Assessment of White Matter Hyperintensity, Cerebral Blood Flow, and Cerebral Oxygenation in Older Subjects Stratified by Cerebrovascular Risk

Objective: Cerebrovascular disease (CVD) is the fifth most common cause of mortality in the United States. Diagnosis of CVD at an early stage is critical for optimal intervention designed to prevent ongoing and future brain injury. CVD is commonly associated with abnormalities of the cerebral microvasculature leading to tissue dysfunction, neuronal injury and death, and resultant clinical symptoms, which in turn, further impacts cerebral autoregulation (CA). This series of studies aims to test the hypothesis that white matter hyperintensities (WMH) and cerebral hemodynamics (quantified by magnetic resonance imaging (MRI) and an by innovative hybrid near-infrared diffuse optical instrument) can be used as biomarkers to distinguish cognitively healthy older subjects with high or low risk for developing CVD. Methods: Using functional MRI, WMH and cerebral blood flow (CBF) were quantified in 26 cognitively healthy older subjects (age: 77.8 ± 6.8 years). In a follow-up study, significant variability in WMH quantification methodology was addressed, with sources of variability identified in selecting image center of gravity, software compatibility, thresholding techniques, and manual editing procedures. Accordingly, post-acquisition processing methods were optimized to develop a standardized protocol with less than 0.5% inter-rater variance. Using a novel laboratory-made hybrid near-infrared spectroscopy/diffuse correlation spectroscopy (NIRS/DCS) and a finger plethysmograph, low-frequency oscillations (LFOs) of CBF, cerebral oxygenation, and main arterial pressure (MAP) were simultaneously measured before, during, and after 70° head-up-tilting (HUT). Gains (associated with CAs) to magnify LFOs were determined by transfer function analyses with MAP as the input and cerebral hemodynamic parameters as the outputs. In a follow-up study, a fast software correlator for DCS and a parallel detection technique for NIRS/DCS were adapted to improve the sampling rate of hybrid optical measurements. In addition, a new DCS probe was developed to measure CBF at the occipital lobe, which represents a novel application of the NIRS/DCS technique. Results: MRI measurements demonstrate that deep WMH (dWMH) and periventricular WMH (pWMH) volumetric measures are associated with reduced regional cortical CBF in patients at high-risk of CVD. Moreover, CBF in white matter (WM) was reduced in regions demonstrating both pWMH and dWMHs. NIRS/DCS optical measurements demonstrate that at resting baseline, LFO gains in the high-risk group were relatively lower compared to the low-risk group. The lower baseline gains in the high-risk group may be attributed to compensatory mechanisms that allow the maintenance of a stronger steady-state CA. However, HUT resulted in smaller gain reductions in the high-risk group compared to the low-risk group, suggesting weaker dynamic CA in association with increased CVD risks. A noteworthy finding in these experiments was that CVD risk more strongly influenced CBF than cerebral oxygenation. Conclusions: Regional WMH volumes, cortical and WM CBF values, and LFO gains of cerebral hemodynamics demonstrate specific associations with CA and may serve as important potential biomarkers for early diagnosis of CVD. The high spatial resolution, large penetration depth, and variety of imaging-sequences afforded by MRI make it an appealing imaging modality for evaluation of CVD, although MRI is costly, time-limited, and requires transfer of subjects from bed to imaging facility. In contrast, low-cost, portable, mobile diffuse optical technologies provide a complementary alternative for early screening of CVD, that can further allow continuous monitoring of disease attenuation or progression at the subject’s bedside. Thus, development of both methodologies is essential for progress in our future understanding of CVD as a major contributor to the morbidity and mortality associated with CVD today

Understanding the Contributions of Alzheimer’s Disease & Cardiovascular Risks to Cerebral Small Vessel Disease Manifest as White Matter Hyperintensities on Magnetic Resonance Imaging (MRI)

