Hillary Protas

Brown University, Providence, Rhode Island, United States

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Publications (19)56.29 Total impact

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    ABSTRACT: IMPORTANCE Converging evidence suggests brain structure alterations may precede overt cognitive impairment in Alzheimer disease by several decades. Early detection of these alterations holds inherent value for the development and evaluation of preventive treatment therapies. OBJECTIVE To compare magnetic resonance imaging measurements of white matter myelin water fraction (MWF) and gray matter volume (GMV) in healthy infant carriers and noncarriers of the apolipoprotein E (APOE) ε4 allele, the major susceptibility gene for late-onset AD. DESIGN, SETTING, AND PARTICIPANTS Quiet magnetic resonance imaging was performed at an academic research imaging center on 162 healthy, typically developing 2- to 25-month-old infants with no family history of Alzheimer disease or other neurological or psychiatric disorders. Cross-sectional measurements were compared in the APOE ε4 carrier and noncarrier groups. White matter MWF was compared in one hundred sixty-two 2- to 25-month-old sleeping infants (60 ε4 carriers and 102 noncarriers). Gray matter volume was compared in a subset of fifty-nine 6- to 25-month-old infants (23 ε4 carriers and 36 noncarriers), who remained asleep during the scanning session. The carrier and noncarrier groups were matched for age, gestational duration, birth weight, sex ratio, maternal age, education, and socioeconomic status. MAIN OUTCOMES AND MEASURES Automated algorithms compared regional white matter MWF and GMV in the carrier and noncarrier groups and characterized their associations with age. RESULTS Infant ε4 carriers had lower MWF and GMV measurements than noncarriers in precuneus, posterior/middle cingulate, lateral temporal, and medial occipitotemporal regions, areas preferentially affected by AD, and greater MWF and GMV measurements in extensive frontal regions and measurements were also significant in the subset of 2- to 6-month-old infants (MWF differences, P < .05, after correction for multiple comparisons; GMV differences, P < .001, uncorrected for multiple comparisons). Infant ε4 carriers also exhibited an attenuated relationship between MWF and age in posterior white matter regions. CONCLUSIONS AND RELEVANCE While our findings should be considered preliminary, this study demonstrates some of the earliest brain changes associated with the genetic predisposition to AD. It raises new questions about the role of APOE in normal human brain development, the extent to which these processes are related to subsequent AD pathology, and whether they could be targeted by AD prevention therapies.
    JAMA neurology. 11/2013;
  • Alzheimer's and Dementia 07/2013; 9(4):P68. · 17.47 Impact Factor
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    ABSTRACT: To characterize and compare measurements of the posterior cingulate glucose metabolism, the hippocampal glucose metabolism, and hippocampal volume so as to distinguish cognitively normal, late-middle-aged persons with 2, 1, or 0 copies of the apolipoprotein E (APOE) ε4 allele, reflecting 3 levels of risk for late-onset Alzheimer disease. Cross-sectional comparison of measurements of cerebral glucose metabolism using 18F-fluorodeoxyglucose positron emission tomography and measurements of brain volume using magnetic resonance imaging in cognitively normal ε4 homozygotes, ε4 heterozygotes, and noncarriers. Academic medical center. A total of 31 ε4 homozygotes, 42 ε4 heterozygotes, and 76 noncarriers, 49 to 67 years old, matched for sex, age, and educational level. The measurements of posterior cingulate and hippocampal glucose metabolism were characterized using automated region-of-interest algorithms and normalized for whole-brain measurements. The hippocampal volume measurements were characterized using a semiautomated algorithm and normalized for total intracranial volume. Although there were no significant differences among the 3 groups of participants in their clinical ratings, neuropsychological test scores, hippocampal volumes (P = .60), or hippocampal glucose metabolism measurements (P = .12), there were significant group differences in their posterior cingulate glucose metabolism measurements (P = .001). The APOE ε4 gene dose was significantly associated with posterior cingulate glucose metabolism (r = 0.29, P = .0003), and this association was significantly greater than those with hippocampal volume or hippocampal glucose metabolism (P < .05, determined by use of pairwise Fisher z tests). Although our findings may depend in part on the analysis algorithms used, they suggest that a reduction in posterior cingulate glucose metabolism precedes a reduction in hippocampal volume or metabolism in cognitively normal persons at increased genetic risk for Alzheimer disease.
