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Open Access Publications from the University of California

Scholarly Works (18 results)

  • Article
  • Peer Reviewed
UC Davis Previously Published Works (2015)
Hypertension, hyperlipidemia, and diabetes are increasingly prevalent with advancing age and have been shown to cause white-matter (WM) injury that may contribute to dementia risk. However, cumulative and over time effects of these medical illnesses have not been systematically examined. One hundred twenty-one cognitively normal old participants received comprehensive clinical evaluations and brain diffusion tensor imaging on 2 occasions. Clinical history and medical treatment of diabetes, hypertension, and hyperlipidemia were assessed at both evaluations. We examined whether exposure to a greater number of vascular risk factors (VRFs) was associated with greater rate of WM integrity change using longitudinal differences in fractional anisotropy (FA). Compared with individuals with no VRF, individuals with 1 VRF did not exhibit significantly different change in FA. However, those with ≥ 2 VRFs had greater decrease in FA within multiple WM regions including the splenium of the corpus callosum. The accumulation of VRF increasingly affected WM integrity, particularly in areas known to be injured in patients with mild cognitive impairment and dementia.
    Cover page: Cooccurrence of vascular risk factors and late-life white-matter integrity changes
    • Article
    • Peer Reviewed
    UC Davis Previously Published Works (2009)

    This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty estimates could be used to detect fully-automated method failures, identify low-quality imaging data, or endow downstream statistical analyses with per-subject uncertainty in derived morphometric measures. Region segmentation is formulated in a statistical inference framework; the probability that a given region-delineating surface accounts for observed image data is quantified by a distribution that takes into account a prior model of plausible region shape and a model of how the region appears in images. Region segmentation consists of finding the maximum a posteriori (MAP) parameters of the delineating surface under this distribution, and segmentation uncertainty is quantified in terms of how sharply peaked the distribution is in the vicinity of the maximum. Uncertainty measures are estimated through Markov Chain Monte Carlo (MCMC) sampling of the distribution in the vicinity of the MAP estimate. Experiments on real and synthetic data show that the uncertainty measures automatically detect when the delineating surface of the entire brain is unclear due to poor image quality or artifact; the experiments cover multiple appearance models to demonstrate the generality of the method. The approach is also general enough to accommodate a wide range of shape models and brain regions.

      Cover page: Estimating uncertainty in brain region delineations.
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2014)

      Background and purpose

      Aging is accompanied by clinically silent cerebral white matter injury identified through white matter hyperintensities (WMHs) on fluid-attenuated inversion recovery (FLAIR)- and diffusion tensor imaging-based measures of white matter integrity. The temporal course of FLAIR and diffusion tensor imaging changes within WMHs and their less-injured periphery (ie, their penumbra), however, has not been fully studied. We used longitudinal diffusion tensor imaging and FLAIR to explore these changes.

      Methods

      One hundred fifteen participants, aged 73.7±6.7 years, received clinical evaluations and MRIs on 2 dates. WMHs and fractional anisotropy (FA) maps were produced from FLAIR and diffusion tensor imaging and coregistered to a standardized space. Each distinct WMH was categorized as growing, stagnant, or noncontiguous incident. The penumbra of each WMH was similarly categorized as corresponding to a stagnant, growing, or noncontiguous incident WMH. Linear mixed-effect models were used to assess whether FA and FLAIR measurements changed between baseline and follow-up and differed between tissue categories.

      Results

      Baseline FA differed significantly by tissue category, with the following ordering of categories from highest to lowest FA: penumbra of noncontiguous incident, then stagnant, then growing WMHs; noncontiguous incident, then stagnant, then growing WMHs. Despite differences in baseline values, all tissue categories experienced declines in FA over time. Only noncontiguous incident WMHs showed significant FLAIR signal increases over time, and FLAIR signal significantly decreased in stagnant WMHs.

      Conclusions

      WMHs and their penumbra vary in severity and together span a continuous spectrum of white matter injury that worsens with time. FLAIR fails to capture this continuous injury process fully but does identify a subclass of lesions that seem to improve over time.
        Cover page: White Matter Hyperintensities and Their Penumbra Lie Along a Continuum of Injury in the Aging Brain
        • Article
        • Peer Reviewed
        UC Davis Previously Published Works (2010)

        BACKGROUND: Trajectories of cognitive decline among elderly individuals are heterogeneous, and markers that have high reliability for predicting cognitive trajectories across a broad spectrum of the elderly population have yet to be identified. METHOD: This study examined the utility of a variety of MRI-based brain measures, obtained at baseline, as predictors of subsequent declines in domain-specific measures of cognitive function in a cohort of 307 community-dwelling elderly individuals with varying degrees of cognitive impairment who were diverse across several relevant demographic variables and were evaluated yearly. Psychometrically matched measures of cognition were used to assess episodic memory, semantic memory, and executive function. Relationships between baseline MRI measures, including the volumes of the brain, hippocampus, and white matter hyperintensities (WMH), and cognitive trajectories were assessed in mixed effects regression models that modeled MRI effects on cognitive performance at baseline and rate of change as well as interindividual variability in cognitive baseline and rate of change. RESULTS: Greater baseline brain volume predicted slower subsequent rate of decline in episodic memory and smaller WMH volume predicted slower subsequent rate of decline in executive function and semantic memory. Baseline hippocampal volume, while strongly related to baseline cognitive function, was not predictive of subsequent change in any of the cognitive domains. CONCLUSIONS: Baseline measures of brain structure and tissue pathology predicted rate of cognitive decline in a diverse and carefully characterized cohort, suggesting that they may provide summary measures of pre-existing neuropathological damage or the capacity of the brain to compensate for the impact of subsequent neuropathology on cognition. Conventional MRI measures may have use for predicting cognitive outcomes in highly heterogeneous elderly populations.

