Rates of brain atrophy over time in autopsy-proven frontotemporal dementia and Alzheimer disease

Decomposing the effect of normal aging and Alzheimer's disease in brain morphological changes via learned aging templates

Alzheimer's disease (AD) subjects usually show more profound morphological changes with time compared to cognitively normal (CN) individuals. These changes are the combination of two major biological processes: normal aging and AD pathology. Investigating normal aging and residual morphological changes separately can increase our understanding of the disease. This paper proposes two scores, the aging score (AS) and the AD-specific score (ADS), whose purpose is to measure these two components of brain atrophy independently. For this, in the first step, we estimate the atrophy due to the normal aging of CN subjects by computing the expected deformation required to match imaging templates generated at different ages. We used a state-of-the-art generative deep learning model for generating such imaging templates. In the second step, we apply deep learning-based diffeomorphic registration to align the given image of a subject with a reference imaging template. Parametrization of this deformation field is then decomposed voxel-wise into their parallel and perpendicular components with respect to the parametrization of the expected atrophy of CN individuals in one year computed in the first step. AS and ADS are the normalized scores of these two components, respectively. We evaluated these two scores on the OASIS-3 dataset with 1,014 T1-weighted MRI scans. Of these, 326 scans were from CN subjects, and 688 scans were from subjects diagnosed with AD at various stages of clinical severity, as defined by clinical dementia rating (CDR) scores. Our results reveal that AD is marked by both disease-specific brain changes and an accelerated aging process. Such changes affect brain regions differently. Moreover, the proposed scores were sensitive to detect changes in the early stages of the disease, which is promising for its potential future use in clinical studies. Our code is freely available at https://github.com/Fjr9516/DBM_with_DL .

Cortex-to-caudate volume ratio as a predictor of cognitive decline in Alzheimer's disease and mild cognitive impairment

BACKGROUND

Brain and cortical atrophy play crucial roles in supporting the clinical diagnosis of Alzheimer's disease (AD). This study hypothesized that the ratios of brain or cortical volume to subcortical gray matter structure volumes are potential imaging markers for cognitive alterations in AD dementia and amnestic mild cognitive impairment (aMCI).

METHODS

Seventy-seven subjects diagnosed with AD dementia or aMCI underwent baseline neuropsychological testing, 2-year follow-up cognitive assessments, and high-resolution T1-weighted MRI scans. Total brain/cortical volume and subcortical gray matter structure volumes were automatically segmented and measured. Univariate and multiple linear regression analyses were conducted to determine the associations between volumetric ratios and interval changes in cognitive scores.

RESULTS

The ratio of cortical volume to caudate volume showed the most significant association with changes in MoCA (B = 0.132, SE = 0.042, p = 0.002), MMSE (B = 0.140, SE = 0.040, p = 0.001), and CDR-SOB (B = -0.013, SE = 0.005, p = 0.007) scores over the 2-year follow-up period. These associations remained significant after adjusting for various covariates. Similar associations were observed for the ratios of cortical volume to putamen and globus pallidum volumes.

CONCLUSIONS

The cortex-to-caudate volume ratio is significantly associated with cognitive decline in AD dementia and aMCI. This ratio may serve as a useful biomarker for monitoring disease progression and predicting cognitive outcomes. Our findings highlight the importance of considering the relative atrophy of cortical and subcortical structures in understanding AD pathology.

Longitudinal cerebral perfusion in presymptomatic genetic frontotemporal dementia: GENFI results

INTRODUCTION

Effective longitudinal biomarkers that track disease progression are needed to characterize the presymptomatic phase of genetic frontotemporal dementia (FTD). We investigate the utility of cerebral perfusion as one such biomarker in presymptomatic FTD mutation carriers.

METHODS

We investigated longitudinal profiles of cerebral perfusion using arterial spin labeling magnetic resonance imaging in 42 C9orf72, 70 GRN, and 31 MAPT presymptomatic carriers and 158 non-carrier controls. Linear mixed effects models assessed perfusion up to 5 years after baseline assessment.

RESULTS

Perfusion decline was evident in all three presymptomatic groups in global gray matter. Each group also featured its own regional pattern of hypoperfusion over time, with the left thalamus common to all groups. Frontal lobe regions featured lower perfusion in those who symptomatically converted versus asymptomatic carriers past their expected age of disease onset.