    JAMA Neurol. 03/2013; 70(3):320-5.
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    ABSTRACT: Given a single index, the receiver operational characteristic (ROC) curve analysis is routinely utilized for characterizing performances in distinguishing two conditions/groups in terms of sensitivity and specificity. Given the availability of multiple data sources (referred to as multi-indices), such as multimodal neuroimaging data sets, cognitive tests, and clinical ratings and genomic data in Alzheimer's disease (AD) studies, the single-index-based ROC underutilizes all available information. For a long time, a number of algorithmic/analytic approaches combining multiple indices have been widely used to simultaneously incorporate multiple sources. In this study, we propose an alternative for combining multiple indices using logical operations, such as "AND,” "OR,” and "at least $(n)$” (where $(n)$ is an integer), to construct multivariate ROC (multiV-ROC) and characterize the sensitivity and specificity statistically associated with the use of multiple indices. With and without the "leave-one-out” cross-validation, we used two data sets from AD studies to showcase the potentially increased sensitivity/specificity of the multiV-ROC in comparison to the single-index ROC and linear discriminant analysis (an analytic way of combining multi-indices). We conclude that, for the data sets we investigated, the proposed multiV-ROC approach is capable of providing a natural and practical alternative with improved classification accuracy as compared to univariate ROC and linear discriminant analysis.
    IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM 11/2012; 10(1):173-180. · 2.25 Impact Factor
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    ABSTRACT: OBJECTIVES: Investigate apolipoprotein E ε4 (APOE4) gene and aging effects on florbetapir F18 positron emission tomography (PET) in normal aging and Alzheimer's disease (AD). Methods: Florbetapir F18 PET images were analyzed from 245 participants, 18-92 years of age, from Avid Radiopharmaceutical's multicenter registered trials, including 86 younger healthy control volunteers (yHC), 61 older healthy control volunteers (oHC), 53 mild cognitive impairment (MCI) patients, and 45 AD dementia patients (DAT). Mean florbetapir standard uptake value ratios (SUVRs) were used to evaluate the effects of APOE4 carrier status, older age, and their interaction in each of these groups. Results: In comparison with non-carriers, the APOE4 carriers in each of the oHC, MCI, and DAT groups had higher mean cortical-to-cerebellar florbetapir SUVRs, patterns of florbetapir PET elevations characteristic of DAT, and a higher proportion meeting florbetapir PET positivity criteria. Only the oHC group had a significant association between mean cortical florbetapir SUVRs and age. In cognitively normal adults, without regards to APOE4 genotype, amyloid began to increase at age 58 (95% confidence interval [CI]: 52.3-63.7), with a predicted typical age of florbetapir positivity occurring around age 71 years. Presence of the APOE4 gene reduced the age of predicted florbetapir positivity in normal aging to around age 56 years, approximately 20 years younger than non-carriers. Interpretation: Cerebral amyloid deposition is associated with APOE4 carrier status in older healthy control subjects and symptomatic AD patients, and increases with age in older cognitively normal individuals. Amyloid imaging positivity appears to begin near age 56 years in cognitively intact APOE4 carriers and age 76 years in APOE4 non-carriers.
