Cited by 116Medical Image Segmentation TechniquesDementia and Cognitive Impairment ResearchMemory and Neural Mechanisms

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In Vivo Hippocampal Measurement and Memory: A Comparison of Manual Tracing and Automated Segmentation in a Large Community-Based Sample

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Cherbuin, Nicolas, Anstey, Kaarin J., Réglade-Meslin, Chantal, Sachdev, Perminder S.·2009·PLoS ONE

DOI 10.1371/journal.pone.0005265PMC PMC2667216

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Abstract

While manual tracing is the method of choice in measuring hippocampal volume, its time intensive nature and proneness to human error make automated methods attractive, especially when applied to large samples. Few studies have systematically compared the performance of the two techniques. In this study, we measured hippocampal volumes in a large (N = 403) population-based sample of individuals aged 44-48 years using manual tracing by a trained researcher and automated procedure using Freesurfer (http://surfer.nmr.mgh.harvard.edu) imaging suite. Results showed that absolute hippocampal volumes assessed with these methods were significantly different, with automated measures using the Freesurfer software suite being significantly larger, by 23% for the left and 29% for the right hippocampus. The correlation between the two methods varied from 0.61 to 0.80, with lower correlations for hippocampi with visible abnormalities. Inspection of 2D and 3D models suggested that this difference was largely due to greater inclusion of boundary voxels by the automated method and variations in subiculum/entorhinal segmentation. The correlation between left and right hippocampal volumes was very similar by the two methods. The relationship of hippocampal volumes to selected sociodemographic and cognitive variables was not affected by the measurement method, with each measure showing an association with memory performance and suggesting that both were equally valid for this purpose. This study supports the use of automated measures, based on Freesurfer in this instance, as being sufficiently reliable and valid particularly in the context of larger sample sizes when the research question does not rely on 'true' hippocampal volumes.

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Figure 1 Examplars of automatically segmented hippocampi rated as a) no or minor defects (defects estimated to be smaller than ∼0.5% of total volume) b) moderate defects (∼0.5–5% of total volume), major defects (greater than 5% of total volume).CC BY · PubMed Central

Figure 2 Left and right hippocampal volumes measured by manual tracing (green) and automatic segmentation (yellow). ** significant difference at p<.01.CC BY · PubMed Central

Figure 3 Bland-Altman diagrams plotting the difference in hipocampal volumes computed with the manual and automated methods against their average for each hippocampal pairs for the right (top) and left (bottom) hippocampus. The even scatter suggests there is no systematic error between methodologies beside the difference in absolute volume.CC BY · PubMed Central

Figure 4 Randomly selected 3D models of manually traced (green) and automatically segmented (yellow) hippocampus pairs. The models were produced using the ITK-Snap software package (www.itksnap.org) for the manual tracings and the Slicer package (www.slicer.org) for the automated measures.CC BY · PubMed Central

Figure 5 Manual tracing (left) and automated segmentation (right) of the hippocampus showing boundary differences (1 & 6: CSF inclusions; 2 greater subicular/entorhinal inclusion; 4 & 5 greater partial volume inclusion).CC BY · PubMed Central

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Authors: Cherbuin, N., Anstey, K. J., Réglade-Meslin, C., & Sachdev, P. S.
Affiliations: Australian National University (AU)
UNSW Sydney (AU)
Corresponding author: Cherbuin, Nicolas
ORCID: Cherbuin, Nicolas
Anstey, Kaarin J.
Sachdev, Perminder S.
Venue: PLoS ONE
Publisher: Public Library of Science (PLoS)
Published: 2009-04-16
Volume: 4
Issue: 4
Pages: e5265
ISSN: 1932-6203 (ISSN-L)
DOI: 10.1371/journal.pone.0005265
PMC: PMC2667216
OpenAlex: W2061639197
Cited by: 116
References: 39
Citations by year: 2026: 1 · 2025: 2 · 2024: 2 · 2023: 5 · 2022: 6 · 2021: 4 · 2020: 5 · 2019: 6 · 2018: 8 · 2017: 6 · 2016: 10 · 2015: 13 · 2014: 9 · 2013: 11 · 2012: 7
FWCI: 10.30
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: PLoS ONE (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
UNSWorks (UNSW Sydney) (submittedVersion, cc-by-nc-nd)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
ANU Open Research (Australian National University) (submittedVersion, cc-by)
Funders: Australian Rotary Health
Medical Research Council
National Health and Medical Research Council (973302, 366756, 418020, 157125, 179805)
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords: hippocampal volume, FreeSurfer, measurement method comparison, memory performance, community sample
MeSH terms: Adult, Female, Hippocampus, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Memory, Middle Aged, Organ Size, Pattern Recognition, Automated, Regression Analysis, Socioeconomic Factors, Imaging, Three-Dimensional

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In Vivo Hippocampal Measurement and Memory: A Comparison of Manual Tracing and Automated Segmentation in a Large Community-Based Sample

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