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  Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset

Kulaga-Yoskovitz, J., Bernhardt, B. C., Hong, S.-J., Mansi, T., Liang, K. E., Van der Kouwe, A. J., et al. (2015). Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset. Scientific Data, 2: 150059. doi:10.1038/sdata.2015.59.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-E5E8-6 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-605A-C
Genre: Journal Article

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 Creators:
Kulaga-Yoskovitz, Jessie 1, Author
Bernhardt, Boris C.1, 2, Author              
Hong, Seok-Jun 1, Author
Mansi, Tommaso 1, Author
Liang, Kevin E. 1, Author
Van der Kouwe, Andre J.W. 1, Author
Smallwood, Jonathan1, Author              
Bernasconi, Andrea 1, Author
Bernasconi, Neda 1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Department Social Neuroscience, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634552              

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Free keywords: Brain; Brain imaging; Magnetic resonance imaging; Neurology; Neuroscience
 Abstract: The hippocampus is composed of distinct anatomical subregions that participate in multiple cognitive processes and are differentially affected in prevalent neurological and psychiatric conditions. Advances in high-field MRI allow for the non-invasive identification of hippocampal substructure. These approaches, however, demand time-consuming manual segmentation that relies heavily on anatomical expertise. Here, we share manual labels and associated high-resolution MRI data (MNI-HISUB25; submillimetric T1- and T2-weighted images, detailed sequence information, and stereotaxic probabilistic anatomical maps) based on 25 healthy subjects. Data were acquired on a widely available 3 Tesla MRI system using a 32 phased-array head coil. The protocol divided the hippocampal formation into three subregions: subicular complex, merged Cornu Ammonis 1, 2 and 3 (CA1-3) subfields, and CA4-dentate gyrus (CA4-DG). Segmentation was guided by consistent intensity and morphology characteristics of the densely myelinated molecular layer together with few geometry-based boundaries flexible to overall mesiotemporal anatomy, and achieved excellent intra-/inter-rater reliability (Dice index ≥90/87%). The dataset can inform neuroimaging assessments of the mesiotemporal lobe and help to develop segmentation algorithms relevant for basic and clinical neurosciences.

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Language(s): eng - English
 Dates: 2015-08-102015-10-072015-11-10
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1038/sdata.2015.59
PMID: 26594378
PMC: PMC4640139
Other: eCollection 2015
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Title: Scientific Data
  Abbreviation : Sci. Data
Source Genre: Journal
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Publ. Info: London, United Kingdom : Nature Publishing Group
Pages: - Volume / Issue: 2 Sequence Number: 150059 Start / End Page: - Identifier: ISSN: 2052-4463
CoNE: https://pure.mpg.de/cone/journals/resource/2052-4463