Task-evoked simultaneous FDG-PET and fMRI data for measurement of neural metabolism in the human visual cortex

Sharna D. Jamadar; Shenjun Zhong; Alexandra Carey; Richard McIntyre; Phillip G.D. Ward; Alex Fornito; Malin Premaratne; N. Jon Shah; Kieran O’Brien; Daniel Stäb; Zhaolin Chen; Gary F. Egan

doi:10.1038/s41597-021-01042-2

Task-evoked simultaneous FDG-PET and fMRI data for measurement of neural metabolism in the human visual cortex

Sharna D. Jamadar, Shenjun Zhong, Alexandra Carey, Richard McIntyre, Phillip G.D. Ward, Alex Fornito, Malin Premaratne, N. Jon Shah, Kieran O’Brien, Daniel Stäb, Zhaolin Chen, Gary F. Egan

Research output: Contribution to journal › Article › Research › peer-review

2 Citations (Scopus)

Abstract

Understanding how the living human brain functions requires sophisticated in vivo neuroimaging technologies to characterise the complexity of neuroanatomy, neural function, and brain metabolism. Fluorodeoxyglucose positron emission tomography (FDG-PET) studies of human brain function have historically been limited in their capacity to measure dynamic neural activity. Simultaneous [18 F]-FDG-PET and functional magnetic resonance imaging (fMRI) with FDG infusion protocols enable examination of dynamic changes in cerebral glucose metabolism simultaneously with dynamic changes in blood oxygenation. The Monash vis-fPET-fMRI dataset is a simultaneously acquired FDG-fPET/BOLD-fMRI dataset acquired from n = 10 healthy adults (18–49 yrs) whilst they viewed a flickering checkerboard task. The dataset contains both raw (unprocessed) images and source data organized according to the BIDS specification. The source data includes PET listmode, normalization, sinogram and physiology data. Here, the technical feasibility of using opensource frameworks to reconstruct the PET listmode data is demonstrated. The dataset has significant re-use value for the development of new processing pipelines, signal optimisation methods, and to formulate new hypotheses concerning the relationship between neuronal glucose uptake and cerebral haemodynamics.

Original language	English
Article number	267
Number of pages	9
Journal	Scientific Data
Volume	8
Issue number	1
DOIs	https://doi.org/10.1038/s41597-021-01042-2
Publication status	Published - 2021

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354277722-oaFinal published version, 2.03 MBLicence: CC BY

Cite this

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title = "Task-evoked simultaneous FDG-PET and fMRI data for measurement of neural metabolism in the human visual cortex",

abstract = "Understanding how the living human brain functions requires sophisticated in vivo neuroimaging technologies to characterise the complexity of neuroanatomy, neural function, and brain metabolism. Fluorodeoxyglucose positron emission tomography (FDG-PET) studies of human brain function have historically been limited in their capacity to measure dynamic neural activity. Simultaneous [18 F]-FDG-PET and functional magnetic resonance imaging (fMRI) with FDG infusion protocols enable examination of dynamic changes in cerebral glucose metabolism simultaneously with dynamic changes in blood oxygenation. The Monash vis-fPET-fMRI dataset is a simultaneously acquired FDG-fPET/BOLD-fMRI dataset acquired from n = 10 healthy adults (18–49 yrs) whilst they viewed a flickering checkerboard task. The dataset contains both raw (unprocessed) images and source data organized according to the BIDS specification. The source data includes PET listmode, normalization, sinogram and physiology data. Here, the technical feasibility of using opensource frameworks to reconstruct the PET listmode data is demonstrated. The dataset has significant re-use value for the development of new processing pipelines, signal optimisation methods, and to formulate new hypotheses concerning the relationship between neuronal glucose uptake and cerebral haemodynamics.",

author = "Jamadar, {Sharna D.} and Shenjun Zhong and Alexandra Carey and Richard McIntyre and Ward, {Phillip G.D.} and Alex Fornito and Malin Premaratne and {Jon Shah}, N. and Kieran O{\textquoteright}Brien and Daniel St{\"a}b and Zhaolin Chen and Egan, {Gary F.}",

note = "Funding Information: This work was supported by an Australian Research Council (ARC) Linkage Project (LP170100494) that includes financial support from Siemens Healthineers. SDJ, PGDW & GFE are supported by the ARC Centre of Excellence for Integrative Brain Function (CE140100007). SDJ is supported by an ARC Discovery Early Career Researcher Award (DE150100406) and National Health and Medical Research Council Fellowship (APP1174164). The authors acknowledge Winnie Orchard, Irene Graafsma and Disha Sasan for their assistance in acquiring data; and Lauren Hudswell and Cameron Pain for assistance with data preparation. Publisher Copyright: {\textcopyright} 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2021",

doi = "10.1038/s41597-021-01042-2",

language = "English",

volume = "8",

journal = "Scientific Data",

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AU - Jamadar, Sharna D.

