: Total-body PET imaging with ultra-high sensitivity makes high-temporal-resolution framing protocols possible for the first time, which allows to capture rapid tracer dynamic changes. However, whether protocols with higher number of temporal frames can justify the efficacy with substantially...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10497476/ https://www.ncbi.nlm.nih.gov/pubmed/37698773 http://dx.doi.org/10.1186/s40658-023-00577-0 |
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author | Ye, Qing Zeng, Hao Zhao, Yizhang Zhang, Weiguang Dong, Yun Fan, Wei Lu, Yihuan |
author_facet | Ye, Qing Zeng, Hao Zhao, Yizhang Zhang, Weiguang Dong, Yun Fan, Wei Lu, Yihuan |
author_sort | Ye, Qing |
collection | PubMed |
description | PURPOSE: Total-body PET imaging with ultra-high sensitivity makes high-temporal-resolution framing protocols possible for the first time, which allows to capture rapid tracer dynamic changes. However, whether protocols with higher number of temporal frames can justify the efficacy with substantially added computation burden for clinical application remains unclear. We have developed a kinetic modeling software package (uKinetics) with the advantage of practical, fast, and automatic workflow for dynamic total-body studies. The aim of this work is to verify the uKinetics with PMOD and to perform framing protocol optimization for the oncological Patlak parametric imaging. METHODS: Six different protocols with 100, 61, 48, 29, 19 and 12 temporal frames were applied to analyze 60-min dynamic (18)F-FDG PET scans of 10 patients, respectively. Voxel-based Patlak analysis coupled with automatically extracted image-derived input function was applied to generate parametric images. Normal tissues and lesions were segmented manually or automatically to perform correlation analysis and Bland–Altman plots. Different protocols were compared with the protocol of 100 frames as reference. RESULTS: Minor differences were found between uKinetics and PMOD in the Patlak parametric imaging. Compared with the protocol with 100 frames, the relative difference of the input function and quantitative kinetic parameters remained low for protocols with at least 29 frames, but increased for the protocols with 19 and 12 frames. Significant difference of lesion K(i) values was found between the protocols with 100 frames and 12 frames. CONCLUSION: uKinetics was proved providing equivalent oncological Patlak parametric imaging comparing to PMOD. Minor differences were found between protocols with 100 and 29 frames, which indicated that 29-frame protocol is sufficient and efficient for the oncological (18)F-FDG Patlak applications, and the protocols with more frames are not needed. The protocol with 19 frames yielded acceptable results, while that with 12 frames is not recommended. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-023-00577-0. |
format | Online Article Text |
id | pubmed-10497476 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-104974762023-09-14 Framing protocol optimization in oncological Patlak parametric imaging with uKinetics Ye, Qing Zeng, Hao Zhao, Yizhang Zhang, Weiguang Dong, Yun Fan, Wei Lu, Yihuan EJNMMI Phys Original Research PURPOSE: Total-body PET imaging with ultra-high sensitivity makes high-temporal-resolution framing protocols possible for the first time, which allows to capture rapid tracer dynamic changes. However, whether protocols with higher number of temporal frames can justify the efficacy with substantially added computation burden for clinical application remains unclear. We have developed a kinetic modeling software package (uKinetics) with the advantage of practical, fast, and automatic workflow for dynamic total-body studies. The aim of this work is to verify the uKinetics with PMOD and to perform framing protocol optimization for the oncological Patlak parametric imaging. METHODS: Six different protocols with 100, 61, 48, 29, 19 and 12 temporal frames were applied to analyze 60-min dynamic (18)F-FDG PET scans of 10 patients, respectively. Voxel-based Patlak analysis coupled with automatically extracted image-derived input function was applied to generate parametric images. Normal tissues and lesions were segmented manually or automatically to perform correlation analysis and Bland–Altman plots. Different protocols were compared with the protocol of 100 frames as reference. RESULTS: Minor differences were found between uKinetics and PMOD in the Patlak parametric imaging. Compared with the protocol with 100 frames, the relative difference of the input function and quantitative kinetic parameters remained low for protocols with at least 29 frames, but increased for the protocols with 19 and 12 frames. Significant difference of lesion K(i) values was found between the protocols with 100 frames and 12 frames. CONCLUSION: uKinetics was proved providing equivalent oncological Patlak parametric imaging comparing to PMOD. Minor differences were found between protocols with 100 and 29 frames, which indicated that 29-frame protocol is sufficient and efficient for the oncological (18)F-FDG Patlak applications, and the protocols with more frames are not needed. The protocol with 19 frames yielded acceptable results, while that with 12 frames is not recommended. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-023-00577-0. Springer International Publishing 2023-09-12 /pmc/articles/PMC10497476/ /pubmed/37698773 http://dx.doi.org/10.1186/s40658-023-00577-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Research Ye, Qing Zeng, Hao Zhao, Yizhang Zhang, Weiguang Dong, Yun Fan, Wei Lu, Yihuan Framing protocol optimization in oncological Patlak parametric imaging with uKinetics |
title | Framing protocol optimization in oncological Patlak parametric imaging with uKinetics |
title_full | Framing protocol optimization in oncological Patlak parametric imaging with uKinetics |
title_fullStr | Framing protocol optimization in oncological Patlak parametric imaging with uKinetics |
title_full_unstemmed | Framing protocol optimization in oncological Patlak parametric imaging with uKinetics |
title_short | Framing protocol optimization in oncological Patlak parametric imaging with uKinetics |
title_sort | framing protocol optimization in oncological patlak parametric imaging with ukinetics |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10497476/ https://www.ncbi.nlm.nih.gov/pubmed/37698773 http://dx.doi.org/10.1186/s40658-023-00577-0 |
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