One of the hallmark pathologies of Alzheimer’s disease (AD) is amyloid plaque deposition. Plaques appear hypointense on T2- and T2*-weighted MR images probably due to the presence of endogenous iron, but no quantitative comparison of various imaging techniques has been reported. We estimated the T1, T2, T2*, and proton density values of cortical plaques and normal cortical tissue and analyzed the plaque contrast generated by a collection of T2-, T2*-, and susceptibility-weighted imaging (SWI) methods in ex vivo transgenic mouse specimens. The proton density and T1 values were similar for both cortical plaques and normal cortical tissue. The T2 and T2* values were similar in cortical plaques, which indicates that the iron content of cortical plaques may not be as large as previously thought. Ex vivo plaque contrast was increased compared to a previously reported spin echo sequence by summing multiple echoes and by performing SWI; however, gradient echo and susceptibility weighted imaging was found to be impractical for in vivo imaging due to susceptibility interface-related signal loss in the cortex.
MR microscopy; Alzheimer’s disease; magnetic resonance imaging; magnetic resonance micro imaging; transgenic mice; susceptibility weighted imaging
In 2010, the authors published a hypothetical model of the major biomarkers of Alzheimer’s disease (AD). The model was received with interest because we described the temporal evolution of AD biomarkers in relation to each other and to the onset and progression of clinical symptoms. In the interim, evidence has accumulated that supports the major assumptions of this model. Evidence has also appeared that challenges some of the assumptions underlying our original model. Recent evidence has allowed us to modify our original model. Refinements include indexing subjects by time rather than clinical symptom severity; incorporating inter-subject variability in cognitive response to the progression of AD pathophysiology; modifications of the specific temporal ordering of some biomarkers; and, recognition that the two major proteinopathies underlying AD biomarker changes, Aβ and tau, may be initiated independently in late onset AD where we hypothesize that an incident Aβopathy can accelerate an antecedent tauopathy.
Biomarkers of Alzheimer's disease (AD) are increasingly important. All modern AD therapeutic trials employ AD biomarkers in some capacity. In addition, AD biomarkers are an essential component of recently updated diagnostic criteria for AD from the National Institute on Aging – Alzheimer's Association. Biomarkers serve as proxies for specific pathophysiological features of disease. The 5 most well established AD biomarkers include both brain imaging and cerebrospinal fluid (CSF) measures – CSF Abeta and tau, amyloid positron emission tomography (PET), fluorodeoxyglucose (FDG) PET, and structural magnetic resonance imaging (MRI). This article reviews evidence supporting the position that MRI is a biomarker of neurodegenerative atrophy. Topics covered include methods of extracting quantitative and semi quantitative information from structural MRI; imaging-autopsy correlation; and evidence supporting diagnostic and prognostic value of MRI measures. Finally, the place of MRI in a hypothetical model of temporal ordering of AD biomarkers is reviewed.
To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.
Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
Two different samples (n=343 and n=598) were created that spanned the cognitive spectrum from normal to AD dementia. Subgroup analyses were performed in members of both cohorts (n=243 and n=328) who were amyloid positive at baseline.
Main Outcome Measures
The shape of biomarker trajectories as a function of MMSE, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebro spinal fluid (CSF) Aβ42 and tau; amyloid and fluoro deoxyglucose position emission tomography (PET) imaging, and structural magnetic resonance imaging (MRI).
Baseline biomarker values generally worsened (i.e., non-zero slope) with lower baseline MMSE. Baseline hippocampal volume, amyloid PET and FDG PET values plateaued (i.e., non-linear slope) with lower MMSE in one or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE. Non-constant within-subject rates (deceleration) of biomarker change were found in only one model.
Biomarker trajectory shapes by MMSE were complex and were affected by interactions with age and APOE status. Non-linearity was found in several baseline effects models. Non-constant within-subject rates of biomarker change were found in only one model, likely due to limited within-subject longitudinal follow up. Creating reliable models that describe the full trajectories of AD biomarkers will require significant additional longitudinal data in individual participants.