DISCUSSION

Cerebral perfusion is a potential biomarker for assessing genetic FTD and its genetic subgroups prior to symptom onset.

HIGHLIGHTS

Gray matter perfusion declines in at-risk genetic frontotemporal dementia (FTD). Regional perfusion decline differs between at-risk genetic FTD subgroups . Hypoperfusion in the left thalamus is common across all presymptomatic groups. Converters exhibit greater right frontal hypoperfusion than non-converters past their expected conversion date. Cerebral hypoperfusion is a potential early biomarker of genetic FTD.

Polypathologic Associations with Gray Matter Atrophy in Neurodegenerative Disease

Mixed pathologies are common in neurodegenerative disease; however, antemortem imaging rarely captures copathologic effects on brain atrophy due to a lack of validated biomarkers for non-Alzheimer's pathologies. We leveraged a dataset comprising antemortem MRI and postmortem histopathology to assess polypathologic associations with atrophy in a clinically heterogeneous sample of 125 human dementia patients (41 female, 84 male) with T1-weighted MRI ≤ 5 years before death and postmortem ordinal ratings of amyloid-[Formula: see text], tau, TDP-43, and [Formula: see text]-synuclein. Regional volumes were related to pathology using linear mixed-effects models; approximately 25% of data were held out for testing. We contrasted a polypathologic model comprising independent factors for each proteinopathy with two alternatives: a model that attributed atrophy entirely to the protein(s) associated with the patient's primary diagnosis and a protein-agnostic model based on the sum of ordinal scores for all pathology types. Model fits were evaluated using log-likelihood and correlations between observed and fitted volume scores. Additionally, we performed exploratory analyses relating atrophy to gliosis, neuronal loss, and angiopathy. The polypathologic model provided superior fits in the training and testing datasets. Tau, TDP-43, and [Formula: see text]-synuclein burden were inversely associated with regional volumes, but amyloid-[Formula: see text] was not. Gliosis and neuronal loss explained residual variance in and mediated the effects of tau, TDP-43, and [Formula: see text]-synuclein on atrophy. Regional brain atrophy reflects not only the primary molecular pathology but also co-occurring proteinopathies; inflammatory immune responses may independently contribute to degeneration. Our findings underscore the importance of antemortem biomarkers for detecting mixed pathology.

Brain ventricles, CSF and cognition: a narrative review

The brain ventricles are structures that have been related to cognition since antiquity. They are essential components in the development and maintenance of brain functions. The aging process runs with the enlargement of ventricles and is related to a less selective blood-cerebrospinal fluid barrier and then a more toxic cerebrospinal fluid environment. The study of brain ventricles as a biological marker of aging is promissing because they are structures easily identified in neuroimaging studies, present good inter-rater reliability, and measures of them can identify brain atrophy earlier than cortical structures. The ventricular system also plays roles in the development of dementia, since dysfunction in the clearance of beta-amyloid protein is a key mechanism in sporadic Alzheimer's disease. The morphometric and volumetric studies of the brain ventricles can help to distinguish between healthy elderly and persons with mild cognitive impairment (MCI) and dementia. Brain ventricle data may contribute to the appropriate allocation of individuals in groups at higher risk for MCI-dementia progression in clinical trials and to measuring therapeutic responses in these studies, as well as providing differential diagnosis, such as normal pressure hydrocephalus. Here, we reviewed the pathophysiology of healthy aging and cognitive decline, focusing on the role of the choroid plexus and brain ventricles in this process.

Ventricular features as reliable differentiators between bvFTD and other dementias

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Our results showed a consistent pattern of ventricle enlargement in the bvFTD patients, particularly in the anterior parts of the frontal and temporal horns of the lateral ventricles.

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The estimation of the proposed ventricular anteroposterior ratio (APR) resulted in statistically significant difference compared to all other groups.

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Our study proposes an easy to obtain and generalizable ventricle-based feature (APR) from T1-weighted structural MRI (routinely acquired and available in the clinic) that can be used not only to differentiate bvFTD from normal subjects, but also from other FTD variants (SV and PNFA), MCI, and AD patients.

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We have made our ventricle feature estimation and bvFTD diagnosis tool (VentRa) publicly available, allowing application of our model in other studies.

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If validated in a prospective study, VentRa has the potential to aid bvFTD diagnosis, particularly in settings where access to specialized FTD care is limited.

