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.
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
Alzheimer’s disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Recent disappointing trial results at the dementia stage of AD have raised multiple questions about our current approaches to the development of disease-modifying agents. Converging evidence suggests that the pathophysiological process of AD begins many years before the onset of dementia. So why do we keep testing drugs aimed at the initial stages of the disease process in patients at the end-stage of the illness?
Alzheimer’s disease (AD) remains one of the most feared consequences of aging, affecting more than one out of every ten individuals over the age of 65. With more than 10,000 baby boomers turning 65 every day in the United States alone, we are truly facing an AD epidemic. Over the past decade, a string of disappointing clinical trial results have raised concerns about our current strategy for development of AD-modifying therapies. Three hypotheses can explain these recent AD trial failures: (i) We are targeting the wrong pathophysiological mechanisms; (ii) The drugs do not engage the intended targets in patients; and (iii) The drugs are hitting the right targets, but are doing so at the wrong stage of the disease. Here, we address the third supposition and suggest that specific amyloid-based therapies be directed at much earlier stages of ADperhaps even prior to the emergence of clinical symptoms. Furthermore, we argue that the field has sufficient tools to begin “secondary prevention” trials in asymptomatic individuals whoare at high risk for progression to cognitive impairment and AD dementia.
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
Acetylcholinesterase inhibitors are commonly used to treat patients with dementia with Lewy bodies. Hippocampal atrophy on magnetic resonance imaging and amyloid-β load on positron emission tomography are associated with the Alzheimer’s disease-related pathology in patients with dementia with Lewy bodies. To date, few studies have investigated imaging markers that predict treatment response in patients with dementia with Lewy bodies. Our objective was to determine whether imaging markers of Alzheimer’s disease-related pathology such as hippocampal volume, brain amyloid-β load on 11C Pittsburgh compound B positron emission tomography predict treatment response to acetylcholinesterase inhibitors in patients with dementia with Lewy bodies. We performed a retrospective analysis on consecutive treatment-naive patients with dementia with Lewy bodies (n = 54) from the Mayo Clinic Alzheimer’s Disease Research Centre who subsequently received acetylcholinesterase inhibitors and underwent magnetic resonance imaging with hippocampal volumetry. Baseline and follow-up assessments were obtained with the Mattis Dementia Rating Scale. Subjects were divided into three groups (reliable improvement, stable or reliable decline) using Dementia Rating Scale reliable change indices determined previously. Associations between hippocampal volumes and treatment response were tested with analysis of covariance adjusting for baseline Dementia Rating Scale, age, gender, magnetic resonance field strength and Dementia Rating Scale interval. Seven subjects underwent 11C Pittsburgh compound B imaging within 12 weeks of magnetic resonance imaging. Global cortical 11C Pittsburgh compound B retention (scaled to cerebellar retention) was calculated in these patients. Using a conservative psychometric method of assessing treatment response, there were 12 patients with reliable decline, 29 stable cases and 13 patients with reliable improvement. The improvers had significantly larger hippocampi than those that declined (P = 0.02) and the stable (P = 0.04) group. An exploratory analysis demonstrated larger grey matter volumes in the temporal and parietal lobes in improvers compared with those who declined (P < 0.05). The two patients who had a positive 11C Pittsburgh compound B positron emission tomography scan declined and those who had a negative 11C Pittsburgh compound B positron emission tomography scan improved or were stable after treatment. Patients with dementia with Lewy bodies who do not have the imaging features of coexistent Alzheimer’s disease-related pathology are more likely to cognitively improve with acetylcholinesterase inhibitor treatment.
dementia with Lewy bodies; acetylcholinesterase inhibitors; MRI; PiB; PET; amyloid
Obsessions and compulsive (OC) behaviors are a frequent feature of behavioral variant frontotemporal dementia (bvFTD), but their structural correlates have not been definitively established.
Patients with bvFTD presenting to the Mayo Clinic Alzheimer’s Disease Research Center were recruited. Each patient’s caregiver was given the Yale-Brown Obsessive-Compulsive scale (YBOCS) to document the type and presence of OC behaviors and to rate their severity. All subjects underwent a standardized MRI which was evaluated using VBM. 17 patients with bvFTD were recruited and 11 were included in the study and compared to 11 age and gender matched controls. Six were excluded for lack of MRI at time of survey or a pre-existing neurodegenerative condition.
