Daniel James Blezek

The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods

The Alzheimers Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimers disease. Magnetic resonance imaging (MRI), (18F)‐fluorodeoxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquiredat multiple time points. All data will be cross‐linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications thatguided protocol development. A major effort was devoted toevaluating 3D T1‐weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced‐scale clinical trial. The protocol selected for the ADNI study includes: back‐to‐back 3D magnetization prepared rapid gradient echo (MP‐RAGE) scans; B1‐calibration scans when applicable; and an axial proton density‐T2 dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. 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. J. Magn. Reson. Imaging 2008.

Atlas stratification

The process of constructing an atlas typically involves selecting one individual from a sample on which to base or root the atlas. If the individual selected is far from the population mean, then the resulting atlas is biased towards this individual. This, in turn, may bias any inferences made with the atlas. Unbiased atlas construction addresses this issue by either basing the atlas on the individual which is the median of the sample or by an iterative technique whereby the atlas converges to the unknown population mean. In this paper, we explore the question of whether a single atlas is appropriate for a given sample or whether there is sufficient image based evidence from which we can infer multiple atlases, each constructed from a subset of the data. We refer to this process as atlas stratification. Essentially, we determine whether the sample, and hence the population, is multi-modal and is best represented by an atlas per mode. In this preliminary work, we use the mean shift algorithm to identify the modes of the sample and multidimensional scaling to visualize the clustering process on clinical MRI neurological image datasets.

128-channel body MRI with a flexible high-density receiver-coil array.

To determine whether the promise of high‐density many‐coil MRI receiver arrays for enabling highly accelerated parallel imaging can be realized in practice.

Automatic repositioning of MRSI voxels in longitudinal studies: impact on reproducibility of metabolite concentration measurements.

To study an automatic repositioning method to reduce variability in longitudinal MRSI exams based on a priori image registration. Longitudinal proton MR spectroscopic imaging (1H MRSI) exams to study the effects of disease or treatment are becoming increasingly common. However, one source of variability in such exams arises from imperfect relocalization of the MRSI grid in the follow‐up exams.

Single image phase-based MRI fat suppression expectation maximization algorithm

MRI fat suppression techniques are primarily approached by variations of the phase based methods. Multipoint methods dominate the literature, specifically methods that require the acquisition of three images at different echo times. These methods estimate the contribution of fat and water signals by solving a set of equations using echos acquired with the relative phase of fat and water at -/spl pi/, 0, /spl pi/. We present a novel approach to fat suppression that requires only a single image. Using an expectation maximization algorithm on a gradient echo image with the relative phase of fat and water at approximately /spl pi//2, the pixel composition and inhomogeneity of the magnetic field are estimated. Fat suppressed images are generated from estimated inhomogeneity. Our method does not need custom pulse sequences. Results from mathematical phantoms and volunteer images are reported.