Paula J. Britson

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.

Longitudinal stability of MRI for mapping brain change using tensor-based morphometry

Measures of brain change can be computed from sequential MRI scans, providing valuable information on disease progression, e.g., for patient monitoring and drug trials. Tensor-based morphometry (TBM) creates maps of these brain changes, visualizing the 3D profile and rates of tissue growth or atrophy, but its sensitivity depends on the contrast and geometric stability of the images. As part of the Alzheimers Disease Neuroimaging Initiative (ADNI), 17 normal elderly subjects were scanned twice (at a 2-week interval) with several 3D 1.5 T MRI pulse sequences: high and low flip angle SPGR/FLASH (from which Synthetic T1 images were generated), MP-RAGE, IR-SPGR (N = 10) and MEDIC (N = 7) scans. For each subject and scan type, a 3D deformation map aligned baseline and follow-up scans, computed with a nonlinear, inverse-consistent elastic registration algorithm. Voxelwise statistics, in ICBM stereotaxic space, visualized the profile of mean absolute change and its cross-subject variance; these maps were then compared using permutation testing. Image stability depended on: (1) the pulse sequence; (2) the transmit/receive coil type (birdcage versus phased array); (3) spatial distortion corrections (using MEDIC sequence information); (4) B1-field intensity inhomogeneity correction (using N3). SPGR/FLASH images acquired using a birdcage coil had least overall deviation. N3 correction reduced coil type and pulse sequence differences and improved scan reproducibility, except for Synthetic T1 images (which were intrinsically corrected for B1-inhomogeneity). No strong evidence favored B0 correction. Although SPGR/FLASH images showed least deviation here, pulse sequence selection for the ADNI project was based on multiple additional image analyses, to be reported elsewhere.

3D characterization of brain atrophy in Alzheimer's disease and mild cognitive impairment using tensor-based morphometry

Tensor-based morphometry (TBM) creates three-dimensional maps of disease-related differences in brain structure, based on nonlinearly registering brain MRI scans to a common image template. Using two different TBM designs (averaging individual differences versus aligning group average templates), we compared the anatomical distribution of brain atrophy in 40 patients with Alzheimers disease (AD), 40 healthy elderly controls, and 40 individuals with amnestic mild cognitive impairment (aMCI), a condition conferring increased risk for AD. We created an unbiased geometrical average image template for each of the three groups, which were matched for sex and age (mean age: 76.1 years+/-7.7 SD). We warped each individual brain image (N=120) to the control group average template to create Jacobian maps, which show the local expansion or compression factor at each point in the image, reflecting individual volumetric differences. Statistical maps of group differences revealed widespread medial temporal and limbic atrophy in AD, with a lesser, more restricted distribution in MCI. Atrophy and CSF space expansion both correlated strongly with Mini-Mental State Exam (MMSE) scores and Clinical Dementia Rating (CDR). Using cumulative p-value plots, we investigated how detection sensitivity was influenced by the sample size, the choice of search region (whole brain, temporal lobe, hippocampus), the initial linear registration method (9- versus 12-parameter), and the type of TBM design. In the future, TBM may help to (1) identify factors that resist or accelerate the disease process, and (2) measure disease burden in treatment trials.

Alzheimer’s Disease Neuroimaging Initiative: A one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognition

Tensor-based morphometry can recover three-dimensional longitudinal brain changes over time by nonlinearly registering baseline to follow-up MRI scans of the same subject. Here, we compared the anatomical distribution of longitudinal brain structural changes, over 12 months, using a subset of the ADNI dataset consisting of 20 patients with Alzheimers disease (AD), 40 healthy elderly controls, and 40 individuals with mild cognitive impairment (MCI). Each individual longitudinal change map (Jacobian map) was created using an unbiased registration technique, and spatially normalized to a geometrically-centered average image based on healthy controls. Voxelwise statistical analyses revealed regional differences in atrophy rates, and these differences were correlated with clinical measures and biomarkers. Consistent with prior studies, we detected widespread cerebral atrophy in AD, and a more restricted atrophic pattern in MCI. In MCI, temporal lobe atrophy rates were correlated with changes in mini-mental state exam (MMSE) scores, clinical dementia rating (CDR), and logical/verbal learning memory scores. In AD, temporal atrophy rates were correlated with several biomarker indices, including a higher CSF level of p-tau protein, and a greater CSF tau/beta amyloid 1-42 (ABeta42) ratio. Temporal lobe atrophy was significantly faster in MCI subjects who converted to AD than in non-converters. Serial MRI scans can therefore be analyzed with nonlinear image registration to relate ongoing neurodegeneration to a variety of pathological biomarkers, cognitive changes, and conversion from MCI to AD, tracking disease progression in 3-dimensional detail.