Nine of the 11 reported OC behaviors, with the most frequent compulsions being checking, hoarding, ordering/arranging, repeating rituals, and cleaning. In the VBM analysis, total YBOCS score correlated with grey matter loss in the bilateral globus pallidus, left putamen, and in the lateral temporal lobe, particularly the left middle and inferior temporal gyri (p<0.001 uncorrected for multiple comparisons).
Obsessive-compulsive behaviors were frequent among these patients. The correlation with basal ganglia atrophy may point to involvement of frontal subcortical neuronal networks. Left lateral temporal lobe volume loss likely reflects the number of MAPT mutation patients included but also provides additional data implicating temporal lobe involvement in OC behaviors.
Frontotemporal dementia; magnetic resonance imaging; obsessive behavior; compulsive behavior
Evaluating the integrity of white matter tracts with diffusion tensor imaging may differentiate primary lateral sclerosis from progressive supranuclear palsy.
Thirty-three prospectively recruited subjects had standardized evaluations and diffusion tensor imaging: 3 with primary lateral sclerosis who presented with features suggestive of progressive supranuclear palsy, 10 with probable or definite progressive supranuclear palsy, and 20 matched controls. We compared fractional anisotropy of the corticospinal tract, superior cerebellar peduncle and body of the corpus callosum between groups.
Both the primary lateral sclerosis and progressive supranuclear palsy subjects showed reduced fractional anisotropy in superior cerebellar peduncles and body of the corpus callosum compared to controls, but only primary lateral sclerosis subjects showed reductions in the corticospinal tracts. A ratio of corticospinal tract/superior cerebellar peduncle best distinguished the disorders (p<0.02).
The corticospinal tract/superior cerebellar peduncle ratio is a marker to differentiate primary lateral sclerosis from progressive supranuclear palsy.
Progressive supranuclear palsy; primary lateral sclerosis; motor neuron disease; diffusion tensor imaging
There is epidemiological evidence that cardiovascular risk factors (CVRF) also are risk factors for Alzheimer’s disease, but there is limited information on this from neuro-pathological studies, and even less from in vivo studies. Therefore, we examined the relationship between CVRF and amyloid-β (Aβ) brain burden measured by Pittsburgh Compound B-positron emission tomography (PiB-PET) studies in the Alzheimer’s Disease Neuroimaging Initiative.
Ninety-nine subjects from the Alzheimer’s Disease Neuroimaging Initiative cohort who had a PiB-PET study measure, apolipoprotein E genotyping data, and information available on CVRF (body mass index [BMI], systolic blood pressure, diastolic blood pressure [DBP1 and cholesterol and fasting glucose test results) were included. Eighty-one subjects also had plasma cortisol C-reactive protein, and superoxide dismutase 1 measurements. Stepwise regression models were used to assess the relation between the CVRF and the composite PiB-PET score.
The first model included the following as baseline variables: age, clinical diagnosis, number of apolipoprotein ε4 alleles, BMI (P = .023), and DBP (P = .012). BMI showed an inverse relation with PiB-PET score, and DBP had a positive relation with PiB-PET score. In the second adjusted model, cortisol plasma levels were also associated with PiB-PET score (P = .004). Systolic blood pressure, cholesterol, or impaired fasting glucose were not found to be associated with PiB-PET values.
In this cross-sectional study, we found an association between Aβ brain burden measured in vivo and DBP and cortisol, indicating a possible link between these CVRF and Aβ burden measured by PiB-PET. These findings highlight the utility of biomarkers to explore potential pathways linking diverse Alzheimer’s disease risk factors.