Introduction

Lateral ventricles are reliable and sensitive indicators of brain atrophy and disease progression in behavioral variant frontotemporal dementia (bvFTD). We aimed to investigate whether an automated tool using ventricular features could improve diagnostic accuracy in bvFTD across neurodegenerative diseases.

Methods

Using 678 subjects −69 bvFTD, 38 semantic variant, 37 primary non-fluent aphasia, 218 amyloid + mild cognitive impairment, 74 amyloid + Alzheimer’s Dementia and 242 normal controls- with a total of 2750 timepoints, lateral ventricles were segmented and differences in ventricular features were assessed between bvFTD, normal controls and other dementia cohorts.

Results

Ventricular antero-posterior ratio (APR) was the only feature that was significantly different and increased faster in bvFTD compared to all other cohorts. We achieved a 10-fold cross-validation accuracy of 80% (77% sensitivity, 82% specificity) in differentiating bvFTD from all other cohorts with other ventricular features (i.e., total ventricular volume and left–right lateral ventricle ratios), and 76% accuracy using only the single APR feature.

Discussion

Ventricular features, particularly the APR, might be reliable and easy-to-implement markers for bvFTD diagnosis. We have made our ventricle feature estimation and bvFTD diagnostic tool publicly available, allowing application of our model in other studies.

Revised Self-Monitoring Scale: A potential endpoint for frontotemporal dementia clinical trials

OBJECTIVE

To investigate whether the Revised Self-Monitoring Scale (RSMS), an informant measure of socioemotional sensitivity, is a potential clinical endpoint for treatment trials for patients with behavioral variant frontotemporal dementia (bvFTD).

METHODS

We investigated whether RSMS informant ratings reflected disease severity in 475 participants (71 bvFTD mutation+, 154 bvFTD mutation-, 12 behavioral mild cognitive impairment [MCI] mutation+, 98 asymptomatic mutation+, 140 asymptomatic mutation-). In a subset of 62 patients (20 bvFTD mutation+, 35 bvFTD mutation-, 7 MCI mutation+) who had at least 2 time points of T1-weighted images available on the same 3T scanner, we examined longitudinal changes in RSMS score over time and its correspondence to progressive gray matter atrophy.

RESULTS

RSMS score showed a similar pattern in mutation carriers and noncarriers, with significant drops at each stage of progression from asymptomatic to very mild, mild, moderate, and severe disease (F 4,48 = 140.10, p < 0.001) and a significant slope of decline over time in patients with bvFTD (p = 0.004, 95% confidence interval [CI] -1.90 to -0.23). More rapid declines on the RSMS corresponded to faster gray matter atrophy predominantly in the salience network (SN), and RSMS score progression best predicted thalamic volume in very mild and mild disease stages of bvFTD. Higher RSMS score predicted more caregiver burden (p < 0.001, 95% CI -0.30 to -0.11).

CONCLUSIONS

The RSMS is sensitive to progression of both socioemotional symptoms and SN atrophy in patients with bvFTD and corresponds directly to caregiver burden. The RSMS may be useful in both neurologic practice and clinical trials aiming to treat behavioral symptoms of patients with bvFTD.

Tracking disease progression in familial and sporadic frontotemporal lobar degeneration: Recent findings from ARTFL and LEFFTDS

INTRODUCTION

Familial frontotemporal lobar degeneration (f-FTLD) due to autosomal dominant mutations is an important entity for developing treatments for FTLD. The Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) longitudinal studies were designed to describe the natural history of f-FTLD.

METHODS

We summarized recent publications from the ARTFL and LEFFTDS studies, along with other recent publications describing the natural history of f-FTLD.

RESULTS

Published and emerging studies are producing data on all phases of f-FTLD, including the asymptomatic and symptomatic phases of disease, as well as the transitional phase when symptoms are just beginning to develop. These data indicate that rates of change increase along with disease severity, which is consistent with commonly cited models of neurodegeneration, and that measurement of biomarkers may predict onset of symptoms.

DISCUSSION

Data from large multisite studies are producing important data on the natural history of f-FTLD that will be critical for planning intervention trials.

Systematic Review on the Impact of Intelligence on Cognitive Decline and Dementia Risk

BACKGROUND

Previous studies have shown that an intellectually stimulating lifestyle is associated with a lower risk for cognitive decline and Alzheimer's disease and related dementia (ADRD). It is unclear so far whether higher intelligence may protect against this. The aim of this study was to conduct a systematic review on the association between intelligence and cognitive decline and ADRD risk.

