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Publication Detailed Description
Scientific journal paper
Q2
Comparing SPM12 and CAT12 segmentation pipelines: a brain tissue volume-based age and Alzheimer's disease study
Journal Title
Journal of Neuroscience Methods
Year (definitive publication)
2020
Language
English
Country
Netherlands
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Abstract
Background: Brain volumes have been used as research biomarkers both in health and in Alzheimer's disease(AD). In order to improve the comparability between studies and aid future analytical software platform choice in the research setting, here we compare two segmentation pipelines of structural brain magnetic resonance imaging(sMRI): the SPM12 toolbox, and a SPM12 add-on, the CAT12 toolbox. Methods: We segmented 1.5T and 3T T1-weighted sMRI images (from the OASIS-brain database) using both pipelines and compared them in terms of their impact on: 1)the effect of age on the total grey matter(GM) and white matter(WM), and on the hippocampi GM volumes in a healthy sample(n = 238); 2)the effect of AD diagnosis on the same volume measures; and 3)the accuracy of each volume measure detecting diagnosis (100 patients with AD and 78 age- and gender-matched healthy subjects). Results and comparison between methods: Our results demonstrated that: 1)volume estimates from SPM12 were highly correlated with the ones from CAT12, albeit absolute differences between pipelines were tissue specific; 2)the choice of pipeline modulated the effect of age on all volume measures and of diagnosis on hippocampi GM volumes computed from 3 T data; and 3)pipeline had no impact on the accuracy of any brain volume measure detecting AD diagnosis. Conclusions: Our findings indicate that other studies should take these pipeline effects on age and AD diagnosis, into account, for improved comparability in previous literature. Additionally, we encourage future studies to use CAT12 as this is a more advanced and computationally efficient brain segmentation tool.
Acknowledgements
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Keywords
Brain tissue segmentation,SPM12,CAT12,Alzheimer’s disease diagnosis,Biomarker,Aging
Fields of Science and Technology Classification
- Biological Sciences - Natural Sciences
- Medical Engineering - Engineering and Technology
- Clinical Medicine - Medical and Health Sciences
- Psychology - Social Sciences
Funding Records
Funding Reference | Funding Entity |
---|---|
IF/00787/2014 | Fundação para a Ciência e a Tecnologia |
P50 AG05681 | Bial Foundation |
U24 RR021382 | Bial Foundation |
UIDB/03125/2020 | Fundação para a Ciência e a Tecnologia |
292/16 | Bial Foundation |
P20 MH071616 | Bial Foundation |
PD/BD/114460/2016 | Fundação para a Ciência e a Tecnologia |
R01 AG021910 | Bial Foundation |
DSAIPA/DS/0065/2018 | Fundação para a Ciência e a Tecnologia |
FP7-PEOPLE-2013-CIG-631952 | Comissão Europeia |
PTDC/MEC-PSQ/30907/2017 | Fundação para a Ciência e a Tecnologia |
P01 AG03991 | Bial Foundation |
P01 AG026276 | Bial Foundation |
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