Alzheimer’s disease biomarkers; Magnetic Resonance Imaging; cerebro spinal fluid; amyloid PET imaging; FDG PET imaging
A workgroup commissioned by the Alzheimer’s Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer’s disease (AD). We performed a preliminary assessment of these guidelines.
We employed Pittsburgh compound B positron emission tomography (PET) imaging as our biomarker of cerebral amyloidosis and 18fluorodeoxyglucose PET imaging and hippocampal volume as biomarkers of neurodegeneration. A group of 42 clinically diagnosed AD subjects was used to create imaging biomarker cut-points. A group of 450 cognitively normal (CN) subjects from a population based sample was used to develop cognitive cut-points and to assess population frequencies of the different preclinical AD stages using different cut-point criteria.
The new criteria subdivide the preclinical phase of AD into stages 1–3. To classify our CN subjects, two additional categories were needed. Stage 0 denotes subjects with normal AD biomarkers and no evidence of subtle cognitive impairment. Suspected Non-AD Pathophysiology (SNAP) denotes subjects with normal amyloid PET imaging, but abnormal neurodegeneration biomarker studies. At fixed cut-points corresponding to 90% sensitivity for diagnosing AD and the 10th percentile of CN cognitive scores, 43% of our sample was classified as stage 0; 16% stage 1; 12 % stage 2; 3% stage 3; and 23% SNAP.
This cross-sectional evaluation of the NIA-AA criteria for preclinical AD indicates that the 1–3 staging criteria coupled with stage 0 and SNAP categories classify 97% of CN subjects from a population-based sample, leaving just 3% unclassified. Future longitudinal validation of the criteria will be important.
The promise of Alzheimer’s disease (AD) biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging (MRI) measure in AD and thus represents the most rational target for an initial effort at standardization.
Methods and Results
The authors of this position paper propose a path toward this goal. The steps include: 1) Establish and empower an oversight board to manage and assess the effort, 2) Adopt the standardized definition of anatomic hippocampal boundaries on MRI arising from the EADC-ADNI hippocampal harmonization effort as a Reference Standard, 3) Establish a scientifically appropriate, publicly available Reference Standard Dataset based on manual delineation of the hippocampus in an appropriate sample of subjects (ADNI), and 4) Define minimum technical and prognostic performance metrics for validation of new measurement techniques using the Reference Standard Dataset as a benchmark.
Although manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent is to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry is envisioned as a template that could be applied to other imaging biomarkers.
Alzheimer’s disease; biomarkers; Magnetic resonance imaging; hippocampus; biomarker standards
To empirically assess the concept that Alzheimer’s disease (AD) biomarkers significantly depart from normality in a temporally ordered manner.
Multi-site, referral centers
We studied 401 elderly cognitively normal (CN), Mild Cognitive Impairment (MCI) and AD dementia subjects from the Alzheimer’s Disease Neuroimaging Initiative. We compared the proportions of three AD biomarkers – CSF Aβ42, CSF total tau (t-tau), and hippocampal volume adjusted by intra-cranial volume (HVa) - that were abnormal as cognitive impairment worsened. Cut-points demarcating normal vs. abnormal for each biomarker were established by maximizing diagnostic accuracy in independent autopsy samples.
Main Outcome measures
Within each clinical group in the entire sample (n=401) CSF Aβ42 was abnormal more often than t-tau or HVa. Among the 298 subjects with both baseline and 12 month data, the proportion of subjects with abnormal Aβ42 did not change from baseline to 12 months in any group. The proportion of subjects with abnormal t-tau increased from baseline to 12 months in CN (p=0.05) but not in MCI or dementia. In 209 subjects with abnormal CSF AB42 at baseline, the percent abnormal HVa, but not t-tau, increased from baseline to 12 months in MCI.
