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Heidi A. Ward

Other affiliations: General Electric, GE Healthcare
Bio: Heidi A. Ward is an academic researcher from Mayo Clinic. The author has contributed to research in topics: Imaging phantom & Rigid body. The author has an hindex of 14, co-authored 22 publications receiving 4430 citations. Previous affiliations of Heidi A. Ward include General Electric & GE Healthcare.

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Journal ArticleDOI
TL;DR: The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom‐based monitoring of all scanners could be used as a model for other multisite trials.
Abstract: Dementia, one of the most feared associates of increasing longevity, represents a pressing public health problem and major research priority. Alzheimer's disease (AD) is the most common form of dementia, affecting many millions around the world. There is currently no cure for AD, but large numbers of novel compounds are currently under development that have the potential to modify the course of the disease and slow its progression. There is a pressing need for imaging biomarkers to improve understanding of the disease and to assess the efficacy of these proposed treatments. Structural magnetic resonance imaging (MRI) has already been shown to be sensitive to presymptomatic disease (1-10) and has the potential to provide such a biomarker. For use in large-scale multicenter studies, however, standardized methods that produce stable results across scanners and over time are needed. The Alzheimer's Disease Neuroimaging Initiative (ADNI) study is a longitudinal multisite observational study of elderly individuals with normal cognition, mild cognitive impairment (MCI), or AD (11,12). It is jointly funded by the National Institutes of Health (NIH) and industry via the Foundation for the NIH. The study will assess how well information (alone or in combination) obtained from MRI, (18F)-fludeoyglucose positron emission tomography (FDG PET), urine, serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical and neuropsychometric assessments, can measure disease progression in the three groups of elderly subjects mentioned above. At the 55 participating sites in North America, imaging, clinical, and biologic samples will be collected at multiple time points in 200 elderly cognitively normal, 400 MCI, and 200 AD subjects. All subjects will be scanned with 1.5 T MRI at each time point, and half of these will also be scanned with FDG PET. Subjects not assigned to the PET arm of the study will be eligible for 3 T MRI scanning. The goal is to acquire both 1.5 T and 3 T MRI studies at multiple time points in 25% of the subjects who do not undergo PET scanning [R2C1]. CSF collection at both baseline and 12 months is targeted for 50% of the subjects. Sampling varies by clinical group. Healthy elderly controls will be sampled at 0, 6, 12, 24, and 36 months. Subjects with MCI will be sampled at 0, 6, 12, 18, 24, and 36 months. AD subjects will be sampled at 0, 6, 12, and 24 months. Major goals of the ADNI study are: to link all of these data at each time point and make this repository available to the general scientific community; to develop technical standards for imaging in longitudinal studies; to determine the optimum methods for acquiring and analyzing images; to validate imaging and biomarker data by correlating these with concurrent psychometric and clinical assessments; and to improve methods for clinical trials in MCI and AD. The ADNI study overall is divided into cores, with each core managing ADNI-related activities within its sphere of expertise: clinical, informatics, biostatistics, biomarkers, and imaging. The purpose of this report is to describe the MRI methods and decision-making process underlying the selection of the MRI protocol employed in the ADNI study.

3,611 citations

Journal ArticleDOI
TL;DR: In this article, the authors used receiver operating characteristic (ROC) analyses to determine whether an fMRI memory encoding task distinguishes among cognitively normal elderly individuals, patients with mild cognitive impairment (MCI), and patients with early Alzheimer's disease (AD).
Abstract: Objective: To determine whether an fMRI memory encoding task distinguishes among cognitively normal elderly individuals, patients with mild cognitive impairment (MCI), and patients with early Alzheimer’s disease (AD). Methods: Twenty-nine subjects (11 normal, 9 MCI, 9 AD) were studied with an fMRI memory encoding task. A passive sensory task was also performed to assess potential intergroup differences in fMRI responsiveness. Activation in the medial temporal lobe for the memory task and in the anatomic rolandic area for the sensory task was studied. Intergroup comparisons were performed using receiver operating characteristic (ROC) analyses. The ROC method provides rigorous control of artifactual false-positive “activation.” Subjects were tested for recall and recognition of the encoding task stimuli following the fMRI study. Results: Medial temporal lobe activation was greater in subjects than MCI and AD patients ( p = 0.03 and p = 0.04). There was no difference between AD and MCI patients in normal fMRI memory performance. There was an association between fMRI memory activation (area under the ROC curve) and post-fMRI performance on recognition and free recall. There was no difference among the three groups on the sensory task. Conclusions: MCI and AD patients had less medial temporal lobe activation on the memory task than the normal subjects but similar activation as normal subjects on the sensory task. These findings suggest decreased medial temporal activation may be a specific marker of limbic dysfunction due to the neurodegenerative changes of AD. In addition, fMRI is sufficiently sensitive to detect changes in the prodromal, MCI, phase of the disease.

