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Iterative framework for image registration and partial volume correction in brain positron emission tomography

Imprecise registration between positron emission tomography (PET) and anatomical magnetic resonance (MR) images is a critical source of error in MR imaging-guided partial volume correction (MR-PVC). Here, we propose a novel framework for image registration and partial volume correction, which we ter...

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Autores principales: Matsubara, Keisuke, Ibaraki, Masanobu, Shidahara, Miho, Kinoshita, Toshibumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688593/
https://www.ncbi.nlm.nih.gov/pubmed/33074484
http://dx.doi.org/10.1007/s12194-020-00591-2
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author Matsubara, Keisuke
Ibaraki, Masanobu
Shidahara, Miho
Kinoshita, Toshibumi
author_facet Matsubara, Keisuke
Ibaraki, Masanobu
Shidahara, Miho
Kinoshita, Toshibumi
author_sort Matsubara, Keisuke
collection PubMed
description Imprecise registration between positron emission tomography (PET) and anatomical magnetic resonance (MR) images is a critical source of error in MR imaging-guided partial volume correction (MR-PVC). Here, we propose a novel framework for image registration and partial volume correction, which we term PVC-optimized registration (PoR), to address imprecise registration. The PoR framework iterates PVC and registration between uncorrected PET and smoothed PV-corrected images to obtain precise registration. We applied PoR to the [(11)C]PiB PET data of 92 participants obtained from the Alzheimer’s Disease Neuroimaging Initiative database and compared the registration results, PV-corrected standardized uptake value (SUV) and its ratio to the cerebellum (SUVR), and intra-region coefficient of variation (CoV) between PoR and conventional registration. Significant differences in registration of as much as 2.74 mm and 3.02° were observed between the two methods (effect size <  − 0.8 or > 0.8), which resulted in considerable SUVR differences throughout the brain, reaching a maximal difference of 62.3% in the sensory motor cortex. Intra-region CoV was significantly reduced using the PoR throughout the brain. These results suggest that PoR reduces error as a result of imprecise registration in PVC and is a useful method for accurately quantifying the amyloid burden in PET. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12194-020-00591-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-76885932020-11-30 Iterative framework for image registration and partial volume correction in brain positron emission tomography Matsubara, Keisuke Ibaraki, Masanobu Shidahara, Miho Kinoshita, Toshibumi Radiol Phys Technol Article Imprecise registration between positron emission tomography (PET) and anatomical magnetic resonance (MR) images is a critical source of error in MR imaging-guided partial volume correction (MR-PVC). Here, we propose a novel framework for image registration and partial volume correction, which we term PVC-optimized registration (PoR), to address imprecise registration. The PoR framework iterates PVC and registration between uncorrected PET and smoothed PV-corrected images to obtain precise registration. We applied PoR to the [(11)C]PiB PET data of 92 participants obtained from the Alzheimer’s Disease Neuroimaging Initiative database and compared the registration results, PV-corrected standardized uptake value (SUV) and its ratio to the cerebellum (SUVR), and intra-region coefficient of variation (CoV) between PoR and conventional registration. Significant differences in registration of as much as 2.74 mm and 3.02° were observed between the two methods (effect size <  − 0.8 or > 0.8), which resulted in considerable SUVR differences throughout the brain, reaching a maximal difference of 62.3% in the sensory motor cortex. Intra-region CoV was significantly reduced using the PoR throughout the brain. These results suggest that PoR reduces error as a result of imprecise registration in PVC and is a useful method for accurately quantifying the amyloid burden in PET. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12194-020-00591-2) contains supplementary material, which is available to authorized users. Springer Singapore 2020-10-19 2020 /pmc/articles/PMC7688593/ /pubmed/33074484 http://dx.doi.org/10.1007/s12194-020-00591-2 Text en © The Author(s) 2020 Open AccessThis 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/.
spellingShingle Article
Matsubara, Keisuke
Ibaraki, Masanobu
Shidahara, Miho
Kinoshita, Toshibumi
Iterative framework for image registration and partial volume correction in brain positron emission tomography
title Iterative framework for image registration and partial volume correction in brain positron emission tomography
title_full Iterative framework for image registration and partial volume correction in brain positron emission tomography
title_fullStr Iterative framework for image registration and partial volume correction in brain positron emission tomography
title_full_unstemmed Iterative framework for image registration and partial volume correction in brain positron emission tomography
title_short Iterative framework for image registration and partial volume correction in brain positron emission tomography
title_sort iterative framework for image registration and partial volume correction in brain positron emission tomography
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688593/
https://www.ncbi.nlm.nih.gov/pubmed/33074484
http://dx.doi.org/10.1007/s12194-020-00591-2
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