Reduction in CSF Aβ42 denotes a pathophysiological process that significantly departs from normality (i.e., becomes dynamic) early, while t-tau and HVa are biomarkers of downstream pathophysiological processes. T-tau becomes dynamic before HVa, but HVa is more dynamic in the clinically symptomatic MCI and dementia phases of the disease than t-tau.
Alzheimer’s disease biomarkers; Magnetic Resonance Imaging; CSF tau; CSF Abeta; Alzheimer’s disease staging
PIB PET and CSF Aβ42 demonstrate a highly significant inverse correlation. Both are presumed to measure brain Aβ amyloid load. Our objectives were to develop a method to transform CSF Aβ42 measures into calculated PIB measures (PIBcalc) of Aβ amyloid load, and to partially validate the method in an independent sample of subjects.
Forty-one ADNI subjects underwent PIB PET imaging and lumbar puncture (LP) at the same time. This sample, referred to as the “training” sample (9 cognitively normal (CN), 22 MCI, and 10 AD), was used to develop a regression model by which CSF Aβ42 (with APOE ε4 genotype as a covariate) was transformed into units of PIB PET (PIBcalc). An independent “supporting” sample of 362 (105 CN, 164 MCI, 93AD) ADNI subjects who underwent LP but not PIB PET imaging had their CSF Aβ42 values converted to PIBcalc. These values were compared to the overall PIB PET distribution found in the ADNI subjects (n = 102).
A linear regression model demonstrates good prediction of actual PIB PET from CSF Aβ42 measures obtained in the training sample (R2 = 0.77, P<0.001). PIBcalc data (derived from CSF Aβ42) in the supporting sample of 362 ADNI subjects who underwent LP but not PIB PET imaging demonstrates group-wise distributions that are highly consistent with the larger ADNI PIB PET distribution and with published PIB PET imaging studies.
Although the precise parameters of this model are specific for the ADNI sample, we conclude that CSF Aβ42 can be transformed into calculated PIB (PIBcalc) measures of Aβ amyloid load. Brain Aβ amyloid load can be ascertained at baseline in therapeutic or observational studies by either CSF or amyloid PET imaging and the data can be pooled using well-established multiple imputation techniques that account for the uncertainty in a CSF-based calculated PIB value.
Alzheimer's disease; Pittsburgh Compound B; amyloid imaging; Aβ amyloid; cerebrospinal fluid; Alzheimer's disease biomarkers
When using imaging to predict time to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD), time-to-event statistical methods account for varying lengths of follow-up times among subjects whereas two-sample t-tests in voxel-based morphometry (VBM) do not. Our objectives were to apply a time-to-event voxel-based analytic method to identify regions on MRI where atrophy is associated with significantly increased risk of future progression to AD in subjects with MCI and to compare it to traditional voxel-level patterns obtained by applying two-sample methods. We also compared the power required to detect an association using time-to-event methods versus two-sample approaches.
Subjects with MCI at baseline were followed prospectively. The event of interest was clinical diagnosis of AD. Cox proportional hazards models adjusted for age, sex, and education were used to estimate the relative hazard of progression from MCI to AD based on rank-transformed voxel-level gray matter density (GMD) estimates.
The greatest risk of progression to AD was associated with atrophy of the medial temporal lobes. Patients ranked at the 25th percentile of GMD in these regions had more than a doubling of risk of progression to AD at a given time-point compared to patients at the 75th percentile. Power calculations showed the time-to-event approach to be more efficient than the traditional two-sample approach.
We present a new voxel-based analytic method that incorporates time-to-event statistical methods. In the context of a progressive disease like AD, time-to-event VBM seems more appropriate and powerful than traditional two-sample methods.
