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.
Primary progressive apraxia of speech, a motor speech disorder of planning and programming is a tauopathy that has overlapping histological features with progressive supranuclear palsy. We aimed to compare, for the first time, atrophy patterns, as well as white matter tract degeneration, between these two syndromes.
Sixteen primary progressive apraxia of speech subjects were age and gender-matched to 16 progressive supranuclear palsy subjects and 20 controls. All subjects were prospectively recruited, underwent neurological and speech evaluations, and 3.0 Tesla magnetic resonance imaging. Grey and white matter atrophy was assessed using voxel-based morphometry and atlas-based parcellation, and white matter tract degeneration was assessed using diffusion tensor imaging.
All progressive supranuclear palsy subjects had typical occulomotor/gait impairments but none had speech apraxia. Both syndromes showed grey matter loss in supplementary motor area, white matter loss in posterior frontal lobes and degeneration of the body of the corpus callosum. While lateral grey matter loss was focal, involving superior premotor cortex, in primary progressive apraxia of speech, loss was less focal extending into prefrontal cortex in progressive supranuclear palsy. Caudate volume loss and tract degeneration of superior cerebellar peduncles was also observed in progressive supranuclear palsy. Interestingly, area of the midbrain was reduced in both syndromes compared to controls, although this was greater in progressive supranuclear palsy.
Although neuroanatomical differences were identified between these distinctive clinical syndromes, substantial overlap was also observed, including midbrain atrophy, suggesting these two syndromes may have common pathophysiological underpinnings.
Progressive supranuclear palsy; apraxia of speech; voxel-based morphometry; diffusion tensor imaging; midbrain
Poor kidney function is associated with increased risk of cognitive decline and generalized brain atrophy. Chronic kidney disease impairs glomerular filtration rate (eGFR), and this deterioration is indicated by elevated blood levels of kidney biomarkers such as creatinine (SCr) and cystatin C (CysC). Here we hypothesized that impaired renal function would be associated with brain deficits in regions vulnerable to neurodegeneration.
Using tensor-based morphometry, we related patterns of brain volumetric differences to SCr, CysC levels, and eGFR in a large cohort of 738 (mean age: 75.5±6·8 years; 438 men/300 women) elderly Caucasian subjects scanned as part of the Alzheimer’s Disease Neuroimaging Initiative.
Elevated kidney biomarkers were associated with volume deficits in the white matter region of the brain. All the three renal parameters in our study showed significant associations consistently with a region that corresponds with the anterior limb of internal capsule, bilaterally.
This is the first study to report a marked profile of structural alterations in the brain associated with elevated kidney biomarkers; helping us explain the cognitive deficits.
creatinine; cystatin C; GFR; kidney function; brain volumes; brain structure; brain atrophy; neuroimaging; cognitive deficits
The new criteria for preclinical Alzheimer’s Disease (AD) proposed 3 stages: abnormal levels of β-amyloid (stage 1); stage 1 plus evidence of brain injury (stage 2); and stage 2 plus subtle cognitive changes (stage 3). However, a large group of subjects with normal β-amyloid biomarkers have evidence of brain injury; we labeled them as “suspected non-Alzheimer pathway” (sNAP) group. The characteristics of the sNAP group are poorly understood.
Using the preclinical AD classification, 430 cognitively normal subjects from the Mayo Clinic Study of Aging who underwent brain MR, 18fluorodeoxyglucose (FDG) and Pittsburgh compound B (PiB) positron emission tomography (PET) were evaluated with FDG PET regional volumetrics, MR regional brain volumetrics, white matter hyperintensity (WMH) volume and number of infarcts. We examined cross-sectional associations across AD preclinical stages, those with all biomarkers normal, and the sNAP group.
The sNAP group had a lower proportion (14%) with APOE ε4 genotype than the preclinical AD stages 2 + 3. The sNAP group did not show any group differences compared to stages 2 + 3 of the preclinical AD group on measures of FDG PET regional hypometabolism, MR regional brain volume loss, cerebrovascular imaging lesions, vascular risk factors, imaging changes associated with α-synucleinopathy or physical findings of parkinsonism.