Alzheimer disease; Vascular risk factors; PiB; Amyloid-β; Cortisol; Blood pressure; Body mass index
Background and method
We investigated whether chronic kidney disease detected by increased serum creatinine (SCr) or urine albumin-to-creatinine ratio (UACR) may reflect arteriosclerosis involving the kidneys. The sample consisted of 1585 members of sibships (804 non-Hispanic whites and 781 non-Hispanic blacks) in which at least two siblings had primary hypertension. We first evaluated the correlations of increased SCr and UACR with the presence of cerebral small vessel arteriosclerosis, which was determined by increased subcortical white matter hyperintensity (WMH) volume on brain magnetic resonance imaging; and with peripheral large vessel arteriosclerosis, which was determined by decreased ankle-brachial index (ABI). After age adjustment, increased SCr and UACR correlated with increased WMH volume (0.54 and 0.52, respectively) and with decreased ABI (0.50 and 0.54, respectively; all P < 0.001). We then used logistic regression to evaluate the dependency of each measure of disease on conventional risk factors for arteriosclerosis to assess whether the risk factors’ effects were proportional across different measures of disease.
Age, race, sex, hypertension, diabetes, total cholesterol, and smoking made similar overall contributions to the prediction of each measure of disease, as judged by the model C-statistics, which varied in a narrow range from 0.84 to 0.85 (all P < 0.001). However, the relative contributions that the modifiable risk factors, including hypertension, diabetes, total cholesterol, and smoking made to prediction of increased SCr and UACR were disproportionate to their relative contributions to prediction of decreased ABI (P < 0.0001).
The findings support the view that chronic kidney disease detected by increased SCr or UACR primarily reflects small vessel arteriosclerosis involving the kidneys.
albuminuria; ankle-brachial blood pressure index; arteriosclerosis; blood pressure; glomerular filtration rate; hypertension; subcortical white matter hyperintensity
The goal was to elucidate the time course of regional brain atrophy rates relative to age in cognitively normal (CN) aging, mild cognitively impairment (MCI) and Alzheimer’s disease (AD), without a-priori models for atrophy progression. Regional brain volumes from 147 CN subjects, 164 stable MCI, 93 MCI-to-AD converters and 111 AD patients, between 51 to 91 years old and who had repeated 1.5T magnetic resonance imaging (MRI) scans over 30 months, were analyzed. Relations between regional brain volume change and age were determined using generalized additive models, an established non-parametric concept for approximating nonlinear relations. Brain atrophy rates varied nonlinearly with age, predominantly in regions of the temporal lobe. Moreover, the atrophy rates of some regions leveled off with increasing age in control and stable MCI subjects whereas those rates progressed further in MCI-to-AD converters and AD patients. The approach has potential uses for early detection of AD and differentiation between stable and progressing MCI.
Alzheimer’s disease; mild cognitive impairment; aging; brain atrophy; hippocampus; magnetic resonance imaging; generalized additive models
The association between antemortem [11C]-Pittsburgh Compound B (PiB) retention and β-amyloid (Aβ) load, Lewy body (LB) and neurofibrillary tangle (NFT) densities were investigated in a pathologically confirmed case of dementia with LB (DLB). 76-year-old man presenting with a clinical diagnosis of DLB had undergone PiB–positron emission tomography (PET), 18F FDG-PET and MRI 18 months before death. The pathologic diagnosis was DLB neocortical-type with low-likelihood of Alzheimer's disease by NIA-Reagan criteria. Sections from regions of interest (ROI) on post-mortem examination were studied. A significant correlation was found between cortical Aβ density and PiB retention in the 17 corresponding ROIs (r=0.899; p<0.0001). Bielschowsky silver stain revealed mostly sparse neocortical neuritic plaques; whereas diffuse plaques were frequent. There was no correlation between LB density and PiB retention (r=0.13; p=0.66); nor between NFT density and PiB retention (r=−0.36; p=0.17). The ROI-based analysis of imaging and histopathological data confirms that PiB uptake on PET is a specific marker for Aβ density, but cannot differentiate neuritic from diffuse amyloid plaques in this case with DLB.
Dementia with Lewy bodies; amyloid imaging; PET; pathology; amyloid
The increasing prevalence of Alzheimer’s disease (AD) has provided motivation for developing novel methods for assessing the disease and the effects of potential treatments. Magnetic resonance elastography (MRE) is an MRI-based method for quantitatively imaging the shear tissue stiffness in vivo. The objective of this research was to determine whether this new imaging biomarker has potential for characterizing neurodegenerative disease. Methods were developed and tested for applying MRE to evaluate the mouse brain, using a conventional large bore 3.0T MRI system. The technique was then applied to study APP-PS1 mice, a well-characterized model of AD. Five APP-PS1 mice and 8 age-matched wild-type mice were imaged immediately following sacrifice. Brain shear stiffness measurements in APP-PS1 mice averaged 22.5% lower than those for wild-type mice (P = .0031). The results indicate that mouse brain MRE is feasible at 3.0T, and brain shear stiffness has merit for further investigation as a potential new biomarker for Alzheimer’s disease.