Alzheimer Disease; mild cognitive impairment; magnetic resonance imaging; Cox proportional hazards model
The clinical diagnosis of Alzheimer Disease (AD) does not exactly match the pathological findings at autopsy in every subject. Therefore, in-vivo imaging measures, such as Magnetic Resonance Imaging (MRI) that measure anatomical variations in each brain due to atrophy, would be clinically useful independent supplementary measures of pathology. We have developed an algorithm that extracts atrophy information from individual patient’s 3D MRI scans and assigns a STructural Abnormality iNDex (STAND)-score to the scan based on the degree of atrophy in comparison to patterns extracted from a large library of clinically well characterized AD and CN (cognitively normal) subject’s MRI scans. STAND-scores can be adjusted for demographics to give adjusted-STAND (aSTAND)-scores which are typically > 0 for subjects with abnormal brains. Since histopathological findings are considered to represent the “ground truth”, our objective was to assess the sensitivity of aSTAND-scores to pathological AD staging. This was done by comparing antemortem MRI based aSTAND-scores with post mortem grading of disease severity in 101 subjects who had both antemortem MRI and postmortem Braak neurofibrillary tangle (NFT) staging. We found a rank correlation of 0.62 (p<0.0001) between Braak NFT stage and aSTAND-scores. The results show that optimally extracted information from MRI scans such as STAND-scores accurately capture disease severity and can be used as an independent approximate surrogate marker for in-vivo pathological staging as well as for early identification of AD in individual subjects.
Alzheimer Disease; neurofibrillary tangles; amnestic mild cognitive impairment; Braak NFT stage; magnetic resonance imaging
Functions of the ADNI MRI core fall into three categories: (1) those of the central MRI core lab at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data, and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI-GO”) and future (“ADNI-2”, if funded) MRI protocol will be to maintain MRI methodological consistency in previously enrolled “ADNI-1” subjects who are followed longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor specific pilot sub-studies of arterial spin labeling perfusion, resting state functional connectivity and diffusion tensor imaging. One each of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multi-center (but single vendor) setting for these three emerging MRI applications.
To investigate the impact white matter hyperintensities (WMH) detected on MRI have on motor dysfunction and cognitive impairment in non-demented elderly subjects.
Population-based study on the incidence and prevalence of cognitive impairment in Olmsted County, MN.
A total of 148 non-demented elderly (65 males) ranging in age from 73 to 91 years.
Main Outcome Measures
We measured the percentage of the total white matter volume classified as WMH (WMHp) in a priori defined brain regions (i.e. frontal, temporal, parietal, occipital, periventricular or subcortical). Motor impairment was evaluated qualitatively using the Unified Parkinson’s Disease Rating Scale (UPDRS) summary measures of motor skills and quantitatively using a digitized portable walkway system. Four cognitive domains were evaluated using z-scores of memory, language, executive function, and visuospatial reasoning.
A higher WMHp in all regions except occipital was associated with lower executive function z-score (p-value<0.01). A higher WMHp in all regions, but most strongly for parietal lobe, correlated with higher gait/postural-stability/posture UPDRS sum (p-value<0.01). A higher WMHp whether periventricular, subcortical or lobar correlated with reduced velocity (p-value<0.001).
We conclude that executive function is the primary cognitive domain affected by WMH burden. The data suggests that WMH in the parietal lobe are chiefly responsible for reduced balance and postural support compared to the other three lobes and may alter integration of sensory information via parietal lobe dysfunction in the aging brain. It is of interest that parietal WM changes were not the predominant correlate with motor speed, lending evidence to a global involvement of neural networks in gait velocity.