Cognitively normal persons with brain injury biomarker abnormalities, with or without abnormal levels of β-amyloid, were indistinguishable on a variety of imaging markers, clinical features and risk factors. The initial appearance of brain injury biomarkers that occurs in cognitively normal persons with preclinical AD may not depend on β-amyloidosis.
Alzheimer’s disease; PET imaging; MR imaging; Epidemiology
We analyzed the baseline and 3-year T1-weighted magnetic resonance imaging data of 110 amnestic mild cognitive impairment (MCI) participants with minimal hippocampal atrophy at baseline from the Alzheimer’s Disease Cooperative Study group (ADCS) MCI Donepezil/Vitamin E trial. 46 subjects converted to AD (MCIc) while 64 remained stable (MCInc). We used the radial distance technique to examine the differences in lateral ventricle shape and size between MCIc and MCInc and the associations between ventricular enlargement and cognitive decline.
MCIc group had significantly larger frontal and right body/occipital horns relative to MCInc at baseline and significantly larger bilateral frontal, body/occipital and left temporal horns at follow-up. Global cognitive decline measured with ADAScog and MMSE and decline in activities of daily living (ADL) were associated with posterior lateral ventricle enlargement. Decline in ADAScog and ADL were associated with left temporal and decline in MMSE with right temporal horn enlargement. After correction for baseline hippocampal volume decline in ADL showed a significant association with right frontal horn enlargement. Executive decline was associated with right frontal and left temporal horn enlargement.
Alzheimer’s disease; AD; mild cognitive impairment; MCI; imaging; MRI; brain atrophy; ventricular enlargement
To model the temporal trajectory of β-amyloid accumulation using serial amyloid PET imaging.
Participants, aged 70–92 years, were enrolled in either the Mayo Clinic Study of Aging (n = 246) or the Mayo Alzheimer's Disease Research Center (n = 14). All underwent 2 or more serial amyloid PET examinations. There were 205 participants classified as cognitively normal and 55 as cognitively impaired (47 mild cognitive impairment and 8 Alzheimer dementia). We measured baseline amyloid PET-relative standardized uptake values (SUVR) and, for each participant, estimated a slope representing their annual amyloid accumulation rate. We then fit regression models to predict the rate of amyloid accumulation given baseline amyloid SUVR, and evaluated age, sex, clinical group, and APOE as covariates. Finally, we integrated the amyloid accumulation rate vs baseline amyloid PET SUVR association to an amyloid PET SUVR vs time association.
Rates of amyloid accumulation were low at low baseline SUVR. Rates increased to a maximum at baseline SUVR around 2.0, above which rates declined—reaching zero at baseline SUVR above 2.7. The rate of amyloid accumulation as a function of baseline SUVR had an inverted U shape. Integration produced a sigmoid curve relating amyloid PET SUVR to time. The average estimated time required to travel from an SUVR of 1.5–2.5 is approximately 15 years.
This roughly 15-year interval where the slope of the amyloid SUVR vs time curve is greatest and roughly linear represents a large therapeutic window for secondary preventive interventions.
Various neuroimaging measures are being evaluated for tracking Alzheimer’s disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Methods to compute brain change must be robust to scan quality. Biases may arise if any scans are thrown out, as this can lead to the true changes being overestimated or underestimated. Here we analyzed the full MRI dataset from the first phase of Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) from the first phase of Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) and assessed several sources of bias that can arise when tracking brain changes with structural brain imaging methods, as part of a pipeline for tensor-based morphometry (TBM). In all healthy subjects who completed MRI scanning at screening, 6, 12, and 24 months, brain atrophy was essentially linear with no detectable bias in longitudinal measures. In power analyses for clinical trials based on these change measures, only 39 AD patients and 95 mild cognitive impairment (MCI) subjects were needed for a 24-month trial to detect a 25% reduction in the average rate of change using a two-sided test (α=0.05, power=80%). Further sample size reductions were achieved by stratifying the data into Apolipoprotein E (ApoE) ε4 carriers versus non-carriers. We show how selective data exclusion affects sample size estimates, motivating an objective comparison of different analysis techniques based on statistical power and robustness. TBM is an unbiased, robust, high-throughput imaging surrogate marker for large, multi-site neuroimaging studies and clinical trials of AD and MCI.