Alzheimer’s disease; MR elastography; Brain; Stiffness; APP-PS1
To determine whether MRI measurements observed in the Alzheimer's Disease Neuroimaging Initiative (ADNI; convenience-sample) differ from those observed in the Mayo Clinic Study of Aging (MCSA; population-based sample).
Comparison of two samples.
59 recruiting sites for the ADNI in US/Canada, and the MCSA, a population-based cohort in Olmsted County, MN.
Cognitively normal (CN) subjects and amnestic mild cognitive impairment (aMCI) subjects were selected from the ADNI convenience cohort and MCSA population-based cohort. Two samples were selected; the first was a simple random sample of subjects from both cohorts in the same age range, and the second applied matching for age, sex, education, apolipoprotein E genotype, and Mini-Mental State Examination.
Main outcome measures
Baseline hippocampal volumes and annual percent decline in hippocampal volume.
In the population-based sample, MCSA subjects were older, less educated, performed worse on MMSE, and less often had family history of AD than ADNI subjects. Baseline hippocampal volumes were larger in ADNI compared to MCSA CN subjects in the random sample, although no differences were observed after matching. Rates of decline in hippocampal volume were greater in ADNI compared to MCSA for both CN and aMCI, even after matching.
Rates of decline in hippocampal volume suggest that ADNI subjects have more aggressive brain pathology than MCSA subjects, and hence may not be representative of the general population. These findings have implications for treatment trials that employ ADNI-like recruitment mechanisms and for studies validating new diagnostic criteria for AD in its various stages.
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
Neuroanatomic substrates of specific cognitive functions have been inferred from anatomic distributions of activated pixels during fMRI studies. With declarative memory tasks, interest has focused on the extent to which various medial temporal lobe anatomic structures are activated while subjects encode new information. The aim of this project was to examine how commonly used variations in fMRI data processing methods affect the distribution of activation in anatomically defined medial temporal lobe regions of interest (ROIs) during a complex scene-encoding task. ROIs were drawn on an MRI anatomic template formed from 3d-SPGR scans of 8 subjects combined in Talairach space. Separate ROIs were drawn for the posterior and anterior hippocampal formation, parahippocampal gyrus, and entorhinal cortex. Twelve different activation maps were created for each subject by using four correlation coefficients and three cluster volumes. Friedman’s two-way ANOVA by ranks was used to test the hypothesis that the distribution of activated pixels among defined anatomic ROIs varied as a function of the data processing method.
By simply varying the combination of correlation-coefficient and cluster volume, significantly different distributions of activation within named medial temporal lobe structures were obtained from the same fMRI datasets (p<0.015; p<0.001). The number of subjects studied (n=8) is in a range commonly found in the literature yet this clearly resulted in spurious associations between processing parameter variations and activation distribution. Using data processing methods that are independent of the arbitrary selection of cutoff values for thresholding activation maps may reduce the likelihood of obtaining spurious results.
The hexanucleotide repeat in the chromosome 9 open reading frame 72 (C9ORF72) gene was recently discovered as the pathogenic mechanism underlying many families with frontotemporal dementia (FTD) and/or amyotrophic lateral sclerosis (ALS) linked to chromosome 9 (c9FTD/ALS). We report the clinical, neuropsychological, and neuroimaging findings of a family with the C9ORF72 mutation and clinical diagnoses bridging the FTD, parkinsonism and ALS spectrum.
To characterize the antemortem characteristics of a family with c9FTD/ALS associated with the GGGGCC repeat expansion in C9ORF72
Tertiary care academic medical center.
The members of the family affected by the mutation with features of FTD and/or ALS.
Main Outcome Measures
Clinical, neuropsychological, and neuroimaging assessments.
All three examined subjects had the hexanucleotide expansion detected in C9ORF72. All had personality/behavioral changes early in the course of the disease. One case had levodopa-unresponsive parkinsonism, and one had ALS. MRI showed symmetric bilateral frontal, temporal, insular and cingulate atrophy.