    Neurobiology of aging 05/2012; · 5.94 Impact Factor
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    ABSTRACT: A cross-sectional study to establish whether a subject's cognitive state can be predicted based on regional values obtained from brain cortical maps of FDDNP Distribution Volume Ratio (DVR), which shows the pattern of beta amyloid and neurofibrillary binding, along with those of early summed FDDNP PET images (reflecting the pattern of perfusion) was performed. Dynamic FDDNP PET studies were performed in a group of 23 subjects (8 control (NL), 8 Mild Cognitive Impairment (MCI) and 7 Alzheimer's Disease (AD) subjects). FDDNP DVR images were mapped to the MR derived hemispheric cortical surface map warped into a common space. A set of Regions of Interest (ROI) values of FDDNP DVR and early summed FDDNP PET (0-6 min post tracer injection), were thus calculated for each subject which along with the MMSE score were used to construct a linear mathematical model relating ROI values to MMSE. After the MMSE prediction models were developed, the models' predictive ability was tested in a non-overlapping set of 8 additional individuals, whose cognitive status was unknown to the investigators who constructed the predictive models. Among all possible subsets of ROIs, we found that the standard deviation of the predicted MMSE was 1.8 by using only DVR values from medial and lateral temporal and prefrontal regions plus the early summed FDDNP value in the posterior cingulate gyrus. The root mean square prediction error for the eight new subjects was 1.6. FDDNP scans reflect progressive neuropathology accumulation and can potentially be used to predict the cognitive state of an individual.
    NeuroImage 02/2012; 61(4):749-60. · 6.25 Impact Factor
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    ABSTRACT: We evaluate an automated approach to the cortical surface mapping (CSM) method of VOI analysis in PET. Although CSM has been previously shown to be successful, the process can be long and tedious. Here, we present an approach that removes these difficulties through the use of 3D image warping to a common space. We test this automated method using studies of FDDNP PET in Alzheimer's disease and mild cognitive impairment. For each subject, VOIs were created, through CSM, to extract regional PET data. After warping to the common space, a single set of CSM-generated VOIs was used to extract PET data from all subjects. The data extracted using a single set of VOIs outperformed the manual approach in classifying AD patients from MCIs and controls. This suggests that this automated method can remove variance in measurements of PET data and can facilitate accurate, high-throughput image analysis.
    International journal of Alzheimer's disease. 01/2012; 2012:512069.
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    ABSTRACT: Epidemiological studies suggest that elevated blood pressure (BP) in midlife is associated with increased risk of Alzheimer's disease (AD) in late life. In this preliminary study, we investigated the extent to which BP measurements are related to positron emission tomography (PET) measurements of fibrillar amyloid-beta burden using Pittsburgh Compound-B (PiB) and fluorodeoxyglucose (FDG) PET measures of cerebral metabolic rate for glucose metabolism (CMRgl) in cognitively normal, late middle-aged to older adult apolipoprotein E (APOE) ε4 homozygotes, heterozygotes and noncarriers. PiB PET results revealed that systolic BP (SBP) and pulse pressure (PP) were each positively correlated with cerebral-to-cerebellar PiB distribution volume ratio (DVR) in frontal, temporal, and posterior-cingulate/precuneus regions, whereas no significant positive correlations were found between PiB distribution volume ratios and diastolic BP (DBP). FDG PET results revealed significant inverse correlations between each of the BP measures and lower glucose metabolism in frontal and temporal brain regions. These preliminary findings provide additional evidence that higher BP, likely a reflection of arterial stiffness, during late midlife may be associated with increased risk of presymptomatic AD.
