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We examined  99m Tc-exametazime brain blood flow single-photon emission computed tomography (SPECT) images using a spatial covariance analysis (SCA) approach to assess its diagnostic value in distinguishing dementia with Lewy bodies (DLB) from Alzheimer's disease (AD). Voxel SCA was simultaneously applied to a set of preprocessed images (AD, n = 40; DLB, n = 26), generating a series of eigenimages representing common intercorrelated voxels in AD and DLB. Linear regression derived a spatial covariance pattern (SCP) that discriminated DLB from AD. To investigate the diagnostic value of the model SCP, the SCP was validated by applying it to a second, independent, AD and DLB cohort (AD, n = 34; DLB, n = 29). Mean SCP expressions differed between AD and DLB ( F 1,64  = 36.2, P &lt; 0.001) with good diagnostic accuracy (receiver operating characteristic (ROC) curve area 0.87, sensitivity 81%, specificity 88%). Forward application of the model SCP to the independent cohort revealed similar differences between groups (F 1,61  = 38.4, P &lt; 0.001), also with good diagnostic accuracy (ROC 0.86, sensitivity 80%, specificity 80%). Multivariate analysis of blood flow SPECT data appears to be robust and shows good diagnostic accuracy in two independent cohorts for distinguishing DLB from AD.

journal of cerebral blood flow and metabolism

Multivariate Spatial Covariance Analysis of <sup>99M</sup>Tc-Exametazime SPECT Images in Dementia with Lewy Bodies and Alzheimer'S Disease: Utility in Differential Diagnosis

Multivariate Spatial Covariance Analysis of 99MTc-Exametazime SPECT Images in Dementia with Lewy Bodies and Alzheimer'S Disease: Utility in Differential Diagnosis

Multivariate Spatial Covariance Analysis of ^99MTc-Exametazime SPECT Images in Dementia with Lewy Bodies and Alzheimer'S Disease: Utility in Differential Diagnosis