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Radiological Physics and Technology
Published in: Radiological Physics and Technology 4/2020

Open Access 01-12-2020 | Positron Emission Tomography

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

Authors: Keisuke Matsubara, Masanobu Ibaraki, Miho Shidahara, Toshibumi Kinoshita, for the Alzheimer’s Disease Neuroimaging Initiative

Published in: Radiological Physics and Technology | Issue 4/2020

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Abstract

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 [11C]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.
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Metadata
Title
Iterative framework for image registration and partial volume correction in brain positron emission tomography
Authors
Keisuke Matsubara
Masanobu Ibaraki
Miho Shidahara
Toshibumi Kinoshita
for the Alzheimer’s Disease Neuroimaging Initiative
Publication date
01-12-2020
Publisher
Springer Singapore
Published in
Radiological Physics and Technology / Issue 4/2020
Print ISSN: 1865-0333
Electronic ISSN: 1865-0341
DOI
https://doi.org/10.1007/s12194-020-00591-2

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