344 citations

Journal ArticleDOI
TL;DR: Some of the imaging artifacts that are commonly observed with 3.0T imaging, and their root causes are described, and when possible, countermeasures that reduce the artifact level are described.
Abstract: Clinical MRI at a field strength of 3.0T is finding increasing use. However, along with the advantages of 3.0T, such as increased SNR, there can be drawbacks, including increased levels of imaging artifacts. Although every imaging artifact observed at 3.0T can also be present at 1.5T, the intensity level is often higher at 3.0T and thus the artifact is more objectionable. This review describes some of the imaging artifacts that are commonly observed with 3.0T imaging, and their root causes. When possible, countermeasures that reduce the artifact level are described.

256 citations

Journal ArticleDOI
TL;DR: In this paper, a 3D spherical navigator (SNAV) echo technique was developed to measure rigid body motion in all six degrees of freedom simultaneously by sampling a spherical shell in k-space.
Abstract: We developed a 3D spherical navigator (SNAV) echo technique that can measure rigid body motion in all six degrees of freedom simultaneously by sampling a spherical shell in k-space. 3D rotations of an imaged object simply rotate the data on this shell and can be detected by registration of k-space magnitude values. 3D translations add phase shifts to the data on the shell and can be detected with a weighted least-squares fit to the phase differences at corresponding points. MRI pulse sequences were developed to study k-space sampling strategies on such a shell. Data collected with a computer-controlled motion phantom with known rotational and translational motions were used to evaluate the technique. The accuracy and precision of the technique depend on the sampling density. Roughly 2000 sample points were necessary for accurate detection to within the error limits of the motion phantom when using a prototype time-intensive sampling method. This number of samples can be captured in an approximately 27-ms double excitation SNAV pulse sequence with a 3D helical spiral trajectory. Preliminary results with the helical SNAV are encouraging and indicate that accurate motion measurement suitable for retrospective or prospective correction should be feasible with SNAV echoes.

219 citations

Journal ArticleDOI
TL;DR: A method for real‐time prospective correction of rotation and translation in all six degrees of rigid body motion by incorporating an orbital navigator echo for each of the sagittal, axial, and coronal planes into the fMRI pulse sequence is presented.
Abstract: Corruption of the image time series due to interimage head motion limits the clinical utility of functional MRI. This paper presents a method for real-time prospective correction of rotation and translation in all six degrees of rigid body motion. By incorporating an orbital navigator (ONAV) echo for each of the sagittal, axial, and coronal planes into the fMRI pulse sequence, rotation and translation can be measured and the spatial orientation of the image acquisition sequence that follows can be corrected prospectively in as little as 160 msec. Testing of the method using a computerized motion phantom capable of performing complex multiaxial motion showed subdegree rotational and submillimeter translational accuracy over a range of 68° and 68 mm of motion. In vivo images demonstrate correction of simultaneous through-plane and in-plane motion and improved detection of fMRI activation in the presence of head motion. Magn Reson Med 43:459 ‐ 469, 2000. © 2000 Wiley-Liss, Inc.

170 citations


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TL;DR: It is found that the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%.
Abstract: The most widely used task functional magnetic resonance imaging (fMRI) analyses use parametric statistical methods that depend on a variety of assumptions. In this work, we use real resting-state data and a total of 3 million random task group analyses to compute empirical familywise error rates for the fMRI software packages SPM, FSL, and AFNI, as well as a nonparametric permutation method. For a nominal familywise error rate of 5%, the parametric statistical methods are shown to be conservative for voxelwise inference and invalid for clusterwise inference. Our results suggest that the principal cause of the invalid cluster inferences is spatial autocorrelation functions that do not follow the assumed Gaussian shape. By comparison, the nonparametric permutation test is found to produce nominal results for voxelwise as well as clusterwise inference. These findings speak to the need of validating the statistical methods being used in the field of neuroimaging.

2,946 citations

Journal ArticleDOI
TL;DR: Head motion was associated with decreased functional coupling in the default and frontoparietal control networks--two networks characterized by coupling among distributed regions of association cortex and other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions.