Alzheimer’s disease; Mild cognitive impairment; Aging; ADNI; Tensor-based morphometry; Drug trial
We aimed to assess associations between clinical, imaging, pathological and genetic features and frontal lobe asymmetry in behavioral variant frontotemporal dementia (bvFTD). Volumes of the left and right dorsolateral, medial and orbital frontal lobes were measured in 80 bvFTD subjects and subjects were classified into three groups according to the degree of asymmetry (asymmetric left, asymmetric right, symmetric) using cluster analysis. The majority of subjects were symmetric (65%), with 20% asymmetric left and 15% asymmetric right. There were no clinical differences across groups, although there was a trend for greater behavioral dyscontrol in right asymmetric compared to left asymmetric subjects. More widespread atrophy involving the parietal lobe was observed in the symmetric group. Genetic features differed across groups with symmetric frontal lobes associated with C9ORF72 and tau mutations, while asymmetric frontal lobes were associated with progranulin mutations. These findings therefore suggest that neuroanatomical patterns of frontal lobe atrophy in bvFTD are influenced by specific gene mutations.
Frontotemporal dementia; frontal lobes; MRI; asymmetry; microtubule associated protein tau; progranulin; C9ORF72; pathology
Four subtypes of frontotemporal lobar degeneration with TDP-43 immunoreactive inclusions have been described (types A–D). Of these four subtypes, motor neuron disease is more commonly associated with type B pathology, but has also been reported with type A pathology. We have noted, however, the unusual occurrence of cases of type C pathology having corticospinal tract degeneration. We aimed to assess the severity of corticospinal tract degeneration in a large cohort of cases with type C (n = 31). Pathological analysis included semi-quantitation of myelin loss of fibres of the corticospinal tract and associated macrophage burden, as well as axonal loss, at the level of the medullary pyramids. We also assessed for motor cortex degeneration and fibre loss of the medial lemniscus/olivocerebellar tract. All cases were subdivided into three groups based on the degree of corticospinal tract degeneration: (i) no corticospinal tract degeneration; (ii) equivocal corticospinal tract degeneration; and (iii) moderate to very severe corticospinal tract degeneration. Clinical, genetic, pathological and imaging comparisons were performed across groups. Eight cases had no corticospinal tract degeneration, and 14 cases had equivocal to mild corticospinal tract degeneration. Nine cases, however, had moderate to very severe corticospinal tract degeneration with myelin and axonal loss. In these nine cases, there was degeneration of the motor cortex without lower motor neuron degeneration or involvement of other brainstem tracts. These cases most commonly presented as semantic dementia, and they had longer disease duration (mean: 15.3 years) compared with the other two groups (10.8 and 9.9 years; P = 0.03). After adjusting for disease duration, severity of corticospinal tract degeneration remained significantly different across groups. Only one case, without corticospinal tract degeneration, was found to have a hexanucleotide repeat expansion in the C9ORF72 gene. All three groups were associated with anterior temporal lobe atrophy on MRI; however, the cases with moderate to severe corticospinal tract degeneration showed right-sided temporal lobe asymmetry and greater involvement of the right temporal lobe and superior motor cortices than the other groups. In contrast, the cases with no or equivocal corticospinal tract degeneration were more likely to show left-sided temporal lobe asymmetry. For comparison, the corticospinal tract was assessed in 86 type A and B cases, and only two cases showed evidence of corticospinal tract degeneration without lower motor neuron degeneration. These findings confirm that there exists a unique association between frontotemporal lobar degeneration with type C pathology and corticospinal tract degeneration, with this entity showing a predilection to involve the right temporal lobe.
TDP-43 type C; corticospinal tract; MRI; semantic dementia; right temporal lobe
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.