Introduction: Alzheimer’s Diseases (AD) & cerebral small vessel disease associated with cardiovascular risk factors (cSVD) frequently coexist, differentially affecting both imaging and clinical features associated with aging and dementia. We hypothesized that Magnetic Resonance Imaging (MRI) can be used in novel ways to identify relative contributions of AD & cardiovascular risks to cSVD and brain atrophy, generating new biomarkers & insights into mixed disease states associated with cognitive decline and dementia. Methods: Three experiments were conducted to address the overarching hypothesis. First, we visually rated the clinical MRI of 325 participants from a community-based cross-sectional sample to elucidate the relative association of age, AD (visualized as hippocampal atrophy) and cSVD (visualized as white matter hyperintensities; WMH) with global brain atrophy in experiment 1. In experiment 2, we analyzed cross-sectional MRI scans from 62 participants from the University of Kentucky Alzheimer’s Disease Center (UKADC) with available clinical data on cardiovascular risk and cerebrospinal fluid (CSF) beta-amyloid levels as a marker of AD. Voxel wise regression was used to examine the association of white matter hyperintensities with AD and/or cardiovascular risk (hypertension). Experiment 3, examined longitudinal MRI changes in WMH volumes in 377 participants from the Alzheimer’s Disease Neuroimaging Initiative 2 (ADNI 2). Subjects were categorized into three groups based on WMH volume change, including those that demonstrated regression (n=96; 25.5%), stability (n=72; 19.1%), and progression (n=209; 55.4%) of WMH volume over time. Differences in brain atrophy measures and cognitive testing among the three group were conducted. Results: In the first experiment, logistic regression analysis demonstrated that a 1-year increase in age was associated with global brain atrophy (OR = 1.04; p = .04), medial temporal lobe atrophy (MTA; a surrogate of AD) (OR = 3.7; p \u3c .001), and WMH as surrogate of cSVD (OR = 8.80; p \u3c .001). Both MTA and WMH were strongly associated with global brain atrophy in our study population, with WMH showing the strongest relationship after adjusting for age. In the second experiment, linear regression as well as mediation and moderation analyses demonstrated significant main effects of hypertension (HTN; the strongest risk factor associated with cSVD) and CSF Aβ 1-42 (a surrogate of AD) on WMH volume, but no significant HTN×CSF Aβ 1-42 interaction. Further exploration of the independence of HTN and Aβ using a voxelwise analysis approach, demonstrated unique patterns of WM alteration associated with either hypertension or CSF Aβ 1-42, confirming that both independently contribute to WMH previously classified as cSVD. Extending this work into a longitudinal model rather than focusing on purely cross-sectional associations, we demonstrated that spontaneous WMH regression is common, and that such regression is associated with a reduced rate of global brain atrophy (p = 0.012), and improvement in memory function over time (p = 0.003). Conclusion: These data demonstrate that both AD and cSVD frequently coexist in the same brain, contributing differentially to alterations in brain structure, subcortical white matter injury, and cognitive function. These effects can be disentangled using MRI, and while we currently lack therapeutic interventions to halt or reverse AD, the dynamic WMH change evident in our data clearly suggests that the ability to reverse cSVD exists today

Assessment Of The Interplay Between Regional β-Amyloid Burden And White Matter Hyperintensities On Cognition And Default Mode Network In Clinically Normal Older Participants

Objective: Alzheimer’s disease (AD) and subcortical vascular dementia are considered the most common pathologic contributors to dementia in the aging population. Both frequently coexist in over 80% of community dwelling adults with dementia. The neuropathological development of AD arguably begins with β-amyloid (Aβ) deposition in the brain. This series of studies aims to test the hypothesis that early focal regional amyloid deposition in the brain is associated with cognitive performance in specific cognitive domain scores in preclinical AD (pAD) (study1). Since mixed dementia is widely recognized as the norm rather than the exception, the second study aimed to explore the relation between regional and global Aβ and WMH with core cognitive function (executive function (EF) and memory) scores in cognitively normal (CN) older adults (study2). Finally, the relationship between WMH and Aβ is strongly determined by the spatial distribution of the two pathologies, so the third study aimed to quantify Aβ in Default mode network (DMN) regions to examine whether cerebral small vessels disease (SVD) disruption of connectivity affects Aβ deposition in disconnected DMN regions (study3). Method: Global and regional Standard Uptake Value ratios (SUVr) from Aβ-PET, WMH volumes from MRI FLAIR images, and cognitive test scores were analyzed across a sample of CN participants. Linear regression models adjusted for age, sex and education used to assess the relationships between regional SUVr and cognitive test scores across 99 CN from Sanders Brown Center on Aging (study1). Moderation, and mediation modeling were used to define the interplay between global, regional Aβ and WMHs measures in relation to EF and memory composite scores outcomes at baseline and after approximately 2 years across a sample of 714 CN from the Alzheimer’s Disease Neuroimaging Initiative ADNI (study2). The association of WMH volume in anatomically defined white matter tracts of atlas-based fiber tract with Aβ SUVr specifically in connected cortical regions within DMN was tested across sample of 74 CN from ADNI3. Results: EF performance was associated with increased regional SUVr in the precuneus and posterior cingulate regions only (p \u3c 0.05). The moderation regression analysis showed additive effects of Aβ and WMH over baseline memory and EF scores (p =0.401 and 0.061 respectively) and synergistic effects over follow-up EF (p \u3c 0.05). Through mediation analysis, the data from study 2 showed that WMH affects, mediated by global and regional amyloid burden, are responsible for baseline cognitive performance deficits in memory and EF. Finally, the regression analysis from study 3 demonstrated that increased WMH volumes in superior longitudinal fasciculus (SLF) was associated with increased regional SUVr in inferior parietal lobule (IPL) (p \u3c 0.05). Conclusion: While the prevailing view in the field suggests that memory performance is the earliest clinical hallmark of AD, the present data demonstrate that changes in EF, mediated by Aβ deposition in the precuneus and posterior cingulate may precede memory decline in pAD. After adding the second key driver of cognitive decline in CN, the finding suggested that WMH dependent changes in baseline cognitive performance are related to direct effect of WMH and an indirect effect through both global and regional Aβ burden. Further studies are needed to show the longitudinal influences of WMH on Aβ distributions in participants with mixed dementia