2,228 citations

Journal ArticleDOI
TL;DR: These projections suggest a prolonged preclinical phase of AD in which Aβ deposition reaches the authors' threshold of positivity at 17·0 (95% CI 14·9-19·9) years, hippocampal atrophy at 4·2 (3·6-5·1] years, and memory impairment at 3·3 (2·5-4·5) years before the onset of dementia (clinical dementia rating score 1).
Abstract: Summary Background Similar to most chronic diseases, Alzheimer's disease (AD) develops slowly from a preclinical phase into a fully expressed clinical syndrome. We aimed to use longitudinal data to calculate the rates of amyloid β (Aβ) deposition, cerebral atrophy, and cognitive decline. Methods In this prospective cohort study, healthy controls, patients with mild cognitive impairment (MCI), and patients with AD were assessed at enrolment and every 18 months. At every visit, participants underwent neuropsychological examination, MRI, and a carbon-11-labelled Pittsburgh compound B ( 11 C-PiB) PET scan. We included participants with three or more 11 C-PiB PET follow-up assessments. Aβ burden was expressed as 11 C-PiB standardised uptake value ratio (SUVR) with the cerebellar cortex as reference region. An SUVR of 1·5 was used to discriminate high from low Aβ burdens. The slope of the regression plots over 3–5 years was used to estimate rates of change for Aβ deposition, MRI volumetrics, and cognition. We included those participants with a positive rate of Aβ deposition to calculate the trajectory of each variable over time. Findings 200 participants (145 healthy controls, 36 participants with MCI, and 19 participants with AD) were assessed at enrolment and every 18 months for a mean follow-up of 3·8 (95% CI CI 3·6–3·9) years. At baseline, significantly higher Aβ burdens were noted in patients with AD (2·27, SD 0·43) and those with MCI (1·94, 0·64) than in healthy controls (1·38, 0·39). At follow-up, 163 (82%) of the 200 participants showed positive rates of Aβ accumulation. Aβ deposition was estimated to take 19·2 (95% CI 16·8–22·5) years in an almost linear fashion—with a mean increase of 0·043 (95% CI 0·037–0·049) SUVR per year—to go from the threshold of 11 C-PiB positivity (1·5 SUVR) to the levels observed in AD. It was estimated to take 12·0 (95% CI 10·1–14·9) years from the levels observed in healthy controls with low Aβ deposition (1·2 [SD 0·1] SUVR) to the threshold of 11 C-PiB positivity. As AD progressed, the rate of Aβ deposition slowed towards a plateau. Our projections suggest a prolonged preclinical phase of AD in which Aβ deposition reaches our threshold of positivity at 17·0 (95% CI 14·9–19·9) years, hippocampal atrophy at 4·2 (3·6–5·1) years, and memory impairment at 3·3 (2·5–4·5) years before the onset of dementia (clinical dementia rating score 1). Interpretation Aβ deposition is slow and protracted, likely to extend for more than two decades. Such predictions of the rate of preclinical changes and the onset of the clinical phase of AD will facilitate the design and timing of therapeutic interventions aimed at modifying the course of this illness. Funding Science and Industry Endowment Fund (Australia), The Commonwealth Scientific and Industrial Research Organisation (Australia), The National Health and Medical Research Council of Australia Program and Project Grants, the Austin Hospital Medical Research Foundation, Victorian State Government, The Alzheimer's Drug Discovery Foundation, and the Alzheimer's Association.

1,733 citations

Journal ArticleDOI
TL;DR: Evidence from many independent research centers strongly supports the existence of a specific disease, as defined by the presence of A&bgr; plaques and neurofibrillary tangles.
Abstract: Clinicopathologic correlation studies are critically important for the field of Alzheimer disease (AD) research. Studies on human subjects with autopsy confirmation entail numerous potential biases that affect both their general applicability and the validity of the correlations. Many sources of data variability can weaken the apparent correlation between cognitive status and AD neuropathologic changes. Indeed, most persons in advanced old age have significant non-AD brain lesions that may alter cognition independently of AD. Worldwide research efforts have evaluated thousands of human subjects to assess the causes of cognitive impairment in the elderly, and these studies have been interpreted in different ways. We review the literature focusing on the correlation of AD neuropathologic changes (i.e. β-amyloid plaques and neurofibrillary tangles) with cognitive impairment. We discuss the various patterns of brain changes that have been observed in elderly individuals to provide a perspective for understanding AD clinicopathologic correlation and conclude that evidence from many independent research centers strongly supports the existence of a specific disease, as defined by the presence of Aβ plaques and neurofibrillary tangles. Although Aβ plaques may play a key role in AD pathogenesis, the severity of cognitive impairment correlates best with the burden of neocortical neurofibrillary tangles.

1,589 citations