Comparing manual and automatic segmentation of hippocampal volumes: reliability and validity issues in younger and older brains
Open accessAbstract
We compared hippocampal volume measures obtained by manual tracing to automatic segmentation with FreeSurfer in 44 younger (20-30 years) and 47 older (60-70 years) adults, each measured with magnetic resonance imaging (MRI) over three successive time points, separated by four months. Retest correlations over time were very high for both manual and FreeSurfer segmentations. With FreeSurfer, correlations over time were significantly lower in the older than in the younger age group, which was not the case with manual segmentation. Pearson correlations between manual and FreeSurfer estimates were sufficiently high, numerically even higher in the younger group, whereas intra-class correlation coefficient (ICC) estimates were lower in the younger than in the older group. FreeSurfer yielded higher volume estimates than manual segmentation, particularly in the younger age group. Importantly, FreeSurfer consistently overestimated hippocampal volumes independently of manually assessed volume in the younger age group, but overestimated larger volumes in the older age group to a less extent, introducing a systematic age bias in the data. Age differences in hippocampal volumes were significant with FreeSurfer, but not with manual tracing. Manual tracing resulted in a significant difference between left and right hippocampus (right > left), whereas this asymmetry effect was considerably smaller with FreeSurfer estimates. We conclude that FreeSurfer constitutes a feasible method to assess d…
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Various studies have reported high rates of failures resulting in exclusion of large number of scans, inconsistencies in segmentations and age related bias for Freesurfer.
“Although Freesurfer is extensively validated and it has been used in a large number of studies, various studies have also reported high rates of failures resulting in exclusion of large number of scans, inconsistencies in segmentations and age related bias (Wenger et al., 2014; Cherbuin et al., 2009).”
From A comparison of Freesurfer and multi-atlas MUSE for brain anatomy segmentation: Findings about size and age bias, and inter-scanner stability in multi-site aging studies (2020) · cites this paper as Wenger et al., 2014
Cites
Intraclass correlations: Uses in assessing rater reliability.
Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 23,433 · see citing works
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610 · see citing works
Navigation-related structural change in the hippocampi of taxi drivers
Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S. J., & Frith, C. D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.070039597 · Cited by 3,225 · see citing works
Neural consequences of enviromental enrichment
van Praag, H., Kempermann, G., & Gage, F. H. (2000) · Nature Reviews Neuroscience · doi:10.1038/35044558 · Cited by 2,468 · see citing works
Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment
Jack, C. R., Petersen, R. C., Xu, Y. C., O’Brien, P. C., Smith, G. E., Ivnik, R. J., Boeve, B. F., Waring, S. C., Tangalos, E. G., & Kokmen, E. (1999) · Neurology · doi:10.1212/wnl.52.7.1397 · Cited by 1,404 · see citing works
Physical exercise prevents age-related decline in precursor cell activity in the mouse dentate gyrus
Kronenberg, G., Bick-Sander, A., Bunk, E., Wolf, C., Ehninger, D., & Kempermann, G. (2006) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2005.09.016 · Cited by 477 · see citing works
Shi, F., Liu, B., Zhou, Y., Yu, C., & Jiang, T. (2009) · Hippocampus · doi:10.1002/hipo.20573 · Cited by 470 · see citing works
Cherbuin, N., Anstey, K. J., Réglade-Meslin, C., & Sachdev, P. S. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005265 · Cited by 116 · see citing works
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Gorbach, T., Pudas, S., Lundquist, A., Orädd, G., Josefsson, M., Salami, A., de Luna, X., & Nyberg, L. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.12.002 · Cited by 245 · see citing works
Hebscher, M., Levine, B., & Gilboa, A. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2017.03.029 · Cited by 112 · see citing works
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Gold, A. L., Steuber, E. R., White, L. K., Pacheco, J., Sachs, J. F., Pagliaccio, D., Berman, E., Leibenluft, E., & Pine, D. S. (2017) · Neuropsychopharmacology · doi:10.1038/npp.2017.83 · Cited by 99 · see citing works
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Henje Blom, E., Han, L. K. M., Connolly, C. G., Ho, T. C., Lin, J., LeWinn, K. Z., Simmons, A. N., Sacchet, M. D., Mobayed, N., Luna, M. E., et al. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.172 · Cited by 51 · see citing works
Srinivasan, D., Erus, G., Doshi, J., Wolk, D. A., Shou, H., Habes, M., & Davatzikos, C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117248 · Cited by 45 · see citing works
Sakurai, R., Ishii, K., Sakuma, N., Yasunaga, M., Suzuki, H., Murayama, Y., Nishi, M., Uchida, H., Shinkai, S., & Fujiwara, Y. (2018) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4785 · Cited by 37 · see citing works
- Authors
- Wenger, E., Mårtensson, J., Noack, H., Bodammer, N. C., Kühn, S., Schaefer, S., Heinze, H., Düzel, E., Bäckman, L., Lindenberger, U., & Lövdén, M.
- Affiliations
- Max Planck Institute for Human Development (DE)
- Lund University (SE)
- German Center for Neurodegenerative Diseases (DE)
- University College London (GB)
- Stockholm University (SE)
- ORCID
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2014-02-14
- Volume
- 35
- Issue
- 8
- Pages
- 4236-4248
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- PMC
- PMC6869097
- OpenAlex
- W1749244360
- Cited by
- 151
- References
- 8
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 5 · 2023: 7 · 2022: 12 · 2021: 16 · 2020: 20 · 2019: 14 · 2018: 19 · 2017: 15 · 2016: 11 · 2015: 21 · 2014: 9
- FWCI
- 16.68
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Human Brain Mapping (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- Lund University Publications (Lund University) (submittedVersion)
- DZNE Pub (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Funders
- Max Planck Society
- Sofja Kovalevskaja Award, the Alexander von Humboldt foundation, the German Federal Ministry for Education and Research
- German Research Council; BMBF
- Swedish Research Council
- Swedish Brain Power
- Alexander von Humboldt Research Award
- af Jochnick Foundation
- International Max Planck Research School “The Life Course: Evolutionary and Ontogenetic Dynamics” (LIFE).
- 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, automatic segmentation, manual tracing, reliability statistics, validity, age bias, older adults, hippocampal asymmetry, hippocampal atrophy
- MeSH terms
- Adult, Aged, Feasibility Studies, Hippocampus, Humans, Functional Laterality, Longitudinal Studies, Magnetic Resonance Imaging, Middle Aged, Organ Size, Pattern Recognition, Automated, Signal Processing, Computer-Assisted, Software, Reproducibility of Results, Young Adult
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