Biomarkers of brain Aβ amyloid deposition can be measured either by cerebrospinal fluid Aβ42 or Pittsburgh compound B positron emission tomography imaging. Our objective was to evaluate the ability of Aβ load and neurodegenerative atrophy on magnetic resonance imaging to predict shorter time-to-progression from mild cognitive impairment to Alzheimer’s dementia and to characterize the effect of these biomarkers on the risk of progression as they become increasingly abnormal. A total of 218 subjects with mild cognitive impairment were identified from the Alzheimer’s Disease Neuroimaging Initiative. The primary outcome was time-to-progression to Alzheimer’s dementia. Hippocampal volumes were measured and adjusted for intracranial volume. We used a new method of pooling cerebrospinal fluid Aβ42 and Pittsburgh compound B positron emission tomography measures to produce equivalent measures of brain Aβ load from either source and analysed the results using multiple imputation methods. We performed our analyses in two phases. First, we grouped our subjects into those who were ‘amyloid positive’ (n = 165, with the assumption that Alzheimer's pathology is dominant in this group) and those who were ‘amyloid negative’ (n = 53). In the second phase, we included all 218 subjects with mild cognitive impairment to evaluate the biomarkers in a sample that we assumed to contain a full spectrum of expected pathologies. In a Kaplan–Meier analysis, amyloid positive subjects with mild cognitive impairment were much more likely to progress to dementia within 2 years than amyloid negative subjects with mild cognitive impairment (50 versus 19%). Among amyloid positive subjects with mild cognitive impairment only, hippocampal atrophy predicted shorter time-to-progression (P < 0.001) while Aβ load did not (P = 0.44). In contrast, when all 218 subjects with mild cognitive impairment were combined (amyloid positive and negative), hippocampal atrophy and Aβ load predicted shorter time-to-progression with comparable power (hazard ratio for an inter-quartile difference of 2.6 for both); however, the risk profile was linear throughout the range of hippocampal atrophy values but reached a ceiling at higher values of brain Aβ load. Our results are consistent with a model of Alzheimer’s disease in which Aβ deposition initiates the pathological cascade but is not the direct cause of cognitive impairment as evidenced by the fact that Aβ load severity is decoupled from risk of progression at high levels. In contrast, hippocampal atrophy indicates how far along the neurodegenerative path one is, and hence how close to progressing to dementia. Possible explanations for our finding that many subjects with mild cognitive impairment have intermediate levels of Aβ load include: (i) individual subjects may reach an Aβ load plateau at varying absolute levels; (ii) some subjects may be more biologically susceptible to Aβ than others; and (iii) subjects with mild cognitive impairment with intermediate levels of Aβ may represent individuals with Alzheimer’s disease co-existent with other pathologies.
mild cognitive impairment; amyloid imaging; magnetic resonance imaging; cerebrospinal fluid; Alzheimer’s disease biomarkers
Currently available evidence strongly supports the position that the initiating event in Alzheimer’s disease (AD) is related to abnormal processing of β-amyloid (Aβ) peptide, ultimately leading to formation of Aβ plaques in the brain. This process occurs while individuals are still cognitively normal. Biomarkers of brain β-amyloidosis are reductions in CSF Aβ42 and increased amyloid PET tracer retention. After a lag period, which varies from patient to patient, neuronal dysfunction and neurodegeneration become the dominant pathological processes. Biomarkers of neuronal injury and neurodegeneration are increased CSF tau and structural MRI measures of cerebral atrophy. Neurodegeneration is accompanied by synaptic dysfunction, which is indicated by decreased fluorodeoxyglucose uptake on PET. We propose a model that relates disease stage to AD biomarkers in which Aβ biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegenerative biomarkers become abnormal later, and correlate with clinical symptom severity.
This study compares diagnostic accuracy of magnetic resonance (MR)-based hippocampal volumetry, single voxel (SV) 1H MR Spectroscopy (MRS) and MR diffusion weighted imaging (DWI) measurements in discriminating patients with amnestic mild cognitive impairment (MCI), Alzheimer’s disease (AD) and normally aging elderly. Sixty-one normally aging elderly, 24 MCI, and 22 AD patients underwent MR-based hippocampal volumetry, 1H MRS, and DWI. 1H MRS voxels were placed over both of the posterior cingulate gyri and N-acetyl aspartate (NAA) / creatine (Cr), myoinositol (MI) /Cr and NAA /MI ratios were obtained. Apparent diffusion coefficient (ADC) maps were derived from DWI and hippocampal borders were traced to measure hippocampal ADC. At 80% specificity, the most sensitive single measurement to discriminate MCI (79 %) and AD (86 %) from controls was hippocampal volumes. The most sensitive single measurement to discriminate AD from MCI was posterior cingulate gyrus NAA /Cr (67 %). At high specificity (>85 –90%) combinations of MR measures had superior diagnostic sensitivity compared to any single MR measurement for the AD vs. control and control vs. MCI comparisons. The MR measures that best discriminate more from less affected individuals along the cognitive continuum from normal to AD vary with disease severity. Selection of imaging measures used for clinical assessment or monitoring efficiency of therapeutic intervention should be tailored to the clinical stage of the disease.
