Longitudinal Assessment of Hippocampal Atrophy in Midlife and Early Old Age: Contrasting Manual Tracing and Semi-automated Segmentation (FreeSurfer)
- 300 Downloads
It is important to have accurate estimates of normal age-related brain structure changes and to understand how the choice of measurement technique may bias those estimates. We compared longitudinal change in hippocampal volume, laterality and atrophy measured by manual tracing and FreeSurfer (version 5.3) in middle age (n = 244, 47.2[1.4] years) and older age (n = 199, 67.0[1.4] years) individuals over 8 years. The proportion of overlap (Dice coefficient) between the segmented hippocampi was calculated and we hypothesised that the proportion of overlap would be higher for older individuals as a consequence of higher atrophy. Hippocampal volumes produced by FreeSurfer were larger than manually traced volumes. Both methods produced a left less than right volume laterality difference. Over time this laterality difference increased for manual tracing and decreased for FreeSurfer leading to laterality differences in left and right estimated atrophy rates. The overlap proportion between methods was not significantly different for older individuals, but was greater for the right hippocampus. Estimated middle age annualised atrophy rates were − 0.39(1.0) left, 0.07(1.01) right, − 0.17(0.88) total for manual tracing and − 0.15(0.69) left, − 0.20(0.63) right, − 0.18(0.57) total for FreeSurfer. Older age atrophy rates were − 0.43(1.32) left, − 0.15(1.41) right, − 0.30 (1.23) total for manual tracing and − 0.34(0.79) left, − 0.68(0.78) right, − 0.51(0.65) total for FreeSurfer. FreeSurfer reliably segments the hippocampus producing atrophy rates that are comparable to manual tracing with some biases that need to be considered in study design. FreeSurfer is suited for use in large longitudinal studies where it is not cost effective to use manual tracing.
KeywordsHippocampus Longitudinal FreeSurfer Manual tracing Normal ageing Magnetic resonance imaging
The authors are grateful to Chantal Réglade-Meslin, Jerome Maller, Peter Butterworth, Simon Easteal, Helen Christensen, Patricia Jacomb, Karen Maxwell, and the PATH interviewers. The study was supported by an Australian Government Research Training Program (RTP) Scholarship, National Health and Medical Research Council (NHMRC) Grant Nos. 973302, 179805,350833 157125, and Australian Research Council (ARC) Grant No. 130101705. Kaarin Anstey was funded by NHMRC Fellowship No.1002560. This research was partly undertaken on the National Computational Infrastructure (NCI) facility in Canberra, Australia, which is supported by the Australian Commonwealth Government. The authors declare no competing financial interests. This research is supported by an Australian Government Research Training Program (RTP) Scholarship. This study is NOT industry sponsored.
MAF contributed to the design of the study, conducted all statistical analyses, and managed all aspects of manuscript preparation and submission. MES contributed to the design of the study and the statistical analyses, provided methodological input and theoretical expertise, and contributed to writing and editing of the manuscript. KJA contributed to the design of the study, provided methodological input and theoretical expertise, and contributed to writing and editing of the manuscript. NC contributed to the design of the study and the statistical analyses, provided methodological input and theoretical expertise, and contributed to writing and editing of the manuscript.
Compliance with Ethical Standards
Conflict of interest
The authors have reported no conflicts of interest.
- Arnold SJ et al (2015) Hippocampal volume is reduced in schizophrenia and schizoaffective disorder but not in psychotic bipolar I disorder demonstrated by both manual tracing and automated parcellation (FreeSurfer). Schizophr Bull 41:233–249. https://doi.org/10.1093/schbul/sbu009 CrossRefPubMedGoogle Scholar
- Barnes J et al (2009a) A meta-analysis of hippocampal atrophy rates in Alzheimer’s disease. Neurobiol Aging 30:1711–1723. https://doi.org/10.1016/j.neurobiolaging.2008.01.010 CrossRefPubMedGoogle Scholar
- Buckner RL, Head D, Parker J, Fotenos AF, Marcus D, Morris JC, Snyder AZ (2004) A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume. Neuroimage 23:724–738. https://doi.org/10.1016/j.neuroimage.2004.06.018 CrossRefPubMedGoogle Scholar
- Doring TM, Kubo TT, Cruz LC Jr, Juruena MF, Fainberg J, Domingues RC, Gasparetto EL (2011) Evaluation of hippocampal volume based on MR imaging in patients with bipolar affective disorder applying manual and automatic segmentation techniques. J Magn Reson Imaging 33:565–572. https://doi.org/10.1002/jmri.22473 CrossRefPubMedGoogle Scholar
- Fjell AM et al (2013) Critical ages in the life course of the adult brain: nonlinear subcortical aging. Neurobiol Aging 34:2239–2247. https://doi.org/10.1016/j.neurobiolaging.2013.04.006 CrossRefPubMedPubMedCentralGoogle Scholar
- Gronenschild EHBM, Habets P, Jacobs HIL, Mengelers R, Rozendaal N, van Os J, Marcelis M (2012) The effects of freesurfer version, workstation type, and macintosh operating system version on anatomical volume and cortical thickness measurements. PLoS ONE https://doi.org/10.1371/journal.pone.0038234 CrossRefPubMedPubMedCentralGoogle Scholar
- Makris N et al (2004) General brain segmentation: method and utilization Massachusetts General Hospital Boston, MA, USAGoogle Scholar
- Pfefferbaum A, Sullivan EV (2015) Cross-sectional versus longitudinal estimates of age-related changes in the adult brain: overlaps and discrepancies. Neurobiol Aging 36:2563–2567. https://doi.org/10.1016/j.neurobiolaging.2015.05.005 CrossRefPubMedPubMedCentralGoogle Scholar
- Sánchez-Benavides G, Gómez-Ansón B, Sainz A, Vives Y, Delfino M, Peña-Casanova J (2010) Manual validation of FreeSurfer’s automated hippocampal segmentation in normal aging, mild cognitive impairment, and Alzheimer disease subjects. Psychiatry Res 181:219–225. https://doi.org/10.1016/j.pscychresns.2009.10.011 CrossRefPubMedGoogle Scholar
- Shaw ME, Sachdev PS, Anstey KJ, Cherbuin N (2016b) Age-related cortical thinning in cognitively healthy individuals in their 60s: the PATH through life study. Neurobiol Aging 39:202–209. https://doi.org/10.1016/j.neurobiolaging.2015.12.009 CrossRefPubMedGoogle Scholar