4.6 Article

Multivariate spatial covariance analysis of Tc-99m-exametazime SPECT images in dementia with Lewy bodies and Alzheimer's disease: utility in differential diagnosis

Journal

JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM
Volume 33, Issue 4, Pages 612-618

Publisher

SAGE PUBLICATIONS INC
DOI: 10.1038/jcbfm.2013.2

Keywords

Alzheimer's disease; differential diagnosis; dementia with Lewy bodies; perfusion; spatial covariance; SPECT

Funding

  1. Medical Research Council UK [G9817682]
  2. National Institute for Health Research (NIHR) Research for Public Benefit
  3. Wellcome Trust
  4. NIHR Newcastle Biomedical Research Centre in Ageing and Chronic Disease
  5. Biomedical Research Unit in Lewy Body Dementia based at Newcastle upon Tyne Hospitals NHS Foundation Trust
  6. Newcastle University
  7. NIHR Dementia Biomedical Research Unit at Cambridge University Hospitals NHS Foundation Trust
  8. University of Cambridge
  9. National Institute for Health Research [NF-SI-0611-10048] Funding Source: researchfish

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We examined Tc-99m-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,F-64 = 36.2, P<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,F-61 = 38.4, P<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 & Metabolism (2013) 33, 612-618; doi:10.1038/jcbfm.2013.2; published online 30 January 2013

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