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Multi-template analysis of human perirhinal cortex in brain MRI : Explicitly accounting for anatomical variability

Xie, Long ; Pluta, John B ; Das, Sandhitsu R ; Wisse, Laura E M LU orcid ; Wang, Hongzhi ; Mancuso, Lauren ; Kliot, Dasha ; Avants, Brian B ; Ding, Song-Lin and Manjón, José V , et al. (2017) In NeuroImage 144(Pt A). p.183-202
Abstract

RATIONAL: The human perirhinal cortex (PRC) plays critical roles in episodic and semantic memory and visual perception. The PRC consists of Brodmann areas 35 and 36 (BA35, BA36). In Alzheimer's disease (AD), BA35 is the first cortical site affected by neurofibrillary tangle pathology, which is closely linked to neural injury in AD. Large anatomical variability, manifested in the form of different cortical folding and branching patterns, makes it difficult to segment the PRC in MRI scans. Pathology studies have found that in ~97% of specimens, the PRC falls into one of three discrete anatomical variants. However, current methods for PRC segmentation and morphometry in MRI are based on single-template approaches, which may not be able to... (More)

RATIONAL: The human perirhinal cortex (PRC) plays critical roles in episodic and semantic memory and visual perception. The PRC consists of Brodmann areas 35 and 36 (BA35, BA36). In Alzheimer's disease (AD), BA35 is the first cortical site affected by neurofibrillary tangle pathology, which is closely linked to neural injury in AD. Large anatomical variability, manifested in the form of different cortical folding and branching patterns, makes it difficult to segment the PRC in MRI scans. Pathology studies have found that in ~97% of specimens, the PRC falls into one of three discrete anatomical variants. However, current methods for PRC segmentation and morphometry in MRI are based on single-template approaches, which may not be able to accurately model these discrete variants METHODS: A multi-template analysis pipeline that explicitly accounts for anatomical variability is used to automatically label the PRC and measure its thickness in T2-weighted MRI scans. The pipeline uses multi-atlas segmentation to automatically label medial temporal lobe cortices including entorhinal cortex, PRC and the parahippocampal cortex. Pairwise registration between label maps and clustering based on residual dissimilarity after registration are used to construct separate templates for the anatomical variants of the PRC. An optimal path of deformations linking these templates is used to establish correspondences between all the subjects. Experimental evaluation focuses on the ability of single-template and multi-template analyses to detect differences in the thickness of medial temporal lobe cortices between patients with amnestic mild cognitive impairment (aMCI, n=41) and age-matched controls (n=44).

RESULTS: The proposed technique is able to generate templates that recover the three dominant discrete variants of PRC and establish more meaningful correspondences between subjects than a single-template approach. The largest reduction in thickness associated with aMCI, in absolute terms, was found in left BA35 using both regional and summary thickness measures. Further, statistical maps of regional thickness difference between aMCI and controls revealed different patterns for the three anatomical variants.

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publishing date
type
Contribution to journal
publication status
published
keywords
Aged, Aged, 80 and over, Cognitive Dysfunction/diagnostic imaging, Female, Humans, Image Processing, Computer-Assisted/methods, Magnetic Resonance Imaging/methods, Male, Middle Aged, Perirhinal Cortex/anatomy & histology
in
NeuroImage
volume
144
issue
Pt A
pages
183 - 202
publisher
Elsevier
external identifiers
  • scopus:85005923885
  • pmid:27702610
ISSN
1095-9572
DOI
10.1016/j.neuroimage.2016.09.070
language
English
LU publication?
no
additional info
Copyright © 2016 Elsevier Inc. All rights reserved.
id
b63876ca-7808-45bc-a913-07adbfa34e92
date added to LUP
2024-02-28 14:56:30
date last changed
2024-03-01 15:14:53
@article{b63876ca-7808-45bc-a913-07adbfa34e92,
  abstract     = {{<p>RATIONAL: The human perirhinal cortex (PRC) plays critical roles in episodic and semantic memory and visual perception. The PRC consists of Brodmann areas 35 and 36 (BA35, BA36). In Alzheimer's disease (AD), BA35 is the first cortical site affected by neurofibrillary tangle pathology, which is closely linked to neural injury in AD. Large anatomical variability, manifested in the form of different cortical folding and branching patterns, makes it difficult to segment the PRC in MRI scans. Pathology studies have found that in ~97% of specimens, the PRC falls into one of three discrete anatomical variants. However, current methods for PRC segmentation and morphometry in MRI are based on single-template approaches, which may not be able to accurately model these discrete variants METHODS: A multi-template analysis pipeline that explicitly accounts for anatomical variability is used to automatically label the PRC and measure its thickness in T2-weighted MRI scans. The pipeline uses multi-atlas segmentation to automatically label medial temporal lobe cortices including entorhinal cortex, PRC and the parahippocampal cortex. Pairwise registration between label maps and clustering based on residual dissimilarity after registration are used to construct separate templates for the anatomical variants of the PRC. An optimal path of deformations linking these templates is used to establish correspondences between all the subjects. Experimental evaluation focuses on the ability of single-template and multi-template analyses to detect differences in the thickness of medial temporal lobe cortices between patients with amnestic mild cognitive impairment (aMCI, n=41) and age-matched controls (n=44).</p><p>RESULTS: The proposed technique is able to generate templates that recover the three dominant discrete variants of PRC and establish more meaningful correspondences between subjects than a single-template approach. The largest reduction in thickness associated with aMCI, in absolute terms, was found in left BA35 using both regional and summary thickness measures. Further, statistical maps of regional thickness difference between aMCI and controls revealed different patterns for the three anatomical variants.</p>}},
  author       = {{Xie, Long and Pluta, John B and Das, Sandhitsu R and Wisse, Laura E M and Wang, Hongzhi and Mancuso, Lauren and Kliot, Dasha and Avants, Brian B and Ding, Song-Lin and Manjón, José V and Wolk, David A and Yushkevich, Paul A}},
  issn         = {{1095-9572}},
  keywords     = {{Aged; Aged, 80 and over; Cognitive Dysfunction/diagnostic imaging; Female; Humans; Image Processing, Computer-Assisted/methods; Magnetic Resonance Imaging/methods; Male; Middle Aged; Perirhinal Cortex/anatomy & histology}},
  language     = {{eng}},
  month        = {{01}},
  number       = {{Pt A}},
  pages        = {{183--202}},
  publisher    = {{Elsevier}},
  series       = {{NeuroImage}},
  title        = {{Multi-template analysis of human perirhinal cortex in brain MRI : Explicitly accounting for anatomical variability}},
  url          = {{http://dx.doi.org/10.1016/j.neuroimage.2016.09.070}},
  doi          = {{10.1016/j.neuroimage.2016.09.070}},
  volume       = {{144}},
  year         = {{2017}},
}