METHODS

We searched the PubMed, web of science, and Scopus databases following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and Population, Intervention, Comparison, and Outcome (PICO) criteria. Quality of evidence was assessed using Critical Appraisal Skills Programme (CASP) checklists.

RESULTS

From an initial n=8,371 search hits, n= 14 studies met the inclusion criteria and had sufficient quality. Evidence indicates that cognitive decline in old age is not significantly associated with childhood intelligence (n=9). Evidence with regard to ADRD risk is inconclusive (n=5) with some studies showing no effects and other studies with significant effects having limitations in their design.

CONCLUSIONS

Even though the majority of the studies show no significant association, we cannot exclude a possible effect that might be moderated by other, so far unknown factors. Further studies are necessary to systematically assess the influence of intelligence on ADRD risk and what factors moderate this association.

Deformation based morphometry study of longitudinal MRI changes in behavioral variant frontotemporal dementia

OBJECTIVE

To objectively quantify how cerebral volume loss could assist with clinical diagnosis and clinical trial design in the behavioural variant of frontotemporal dementia (bvFTD).

METHODS

We applied deformation-based morphometric analyses with robust registration to precisely quantify the magnitude and pattern of atrophy in patients with bvFTD as compared to cognitively normal controls (CNCs), to assess the progression of atrophy over one year follow up and to generate clinical trial sample size estimates to detect differences for the structures most sensitive to change. This study included 203 subjects - 70 bvFTD and 133 CNCs - with a total of 482 timepoints from the Frontotemporal Lobar Degeneration Neuroimaging Initiative.

RESULTS

Deformation based morphometry (DBM) revealed significant atrophy in the frontal lobes, insula, medial and anterior temporal regions bilaterally in bvFTD subjects compared to controls with outstanding subcortical involvement. We provide detailed information on regional changes per year. In both cross-sectional analysis and over a one-year follow-up period, ventricle expansion was the most prominent differentiator of bvFTD from controls and a sensitive marker of disease progression.

CONCLUSIONS

Automated measurement of ventricular expansion is a sensitive and reliable marker of disease progression in bvFTD to be used in clinical trials for potential disease modifying drugs, as well as possibly to implement in clinical practice. Ventricular expansion measured with DBM provides the lowest published estimated sample size for clinical trial design to detect significant differences over one and two years.

Ventricular volume expansion in presymptomatic genetic frontotemporal dementia

Objective

To characterize the time course of ventricular volume expansion in genetic frontotemporal dementia (FTD) and identify the onset time and rates of ventricular expansion in presymptomatic FTD mutation carriers.

Methods

Participants included patients with a mutation in MAPT, PGRN, or C9orf72, or first-degree relatives of mutation carriers from the GENFI study with MRI scans at study baseline and at 1 year follow-up. Ventricular volumes were obtained from MRI scans using FreeSurfer, with manual editing of segmentation and comparison to fully automated segmentation to establish reliability. Linear mixed models were used to identify differences in ventricular volume and in expansion rates as a function of time to expected disease onset between presymptomatic carriers and noncarriers.

Results

A total of 123 participants met the inclusion criteria and were included in the analysis (18 symptomatic carriers, 46 presymptomatic mutation carriers, and 56 noncarriers). Ventricular volume differences were observed 4 years prior to symptom disease onset for presymptomatic carriers compared to noncarriers. Annualized rates of ventricular volume expansion were greater in presymptomatic carriers relative to noncarriers. Importantly, time-intensive manually edited and fully automated ventricular volume resulted in similar findings.

Conclusions

Ventricular volume differences are detectable in presymptomatic genetic FTD. Concordance of results from time-intensive manual editing and fully automatic segmentation approaches support its value as a measure of disease onset and progression in future studies in both presymptomatic and symptomatic genetic FTD.