Measurement of MRI scanner performance with the ADNI phantom.

The objectives of this study are as follows: to describe practical implementation challenges of multisite, multivendor quantitative studies; to describe the MRI phantom and analysis software used in the Alzheimers Disease Neuroimaging Initiative (ADNI) study, illustrate the utility of the system for measuring scanner performance, the ability to assess gradient field nonlinearity corrections: and to recover human brain images without geometric scaling errors in multisite studies. ADNI is a large multicenter study with each center having its own copy of the phantom. The design of the phantom and analysis software are presented as results from predistribution systematics studies and results from field experience with the phantom at 58 enrolling ADNI sites over a 3 year period. The estimated coefficients of variation intrinsic to measurements of geometry in a single phantom are in the range of 3-5 parts in 10(4). Phantom measurements accurately detect linear and nonlinear scaling in images. Gradient unwarping methods are readily assessed by phantom nonlinearity measurements. Phantom-based scaling correction reduces observed geometric drift in human images by one-third or more. Repair or replacement of phantoms between scans, however, is a confounding factor. The ADNI phantom can be used to assess both scanner performance and the validity of postprocessing image corrections in order to reduce systematic errors in human images. Reduced measurement errors should decrease measurement bias and increase statistical power for measurements of rates of change in the brain structure in AD treatment trials. Perhaps the greatest practical value of incorporating ADNI phantom measurements in a multisite study is to identify scanner errors through central monitoring. This approach has resulted in identification of system errors including sites misidentification of their own gradient hardware and the disabling of autoshim, and a miscalibrated laser alignment light. If undetected, these errors would have contributed to imprecision in quantitative metrics at over 25% of all enrolling ADNI sites.

Automatic quality assessment in structural brain magnetic resonance imaging

MRI has evolved into an important diagnostic technique in medical imaging. However, reliability of the derived diagnosis can be degraded by artifacts, which challenge both radiologists and automatic computer‐aided diagnosis. This work proposes a fully‐automatic method for measuring image quality of three‐dimensional (3D) structural MRI. Quality measures are derived by analyzing the air background of magnitude images and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring, and ghosting. The method has been validated on 749 3D T1‐weighted 1.5T and 3T head scans acquired at 36 Alzheimers Disease Neuroimaging Initiative (ADNI) study sites operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the ADNI quality control center (taken as the reference standard). The derived quality indices are independent of the MRI system used and agree with the reference standard quality ratings with high sensitivity and specificity (>85%). The proposed procedures for quality assessment could be of great value for both research and routine clinical imaging. It could greatly improve workflow through its ability to rule out the need for a repeat scan while the patient is still in the magnet bore. Magn Reson Med, 2009.

Validation of a new UNIX‐based quantitative coronary angiographic system for the measurement of coronary artery lesions

We describe a method of validation of computerized quantitative coronary arteriography and report the results of a new UNIX-based quantitative coronary arteriography software program developed for rapid on-line (digital) and off-line (digital or cinefilm) analysis. The UNIX operating system is widely available in computer systems using very fast processors and has excellent graphics capabilities. The system is potentially compatible with any cardiac digital x-ray system for on-line analysis and has been designed to incorporate an integrated database, have on-line and immediate recall capabilities, and provide digital access to all data. The accuracy (mean signed differences of the observed minus the true dimensions) and precision (pooled standard deviations of the measurements) of the program were determined x-ray vessel phantoms. Intra- and interobserver variabilities were assessed from in vivo studies during routine clinical coronary arteriography. Precision from the x-ray phantom studies (6-In. field of view) for digital images was 0.066 mm and for digitized cine images was 0.060 mm. Accuracy was 0.076 mm (overestimation) for digital images compared to 0.008 mm for digitized cine images. Diagnostic coronary catheters were also used for calibration; accuracy.varied according to size of catheter and whether or not they were filled with iodinated contrast. Intra- and interobserver variabilities were excellent and indicated that coronary lesion measurements were relatively user-independent. Thus, this easy to use and very fast UNIX based program appears to be robust with optimal accuracy and precision for clinical and research applications.