The appearance of β-amyloidosis and brain injury biomarkers in cognitively normal (CN) persons is thought to define risk for the future development of cognitive impairment due to Alzheimer’s disease (AD), but their interaction is poorly understood.
To test the hypothesis that the joint presence of β-amyloidosis and brain injury biomarkers would lead to more rapid neurodegeneration.
Longitudinal Cohort Study
Population-based Mayo Clinic Study of Aging.
191 CN persons (median age 77, range 71–93) in the Mayo Clinic Study of Aging who underwent MR, FDG PET and PiB PET imaging at least twice 15 months apart. Subjects were grouped according to the recommendations of the NIA-AA Preclinical AD criteria, based on the presence of β-amyloidosis, defined as a PiB PET SUVr >1.5, alone (Stage 1) or with brain injury (stage 2+3), defined as hippocampal atrophy or FDG hypometabolism. We also studied a group of MCI (n=17) and dementia (n=9) patients from the Mayo Clinic Study of Aging or the Mayo Alzheimer Center with similar follow-up times who had had comparable imaging and who all had PiB PET SUVr >1.5.
Main Outcome Measures
Rate of change of cortical volume on volumetric MR scans and rate of change of glucose metabolism on FDG PET scans.
There were 25 CN subjects with both high PiB retention and low hippocampal volume or FDG hypometabolism at baseline (Preclinical AD stages 2+3). On follow-up scans, the Preclinical AD stages 2+3 subjects had greater loss of medial temporal lobe volume and greater glucose hypometabolism in the medial temporal lobe compared to other CN groups. The changes were similar to the cognitively impaired participants. Extra-temporal regions did not show similar changes.
Higher rates of medial temporal neurodegeneration occurred in CN individuals who, on their initial scans, had abnormal levels of both β-amyloid and brain injury biomarkers.
Alzheimer’s disease; PET imaging; MR imaging; Epidemiology
Leptin, a hormone produced by body fat tissue, acts on hypothalamic receptors in the brain to regulate appetite and energy expenditure, and on neurons in the arcuate nucleus to signal that a individual has had enough to eat. Leptin enters the central nervous system at levels that depend on a individual’s body fat. Obese people, on average, show greater brain atrophy in old age, so it is valuable to know whether brain atrophy relates to leptin levels, which can be targeted by interventions. We therefore determined how plasma leptin levels, and BMI, relate to brain structure, and whether leptin levels might account for BMI’s effect on the brain. We measured regional brain volumes using tensor-based morphometry, in MRI scans of 517 elderly individuals with plasma leptin measured (mean: 13.3±0.6 ng/ml; mean age: 75.2±7.3 years; 321 men/196 women). We related plasma leptin levels to brain volumes at every location in the brain after adjusting for age, sex, and diagnosis and, later, also BMI. Plasma leptin levels were significantly higher (a) in women than men, and (b) in obese versus overweight, normal or underweight individuals. People with higher leptin levels showed deficits in frontal, parietal, temporal and occipital lobes, brainstem, and the cerebellum, irrespective of age, sex, or diagnosis. These associations persisted after controlling for BMI. Greater brain atrophy may occur in people with central leptin insufficiency, a marker of obesity. Therapeutic manipulation of leptin may be a promising direction for slowing brain decline.