The "rights" of precision drug development for Alzheimer's disease

There is a high rate of failure in Alzheimer's disease (AD) drug development with 99% of trials showing no drug-placebo difference. This low rate of success delays new treatments for patients and discourages investment in AD drug development. Studies across drug development programs in multiple disorders have identified important strategies for decreasing the risk and increasing the likelihood of success in drug development programs. These experiences provide guidance for the optimization of AD drug development. The "rights" of AD drug development include the right target, right drug, right biomarker, right participant, and right trial. The right target identifies the appropriate biologic process for an AD therapeutic intervention. The right drug must have well-understood pharmacokinetic and pharmacodynamic features, ability to penetrate the blood-brain barrier, efficacy demonstrated in animals, maximum tolerated dose established in phase I, and acceptable toxicity. The right biomarkers include participant selection biomarkers, target engagement biomarkers, biomarkers supportive of disease modification, and biomarkers for side effect monitoring. The right participant hinges on the identification of the phase of AD (preclinical, prodromal, dementia). Severity of disease and drug mechanism both have a role in defining the right participant. The right trial is a well-conducted trial with appropriate clinical and biomarker outcomes collected over an appropriate period of time, powered to detect a clinically meaningful drug-placebo difference, and anticipating variability introduced by globalization. We lack understanding of some critical aspects of disease biology and drug action that may affect the success of development programs even when the "rights" are adhered to. Attention to disciplined drug development will increase the likelihood of success, decrease the risks associated with AD drug development, enhance the ability to attract investment, and make it more likely that new therapies will become available to those with or vulnerable to the emergence of AD.

Cognitive Profiles and Atrophy Ratings on MRI in Senior Patients With Mild Cognitive Impairment

In this cross-sectional study, we sought to describe cognitive and neuroimaging profiles of Memory clinic patients with Mild Cognitive Impairment (MCI). 51 MCI patients and 51 controls, matched on age, sex, and socio-economic status (SES), were assessed with an extensive neuropsychological test battery that included a measure of intelligence (General Ability Index, "GAI," from WAIS-IV), and structural magnetic resonance imaging (MRI). MCI subtypes were determined after inclusion, and z-scores normalized to our control group were generated for each cognitive domain in each MCI participant. MR-images were scored by visual rating scales. MCI patients performed significantly worse than controls on 23 of 31 cognitive measures (Bonferroni corrected p = 0.001), and on 8 of 31 measures after covarying for intelligence (GAI). Compared to nonamnestic MCI patients, amnestic MCI patients had lower test results in 13 of 31 measures, and 5 of 31 measures after co-varying for GAI. Compared to controls, the MCI patients had greater atrophy on Schelten's Medial temporal lobe atrophy score (MTA), especially in those with amnestic MCI. The only structure-function correlation that remained significant after correction for multiple comparisons was the MTA-long delay recall domain. Intelligence operationalized as GAI appears to be an important moderator of the neuropsychological outcomes. Atrophy of the medial temporal lobe, based on MTA scores, may be a sensitive biomarker for the functional episodic memory deficits associated with MCI.

Biological, Neuroimaging, and Neurophysiological Markers in Frontotemporal Dementia: Three Faces of the Same Coin

Frontotemporal dementia (FTD) is a heterogeneous clinical, genetic, and neuropathological disorder. Clinical diagnosis and prediction of neuropathological substrates are hampered by heterogeneous pictures. Diagnostic markers are key in clinical trials to differentiate FTD from other neurodegenerative dementias. In the same view, identifying the neuropathological hallmarks of the disease is key in light of future disease-modifying treatments. The aim of the present review is to unravel the progress in biomarker discovery, discussing the potential applications of available biological, imaging, and neurophysiological markers.

Advances in neuroimaging in frontotemporal dementia

Frontotemporal dementia (FTD) is a clinically and neuroanatomically heterogeneous neurodegenerative disorder with multiple underlying genetic and pathological causes. Whilst initial neuroimaging studies highlighted the presence of frontal and temporal lobe atrophy or hypometabolism as the unifying feature in patients with FTD, more detailed studies have revealed diverse patterns across individuals, with variable frontal or temporal predominance, differing degrees of asymmetry, and the involvement of other cortical areas including the insula and cingulate, as well as subcortical structures such as the basal ganglia and thalamus. Recent advances in novel imaging modalities including diffusion tensor imaging, resting-state functional magnetic resonance imaging and molecular positron emission tomography imaging allow the possibility of investigating alterations in structural and functional connectivity and the visualisation of pathological protein deposition. This review will cover the major imaging modalities currently used in research and clinical practice, focusing on the key insights they have provided into FTD, including the onset and evolution of pathological changes and also importantly their utility as biomarkers for disease detection and staging, differential diagnosis and measurement of disease progression. Validating neuroimaging biomarkers that are able to accomplish these tasks will be crucial for the ultimate goal of powering upcoming clinical trials by correctly stratifying patient enrolment and providing sensitive markers for evaluating the effects and efficacy of disease-modifying therapies. This review describes the key insights provided by research into the major neuroimaging modalities currently used in research and clinical practice, including what they tell us about the onset and evolution of FTD and how they may be used as biomarkers for disease detection and staging, differential diagnosis and measurement of disease progression. This article is part of the Frontotemporal Dementia special issue.