          Cover page: MRI predictors of cognitive change in a diverse and carefully characterized elderly population.
          • Article
          • Peer Reviewed
          UC Davis Previously Published Works (2005)

          This study assesses the performance of public-domain automated methodologies for MRI-based segmentation of the hippocampus in elderly subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Structural MR images of 54 age- and gender-matched healthy elderly individuals, subjects with probable AD, and subjects with MCI were collected at the University of Pittsburgh Alzheimer's Disease Research Center. Hippocampi in subject images were automatically segmented by using AIR, SPM, FLIRT, and the fully deformable method of Chen to align the images to the Harvard atlas, MNI atlas, and randomly selected, manually labeled subject images ("cohort atlases"). Mixed-effects statistical models analyzed the effects of side of the brain, disease state, registration method, choice of atlas, and manual tracing protocol on the spatial overlap between automated segmentations and expert manual segmentations. Registration methods that produced higher degrees of geometric deformation produced automated segmentations with higher agreement with manual segmentations. Side of the brain, presence of AD, choice of reference image, and manual tracing protocol were also significant factors contributing to automated segmentation performance. Fully automated techniques can be competitive with human raters on this difficult segmentation task, but a rigorous statistical analysis shows that a variety of methodological factors must be carefully considered to insure that automated methods perform well in practice. The use of fully deformable registration methods, cohort atlases, and user-defined manual tracings are recommended for highest performance in fully automated hippocampus segmentation.

            Cover page: Atlas-based hippocampus segmentation in Alzheimer's disease and mild cognitive impairment.
            • Article
            • Peer Reviewed
            UC Davis Previously Published Works (2018)

            Introduction

            Fluid-attenuated Inversion Recovery (FLAIR) and dual T2w and proton density (PD) magnetic resonance images (MRIs) are considered to be the optimum sequences for detecting white matter hyperintensities (WMHs) in aging and Alzheimer's disease populations. However, many existing large multisite studies forgo their acquisition in favor of other MRI sequences due to economic and time constraints.

            Methods

            In this article, we have investigated whether FLAIR and T2w/PD sequences are necessary to detect WMHs in Alzheimer's and aging studies, compared to using only T1w images. Using a previously validated automated tool based on a Random Forests classifier, WMHs were segmented for the baseline visits of subjects from ADC, ADNI1, and ADNI2/GO studies with and without T2w/PD and FLAIR information. The obtained WMH loads (WMHLs) in different lobes were then correlated with manually segmented WMHLs, each other, age, cognitive, and clinical measures to assess the strength of the correlations with and without using T2w/PD and FLAIR information.

            Results

            The WMHLs obtained from T1w-Only segmentations correlated with the manual WMHLs (ADNI1: r = .743, p < .001, ADNI2/GO: r = .904, p < .001), segmentations obtained from T1w + T2w + PD for ADNI1 (r = .888, p < .001) and T1w + FLAIR for ADNI2/GO (r = .969, p < .001), age (ADNI1: r = .391, p < .001, ADNI2/GO: r = .466, p < .001), and ADAS13 (ADNI1: r = .227, p < .001, ADNI2/GO: r = .190, p < 0.001), and NPI (ADNI1: r = .290, p < .001, ADNI2/GO: r = 0.144, p < .001), controlling for age.