    Neurobiology of aging 08/2011; 33(4):827.e11-9. · 5.94 Impact Factor
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    ABSTRACT: In the field of quantitative imaging, the creation of accurate volumes of interest (VOIs) is often of central importance. However, the process of creating these VOIS for multiple subjects can be time-intensive and there are many chances to introduce variability on inter- and intra-investigator levels. Although previous work has shown that image normalization through cortical surface mapping can be helpful in VOI analysis, the process is complicated and labor-intensive. In this paper we present a method to eliminate this variability by warping structural and functional images to a common space in which valid VOIs already exist. We apply this method to a study of Alzheimer's disease (AD) and 2-(1-{6-[(2-[18F]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile (FDDNP), which is known to co-localize with amyloid plaques and neurofibrillary tangles. We normalize the MRIs of control subjects and mild cognitive impairment (MCI) and AD patients, to a common space. The same normalization is applied to FDDNP PET images. The normalization technique reduces average voxel-to-voxel variance in MRIs by 54% as compared to linear normalization alone. Biologically important structures, such as the segmentation between white and gray matter, are maintained after normalization. Discriminant analysis shows that data extracted from VOIs in the common space out-performs data extracted from unnormalized PET images in classifying subjects as control, MCI, or AD. This suggests that image normalization may be useful in eliminating inter- and intra-investigator variability and increasing the predictive capability of data extracted from imaging modalities. Further study will examine the applicability of this method to predicting longitudinal changes in cognitive ability from functional imaging data.
    Nuclear Science Symposium Conference Record (NSS/MIC), 2010 IEEE; 01/2010
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    ABSTRACT: To assess quantitatively the cortical pattern profile of regional FDDNP binding to beta-amyloid and neurofibrillary tangles on MR derived cortical maps, FDDNP PET images were corrected for movement and partial volume (PV), and optimized for kernel size. FDDNP DVR PET images from 23 subjects (7 with Alzheimer's disease (AD), 6 with mild cognitive impairment and 10 controls) were obtained from Logan analysis using cerebellum as reference. A hemispheric cortical surface model for each subject was extracted from the MRI. The same transformations were applied to the FDDNP DVR PET images to map them into the same space. The cortical map with PV correction was calculated as the ratio of the DVR cortical surface and that of the simulated map, created from the mask derived from MRI and smoothed to the PET resolution. Discriminant analysis was used to order the FDDNP DVR cortical surfaces based on subjects' disease state. Linear regression was used to assess the rate of change of DVR vs. MMSE for each hemispheric cortical surface point. The FDDNP DVR cortical surface corrected for movement and PV had less hemispheric asymmetry. Optimal kernel size was determined to be 9 mm. The corrected cortical surface map of FDDNP DVR showed clear spatial pattern that was consistent with the known pathological progression of AD. Correcting for movement, PV as well as optimizing kernel size provide sensitive statistical analysis of FDDNP distribution which confirms in the living brain known pathology patterns earlier observed with cognitive decline with brain specimens.
    NeuroImage 09/2009; 49(1):240-8. · 6.25 Impact Factor
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    ABSTRACT: Amyloid plaques and tau neurofibrillary tangles, the pathological hallmarks of Alzheimer's disease (AD), begin accumulating in the healthy human brain decades before clinical dementia symptoms can be detected. There is great interest in how this pathology spreads in the living brain and its association with cognitive deterioration. Using MRI-derived cortical surface models and four-dimensional animation techniques, we related cognitive ability to positron emission tomography (PET) signal from 2-(1-{6-[(2-[F-18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile ([(18)F]FDDNP), a molecular imaging probe for plaques and tangles. We examined this relationship at each cortical surface point in 23 older adults (10 cognitively intact, 6 with amnestic mild cognitive impairment, 7 with AD). [(18)F]FDDNP-PET signal was highly correlated with cognitive performance, even in cognitively intact subjects. Animations of [(18)F]FDDNP signal growth with decreased cognition across all subjects (http://www.loni.ucla.edu/ approximately thompson/FDDNP/video.html) mirrored the classic Braak and Braak trajectory in lateral temporal, parietal, and frontal cortices. Regions in which cognitive performance was significantly correlated with [(18)F]FDDNP signal include those that deteriorate earliest in AD, suggesting the potential utility of [(18)F]FDDNP for early diagnosis.