Different patterns of cortical gray matter loss over time in behavioral variant frontotemporal dementia and Alzheimer's disease

We examined patterns of cortical thickness loss and cognitive decline over time in 19 patients with Alzheimer's disease (AD), 10 with behavioral variant frontotemporal dementia (bvFTD), and 34 controls with a mean interval of 2.1 ± 0.4 years. We measured vertexwise and regional cortical thickness changes of 6 lobar regions of interest between groups with the longitudinal FreeSurfer pipeline. Compared with controls, AD and bvFTD had a steeper rate of cognitive decline and showed faster cortical thinning per year. Decrease of thickness over time was highest in AD and generalized throughout the whole brain, most pronounced posteriorly, whereas bvFTD patients had a more selective loss in frontal cortex and in anterior parts of the temporal lobes. In a direct comparison, AD patients showed faster cortical thinning in the insula, temporal, and parietal regions, whereas bvFTD patients only showed faster cortical thinning in the orbitofrontal gyrus. Decline of cognitive performances was in line with cortical thinning and deteriorated the most in AD patients.

Cerebral small vessel disease and Alzheimer's disease

Cerebral small vessel disease (CSVD) is a group of pathological processes with multifarious etiology and pathogenesis that are involved into the small arteries, arterioles, venules, and capillaries of the brain. CSVD mainly contains lacunar infarct or lacunar stroke, leukoaraiosis, Binswanger's disease, and cerebral microbleeds. CSVD is an important cerebral microvascular pathogenesis as it is the cause of 20% of strokes worldwide and the most common cause of cognitive impairment and dementia, including vascular dementia and Alzheimer's disease (AD). It has been well identified that CSVD contributes to the occurrence of AD. It seems that the treatment and prevention for cerebrovascular diseases with statins have such a role in the same function for AD. So far, there is no strong evidence-based medicine to support the idea, although increasing basic studies supported the fact that the treatment and prevention for cerebrovascular diseases will benefit AD. Furthermore, there is still lack of evidence in clinical application involved in specific drugs to benefit both AD and CSVD.

Comparative study of subcortical atrophy in patients with frontotemporal dementia and dementia with extrapyramidal signs

Objectives : To investigate the severity of subcortical atrophy in frontotemporal dementia (FTD) without extrapyramidal symptoms (EPS) and dementia with EPS. In addition, we aim to verify if there is correlation between demographic and clinical characteristics and subcortical atrophy in the groups. Methodology : The sample was composed of 21 patients with dementia and EPS as well as 19 patients with FTD without EPS. A linear assessment was conducted in order to identify the degree of subcortical atrophy (i.e., bifrontal index - BFI) using MRI. Moreover, the Mini-Mental State Examination (MMSE), Pfeffer Functional Activities Questionnaire (FAQ) and the Clinical Dementia Rating (CDR) were used to investigate clinical aspects. Results : It was verified that patients with dementia and EPS was older than the patients with FTD (p=0.01). The severity of cognitive deficits was associated with BFI, as well as the dementia severity in the EPS group. Conclusion : FTD group presented mean BFI scores above the cutoff for normal elderly population, indicating the presence of subcortical atrophy in this group. Mean BFI was higher (although not statistically significant) in FTD group than in dementia with EPS, which can suggest at least that subcortical pathology in FTD may be as important as in the dementia with EPS group. Subcortical atrophy is a good biological marker for cognitive deterioration in FTD and in dementia with EPS.

