Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/11537
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dc.contributor.authorPardoe, Heath Ren
dc.contributor.authorAbbott, David Fen
dc.contributor.authorJackson, Graeme Den
dc.date.accessioned2015-05-16T01:09:03Z
dc.date.available2015-05-16T01:09:03Z
dc.date.issued2012-07-17en
dc.identifier.citationHuman Brain Mapping 2012; 34(11): 3000-9en
dc.identifier.govdoc22807270en
dc.identifier.otherPUBMEDen
dc.identifier.urihttp://ahro.austin.org.au/austinjspui/handle/1/11537en
dc.description.abstractCortical thickness mapping is a widely used method for the analysis of neuroanatomical differences between subject groups. We applied power analysis methods over a range of image processing parameters to derive a model that allows researchers to calculate the number of subjects required to ensure a well-powered cross-sectional cortical thickness study.0.9-mm isotropic T1 -weighted 3D MPRAGE MRI scans from 98 controls (53 females, age 29.1 ± 9.7 years) were processed using Freesurfer 5.0. Power analyses were carried out using vertex-wise variance estimates from the coregistered cortical thickness maps, systematically varying processing parameters. A genetic programming approach was used to derive a model describing the relationship between sample size and processing parameters. The model was validated on four Alzheimer's Disease Neuroimaging Initiative control datasets (mean 126.5 subjects/site, age 76.6 ± 5.0 years).Approximately 50 subjects per group are required to detect a 0.25-mm thickness difference; less than 10 subjects per group are required for differences of 1 mm (two-sided test, 10 mm smoothing, α = 0.05). Sample size estimates were heterogeneous over the cortical surface. The model yielded sample size predictions within 2-6% of that determined experimentally using independent data from four other datasets. Fitting parameters of the model to data from each site reduced the estimation error to less than 2%.The derived model provides a simple tool for researchers to calculate how many subjects should be included in a well-powered cortical thickness analysis.en
dc.language.isoenen
dc.subject.otherMRIen
dc.subject.othercortical thicknessen
dc.subject.othermorphometryen
dc.subject.otherneuroimagingen
dc.subject.otherpower analysisen
dc.subject.otherstudy designen
dc.subject.otherAdulten
dc.subject.otherAnatomy, Cross-Sectional.methodsen
dc.subject.otherBrain Mapping.methodsen
dc.subject.otherCerebral Cortex.anatomy & histologyen
dc.subject.otherCohort Studiesen
dc.subject.otherData Interpretation, Statisticalen
dc.subject.otherFemaleen
dc.subject.otherGenetic Processesen
dc.subject.otherHumansen
dc.subject.otherImage Processing, Computer-Assisteden
dc.subject.otherMagnetic Resonance Imagingen
dc.subject.otherMaleen
dc.subject.otherModels, Neurologicalen
dc.subject.otherReproducibility of Resultsen
dc.subject.otherSample Sizeen
dc.subject.otherYoung Adulten
dc.titleSample size estimates for well-powered cross-sectional cortical thickness studies.en
dc.typeJournal Articleen
dc.identifier.journaltitleHuman brain mappingen
dc.identifier.affiliationBrain Research Institute, Florey Neuroscience Institutes, Melbourne Brain Centre, Austin Hospital, Heidelberg, Victoria, Australiaen
dc.identifier.affiliationDepartment of Medicine, The University of Melbourne, Victoria, Australiaen
dc.identifier.doi10.1002/hbm.22120en
dc.description.pages3000-9en
dc.relation.urlhttps://pubmed.ncbi.nlm.nih.gov/22807270en
dc.contributor.corpauthorAlzheimer's Disease Neuroimaging Initiativeen
dc.type.austinJournal Articleen
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeJournal Article-
crisitem.author.deptThe Florey Institute of Neuroscience and Mental Health-
crisitem.author.deptNeurology-
crisitem.author.deptThe Florey Institute of Neuroscience and Mental Health-
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