Alzheimer’s disease; BMI; brain structure; leptin; MRI; obesity
Biomarkers are the only feasible way to detect and monitor presymptomatic Alzheimer's disease (AD). No single biomarker can predict future cognitive decline with an acceptable level of accuracy. In addition to designing powerful multimodal diagnostic platforms, a careful investigation of the major sources of disease heterogeneity and their influence on biomarker changes is needed. Here we investigated the accuracy of a novel multimodal biomarker classifier for differentiating cognitively normal (NC), mild cognitive impairment (MCI) and AD subjects with and without stratification by ApoE4 genotype. 111 NC, 182 MCI and 95 AD ADNI participants provided both structural MRI and CSF data at baseline. We used an automated machine-learning classifier to test the ability of hippocampal volume and CSF Aβ, t-tau and p-tau levels, both separately and in combination, to differentiate NC, MCI and AD subjects, and predict conversion. We hypothesized that the combined hippocampal/CSF biomarker classifier model would achieve the highest accuracy in differentiating between the three diagnostic groups and that ApoE4 genotype will affect both diagnostic accuracy and biomarker selection. The combined hippocampal/CSF classifier performed better than hippocampus-only classifier in differentiating NC from MCI and NC from AD. It also outperformed the CSF-only classifier in differentiating NC vs. AD. Our amyloid marker played a role in discriminating NC from MCI or AD but not for MCI vs. AD. Neurodegenerative markers contributed to accurate discrimination of AD from NC and MCI but not NC from MCI. Classifiers predicting MCI conversion performed well only after ApoE4 stratification. Hippocampal volume and sex achieved AUC = 0.68 for predicting conversion in the ApoE4-positive MCI, while CSF p-tau, education and sex achieved AUC = 0.89 for predicting conversion in ApoE4-negative MCI. These observations support the proposed biomarker trajectory in AD, which postulates that amyloid markers become abnormal early in the disease course while markers of neurodegeneration become abnormal later in the disease course and suggests that ApoE4 could be at least partially responsible for some of the observed disease heterogeneity.
•Multimodal classifiers have better predictive power than unimodal classifier.•ApoE4 significantly affects diagnostic discriminability in the MCI and dementia stages.•Our data supports the hypothesized biomarker trajectory in AD.
Aβ, Amyloid beta; Aβ42, Amyloid beta with 42 amino acid residues; AD, Alzheimer's disease; ADNI, Alzheimer's Disease Neuroimaging Initiative; ApoE, apolipoprotein E; AUC, area under the curve; CSF, cerebrospinal fluid; ICBM, International Consortium for Brain Mapping; MCI, mild cognitive impairment; MCIc, MCI converters; MCInc, MCI nonconverters; MMSE, Mini-Mental State Examination; NC, normal control; ROC, receiver operating curve; SVM, support vector machine; t-tau, total tau protein; p-tau, phosphorylated tau protein; Alzheimer's disease; Abeta; Tau; Hippocampus atrophy; ADNI; Diagnosis
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
To develop a reliable magnetic resonance elastography (MRE)-based method for measuring regional brain stiffness.
First, simulation studies were used to demonstrate how stiffness measurements can be biased by changes in brain morphometry, such as those due to atrophy. Adaptive postprocessing methods were created that significantly reduce the spatial extent of edge artifacts and eliminate atrophy-related bias. Second, a pipeline for regional brain stiffness measurement was developed and evaluated for test-retest reliability in 10 healthy control subjects.
This technique indicates high test-retest repeatability with a typical coefficient of variation of less than 1% for global brain stiffness and less than 2% for the lobes of the brain and the cerebellum. Furthermore, this study reveals that the brain possesses a characteristic topography of mechanical properties, and also that lobar stiffness measurements tend to correlate with one another within an individual.
The methods presented in this work are resistant to noise- and edge-related biases that are common in the field of brain MRE, demonstrate high test-retest reliability, and provide independent regional stiffness measurements. This pipeline will allow future investigations to measure changes to the brain’s mechanical properties and how they relate to the characteristic topographies that are typical of many neurologic diseases.
White matter hyperintensities (WMHs) associate with both cognitive slowing and motor dysfunction in the neurologically normal elderly. A full understanding of the pathology underlying this clinicoradiologic finding is currently lacking in autopsy-confirmed normal brains. To determine the histopathologic basis of WMH seen on MRI, we studied the relationship between postmortem fluid-attenuated inversion recovery (FLAIR) intensity and neuropathologic markers of white matter lesions (WMLs) that correspond to WMH in cognitively normal aging brains. Samples of periventricular (n = 24), subcortical (n = 26), and normal-appearing white matter (NAWM, n = 31) from 4 clinically and pathologically-confirmed normal cases were examined. FLAIR intensity, vacuolation, and myelin basic protein (MBP) immunoreactivity loss were significantly higher in periventricular WML vs. subcortical WML; both were higher than in NAWM. The subcortical WML and NAWM had significantly less axonal loss, astrocytic burden, microglial density, and oligodendrocyte loss than the periventricular WML. Thus, vacuolation, myelin density and small vessel density contribute to the rarefaction of white matter whereas axonal density, oligodendrocyte density, astroglial burden and microglial density did not. These data suggest that the age-related loss of MBP and a decrease in small vessel density, may contribute to vacuolation of white matter. The vacuolation enables interstitial fluid to accumulate, which contributes to the prolonged T2 relaxation and elevated FLAIR intensity in the white matter.