Three-Class Differential Diagnosis among Alzheimer Disease, Frontotemporal Dementia, and Controls

Biomarkers derived from brain magnetic resonance (MR) imaging have promise in being able to assist in the clinical diagnosis of brain pathologies. These have been used in many studies in which the goal has been to distinguish between pathologies such as Alzheimer's disease and healthy aging. However, other dementias, in particular, frontotemporal dementia, also present overlapping pathological brain morphometry patterns. Hence, a classifier that can discriminate morphometric features from a brain MRI from the three classes of normal aging, Alzheimer's disease (AD), and frontotemporal dementia (FTD) would offer considerable utility in aiding in correct group identification. Compared to the conventional use of multiple pair-wise binary classifiers that learn to discriminate between two classes at each stage, we propose a single three-way classification system that can discriminate between three classes at the same time. We present a novel classifier that is able to perform a three-class discrimination test for discriminating among AD, FTD, and normal controls (NC) using volumes, shape invariants, and local displacements (three features) of hippocampi and lateral ventricles (two structures times two hemispheres individually) obtained from brain MR images. In order to quantify its utility in correct discrimination, we optimize the three-class classifier on a training set and evaluate its performance using a separate test set. This is a novel, first-of-its-kind comparative study of multiple individual biomarkers in a three-class setting. Our results demonstrate that local atrophy features in lateral ventricles offer the potential to be a biomarker in discriminating among AD, FTD, and NC in a three-class setting for individual patient classification.

Automated measurement of cerebral cortical thickness based on fuzzy membership map derived from MR images for evaluation of Alzheimer's disease

We have proposed an automated method for three-dimensional (3D) measurement of cerebral cortical thicknesses based on fuzzy membership maps derived from magnetic resonance (MR) images for evaluation of Alzheimer's disease (AD). The cerebral cortical thickness was three-dimensionally measured on each cortical surface voxel by using a localized gradient vector trajectory in a fuzzy membership map. The proposed method could be useful for the 3D measurement of the cerebral cortical thickness on individual cortical surface voxels as an atrophy feature in AD.

Analysis of alternative splicing associated with aging and neurodegeneration in the human brain

Age is the most important risk factor for neurodegeneration; however, the effects of aging and neurodegeneration on gene expression in the human brain have most often been studied separately. Here, we analyzed changes in transcript levels and alternative splicing in the temporal cortex of individuals of different ages who were cognitively normal, affected by frontotemporal lobar degeneration (FTLD), or affected by Alzheimer's disease (AD). We identified age-related splicing changes in cognitively normal individuals and found that these were present also in 95% of individuals with FTLD or AD, independent of their age. These changes were consistent with increased polypyrimidine tract binding protein (PTB)-dependent splicing activity. We also identified disease-specific splicing changes that were present in individuals with FTLD or AD, but not in cognitively normal individuals. These changes were consistent with the decreased neuro-oncological ventral antigen (NOVA)-dependent splicing regulation, and the decreased nuclear abundance of NOVA proteins. As expected, a dramatic down-regulation of neuronal genes was associated with disease, whereas a modest down-regulation of glial and neuronal genes was associated with aging. Whereas our data indicated that the age-related splicing changes are regulated independently of transcript-level changes, these two regulatory mechanisms affected expression of genes with similar functions, including metabolism and DNA repair. In conclusion, the alternative splicing changes identified in this study provide a new link between aging and neurodegeneration.

Joint assessment of structural, perfusion, and diffusion MRI in Alzheimer's disease and frontotemporal dementia

Most MRI studies of Alzheimer's disease (AD) and frontotemporal dementia (FTD) have assessed structural, perfusion and diffusion abnormalities separately while ignoring the relationships across imaging modalities. This paper aimed to assess brain gray (GM) and white matter (WM) abnormalities jointly to elucidate differences in abnormal MRI patterns between the diseases. Twenty AD, 20 FTD patients, and 21 healthy control subjects were imaged using a 4 Tesla MRI. GM loss and GM hypoperfusion were measured using high-resolution T1 and arterial spin labeling MRI (ASL-MRI). WM degradation was measured with diffusion tensor imaging (DTI). Using a new analytical approach, the study found greater WM degenerations in FTD than AD at mild abnormality levels. Furthermore, the GM loss and WM degeneration exceeded the reduced perfusion in FTD whereas, in AD, structural and functional damages were similar. Joint assessments of multimodal MRI have potential value to provide new imaging markers for improved differential diagnoses between FTD and AD.

