Evaluation of Cerebral Lateral Ventricular Enlargement Derived from Magnetic Resonance Imaging: A Candidate Biomarker of Alzheimer Disease Progression in Vivo

Alzheimer disease (AD) is the most common form of dementia and has grievous mortality rates. Measuring brain volumes from structural magnetic resonance images (MRI) may be useful for illuminating disease progression. The goal of this thesis was to (1) help refine a novel technique used to segment the lateral cerebral ventricles from MRI, (2) validate this tool, and determine group-wise differences between normal elderly controls (NEC) and subjects with mild cognitive impairment (MCI) and AD and (3) determine the number of subjects necessary to detect a 20 percent change from the natural history of ventricular enlargement with respect to genotype. Three dimensional Ti-weighted MRI and cognitive measures were acquired from 504 subjects (NEC n = 152, MCI n = 247 and AD n = 105) participating in the multi-centre Alzheimer\u27s Disease Neuroimaging Initiative. Cerebral ventricular volume was quantified at baseline and after six months. For secondary analyses, all groups were dichotomized for Apolipoprotein E genotype based on the presence of an e4 polymorphism. The AD group had greater ventricular enlargement compared to both subjects with MCI (P = 0.0004) and NEC (P \u3c 0.0001), and subjects with MCI had a greater rate of ventricular enlargement compared to NEC (P =0.0001). MCI subjects that progressed to clinical AD after six months had greater ventricular enlargement than stable MCI subjects (P = 0.0270). Ventricular enlargement was different between apolipoprotein E genotypes within the AD group (P = 0.010). The number of subjects required to demonstrate a 20% change in ventricular enlargement (AD: N=342, MCI: N=1180) was substantially lower than that required to demonstrate a 20% change in cognitive scores (MMSE) (AD: N=7056, MCI: N=7712). Therefore, ventricular enlargement represents a feasible short-term marker of disease progression in subjects with MCI and subjects with AD for multi-centre studie

Imaging in Alzheimer's disease

Neuroimaging in the early differential diagnosis of dementia has gained considerable interest over the last decade. From being used for exclusive purposes only, neuroimaging is now in the forefront of aiding in the diagnosis of Alzheimer's disease (AD), frontotemporal dementia, vascular dementia, and and dementia with Lewy bodies (DLB). With the exception of dopamine transporter single photon-emission computed tomography imaging in DLB, imaging has not yet been incorporated into the diagnostic criteria for the various dementia syndromes, but that will soon change. The recently formulated research criteria for early AD recently formulated by Dubois et al explicitly mention magnetic resonance imaging and positron emission tomography for AD, and are an example of a new diagnostic process developing. In this review, the various imaging techniques will be highlighted, with an emphasis on their ability to diagnose Alzheimer's disease and separate it from other entities

What can imaging tell us about cognitive impairment and dementia?

Peer reviewedPublisher PD

Multimodal MRI-based Imputation of the Aβ+ in Early Mild Cognitive Impairment.

ObjectiveTo identify brain atrophy from structural-MRI and cerebral blood flow(CBF) patterns from arterial spin labeling perfusion-MRI that are best predictors of the Aβ-burden, measured as composite 18F-AV45-PET uptake, in individuals with early mild cognitive impairment(MCI). Furthermore, to assess the relative importance of imaging modalities in classification of Aβ+/Aβ- early mild cognitive impairment.MethodsSixty-seven ADNI-GO/2 participants with early-MCI were included. Voxel-wise anatomical shape variation measures were computed by estimating the initial diffeomorphic mapping momenta from an unbiased control template. CBF measures normalized to average motor cortex CBF were mapped onto the template space. Using partial least squares regression, we identified the structural and CBF signatures of Aβ after accounting for normal cofounding effects of age, sex, and education.Results18F-AV45-positive early-MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, ApoE ε4-genotype, and a multimodal MRI-based Aβ score.InterpretationMultimodal-MRI can be used to predict the amyloid status of early-MCI individuals. MRI is a very attractive candidate for the identification of inexpensive and non-invasive surrogate biomarkers of Aβ deposition. Our approach is expected to have value for the identification of individuals likely to be Aβ+ in circumstances where cost or logistical problems prevent Aβ detection using cerebrospinal fluid analysis or Aβ-PET. This can also be used in clinical settings and clinical trials, aiding subject recruitment and evaluation of treatment efficacy. Imputation of the Aβ-positivity status could also complement Aβ-PET by identifying individuals who would benefit the most from this assessment