Multi-Modal Magnetic Resonance Imaging Predicts Regional Amyloid Burden in the Brain

Alzheimer’s disease (AD) is the most common cause of dementia and identifying early markers of this disease is important for prevention and treatment strategies. Amyloid- β (Aβ) protein deposition is one of the earliest detectable pathological changes in AD. But in-vivo detection of Aβ using positron emission tomography (PET) is hampered by high cost and limited geographical accessibility. These factors can become limiting when PET is used to screen large numbers of subjects into prevention trials when only a minority are expected to be amyloid-positive. Structural MRI is advantageous; as it is non-invasive, relatively inexpensive and more accessible. Thus it could be widely used in large studies, even when frequent or repetitive imaging is necessary. We used a machine learning, pattern recognition, approach using intensity-based features from individual and combination of MR modalities (T1 weighted, T2 weighted, T2 fluid attenuated inversion recovery [FLAIR], susceptibility weighted imaging) to predict voxel-level amyloid in the brain. The MR- Aβ relation was learned within each subject and generalized across subjects using subject–specific features (demographic, clinical, and summary MR features). When compared to other modalities, combination of T1-weighted, T2-weighted FLAIR, and SWI performed best in predicting the amyloid status as positive or negative. A combination of T2-weighted and SWI imaging performed the best in predicting change in amyloid over two timepoints. Overall, our results show feasibility of amyloid prediction by MRI and its potential use as an amyloid-screening tool

Unconventional markers of Alzheimer Disease

Although typically conceptualized as a cortical disease, recent neuropathological and neuroimaging investigations on Alzheimer Disease suggest that other brain structures play an important role in the pathogenesis and progression of this devastating condition. In this thesis, we explored novel markers of Alzheimer Disease beyond the classical cortical pathology measures of amyloid, tau, and neurodegeneration. We focused on the role of white matter abnormalities, assessed with magnetic resonance imaging but also with amyloid positron emission tomography, in predicting early pathologic changes and disease progression, as well as on the added value of cognition to amyloid, tau, and neurodegeneration biomarkers. Overall, we found that these unconventional markers provide useful information to detect the earliest pathological changes of the disease, providing a better understanding of the mechanisms that lead to amyloid deposition and cognitive decline