            Conclusion

            Our results suggest that while T2w/PD and FLAIR provide more accurate estimates of the true WMHLs, T1w-Only segmentations can still provide estimates that hold strong correlations with the actual WMHLs, age, and performance on various cognitive/clinical scales, giving added value to datasets where T2w/PD or FLAIR are not available.
              Cover page: Validation of T1w‐based segmentations of white matter hyperintensity volumes in large‐scale datasets of aging
              • Article
              • Peer Reviewed
              UC Davis Previously Published Works (2016)
              Cross-sectional studies show that elevated cerebral amyloid is associated with greater white-matter hyperintensity (WMH) burden in cognitively normal (CN) older adults. However, the relative time courses of amyloid and WMH accrual are unclear. To address this, we tested the associations between known WMH correlates-age, hypertension, and amyloid-with WMH accrual rate. We used brain magnetic resonance imaging to measure WMH change in 112 CN Alzheimer's Disease Neuroimaging Initiative (GO/2) participants over a 2-year period. A linear mixed effects model assessed baseline cerebrospinal fluid amyloid beta (Aβ) 1-42, hypertension, age, and their interactions, as predictors of greater WMH accrual. Greater amyloid burden was associated with greater WMH accrual over time. Those with hypertension showed a stronger association between greater amyloid burden and WMH accrual rate. Greater age was not significantly associated with greater WMH accrual in this model. Although the direction of the relationship cannot be tested in this model, CN individuals harboring cerebral amyloid had greater accrual of WMH over a 2-year period after accounting for hypertension and age. Impaired amyloid clearance and cerebral small vessel disease may both underlie the more rapid emergence of WM lesions. The role of cerebral amyloid burden in white-matter injury should thus be considered as a relevant factor when WMHs are detected clinically.
                Cover page: Cerebral amyloid is associated with greater white-matter hyperintensity accrual in cognitively normal older adults
                • Article
                • Peer Reviewed
                UC San Francisco Previously Published Works (2017)
                The purpose of this study was to determine whether white matter microstructure measured by diffusion magnetic resonance imaging (dMRI) provides independent information about baseline level or change in executive function (EF) or memory (MEM) in older adults with and without cognitive impairment. Longitudinal data was acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study from phases GO and 2 (2009-2015). ADNI participants included were diagnosed as cognitively normal (n = 46), early mild cognitive impairment (MCI) (n = 48), late MCI (n = 29), and dementia (n = 39) at baseline. We modeled the association between dMRI-based global white matter mean diffusivity (MD) and baseline level and change in EF and MEM composite scores, in models controlling for baseline bilateral hippocampal volume, regional cerebral FDG PET metabolism and global cerebral AV45 PET uptake. EF and MEM composite scores were measured at baseline, 6, 12, 24 and 36 months. In the baseline late MCI and dementia groups, greater global MD was associated with lesser baseline EF, but not EF change nor MEM baseline or change. As expected, lesser hippocampal volume and lesser FDG PET metabolism was associated with greater rates of EF and MEM decline. In ADNI-GO/2 participants, white matter integrity provided independent information about current executive function, but was not sensitive to future cognitive change. Since individuals experiencing executive function declines progress to dementia more rapidly than those with only memory impairment, better biomarkers of future executive function decline are needed.
                  Cover page: Independent value added by diffusion MRI for prediction of cognitive function in older adults
                  • Article
                  • Peer Reviewed
                  UC Davis Previously Published Works (2016)

                  Background

                  Individuals with 22q11.2 deletion syndrome (22q11.2DS) have an elevated risk for schizophrenia, which increases with history of childhood anxiety. Altered hippocampal morphology is a common neuroanatomical feature of 22q11.2DS and idiopathic schizophrenia. Relating hippocampal structure in children with 22q11.2DS to anxiety and impaired cognitive ability could lead to hippocampus-based characterization of psychosis-proneness in this at-risk population.

                  Methods

                  We measured hippocampal volume using a semiautomated approach on MRIs collected from typically developing children and children with 22q11.2DS. We then analyzed hippocampal morphology with Localized Components Analysis. We tested the modulating roles of diagnostic group, hippocampal volume, sex and age on local hippocampal shape components. Lastly, volume and shape components were tested as covariates of IQ and anxiety.

                  Results

                  We included 48 typically developing children and 69 children with 22q11.2DS in our study. Hippocampal volume was reduced bilaterally in children with 22q11.2DS, and these children showed greater variation in the shape of the anterior hippocampus than typically developing children. Children with 22q11.2DS had greater inward deformation of the anterior hippocampus than typically developing children. Greater inward deformation of the anterior hippocampus was associated with greater severity of anxiety, specifically fear of physical injury, within the 22q11.2DS group.

                  Limitations

                  Shape alterations are not specific to hippocampal subfields.

                  Conclusion

                  Alterations in the structure of the anterior hippocampus likely affect function and may impact limbic circuitry. We suggest these alterations potentially contribute to anxiety symptoms in individuals with 22q11.2DS through modulatory pathways. Altered hippocampal morphology may be uniquely linked to anxiety risk factors for schizophrenia, which could be a powerful neuroanatomical marker of schizophrenia risk and hence protection.
                    Cover page: The hippocampi of children with chromosome 22q11.2 deletion syndrome have localized anterior alterations that predict severity of anxiety
                    • Article
                    • Peer Reviewed
                    UC Davis Previously Published Works (2008)

                    Hypertension is highly prevalent in elderly individuals and may be associated with cognitive decline, but the mechanisms by which hypertension may impact brain structure, and thereby modulate the time course of late-life cognitive performance, are not well understood. Therefore we used Localized Components Analysis, a novel computational method, to measure spatially-localized patterns of corpus callosum (CC) atrophy in 28 right-handed female subjects aged 75-79 years in the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik), a large-scale epidemiological study of aging. Localized callosal atrophy in the posterior midbody and splenium was significantly associated with systolic blood pressure in linear statistical models that controlled for age, while associations between blood pressure and anterior CC atrophy measures were not statistically significant. Additionally, overall measures of global CC atrophy were not significantly associated with blood pressure. The posterior CC may be differentially vulnerable to hypertension-associated atrophy, possibly due to its relatively tenuous vascularization.

                      Cover page: Localized measures of callosal atrophy are associated with late-life hypertension: AGES-Reykjavik Study.
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