Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease
(2019) In Human Brain Mapping 40(12). p.3431-3451- Abstract
Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the... (More)
Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.
(Less)
- author
- author collaboration
- publishing date
- 2019-08-15
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Aged, Aged, 80 and over, Alzheimer Disease/diagnostic imaging, Cognitive Dysfunction/diagnostic imaging, Female, Humans, Magnetic Resonance Imaging/methods, Male, Mental Status and Dementia Tests, Middle Aged, Temporal Lobe/diagnostic imaging
- in
- Human Brain Mapping
- volume
- 40
- issue
- 12
- pages
- 3431 - 3451
- publisher
- Wiley-Blackwell
- external identifiers
-
- scopus:85065180760
- pmid:31034738
- ISSN
- 1065-9471
- DOI
- 10.1002/hbm.24607
- language
- English
- LU publication?
- no
- additional info
- © 2019 Wiley Periodicals, Inc.
- id
- e5ff58a7-2441-4862-a014-374aa6df5f61
- date added to LUP
- 2024-02-28 14:42:08
- date last changed
- 2024-04-14 00:19:02
@article{e5ff58a7-2441-4862-a014-374aa6df5f61, abstract = {{<p>Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.</p>}}, author = {{Xie, Long and Wisse, Laura E M and Pluta, John and de Flores, Robin and Piskin, Virgine and Manjón, Jose V and Wang, Hongzhi and Das, Sandhitsu R and Ding, Song-Lin and Wolk, David A and Yushkevich, Paul A}}, issn = {{1065-9471}}, keywords = {{Aged; Aged, 80 and over; Alzheimer Disease/diagnostic imaging; Cognitive Dysfunction/diagnostic imaging; Female; Humans; Magnetic Resonance Imaging/methods; Male; Mental Status and Dementia Tests; Middle Aged; Temporal Lobe/diagnostic imaging}}, language = {{eng}}, month = {{08}}, number = {{12}}, pages = {{3431--3451}}, publisher = {{Wiley-Blackwell}}, series = {{Human Brain Mapping}}, title = {{Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease}}, url = {{http://dx.doi.org/10.1002/hbm.24607}}, doi = {{10.1002/hbm.24607}}, volume = {{40}}, year = {{2019}}, }