The PREMISE database of 20 Macaca fascicularis PET/MRI brain images available for research
Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of...
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Published in | Lab animal Vol. 53; no. 1; pp. 13 - 17 |
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Main Authors | , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Nature Publishing Group US
01.01.2024
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
ISSN | 0093-7355 1548-4475 1548-4475 |
DOI | 10.1038/s41684-023-01289-9 |
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Abstract | Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20
Macaca fascicularis
images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [
15
O]H
2
O and [
11
C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository.
The authors present a simultaneous PET/MR dataset of 20
Macaca fascicularis
images structured according to the Brain Imaging Data Structure standards. The PREMISE database is stored and available through the PRIME-DE consortium repository. |
---|---|
AbstractList | Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [15O]H2O and [11C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository.The authors present a simultaneous PET/MR dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. The PREMISE database is stored and available through the PRIME-DE consortium repository. Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [ 15 O]H 2 O and [ 11 C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository. Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [ 15 O]H 2 O and [ 11 C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository. Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [15O]H2O and [11C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository.Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [15O]H2O and [11C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository. Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [ O]H O and [ C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository. Non-human primate studies are unique in translational research, especially in neurosciences where neuroimaging approaches are the preferred methods used for cross-species comparative neurosciences. In this regard, neuroimaging database development and sharing are encouraged to increase the number of subjects available to the community, while limiting the number of animals used in research. Here we present a simultaneous positron emission tomography (PET)/magnetic resonance (MR) dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. This database contains multiple MR imaging sequences (anatomical, diffusion and perfusion imaging notably), as well as PET perfusion and inflammation imaging using respectively [ 15 O]H 2 O and [ 11 C]PK11195 radiotracers. We describe the pipeline method to assemble baseline data from various cohorts and qualitatively assess all the data using signal-to-noise and contrast-to-noise ratios as well as the median of intensity and the pseudo-noise-equivalent-count rate (dynamic and at maximum) for PET data. Our study provides a detailed example for quality control integration in preclinical and translational PET/MR studies with the aim of increasing reproducibility. The PREMISE database is stored and available through the PRIME-DE consortium repository. The authors present a simultaneous PET/MR dataset of 20 Macaca fascicularis images structured according to the Brain Imaging Data Structure standards. The PREMISE database is stored and available through the PRIME-DE consortium repository. |
Author | Boutelier, Timothe Costes, Nicolas Langlois, Jean-Baptiste Cho, Tae-Hee Nighoghossian, Norbert Léon, Christelle Wateau, Oceane Mechtouff, Laura Eker, Omer Faruk Canet-Soulas, Emmanuelle Debatisse, Justine Chalet, Lucie Becker, Guillaume Wiart, Marlène Redouté, Jérôme Lancelot, Sophie Mérida, Inés |
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References | Chauveau, Becker, Boutin (CR15) 2021; 49 Poldrack (CR3) 2017; 18 Autio (CR17) 2021; 236 Luurtsema (CR27) 2021; 6 Percie du Sert (CR21) 2020; 18 Watson (CR29) 2003; 50 Debatisse (CR18) 2021; 41 Wilkinson (CR2) 2016; 3 Phillips (CR5) 2014; 76 Wintermark (CR14) 2005; 36 Otsu (CR28) 1979; 9 CR30 O’Grady (CR9) 2022 Subbaraman (CR8) 2021; 595 Gorgolewski (CR1) 2016; 3 Norgaard (CR12) 2022; 9 Becker (CR16) 2023; 20 CR26 CR24 Mérida (CR13) 2021; 11 CR23 CR22 CR20 Milham (CR7) 2020; 105 Yushkevich, Gao, Gerig (CR25) 2016; 2016 Milham (CR10) 2018; 100 Friedrich (CR4) 2021; 228 Debatisse (CR19) 2020; 2 Aske, Waugh (CR6) 2017; 18 Knudsen (CR11) 2020; 40 J Debatisse (1289_CR18) 2021; 41 N Percie du Sert (1289_CR21) 2020; 18 M Norgaard (1289_CR12) 2022; 9 1289_CR30 JA Autio (1289_CR17) 2021; 236 MD Wilkinson (1289_CR2) 2016; 3 N Subbaraman (1289_CR8) 2021; 595 N Otsu (1289_CR28) 1979; 9 F Chauveau (1289_CR15) 2021; 49 J Debatisse (1289_CR19) 2020; 2 1289_CR24 1289_CR23 1289_CR22 1289_CR20 GM Knudsen (1289_CR11) 2020; 40 MP Milham (1289_CR10) 2018; 100 KA Phillips (1289_CR5) 2014; 76 KC Aske (1289_CR6) 2017; 18 G Luurtsema (1289_CR27) 2021; 6 CC Watson (1289_CR29) 2003; 50 KJ Gorgolewski (1289_CR1) 2016; 3 M Milham (1289_CR7) 2020; 105 P Friedrich (1289_CR4) 2021; 228 M Wintermark (1289_CR14) 2005; 36 G Becker (1289_CR16) 2023; 20 RA Poldrack (1289_CR3) 2017; 18 PA Yushkevich (1289_CR25) 2016; 2016 C O’Grady (1289_CR9) 2022 I Mérida (1289_CR13) 2021; 11 1289_CR26 |
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