Correlates of neuroimaging measures with pathological scales of cerebrovascular disease. (December 2021)

• Record Type: Journal Article
• Authors: Vemuri, Prashanthi; Kouri, Naomi; Przybelski, Scott A.; Labuzan, Sydney A.; Lesnick, Timothy G.; Reid, Robert I.; Reichard, Ross R.; Knopman, David S.; Petersen, Ronald C.; Jack, Clifford R.; Mielke, Michelle M.; Dickson, Dennis W.; Graff‐Radford, Jonathan; Murray, Melissa E.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.056145
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Summarizing the multiplicity and heterogeneity of cerebrovascular disease (CVD) features into a single measure has been difficult in both pathology and imaging studies. The objective of this work was to evaluate the association between neuroimaging surrogates of CVD and two available neuropathologic CVD scales in those with both antemortem imaging CVD measures and post‐mortem CVD evaluation. We used (1) Strozyk scale (Strozyk et. al. NBA 2010) which is based on presence and number of three macroscopic lesions (large infarctions, lacunar infarctions, and leukoencephalopathy) and (2) Kalaria scale (Deramecourt et. al. Neurology 2012) which summarizes detailed evaluation of vessel wall modifications (arteriolosclerosis, amyloid angiopathy), perivascular spaces, myelin loss, microinfarctions, and large infarctions. Method: We identified n=51 individuals in Mayo Clinic Study of Aging (mean age of 83.8 years, 37% female) with MRI scans within 5 years of death. We computed CVD measures from DTI (fractional anisotropy of the genu of the corpus callosum [FAGCC] and fractional anisotropy of cingulum adjoining the hippocampus [FACGH]), FLAIR (white matter hyperintensities [WMH] and total number of infarctions), and T2* GRE (total number of microbleeds). We also computed our recently developed imaging CVD composite score which summarizes the variability in all individual CVD imaging measures described above. We computed the Strozyk and Kalaria scales on postmortem tissue. We used weighted linear regression models with adjustments for MRI scan time to death to evaluate the associations between the antemortem neuroimaging measures and pathology scales in those who had scans within 3 years of death (N=31) and 5 years of death (N=51) (tables 1 and 2). Result: Of all the neuroimaging measures, DTI measures were the best predictors of the Strozyk and Kalaria Scales (p<0.05). In sensitivity analyses of data in Table 1, FAGCC explained 44% and FACGH predicted only 5.5% variability in white matter sub‐component of the Strozyk scale. The CVD composite score was a poor surrogate of the composite pathological scales. Conclusion: Microstructural white matter injury measurement using DTI may be a good surrogate of pathological CVD scales and possibly captures diffuse (and early) changes to white matter and secondary neurodegeneration due to lesions.