Digital microscopy; Fluid attenuated inversion recovery; Normal aging; Oligodendrocytes; Postmortem magnetic resonance imaging; White matter
Manual segmentation from magnetic resonance imaging (MR) is the gold standard for evaluating hippocampal atrophy in Alzheimer’s disease (AD). Nonetheless, different segmentation protocols provide up to 2.5-fold volume differences. Here we surveyed the most frequently used segmentation protocols in the AD literature as a preliminary step for international harmonization. The anatomical landmarks (anteriormost and posteriormost slices, superior, inferior, medial, and lateral borders) were identified from 12 published protocols for hippocampal manual segmentation ([Abbreviation] first author, publication year: [B] Bartzokis, 1998; [C] Convit, 1997; [dTM] deToledo-Morrell, 2004; [H] Haller, 1997; [J] Jack, 1994; [K] Killiany, 1993; [L] Lehericy, 1994; [M] Malykhin, 2007; [Pa] Pantel, 2000; [Pr] Pruessner, 2000; [S] Soininen, 1994; [W] Watson, 1992). The hippocampi of one healthy control and one AD patient taken from the 1.5T MR ADNI database were segmented by a single rater according to each protocol. The accuracy of the protocols’ interpretation and translation into practice was checked with lead authors of protocols through individual interactive web conferences. Semantically harmonized landmarks and differences were then extracted, regarding: (a) the posteriormost slice, protocol [B] being the most restrictive, and [H, M, Pa, Pr, S] the most inclusive; (b) inclusion [C, dTM, J, L, M, Pr, W] or exclusion [B, H, K, Pa, S] of alveus/fimbria; (c) separation from the parahippocampal gyrus, [C] being the most restrictive, [B, dTM, H, J, Pa, S] the most inclusive. There were no substantial differences in the definition of the anteriormost slice. This survey will allow us to operationalize differences among protocols into tracing units, measure their impact on the repeatability and diagnostic accuracy of manual hippocampal segmentation, and finally develop a harmonized protocol.
Hippocampus; manual segmentation protocol; harmonization; anatomical landmark; Alzheimer’s disease; manual tracing; medial temporal lobes; atrophy; degeneration; MRI
To estimate the incidence of and to characterize cognitive and imaging findings associated with incident amyloid PET positivity.
Cognitively normal (CN) participants in the Mayo Clinic Study of Aging who had 2 or more serial imaging assessments, which included amyloid PET, FDG-PET, and MRI at each time point, were eligible for analysis (n = 207). Twelve subjects with Alzheimer disease dementia were included for comparison.
Of the 123 CN participants who were amyloid-negative at baseline, 26 met criteria for incident amyloid PET positivity. Compared to the 69 subjects who remained stable amyloid-negative, on average these 26 did not differ on any imaging, demographic, or cognitive variables except amyloid PET (by definition) and task-free functional connectivity, which at baseline was greater in the incident amyloid-positive group. Eleven of the 26 incident amyloid-positive subjects had abnormal hippocampal volume, FDG-PET, or both at baseline.
The incidence of amyloid PET positivity is approximately 13% per year among CN participants over age 70 sampled from a population-based cohort. In 15/26 (58%), incident amyloid positivity occurred prior to abnormalities in FDG-PET and hippocampal volume. However, 11/26 (42%) incident amyloid-positive subjects had evidence of neurodegeneration prior to incident amyloid positivity. These 11 could be subjects with combinations of preexisting non-Alzheimer pathophysiologies and tau-mediated neurodegeneration who newly entered the amyloid pathway. Our findings suggest that both “amyloid-first” and “neurodegeneration-first” biomarker profile pathways to preclinical AD exist.