Alzheimer’s disease; mild cognitive impairment; 1H MRS; diffusion weighted imaging; hippocampal volumetry; MRI
This study tests if measures of hippocampal water diffusivity at baseline can predict future progression to Alzheimer’s Disease (AD) in amnestic mild cognitive impairment (aMCI). Higher baseline hippocampal diffusivity was associated with a greater hazard of progression to AD in aMCI (p=0.002). MR diffusion weighted imaging (DWI) may help identify patients with aMCI who will progress to AD as well or better than structural MRI measures of hippocampal atrophy.
To determine the annualized rates of volumetric change of the hippocampus and temporal horn in cognitively normal elderly control subjects and individually matched patients with Alzheimer's disease (AD). To test the hypothesis that these rates were different .
Cross-sectional studies consistently reveal cerebral atrophy in elderly non-demented subjects compared to healthy young adults, and greater atrophy in patients with AD relative to elderly controls. However, rates of atrophy are most accurately estimated by performing serial measurements in the same individuals.
Magnetic resonance imaging (MRI)-based volume measurements of the hippocampi and temporal horns were performed in 24 cognitively normal subjects ages 70–89 years who were individually matched with respect to gender and age with 24 patients with AD. Each subject underwent an MRI scanning protocol twice, separated by 12 months or more.
The mean annualized rate of hippocampal volume loss among controls was −1.55% ± 1.38%/year and the temporal horns increased in volume by 6.15% ± 7.69%/year. These rates were significantly greater among AD patients: hippocampus −3.98% ± 1.92%/year, P <.001; temporal horn 14.16% ± 8.47%/year, P = .002.
A statistically significant yearly decline in hippocampal volume and increase in temporal horn volume was identified in elderly controls who represent typical aging individuals. These rates were approximately 2◻ times greater in patients with AD than in individually age and gender matched controls.
The vitamin E and donepezil trial for the treatment of amnestic mild cognitive impairment (MCI) was conducted at 69 centers in North America; 24 centers participated in an MRI sub study. The objective of this study was to evaluate the effect of treatment on MRI atrophy rates; and validate rate measures from serial MRI as indicators of disease progression in multi center therapeutic trials for MCI. Annual percent change (APC) from baseline to follow-up was measured for hippocampus, entorhinal cortex, whole brain, and ventricle in the 131 subjects who remained in the treatment study and completed technically satisfactory baseline and follow-up scans. Although a non-significant trend toward slowing of hippocampal atrophy rates was seen in APOE ∈4 carriers treated with donepezil; no treatment effect was confirmed for any MRI measure in either treatment group. For each of the four brain atrophy rate measures, APCs were greater in subjects who converted to AD than non-converters, and were greater in APOE ∈4 carriers than non-carriers. MRI APCs and changes in cognitive test performance were uniformly correlated in the expected direction (all p < 0.000). Results of this study support the feasibility of using MRI as an outcome measure of disease progression in multi center therapeutic trials for MCI.
dementia; Alzheimer's disease; mild cognitive impairment; clinical trials; therapeutic trials; MRI; magnetic resonance imaging; serial MRI; longitudinal imaging; brain atrophy; brain atrophy rates
To determine the 1H MR spectroscopic (MRS) findings and inter-group differences among common dementias: Alzheimer's disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD).