REGISTRATION AND SEGMENTATION OF BRAIN MR IMAGES FROM ELDERLY INDIVIDUALS

Quantitative analysis of the MRI structural and functional images is a fundamental component in the assessment of brain anatomical abnormalities, in mapping functional activation onto human anatomy, in longitudinal evaluation of disease progression, and in computer-assisted neurosurgery or surgical planning. Image registration and segmentation is central in analyzing structural and functional MR brain images. However, due to increased variability in brain morphology and age-related atrophy, traditional methods for image registration and segmentation are not suitable for analyzing MR brain images from elderly individuals. The overall goal of this dissertation is to develop algorithms to improve the registration and segmentation accuracy in the geriatric population. The specific aims of this work includes 1) to implement a fully deformable registration pipeline to allow a higher degree of spatial deformation and produce more accurate deformation field, 2) to propose and validate an optimum template selection method for atlas-based segmentation, 3) to propose and validate a multi-template strategy for image normalization, which characterizes brain structural variations in the elderly, 4) to develop an automated segmentation and localization method to access white matter integrity (WMH) in the elderly population, and finally 5) to study the default-mode network (DMN) connectivity and white matter hyperintensity in late-life depression (LLD) with the developed registration and segmentation methods. Through a series of experiments, we have shown that the deformable registration pipeline and the template selection strategies lead to improved accuracy in the brain MR image registration and segmentation, and the automated WMH segmentation and localization method provides more specific and more accurate information about volume and spatial distribution of WMH than traditional visual grading methods. Using the developed methods, our clinical study provides evidence for altered DMN connectivity in LLD. The correlation between WMH volume and DMN connectivity emphasizes the role of vascular changes in LLD's etiopathogenesis

Cerebral blood flow measurements with arterial spin labelling in a tri-ethnic population cohort: associations of cardiovascular risk factors and MR imaging markers of brain ageing

Differences in cerebral blood flow (CBF) have been identified between older individuals in good cognitive health and those experiencing cognitive decline and dementia. Previous studies have shown that the aetiology of dementia includes a substantial vascular component and there is evidence that CBF decline in old age may be linked to cardiovascular disease. Although the incidence, prevalence and impact of vascular risk varies by ethnicity and gender, many previous studies have focused on participants of white European origin or have pooled ethnically diverse samples, while differences between sexes have been under-investigated. This thesis used arterial spin labelling (ASL) to measure cortical CBF in an elderly tri-ethnic population cohort and examined its relationship with vascular risk and the brain ageing markers of cortical volume and white matter hyperintensity (WMH) volume from magnetic resonance imaging (MRI). Chapter 4 showed that use of the currently recommended mean haematocrit (Hct) value in equations that calculate CBF from ASL underestimated CBF in women and non-European ethnicities. The alternative method of substituting individually measured Hct into the equation was implemented in the following chapters. Results from Chapter 5 indicated that increased vascular risk factors were associated with lower CBF, but these relationships varied by ethnicity and sex. Ethnicity and sex also modified the strength of associations of increased vascular risk with decreased cortical tissue volume and increased volume of WMHs examined in Chapter 6. However, there was no evidence of any association of CBF with the MRI markers of brain ageing

The Rationale and Design of the Reducing Pathology in Alzheimer's Disease through Angiotensin TaRgeting (RADAR) Trial

BACKGROUND: Anti-hypertensives that modify the renin angiotensin system may reduce Alzheimer's disease (AD) pathology and reduce the rate of disease progression. OBJECTIVE: To conduct a phase II, two arm, double-blind, placebo-controlled, randomized trial of losartan to test the efficacy of Reducing pathology in Alzheimer's Disease through Angiotensin TaRgeting (RADAR). METHODS: Men and women aged at least 55 years with mild-to-moderate AD will be randomly allocated 100 mg encapsulated generic losartan or placebo once daily for 12 months after successful completion of a 2-week open-label phase and 2-week placebo washout to establish drug tolerability. 228 participants will provide at least 182 subjects with final assessments to provide 84% power to detect a 25% difference in atrophy rate (therapeutic benefit) change over 12 months at an alpha level of 0.05. We will use intention-to-treat analysis, estimating between-group differences in outcomes derived from appropriate (linear or logistic) multivariable regression models adjusting for minimization variables. RESULTS: The primary outcome will be rate of whole brain atrophy as a surrogate measure of disease progression. Secondary outcomes will include changes to 1) white matter hyperintensity volume and cerebral blood flow; 2) performance on a standard series of assessments of memory, cognitive function, activities of daily living, and quality of life. Major assessments (for all outcomes) and relevant safety monitoring of blood pressure and bloods will be at baseline and 12 months. Additional cognitive assessment will also be conducted at 6 months along with safety blood pressure and blood monitoring. Monitoring of blood pressure, bloods, and self-reported side effects will occur during the open-label phase and during the majority of the post-randomization dispensing visits. CONCLUSION: This study will identify whether losartan is efficacious in the treatment of AD and whether definitive Phase III trials are warranted