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dc.contributor.authorSörös, Peter
dc.contributor.authorWölk, Louise
dc.contributor.authorBantel, Carsten
dc.contributor.authorBräuer, Anja
dc.contributor.authorKlawonn, Frank
dc.contributor.authorWitt, Karsten
dc.date.accessioned2021-02-15T13:29:46Z
dc.date.available2021-02-15T13:29:46Z
dc.date.issued2021-01-09
dc.identifier.citationCerebellum. 2021 Jan 9. doi: 10.1007/s12311-020-01227-2. Epub ahead of print.en_US
dc.identifier.pmid33421018
dc.identifier.doi10.1007/s12311-020-01227-2
dc.identifier.urihttp://hdl.handle.net/10033/622741
dc.description.abstractTo identify robust and reproducible methods of cerebellar morphometry that can be used in future large-scale structural MRI studies, we investigated the replicability, repeatability, and long-term reproducibility of three fully automated software tools: FreeSurfer, CEREbellum Segmentation (CERES), and automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization (ACAPULCO). Replicability was defined as computational replicability, determined by comparing two analyses of the same high-resolution MRI data set performed with identical analysis software and computer hardware. Repeatability was determined by comparing the analyses of two MRI scans of the same participant taken during two independent MRI sessions on the same day for the Kirby-21 study. Long-term reproducibility was assessed by analyzing two MRI scans of the same participant in the longitudinal OASIS-2 study. We determined percent difference, the image intraclass correlation coefficient, the coefficient of variation, and the intraclass correlation coefficient between two analyses. Our results show that CERES and ACAPULCO use stochastic algorithms that result in surprisingly high differences between identical analyses for ACAPULCO and small differences for CERES. Changes between two consecutive scans from the Kirby-21 study were less than ± 5% in most cases for FreeSurfer and CERES (i.e., demonstrating high repeatability). As expected, long-term reproducibility was lower than repeatability for all software tools. In summary, CERES is an accurate, as demonstrated before, and reproducible tool for fully automated segmentation and parcellation of the cerebellum. We conclude with recommendations for the assessment of replicability, repeatability, and long-term reproducibility in future studies on cerebellar structure.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectCERESen_US
dc.subjectCerebellumen_US
dc.subjectFreeSurferen_US
dc.subjectParcellationen_US
dc.subjectReproducibilityen_US
dc.subjectSegmentationen_US
dc.titleReplicability, Repeatability, and Long-term Reproducibility of Cerebellar Morphometry.en_US
dc.typeArticleen_US
dc.identifier.eissn1473-4230
dc.contributor.departmentHZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.en_US
dc.identifier.journalCerebellum (London, England)en_US
refterms.dateFOA2021-02-15T13:29:47Z
dc.source.journaltitleCerebellum (London, England)
dc.source.countryUnited States


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International