Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment
(2015) In Human Brain Mapping 36(1). p.87-258- Abstract
We evaluate a fully automatic technique for labeling hippocampal subfields and cortical subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs segmentation on a T2-weighted MRI scan with 0.4 × 0.4 × 2.0 mm(3) resolution, partial brain coverage, and oblique orientation. Hippocampal subfields, entorhinal cortex, and perirhinal cortex are labeled using a pipeline that combines multi-atlas label fusion and learning-based error correction. In contrast to earlier work on automatic subfield segmentation in T2-weighted MRI [Yushkevich et al., 2010], our approach requires no manual initialization, labels hippocampal subfields over a greater anterior-posterior extent, and labels the perirhinal cortex, which is further... (More)
We evaluate a fully automatic technique for labeling hippocampal subfields and cortical subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs segmentation on a T2-weighted MRI scan with 0.4 × 0.4 × 2.0 mm(3) resolution, partial brain coverage, and oblique orientation. Hippocampal subfields, entorhinal cortex, and perirhinal cortex are labeled using a pipeline that combines multi-atlas label fusion and learning-based error correction. In contrast to earlier work on automatic subfield segmentation in T2-weighted MRI [Yushkevich et al., 2010], our approach requires no manual initialization, labels hippocampal subfields over a greater anterior-posterior extent, and labels the perirhinal cortex, which is further subdivided into Brodmann areas 35 and 36. The accuracy of the automatic segmentation relative to manual segmentation is measured using cross-validation in 29 subjects from a study of amnestic mild cognitive impairment (aMCI) and is highest for the dentate gyrus (Dice coefficient is 0.823), CA1 (0.803), perirhinal cortex (0.797), and entorhinal cortex (0.786) labels. A larger cohort of 83 subjects is used to examine the effects of aMCI in the hippocampal region using both subfield volume and regional subfield thickness maps. Most significant differences between aMCI and healthy aging are observed bilaterally in the CA1 subfield and in the left Brodmann area 35. Thickness analysis results are consistent with volumetry, but provide additional regional specificity and suggest nonuniformity in the effects of aMCI on hippocampal subfields and MTL cortical subregions.
(Less)
- author
- Yushkevich, Paul A
; Pluta, John B
; Wang, Hongzhi
; Xie, Long
; Ding, Song-Lin
; Gertje, Eske C
LU
; Mancuso, Lauren ; Kliot, Daria ; Das, Sandhitsu R and Wolk, David A
- publishing date
- 2015-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Algorithms, Brain Mapping, Cognitive Dysfunction/pathology, Electronic Data Processing, Female, Hippocampus/pathology, Humans, Image Processing, Computer-Assisted, Learning/physiology, Magnetic Resonance Imaging, Male, Temporal Lobe/pathology
- in
- Human Brain Mapping
- volume
- 36
- issue
- 1
- pages
- 87 - 258
- publisher
- Wiley-Liss Inc.
- external identifiers
-
- pmid:25181316
- scopus:84916925772
- ISSN
- 1065-9471
- DOI
- 10.1002/hbm.22627
- language
- English
- LU publication?
- no
- additional info
- © 2014 Wiley Periodicals, Inc.
- id
- c051d9f2-07e1-42de-b249-0f02d7b1f853
- date added to LUP
- 2025-03-05 16:36:26
- date last changed
- 2025-07-25 01:30:14
@article{c051d9f2-07e1-42de-b249-0f02d7b1f853, abstract = {{<p>We evaluate a fully automatic technique for labeling hippocampal subfields and cortical subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs segmentation on a T2-weighted MRI scan with 0.4 × 0.4 × 2.0 mm(3) resolution, partial brain coverage, and oblique orientation. Hippocampal subfields, entorhinal cortex, and perirhinal cortex are labeled using a pipeline that combines multi-atlas label fusion and learning-based error correction. In contrast to earlier work on automatic subfield segmentation in T2-weighted MRI [Yushkevich et al., 2010], our approach requires no manual initialization, labels hippocampal subfields over a greater anterior-posterior extent, and labels the perirhinal cortex, which is further subdivided into Brodmann areas 35 and 36. The accuracy of the automatic segmentation relative to manual segmentation is measured using cross-validation in 29 subjects from a study of amnestic mild cognitive impairment (aMCI) and is highest for the dentate gyrus (Dice coefficient is 0.823), CA1 (0.803), perirhinal cortex (0.797), and entorhinal cortex (0.786) labels. A larger cohort of 83 subjects is used to examine the effects of aMCI in the hippocampal region using both subfield volume and regional subfield thickness maps. Most significant differences between aMCI and healthy aging are observed bilaterally in the CA1 subfield and in the left Brodmann area 35. Thickness analysis results are consistent with volumetry, but provide additional regional specificity and suggest nonuniformity in the effects of aMCI on hippocampal subfields and MTL cortical subregions.</p>}}, author = {{Yushkevich, Paul A and Pluta, John B and Wang, Hongzhi and Xie, Long and Ding, Song-Lin and Gertje, Eske C and Mancuso, Lauren and Kliot, Daria and Das, Sandhitsu R and Wolk, David A}}, issn = {{1065-9471}}, keywords = {{Algorithms; Brain Mapping; Cognitive Dysfunction/pathology; Electronic Data Processing; Female; Hippocampus/pathology; Humans; Image Processing, Computer-Assisted; Learning/physiology; Magnetic Resonance Imaging; Male; Temporal Lobe/pathology}}, language = {{eng}}, number = {{1}}, pages = {{87--258}}, publisher = {{Wiley-Liss Inc.}}, series = {{Human Brain Mapping}}, title = {{Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment}}, url = {{http://dx.doi.org/10.1002/hbm.22627}}, doi = {{10.1002/hbm.22627}}, volume = {{36}}, year = {{2015}}, }