We consecutively recruited 206 normal elderly, 121 patients with AD, 41 with FTLD, 20 with DLB, and 8 with VaD. We evaluated the 1H MRS metabolite ratio changes in common dementias with respect to normal, and also differences among the common dementias.
N-acetylaspartate/Creatine (NAA/Cr) was lower than normal in patients with AD, FTLD, and VaD. Myo-inositol (mI)/Cr was higher than normal in patients with AD and FTLD. Choline (Cho)/Cr was higher than normal in patients with, AD, FTLD, and DLB. There were no metabolite differences between patients with AD and FTLD, nor between patients with DLB and VaD. NAA /Cr was lower in patients with AD and FTLD than DLB. MI /Cr was higher in patients with AD and FTLD than VaD. MI /Cr was also higher in patients with FTLD than DLB.
NAA/Cr levels are decreased in dementias that are characterized by neuron loss such as AD, FTLD, and VaD. MI/Cr levels are elevated in dementias that are pathologically characterized by gliosis such as AD and FTLD. Cho/Cr levels are elevated in dementias that are characterized by a profound cholinergic deficit such as AD and DLB.
The purpose of this study was to develop a method to measure brain and white matter hyperintensity (leukoaraiosis) volume that is based on the segmentation of the intensity histogram of fluid attenuated inversion recovery (FLAIR) images, and to assess the accuracy and reproducibility of the method. Whole head synthetic image phantoms with manually introduced leukoaraiosis lesions of varying severity were constructed. These synthetic image phantom sets incorporated image contrast and anatomic features which mimicked leukoaraiosis found in real life. One set of synthetic image phantoms was used to develop the segmentation algorithm (FLAIR-histoseg). A second set was used to measure its accuracy. Test re-test reproducibility was assessed in 10 elderly volunteers who were imaged twice. The mean absolute error of the FLAIR-histoseg method for measurement of leukoaraiosis volume was 6.6% and for brain volume 1.4%. The mean test re-test coefficient of variation for leukoaraiosis volume was 1.4% and for brain volume was 0.3%. We conclude that the FLAIR-histoseg method is an accurate and reproducible method for measuring leukoaraiosis and whole brain volume in elderly subjects.
quantitative MRI; pulse sequences; segmentation; white matter disease; dementia
A variety of anatomic and functional neuroimaging findings are associated with Alzheimer's Disease (AD). One of the strongest imaging associations identified is between AD and hippocampal atrophy. The ∈4 allele of the apolipoprotein E (APOE) gene increases the risk of developing AD and lowers the mean age of onset of the disease. The purpose of this paper was to assess the association between hippocampal volume and APOE polymorphisms in elderly control subjects and patients with probable AD. We performed magnetic resonance imaging-based volume measurements of the hippocampus in 125 cognitively normal elderly controls and 62 patients with probable AD. APOE genotyping was performed using standard methods.
Hippocampal volumes were significantly smaller in AD cases than in control subjects (p <0.001). Hippocampal volumes did not differ significantly within either clinical group on the basis of APOE genotype. Both the ∈4 allele of APOE (p = 0.006) and hippocampal atrophy (p <0.001) were significantly but independently associated with AD.
Alzheimer's Disease; Dementia; MRI; Quantitative MRI; Hippocampus
Measuring rates of brain atrophy from serial magnetic resonance imaging (MRI) studies is an attractive way to assess disease progression in neurodegenerative disorders, particularly Alzheimer's disease (AD). A widely recognized approach is the boundary shift integral (BSI). The objective of this study was to evaluate how several common scan non-idealities affect the output of the BSI algorithm. We created three types of image non-idealities between the image volumes in a serial pair used to measure between-scan change: inconsistent image contrast between serial scans, head motion, and poor signal-to-noise (SNR). In theory the BSI volume difference measured between each pair of images should be zero and any deviation from zero should represent corruption of the BSI measurement by some non-ideality intentionally introduced into the second scan in the pair. As the severity of motion, noise and non-congruent image contrast increases in the second scan, the calculated brain BSI values deviate progressively more from the expected value of zero. This study illustrates the magnitude of the error in measures of change in brain volume across serial MRI scans that can result from commonly encountered deviations from ideal image quality. The magnitudes of some of the measurement errors seen in this study significantly exceed the disease effect in AD. For example, measurement error may exceed 30% if image contrast properties differ between the two scans in a measurement pair. Methods to maximize consistency of image quality over time are an essential component of any quantitative serial MRI study.
