In vivo Analysis of Hippocampal Subfield Atrophy in Mild Cognitive Impairment via Semi-Automatic Segmentation of T2-Weighted MRI
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The measurement of hippocampal volumes using MRI is a useful in-vivo biomarker for detection and monitoring of early Alzheimer's disease (AD), including during the amnestic mild cognitive impairment (a-MCI) stage. The pathology underlying AD has regionally selective effects within the hippocampus. As such, we predict that hippocampal subfields are more sensitive in discriminating prodromal AD (i.e., a-MCI) from cognitively normal controls than whole hippocampal volumes, and attempt to demonstrate this using a semi-automatic method that can accurately segment hippocampal subfields. High-resolution coronal-oblique T2-weighted images of the hippocampal formation were acquired in 45 subjects (28 controls and 17 a-MCI (mean age: 69.5 ± 9.2; 70.2 ± 7.6)). CA1, CA2, CA3, and CA4/DG subfields, along with head and tail regions, were segmented using an automatic algorithm. CA1 and CA4/DG segmentations were manually edited. Whole hippocampal volumes were obtained from the subjects' T1-weighted anatomical images. Automatic segmentation produced significant group differences in the following subfields: CA1 (left: p = 0.001, right: p = 0.038), CA4/DG (left: p = 0.002, right: p = 0.043), head (left: p = 0.018, right: p = 0.002), and tail (left: p = 0.019). After manual correction, differences were increased in CA1 (left: p < 0.001, right: p = 0.002), and reduced in CA4/DG (left: p = 0.029, right: p = 0.221). Whole hippocampal volumes significantly differed bilaterally (left: p = 0.028, right: p = 0.009). This pattern of atrophy in a-MCI is consistent with the topography of AD pathology observed in postmortem studies, and corrected left CA1 provided stronger discrimination than whole hippocampal volume (p = 0.03). These results suggest that semi-automatic segmentation of hippocampal subfields is efficient and may provide additional sensitivity beyond whole hippocampal volumes.
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Literature on individuals with MCI is more controversial, with discrepant data resulting from adoption of the same subfield segmentation procedure.
“Analogous literature on individuals with MCI is still more controversial, with discrepant data resulting from adoption of the same subfield segmentation procedure.”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [38]
The volume of the subiculum was reported to be normal in MCI in a manual segmentation study and an automated segmentation study but significantly reduced in two other studies using manual or automated segmentation.
“Thus, for example, the volume of the subiculum was reported to be normal in MCI in a study that relied on manual segmentation [35] and in another study that used an automated segmentation method [38] but was significantly reduced in two other studies that also used a method of manual [39] or automated segmentation [40].”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [38]
Discrepancies exist as regards to the area of largest difference between HC and aMCI patients, probably reflecting variations in the anatomical landmarks used for subfield delineation.
“However, discrepancies exist as regards to the area of largest difference between HC and aMCI patients (CA1 (Pluta et al., 2012), CA1–CA2 transition area (Mueller et al., 2010) or subiculum (Hanseeuw, 2011), probably reflecting variations in the anatomical landmarks used for subfield delineation”
From Hippocampal subfield volumetry in mild cognitive impairment, Alzheimer's disease and semantic dementia (2013) · cites this paper as Pluta et al., 2012
Subfield measurements were more accurate than global hippocampal volumetry to differentiate aMCI from HC.
“we showed that subfield measurements were more accurate than global hippocampal volumetry to differentiate aMCI from HC”
From Hippocampal subfield volumetry in mild cognitive impairment, Alzheimer's disease and semantic dementia (2013) · cites this paper as Pluta et al., 2012
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- Authors
- Pluta, J., Yushkevich, P., Das, S., & Wolk, D.
- Affiliations
- Hospital of the University of Pennsylvania (US)
- University of Pennsylvania (US)
- Corresponding author
- Pluta, John
- Venue
- Journal of Alzheimer's Disease
- Publisher
- SAGE Publications
- Published
- 2012-07-05
- Volume
- 31
- Issue
- 1
- Pages
- 85-99
- ISSN
- 1387-2877 (ISSN-L)
- 1875-8908
- PMC
- PMC3391337
- OpenAlex
- W1508239224
- Cited by
- 107
- References
- 74
- Citations by year
- 2026: 1 · 2024: 7 · 2023: 3 · 2022: 4 · 2021: 4 · 2020: 9 · 2019: 6 · 2018: 4 · 2017: 10 · 2016: 8 · 2015: 23 · 2014: 18 · 2013: 9 · 2012: 1
- FWCI
- 11.61
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Alzheimer s Disease (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (P30AG010124, R01AG037376, K23AG028018, K25AG027785)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Keywords
- hippocampal atrophy
- MeSH terms
- Atrophy, Electronic Data Processing, Female, Hippocampus, Humans, Functional Laterality, Magnetic Resonance Imaging, Male, ROC Curve, Chi-Square Distribution, Case-Control Studies, Area Under Curve, Cognitive Dysfunction
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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