To evaluate the effects of recent advances in MRI RF coil and parallel imaging technology on brain volume measurement consistency.
Materials and Methods
103 whole-brain MRI volumes were acquired at a clinical 3T MRI, equipped with a 12- and 32-channel head coil, using the T1-weighted protocol as employed in the Alzheimer’s Disease Neuroimaging Initiative study with parallel imaging accelerations ranging from 1 to 5. An experienced reader performed qualitative ratings of the images. For quantitative analysis, differences in composite width (CW, a measure of image similarity) and boundary shift integral (BSI, a measure of whole-brain atrophy) were calculated.
Intra- and inter-session comparisons of CW and BSI measures from scans with equal acceleration demonstrated excellent scan-rescan accuracy, even at the highest acceleration applied. Pairs-of-scans acquired with different accelerations exhibited poor scan-rescan consistency only when differences in the acceleration factor were maximized. A change in the coil hardware between compared scans was found to bias the BSI measure.
The most important findings are that the accelerated acquisitions appear to be compatible with the assessment of high-quality quantitative information and that for highest scan-rescan accuracy in serial scans the acquisition protocol should be kept as consistent as possible over time.
Magnetic resonance imaging (MRI); brain; measurement consistency
To investigate the effect of intellectual and physical activity on biomarkers of Alzheimer’s disease (AD) pathophysiology and cognition in a non-demented elderly population. The biomarkers evaluated were brain Aβ-amyloid load via PIB-PET, neuronal dysfunction via FDG-PET and neurodegeneration via Structural-MRI.
We studied 515 non-demented (428 cognitively normal and 87 MCI) participants in the population based Mayo Clinic Study of Aging who completed a 3T MRI, PET scans, APOE genotype, had lifestyle activity measures and cognition data available. The imaging measures computed were global PiB-PET uptake; global FDG-PET and MRI based hippocampal volume. We consolidated activity variables into lifetime intellectual, current intellectual and current physical activities. We used a global cognitive Z-score as a measure of cognition. We applied two independent methods – partial correlation analysis adjusted for age and gender and path analysis using structural equations to evaluate the associations between lifestyle activities, imaging biomarkers and global cognition.
None of the lifestyle variables correlated with the biomarkers and the path associations between lifestyle variables and biomarkers were not significant (p>0.05). On the other hand, all the biomarkers were correlated with global cognitive Z-score (p<0.05) and the path associations between (lifetime and current) intellectual activities and global Z-score were significant (p<0.01).
Intellectual and physical activity lifestyle factors were not associated with AD biomarkers but intellectual lifestyle factors explained variability in the cognitive performance in this non-demented population. This study provides evidence that lifestyle activities may delay the onset of dementia but do not significantly influence the expression of AD pathophysiology.
Alzheimer’s disease; Imaging biomarkers; Lifestyle Activities
Atypical variants of Alzheimer’s disease (AD) have been pathologically defined based on the distribution of neurofibrillary tangles; hippocampal sparing (HpSp) AD shows minimal involvement of the hippocampus and limbic predominant (LP) AD shows neurofibrillary tangles restricted to the medial temporal lobe. We aimed to determine whether MRI patterns of atrophy differ across HpSp AD, LP AD and typical AD, and whether imaging could be a useful predictor of pathological subtype during life.
In this case-control study, we identified 177 patients who had been prospectively followed in the Mayo Clinic Alzheimer’s Disease Research Center, were demented during life, had AD pathology at autopsy (Braak stage ≥ IV, intermediate-high probability AD) and an antemortem MRI. Cases were assigned to one of three pathological subtypes (HpSp n=19, typical n=125, or LP AD n=33) based on neurofibrillary tangle counts and their ratio in association cortices to hippocampus, without reference to neuronal loss. Voxel-based morphometry and atlas-based parcellation were used to compare patterns of grey matter loss across groups, and to controls.