MRI; image processing; image artifacts; Alzheimer's disease
Mild cognitive impairment (MCI), particularly the amnestic subtype (aMCI), is considered as a transitional stage between normal aging and a diagnosis of clinically probable Alzheimer's disease (AD). The aMCI construct is particularly useful as it provides an opportunity to assess a clinical stage which in most subjects represents prodromal AD. The aim of this study was to assess the progression of cerebral atrophy over multiple serial MRI during the period from aMCI to conversion to AD. Thirty-three subjects were selected that fulfilled clinical criteria for aMCI and had three serial MRI scans: the first scan approximately three years before conversion to AD, the second scan approximately one year before conversion, and the third scan at the time of conversion from aMCI to AD. A group of 33 healthy controls were age and gender-matched to the study cohort. Voxel-based morphometry (VBM) was used to assess patterns of grey matter atrophy in the aMCI subjects at each time-point compared to the control group. Customized templates and prior probability maps were used to avoid normalization and segmentation bias. The pattern of grey matter loss in the aMCI subject scans that were three years before conversion was focused primarily on the medial temporal lobes, including the amygdala, anterior hippocampus and entorhinal cortex, with some additional involvement of the fusiform gyrus, compared to controls. The extent and magnitude of the cerebral atrophy further progressed by the time the subjects were one year before conversion. At this point atrophy in the temporal lobes spread to include the middle temporal gyrus, and extended into more posterior regions of the temporal lobe to include the entire extent of the hippocampus. The parietal lobe also started to become involved. By the time the subjects had converted to a clinical diagnosis of AD the pattern of grey matter atrophy had become still more widespread with more severe involvement of the medial temporal lobes and the temporoparietal association cortices and, for the first time, substantial involvement of the frontal lobes. This pattern of progression fits well with the Braak and Braak neurofibrillary pathological staging scheme in AD. It suggests that the earliest changes occur in the anterior medial temporal lobe and fusiform gyrus, and that these changes occur at least three years before conversion to AD. These results also suggest that 3-dimensional patterns of grey matter atrophy may help to predict the time to conversion in subjects with aMCI.
Alzheimer's disease; mild cognitive impairment; longitudinal; magnetic resonance imaging; voxel-based morphometry
One of the cardinal pathologic features of Alzheimer’s disease (AD) is formation of senile, or amyloid, plaques. Transgenic mice have been developed that express one or more of the genes responsible for familial AD in humans. Doubly transgenic mice develop “human-like” plaques, providing a mechanism to study amyloid plaque biology in a controlled manner. Imaging of labeled plaques has been accomplished with other modalities, but only MRI has sufficient spatial and contrast resolution to visualize individual plaques non-invasively. Methods to optimize visualization of plaques in vivo in transgenic mice at 9.4 T using a spin echo sequence based on adiabatic pulses are described. Preliminary results indicate that a spin echo acquisition more accurately reflects plaque size, while a T2* weighted gradient echo sequence reflects plaque iron content not plaque size. In vivo MRI – ex vivo MRI – in vitro histological correlations are provided. Histologically verified plaques as small as 50 μm in diameter were visualized in the living animal. To our knowledge this work represents the first demonstration of non-invasive in vivo visualization of individual AD plaques without the use of a contrast agent.
MR microscopy; Alzheimer’s Disease; Magnetic Resonance Imaging; Transgenic mice