    Neurobiology of aging 12/2008; 31(10):1669-78. · 5.94 Impact Factor
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    ABSTRACT: Cortical surface maps are advantageous for visualizing the 3D profile of cortical gray matter development and atrophy, and for integrating structural and functional images. In addition, cortical surface maps for PET data, when analyzed in conjunction with structural MRI data allow us to investigate, and correct for, partial volume effects. Here we compared quantitative regional PET values based on a 3D cortical surface modeling approach with values obtained directly from the 3D FDG PET images in various atlas-defined regions of interest (ROIs; temporal, parietal, frontal, and occipital lobes). FDG PET and 3D MR (SPGR) images were obtained and aligned to ICBM space for 15 normal subjects. Each image was further elastically warped in 2D parameter space of the cortical surface, to align major cortical sulci. For each point within a 15 mm distance of the cortex, the value of the PET intensity was averaged to give a cortical surface map of FDG uptake. The average PET values on the cortical surface map were calculated for each cortical point in a lobe, and were compared to those obtained by averaging across the entire ROIs on the 3D PET image directly. The average regional values obtained from the cortical surface map were found to match well with those taken directly from the 3D PET images. The results demonstrate that cortical surface maps of FDG PET images give accurate quantitative information on regional brain function, in addition to offering an improved visualization.
    Nuclear Science Symposium Conference Record, 2005 IEEE; 11/2005
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    ABSTRACT: This paper presents a novel approach to feature-based brain image warping, by using a hybrid implicit/explicit framework, which unifies many prior approaches in a common framework. In the first step, we develop links between image warping and the level-set method, and we formulate the fundamental mathematics required for this hybrid implicit/explicit approach. In the second step, we incorporate the large-deformation models into these formulations, leading to a complete and elegant treatment of anatomical structure matching. In this latest approach, exact matching of anatomy is achieved by comparing the target to the warped source structure under the forward mapping and the source to the warped target structure under the backward mapping. Because anatomy is represented nonparametrically, a path is constructed linking the source to the target structure without prior knowledge of their point correspondence. The final point correspondence is constructed based on the linking path with the minimal energy. Intensity-similarity measures can be naturally incorporated in the same framework as landmark constraints by combining them in the gradient descent body forces. We illustrate the approach with two applications: (1) tensor-based morphometry of the corpus callosum in autistic children; and (2) matching cortical surfaces to measure the profile of cortical anatomic variation. In summary, the new mathematical techniques introduced here contribute fundamentally to the mapping of brain structure and its variation and provide a framework that unites feature and intensity-based image registration techniques.
    NeuroImage 03/2005; 24(3):910-27. · 6.25 Impact Factor
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    ABSTRACT: This paper deals with the matching of geometric objects including points, curves, surfaces, and subvolumes using implicit object representations in both linear and non-linear settings. This framework can be applied to feature-based non-linear image warping in biomedical imaging with the deformation constrained to be one-to-one, onto, and diffeomorphic. Moreover, a theoretical connection is established between the well known Hausdorff metric and the framework proposed in this paper. A general strategy for matching geometric objects in both 2D and 3D is discussed. The corresponding Euler-Lagrange equations are presented and gradient descent method is employed to solve the time dependent partial differential equations.
    Pattern Recognition, International Conference on. 08/2004; 3:710-713.
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    ABSTRACT: This paper presents and validates a non-linear image registration method driven by points and curved landmarks using implicit representation.
    07/2004;
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    ABSTRACT: In this paper, a new framework for brain warping via landmark matching is proposed using implicit representations or the level set method. We demonstrate this powerful technique by matching landmark curves identified on brain surfaces. Each landmark curve to be matched is represented by the intersection of the zero level sets of two level set functions. A diffeomorphic mapping from the template to the target image is then generated by solving a non-linear Euler transport equation with a semi-Lagrangian formulation for the corresponding level set functions. This representation technique has applications in mapping growth processes, recovering intra-operative brain deformation, and integrating and comparing brain imaging data across subjects and groups.
    Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on; 05/2004
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    ABSTRACT: In this paper, we present a new framework for object matching between two images. This method could handle multiple pairs of overlapping and non-overlapping shapes, open curves, and landmarks. When implemented in 3-D, the same framework could be used to warp 3-D objects with minimal modification. Our approach is to use the level set formulation to represent the objects to be matched. Using this representation, the problem becomes an energy minimization problem. Cost functions for warping overlapping, non-overlapping, open curves, and landmarks are proposed. Euler-Lagrange equations are applied and gradient descent is used to solve the corresponding partial differential equations. Moreover, a general framework for linking the level set approach and the infinite dimensional group actions is discussed.
    Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on; 10/2003
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    ABSTRACT: Objective The level set method using implicit representation has recently been developed and shown to be capable of matching curves of different shapes as well as other types of geometric objects (Liao et al., 2003). The method was evaluated in this study for its ability to match sulci on flattened 2D brain surfaces of individual subjects to a population average set of sulci to provide a diffeomorphic warping of the brain surface. This is a key step in cross-subject brain image registration, allowing multiple subjects' data to be compared and integrated, after adjusting for gyral pattern differences. Prior deformation methods that involve matching equidistant landmark points along each sulcus using point matching techniques do not allow relaxation along each sulcus. Moreover, it is relatively difficult to incorporate these techniques into other methods due to the non-variational nature of point constraints. The method proposed by Liao incorporates infinite dimensional group actions into the level set method and offers a unifying approach for different types of feature-based matching. Thus, a diffeomorphic, one-to-one, and onto mapping can be generated using this approach, subject to different kinds of feature-based constraints. Method The surface of a brain hemisphere, as determined from high resolution MRI, was flattened to a 2D square (size 256x256) using the method by Thompson et al. 2002, and nine major sulci were traced (including the central, precentral, postcentral, middle frontal, primary intermediate, collateral, and olfactory sulci, an olfactory control line and the Sylvian fissure). The traced sulci were discretized to a reduced grid space of 64x64. Two level sets were defined on the grid space such that the part of one level set that was enclosed by the other coincided with one or multiple sulci. Additional pairs of level sets were defined until all the selected sulci had been included. The boundary of the hemisphere at the interhemispheric midline was represented by a single level set. A similar procedure was performed to generate the level sets for the population average sulci. Liao's level-set based method was then applied to match the sulci of the individual to the population average. The resulting diffeomorphic transformation (interpolated back to 256x256 size) was then applied to warp the flattened brain surface of the individual. The procedure was repeated for the brain surfaces of 3 normal individuals, and the spread of the matched sulci was evaluated as a measure of the adequacy of the method. The mean difference from the average template curves was calculated by evaluating the signed distance functions of the average curves and the signed distance functions of the warped curves. All the warped brain surfaces were averaged together and compared to the population average brain surface.
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    ABSTRACT: This paper presents and validates a non-linear image registration method driven by points and curved landmarks using implicit representation. This approach produces smooth one-to-one mappings between topologically equivalent images by constraining the transformations to adhere to continuum mechanical laws. In this paper, the elastic operator is used for fast computation when only small deformation is needed. For large deformation, the same strategy is coupled with the method of infinite dimensional group actions to generate highly non-linear diffeomorphic maps. We applied this method to register brain magnetic resonance images in a flattened parameter space, and visualize sulcal variability by pulling back the mapping to 3D. Results show accurate registration of MRI images using delineated sulcal landmarks, while relaxing the registration field along the sulcal lines.

Publication Stats

219 Citations
56.29 Total Impact Points

Institutions

  • 2013
    • Brown University
      • School of Engineering
      Providence, Rhode Island, United States
  • 2011–2013
    • Banner Alzheimer's Institute
      Phoenix, Arizona, United States
  • 2005–2012
    • University of California, Los Angeles
      • • Department of Biomathematics
      • • Department of Molecular and Medical Pharmacology
      Los Angeles, California, United States
    • Children's Hospital Los Angeles
      • DIvision of Neurology
      Los Angeles, California, United States
  • 2008
    • University of California, Berkeley
      Berkeley, California, United States