AU - Zhong, Shenjun

AU - Carey, Alexandra

AU - McIntyre, Richard

AU - Ward, Phillip G.D.

AU - Fornito, Alex

AU - Premaratne, Malin

AU - Jon Shah, N.

AU - O’Brien, Kieran

AU - Stäb, Daniel

AU - Chen, Zhaolin

AU - Egan, Gary F.

N1 - Funding Information: This work was supported by an Australian Research Council (ARC) Linkage Project (LP170100494) that includes financial support from Siemens Healthineers. SDJ, PGDW & GFE are supported by the ARC Centre of Excellence for Integrative Brain Function (CE140100007). SDJ is supported by an ARC Discovery Early Career Researcher Award (DE150100406) and National Health and Medical Research Council Fellowship (APP1174164). The authors acknowledge Winnie Orchard, Irene Graafsma and Disha Sasan for their assistance in acquiring data; and Lauren Hudswell and Cameron Pain for assistance with data preparation. Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021

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N2 - Understanding how the living human brain functions requires sophisticated in vivo neuroimaging technologies to characterise the complexity of neuroanatomy, neural function, and brain metabolism. Fluorodeoxyglucose positron emission tomography (FDG-PET) studies of human brain function have historically been limited in their capacity to measure dynamic neural activity. Simultaneous [18 F]-FDG-PET and functional magnetic resonance imaging (fMRI) with FDG infusion protocols enable examination of dynamic changes in cerebral glucose metabolism simultaneously with dynamic changes in blood oxygenation. The Monash vis-fPET-fMRI dataset is a simultaneously acquired FDG-fPET/BOLD-fMRI dataset acquired from n = 10 healthy adults (18–49 yrs) whilst they viewed a flickering checkerboard task. The dataset contains both raw (unprocessed) images and source data organized according to the BIDS specification. The source data includes PET listmode, normalization, sinogram and physiology data. Here, the technical feasibility of using opensource frameworks to reconstruct the PET listmode data is demonstrated. The dataset has significant re-use value for the development of new processing pipelines, signal optimisation methods, and to formulate new hypotheses concerning the relationship between neuronal glucose uptake and cerebral haemodynamics.

AB - Understanding how the living human brain functions requires sophisticated in vivo neuroimaging technologies to characterise the complexity of neuroanatomy, neural function, and brain metabolism. Fluorodeoxyglucose positron emission tomography (FDG-PET) studies of human brain function have historically been limited in their capacity to measure dynamic neural activity. Simultaneous [18 F]-FDG-PET and functional magnetic resonance imaging (fMRI) with FDG infusion protocols enable examination of dynamic changes in cerebral glucose metabolism simultaneously with dynamic changes in blood oxygenation. The Monash vis-fPET-fMRI dataset is a simultaneously acquired FDG-fPET/BOLD-fMRI dataset acquired from n = 10 healthy adults (18–49 yrs) whilst they viewed a flickering checkerboard task. The dataset contains both raw (unprocessed) images and source data organized according to the BIDS specification. The source data includes PET listmode, normalization, sinogram and physiology data. Here, the technical feasibility of using opensource frameworks to reconstruct the PET listmode data is demonstrated. The dataset has significant re-use value for the development of new processing pipelines, signal optimisation methods, and to formulate new hypotheses concerning the relationship between neuronal glucose uptake and cerebral haemodynamics.

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DO - 10.1038/s41597-021-01042-2

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VL - 8

JO - Scientific Data

JF - Scientific Data

IS - 1

M1 - 267

ER -

Task-evoked simultaneous FDG-PET and fMRI data for measurement of neural metabolism in the human visual cortex

Abstract

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Other files and links

Neural metabolic connectivity in ageing and neurodegeneration

Integrative brain imaging technologies

Cognitive Compensation in Ageing

Cite this

Task-evoked simultaneous FDG-PET and fMRI data for measurement of neural metabolism in the human visual cortex

Abstract

UN SDGs

Access to Document

Other files and links

Projects

Neural metabolic connectivity in ageing and neurodegeneration

Integrative brain imaging technologies

Cognitive Compensation in Ageing

Cite this