This report highlights the clinical and neuroimaging characteristics of a family with c9FTD/ALS. Further studies are needed to better understand the phenotypical variability and the clinico-neuroimaging-neuropathologic correlations.
Voxel-based morphometry (VBM) is a popular method for probing inter-group differences in brain morphology. Variation in the detailed implementation of the algorithm, however, will affect the apparent results of VBM analyses and in turn the inferences drawn about the anatomic expression of specific disease states. We qualitatively assessed group comparisons of 43 normal elderly control subjects and 51 patients with probable Alzheimer's disease, using five different VBM variations. Based on the known pathologic expression of the disease, we evaluated the biological plausibility of each. The use of a custom template and custom tissue class prior probability images (priors) produced inter-group comparison maps with greater biological plausibility than the use of the Montreal Neurological Institute (MNI) template and priors. We present a method for initializing the normalization to a custom template, and conclude that, when incorporated into the VBM processing chain, it yields the most biologically plausible inter-group differences of the five methods presented.
The clinical syndromes of frontotemporal lobar degeneration include behavioral variant frontotemporal dementia (bvFTD) and semantic (SV-PPA) and nonfluent variants (NF-PPA) of primary progressive aphasia. Using magnetic resonance imaging (MRI), tensor-based morphometry (TBM) was used to determine distinct patterns of atrophy between these three clinical groups.
Twenty-seven participants diagnosed with bvFTD, 16 with SV-PPA, and 19 with NF-PPA received baseline and follow-up MRI scans approximately 1 year apart. TBM was used to create three-dimensional Jacobian maps of local brain atrophy rates for individual subjects.
Regional analyses were performed on the three-dimensional maps and direct comparisons between groups (corrected for multiple comparisons using permutation tests) revealed significantly greater frontal lobe and frontal white matter atrophy in the bvFTD relative to the SV-PPA group (p < 0.005). The SV-PPA subjects exhibited significantly greater atrophy than the bvFTD in the fusiform gyrus (p = 0.007). The NF-PPA group showed significantly more atrophy in the parietal lobes relative to both bvFTD and SV-PPA groups (p < 0.05). Percent volume change in ventromedial prefrontal cortex was significantly associated with baseline behavioral symptomatology.
The bvFTD, SV-PPA, and NF-PPA groups displayed distinct patterns of progressive atrophy over a 1-year period that correspond well to the behavioral disturbances characteristic of the clinical syndromes. More specifically, the bvFTD group showed significant white matter contraction and presence of behavioral symptoms at baseline predicted significant volume loss of the ventromedial prefrontal cortex.
Frontotemporal dementia; Primary progressive aphasia; Longitudinal study; Magnetic resonance imaging; Tensor-based morphometry; White matter
To develop and validate a tool for Alzheimer's disease (AD) diagnosis in individual subjects using support vector machine (SVM) based classification of structural MR (sMR) images.
Libraries of sMR scans of clinically well characterized subjects can be harnessed for the purpose of diagnosing new incoming subjects.
190 patients with probable AD were age- and gender-matched with 190 cognitively normal (CN) subjects. Three different classification models were implemented: Model I uses tissue densities obtained from sMR scans to give STructural Abnormality iNDex (STAND)-score; and Models II and III use tissue densities as well as covariates (demographics and Apolipoprotein E genotype) to give adjusted-STAND (aSTAND)-score. Data from 140 AD and 140 CN were used for training. The SVM parameter optimization and training was done by four-fold cross validation. The remaining independent sample of 50 AD and 50 CN were used to obtain a minimally biased estimate of the generalization error of the algorithm.
The CV accuracy of Model II and Model III aSTAND-scores was 88.5% and 89.3% respectively and the developed models generalized well on the independent test datasets. Anatomic patterns best differentiating the groups were consistent with the known distribution of neurofibrillary AD pathology.
This paper presents preliminary evidence that application of SVM-based classification of an individual sMR scan relative to a library of scans can provide useful information in individual subjects for diagnosis of AD. Including demographic and genetic information in the classification algorithm slightly improves diagnostic accuracy.
support vector machines; classification; diagnosis; Alzheimer's