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Keuken MC, Liebrand LC, Bazin PL, Alkemade A, van Berendonk N, Groot JM, Isherwood SJS, Kemp S, Lute N, Mulder MJ, Trutti AC, Caan MWA, Forstmann BU. A high-resolution multi-shell 3T diffusion magnetic resonance imaging dataset as part of the Amsterdam Ultra-high field adult lifespan database (AHEAD). Data Brief 2022; 42:108086. [PMID: 35372652 PMCID: PMC8971326 DOI: 10.1016/j.dib.2022.108086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 03/07/2022] [Accepted: 03/16/2022] [Indexed: 11/18/2022] Open
Abstract
In order to further our understanding of brain function and the underlying networks, more advanced diffusion weighted magnetic resonance imaging (DWI MRI) data are essential. Here we present freely available high-resolution multi-shell multi-directional 3 Tesla (T) DWI MRI data as part of the ‘Amsterdam Ultra-high field adult lifespan database’ (AHEAD). The 3T DWI AHEAD dataset include 1.28mm isotropic whole brain DWI data of 49 healthy adult participants between 18 and 90 years old. The acquired data include DWIs at three non-zero b-values (48 directions, b-value 700 s/mm2; 56 directions, b-value 1000 s/mm2; 64 directions, b-value 1600 s/mm2) including a total of twelve volumes with a b-value of 0 s/mm2 (b0 volumes). In addition, eight b0 volumes with a reversed phase encoding direction were acquired to correct for distortions. To facilitate future use, the DWI data have been denoised, corrected for eddy currents, susceptibility-induced off-resonance field distortions, bias fields, and are skull stripped.
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Affiliation(s)
- Max C Keuken
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands
| | - Luka C Liebrand
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands.,Departments of Neurophysics and Neurology, Max Planck Institute for Human, Cognitive and Brain Sciences, Leipzig, Germany
| | - Anneke Alkemade
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands
| | - Nikita van Berendonk
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands
| | - Josephine M Groot
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands.,Department of Psychology, UiT-The Arctic University of Norway, Tromsø, Norway
| | - Scott J S Isherwood
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands
| | - Sarah Kemp
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands.,Sensorimotor Neuroscience and Ageing Research Lab, School of Psychological Sciences, College of Health and Medicine, University of Tasmania, Hobart, Australia
| | - Nicky Lute
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands
| | - Martijn J Mulder
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
| | - Anne C Trutti
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands.,Cognitive Psychology Unit and Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Matthan W A Caan
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Birte U Forstmann
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, The Netherlands
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Isaacs BR, Mulder MJ, Groot JM, van Berendonk N, Lute N, Bazin PL, Forstmann BU, Alkemade A. 3 versus 7 Tesla magnetic resonance imaging for parcellations of subcortical brain structures in clinical settings. PLoS One 2020; 15:e0236208. [PMID: 33232325 PMCID: PMC7685480 DOI: 10.1371/journal.pone.0236208] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022] Open
Abstract
7 Tesla (7T) magnetic resonance imaging holds great promise for improved visualization of the human brain for clinical purposes. To assess whether 7T is superior regarding localization procedures of small brain structures, we compared manual parcellations of the red nucleus, subthalamic nucleus, substantia nigra, globus pallidus interna and externa. These parcellations were created on a commonly used clinical anisotropic clinical 3T with an optimized isotropic (o)3T and standard 7T scan. The clinical 3T MRI scans did not allow delineation of an anatomically plausible structure due to its limited spatial resolution. o3T and 7T parcellations were directly compared. We found that 7T outperformed the o3T MRI as reflected by higher Dice scores, which were used as a measurement of interrater agreement for manual parcellations on quantitative susceptibility maps. This increase in agreement was associated with higher contrast to noise ratios for smaller structures, but not for the larger globus pallidus segments. Additionally, control-analyses were performed to account for potential biases in manual parcellations by assessing semi-automatic parcellations. These results showed a higher consistency for structure volumes for 7T compared to optimized 3T which illustrates the importance of the use of isotropic voxels for 3D visualization of the surgical target area. Together these results indicate that 7T outperforms c3T as well as o3T given the constraints of a clinical setting.
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Affiliation(s)
- Bethany R. Isaacs
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Department of Experimental Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Martijn J. Mulder
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Psychology and Social Sciences, University of Utrecht, Utrecht, The Netherlands
| | - Josephine M. Groot
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Nikita van Berendonk
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Nicky Lute
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Clinical Neuropsychology, Vrije University, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Max Planck Institute for Human, Cognitive and Brain Sciences, Leipzig, Germany
| | - Birte U. Forstmann
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
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