The severity of medial temporal and cortical grey matter atrophy differed across subtypes. The most severe medial temporal atrophy was observed in LP AD, followed by typical AD, and then HpSp AD. Conversely, the most severe cortical atrophy was observed in HpSp AD, followed by typical AD, and then LP AD. A ratio of hippocampal-to-cortical volume provided the best discrimination across all three AD subtypes. The majority of typical AD (98/125;78%) and LP AD (31/33;94%) subjects, but only 8/19 (42%) of the HpSp AD subjects, presented with a dominant amnestic syndrome.
Patterns of atrophy on MRI differ across the pathological subtypes of AD, suggesting that MR regional volumetrics reliably track the distribution of neurofibrillary tangle pathology and can predict pathological subtype during life.
US National Institutes of Health (National Institute on Aging)
The lack of an in vivo diagnostic test for AD has prompted the targeting of amyloid plaques with diagnostic imaging probes. We describe the development of a contrast agent (CA) for magnetic resonance microimaging that utilizes the F(ab′)2 fragment of a monoclonal antibody raised against fibrillar human Aβ42
This fragment is polyamine modified to enhance its BBB permeability and its ability to bind to amyloid plaques. It is also conjugated with a chelator and gadolinium for subsequent imaging of individual amyloid plaques
Pharmacokinetic studies demonstrated this 125I-CA has higher BBB permeability and lower accumulation in the liver and kidney than F(ab′)2 in WT mice. The CA retains its ability to bind Aβ40/42 monomers/fibrils and also binds to amyloid plaques in sections of AD mouse brain. Intravenous injection of 125I-CA into the AD mouse demonstrates targeting of amyloid plaques throughout the cortex/hippocampus as detected by emulsion autoradiography. Incubation of AD mouse brain slices in vitro with this CA resulted in selective enhancement on T1-weighted spin-echo images, which co-register with individual plaques observed on spatially matched T2-weighted spin-echo image
Development of such a molecular probe is expected to open new avenues for the diagnosis of AD.
Alzheimer’s disease; amyloid plaques; antibody fragments; contrast agent; magnetic resonance imaging
This supplement to the Journal of Alzheimer's Disease contains more than half of the chapters from The Handbook of Imaging the Alzheimer Brain, which was first presented at the International Conference on Alzheimer's Disease in Paris, in July, 2011.
While the Handbook contains 27 chapters that are modified articles from 2009, 2010, and 2011 issues of the Journal of Alzheimer's Disease, this supplement contains the 31 new chapters of that book and an introductory article drawn from the introductions to each section of the book.
The Handbook was designed to provide a multilevel overview of the full field of brain imaging related to Alzheimer's disease (AD). The Handbook, as well as this supplement, contains both reviews of the basic concepts of imaging, the latest developments in imaging, and various discussions and perspectives of the problems of the field and promising directions.
The Handbook was designed to be useful for students and clinicians interested in AD as well as scientists studying the brain and pathology related to AD.
Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia after Alzheimer's disease (AD). Our objective was to determine whether the 11C–Pittsburgh Compound-B (PiB) retention and regional hypometabolism on PET and regional cortical atrophy on MRI are complementary in characterizing patients with DLB and differentiating them from AD. We studied age, gender and education matched patients with a clinical diagnosis of DLB (n=21), AD (n=21), and cognitively normal subjects (n=42). Hippocampal atrophy, global cortical PiB retention and occipital lobe metabolism in combination distinguished DLB from AD better than any of the measurements alone (area under the receiver operating characteristic=0.98).Five of the DLB and AD patients who underwent autopsy were distinguished through multimodality imaging. These data demonstrate that MRI and PiB PET contribute to characterizing the distinct pathological mechanisms in patients with AD compared to DLB. Occipital and posterior parietotemporal lobe hypometabolism is a distinguishing feature of DLB and this regional hypometabolic pattern is independent of the amyloid pathology.
Dementia with Lewy bodies; MRI; PET; FDG; PiB; Alzheimer's disease