RESUMEN
Statistical issues in the analysis of neuroimages are reviewed. These include biological questions of interest, basic problems of measurement and experimental design, normalisation, standardisation and transformation, and statistical methodology. Finally, three data sets are reviewed to illustrate some of the issues raised in the report.
Asunto(s)
Autorradiografía/estadística & datos numéricos , Interpretación Estadística de Datos , Tomografía Computarizada de Emisión de Fotón Único/estadística & datos numéricos , Tomografía Computarizada de Emisión/estadística & datos numéricos , Enfermedad de Alzheimer/diagnóstico por imagen , Animales , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Encéfalo/fisiopatología , Circulación Cerebrovascular , Glucosa/metabolismo , HumanosRESUMEN
Modern neuroimaging techniques such as positron emission tomography and single photon emission computed tomography (SPECT) often generate datasets consisting of a large number of variables measured on a small number of subjects. In addition, the data contain large 'subject effects' which must be adjusted for in any statistical analysis. This paper illustrates the dangers inherent in naive univariate analysis and proceeds to demonstrate the application of multivariate methods such as Hotellings T2-test, canonical correlation analysis and discriminant analysis. The issues and statistical methods are illustrated using a dataset from a SPECT study of groups of normal control subjects and subjects with a clinical diagnosis of Alzheimer's disease.