Evidence map›Paper›PMID 26243707›Full record

ArticleJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism2015

Comparative assessment of parametric neuroreceptor mapping approaches based on the simplified reference tissue model using [¹¹C]ABP688 PET.

Seongho Seo, Su J Kim, Yu K Kim, Jee-Young Lee, Jae M Jeong, Dong S Lee, Jae S Lee

Abstract readComparative Study
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Article in Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Seongho SeoDepartment of Nuclear Medicine, College of Medicine, Seoul National University, Seoul, Korea.
Su J KimNeuroscience Research Institute, Gachon University, Incheon, Korea.
Yu K KimDepartment of Nuclear Medicine, Seoul National University-Seoul Metropolitan Government Boramae Medical Center, College of Medicine, Seoul National University, Seoul, Korea.
Jee-Young LeeDepartment of Neurology, Seoul National University-Seoul Metropolitan Government Boramae Medical Center, College of Medicine, Seoul National University, Seoul, Korea.
Jae M JeongDepartment of Nuclear Medicine, College of Medicine, Seoul National University, Seoul, Korea.
Dong S LeeDepartment of Nuclear Medicine, College of Medicine, Seoul National University, Seoul, Korea.
Jae S LeeDepartment of Nuclear Medicine, College of Medicine, Seoul National University, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, several linearized model approaches for fast and reliable parametric neuroreceptor mapping based on dynamic nuclear imaging have been developed from the simplified reference tissue model (SRTM) equation. All the methods share the basic SRTM assumptions, but use different schemes to alleviate the effect of noise in dynamic-image voxels. Thus, this study aimed to compare those approaches in terms of their performance in parametric image generation. We used the basis function method and MRTM2 (multilinear reference tissue model with two parameters), which require a division process to obtain the distribution volume ratio (DVR). In addition, a linear model with the DVR as a model parameter (multilinear SRTM) was used in two forms: one based on linear least squares and the other based on extension of total least squares (TLS). Assessment using simulated and actual dynamic [(11)C]ABP688 positron emission tomography data revealed their equivalence with the SRTM, except for different noise susceptibilities. In the DVR image production, the two multilinear SRTM approaches achieved better image quality and regional compatibility with the SRTM than the others, with slightly better performance in the TLS-based method.

Indexed as

OximesPyridinesRadiopharmaceuticalsSensory Receptor CellsAlgorithmsBrain MappingComputer SimulationHumansImage Processing, Computer-AssistedLeast-Squares AnalysisLinear ModelsParkinson DiseasePositron-Emission TomographyReference Values3-(6-methylpyridin-2-ylethynyl)cyclohex-2-enone-O-methyloximeOximesPyridinesRadiopharmaceuticals

Identifiers

PMID26243707
PMCPMC4671133

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.