Effects of MRI scan acceleration on brain volume measurement consistency

To evaluate the effects of recent advances in magnetic resonance imaging (MRI) radiofrequency (RF) coil and parallel imaging technology on brain volume measurement consistency.

P2-011: Systematics of the Alzheimer's disease neuroimaging initiative phantom

venular disorder or CSF circulation disturbance in perivascular spaces may need to be considered to explain non-lacunar focal WMH in AD. Methods: Thirty-two AD (age 74) and 10 healthy elderly(age 72) had two high resolution MRI at 1.3 years apart. After 3D-T1, T2W and PDW images were co-registered, focal WMH were identified, and locations compared with intraparenchymal vascular anatomy (including perivascular spaces), evident as linear hypointense signals on appropriately windowed 3D-T1 images. Vessels or perivascular spaces were considered to be deep intramedullary or transcerebral venous structures if connected to the lateral ventricle (Fig1A), and overlap of focal WMH with these veins was deemed to implicate venous pathology. Change over time (enlargement, shrinkage, new appearance or disappearance) of each focal WMH was carefully analyzed. Results: Total WMH volume and mean focal WMH count did not differ in AD vs controls. Anatomically, 94% of 561 focal WMH at baseline and 94% of 33 new focal WMH at one year overlapped with enlarged intraparenchymal vessels or perivascular spaces (see examples in Fig1B,C,D and Fig2A). Approximately 52% of these lesions overlapped the deep intramedullary or transcerebral veins. Over one year, 30% enlarged concentrically or spread along perivascular spaces (Fig2B), and 6% either shrunk or disappeared (Fig2C) at time. Conclusions: Most incidental WMH (i.e. non-lacunar) were associated with enlarged intraparenchymal vessels or perivascular spaces, likely to be venousrelated in both AD and normal aging. Their dynamic change over time, their tendency to spread along the perivascular spaces or to disappear would be compatible with cerebral venular insufficiency (related to venous collagenosis of aging) causing leakage of fluid i.e. edema, which appears as hyperintense in T2W/PDW MRI.We suggest that small vessel disease involving both the venous and arterial sides of the cerebral occlusion may contribute to white matter disease in aging and dementia. P2-011 SYSTEMATICS OF THE ALZHEIMER’S DISEASE NEUROIMAGING INITIATIVE PHANTOM

IC-P3-181: ADNI phantom & scanner longitudinal performance

labeled perfusion MRI (ASL-pMRI) and a neuropsychological test battery that included the Mini-mental State Examination, verbal fluency, and memory testing. MRI was performed on a 3 Tesla whole body scanner using the head coil. ASL was performed using flow driven adiabatic inversion and an improved version of a previously published method for subtracting off-resonance saturation effects. The blood flow images were spatially normalized and group comparisons performed using Statistical Parametric Mapping (SPM2). Results: With a threshold of p 0.0.5 uncorrected for multiple comparisons, significant differences in rCBF were found for both the DLB and AD groups in frontal and parieto-occipital cortex. However, the magnitude in reduction in blood flow was significantly more pronounced in the DLB group compared to the AD group, despite a milder degree of cognitive impairment amongst the subjects with DLB. Conclusions: The regional pattern of decreased rCBF measured with ASL may have limited specificity for separating mild DLB from mild AD. Clinically, patients with DLB have been observed to exhibit dramatic clinical response to treatment with cholinesterase inhibitors, and a more severe cholinergic deficit is known to be present in DLB relative to AD. The hypoperfusion in association areas detected by ASL-pMRI in DLB may therefore be associated with decreased cholinergic function.