Neuroimaging findings in frontotemporal lobar degeneration spectrum of disorders

Frontotemporal lobar degeneration (FTLD) is a clinically and pathologically heterogeneous spectrum of disorders. In the last few years, neuroimaging has contributed to the phenotypic characterisation of these patients. Complementary to the clinical and neuropsychological evaluations, structural magnetic resonance imaging (MRI) and functional techniques provide important pieces of information for the diagnosis of FTLD. They also appear to be useful in distinguishing FTLD from patients with Alzheimer's disease (AD). Preliminary studies in pathologically proven cases suggested that distinct patterns of tissue loss could assist in predicting in vivo the pathological subtype. Recent years have also witnessed impressive advances in the development of novel imaging approaches. Diffusion tensor MRI and functional MRI have improved our understanding of the pathophysiology of the disease, and this should lead to the identification of additional useful markers of disease progression. This reviews discusses comprehensively the state-of-the-art of neuroimaging in the study of FTLD spectrum of disorders, and attempts to envisage which will be new neuroimaging biomarkers that could serve as surrogate measures of the underlying pathology. This will be central in the design of treatment trials of experimental drugs, which are likely to emerge in the near future, to target the pathological processes associated with this condition.

Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort

Atrophic changes in early Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI) have been proposed as biomarkers for detection and monitoring. We analyzed magnetic resonance imaging (MRI) atrophy rate from baseline to 1 year in 4 groups of participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI): AD (n = 152), converters from MCI to probable AD (MCI-C, n = 60), stable MCI (MCI-S, n = 261), and healthy controls (HC, n = 200). Scans were analyzed using multiple methods, including voxel-based morphometry (VBM), regions of interest (ROIs), and automated parcellation, permitting comparison of annual percent change (APC) in neurodegeneration markers. Effect sizes and the sample required to detect 25% reduction in atrophy rates were calculated. The influence of APOE genotype on APC was also evaluated. AD patients and converters from MCI to probable AD demonstrated high atrophy APCs across regions compared with minimal change in healthy controls. Stable MCI subjects showed intermediate atrophy rates. APOE genotype was associated with APC in key regions. In sum, APC rates are influenced by APOE genotype, imminent MCI to AD conversion, and AD-related neurodegeneration.

Predicting functional decline in behavioural variant frontotemporal dementia

Behavioural variant frontotemporal dementia is characterized by a change in comportment. It is associated with considerable functional decline over the course of the illness albeit with sometimes dramatic variability among patients. It is unknown whether any baseline features, or combination of features, could predict rate of functional decline in behavioural variant frontotemporal dementia. The aim of this study was to investigate the effects of different baseline clinical, neuropsychological, neuropsychiatric, genetic and anatomic predictors on the rate of functional decline as measured by the Clinical Dementia Rating Sum of Boxes scale. We identified 86 subjects with behavioural variant frontotemporal dementia that had multiple serial Clinical Dementia Rating Sum of Boxes assessments (mean 4, range 2-18). Atlas-based parcellation was used to generate volumes for specific regions of interest at baseline. Volumes were utilized to classify subjects into different anatomical subtypes using the advanced statistical technique of cluster analysis and were assessed as predictor variables. Composite scores were generated for the neuropsychological domains of executive, language, memory and visuospatial function. Behaviours from the brief questionnaire form of the Neuropsychiatric Inventory were assessed. Linear mixed-effects regression modelling was used to determine which baseline features predict rate of future functional decline. Rates of functional decline differed across the anatomical subtypes of behavioural variant frontotemporal dementia, with faster rates observed in the frontal dominant and frontotemporal subtypes. In addition, subjects with poorer performance on neuropsychological tests of executive, language and visuospatial function, less disinhibition, agitation/aggression and night-time behaviours at presentation, and smaller medial, lateral and orbital frontal lobe volumes showed faster rates of decline. In many instances, the effect of the predictor variables observed across all subjects was also preserved within anatomical subtypes. Furthermore, some of the predictor variables improved our prediction of rate of functional decline after anatomical subtype was taken into account. In particular, age at onset was a highly significant predictor but only after adjusting for subtype. We also found that although some predictor variables, for example gender, Mini-Mental State Examination score, and apathy/indifference, did not affect the rate of functional decline; these variables were associated with the actual Clinical Dementia Rating Sum of Boxes score estimated for any given time-point. These findings suggest that in behavioural variant frontotemporal dementia, rate of functional decline is driven by the combination of anatomical pattern of atrophy, age at onset, and neuropsychiatric characteristics of the subject at baseline.

Assessing subtle structural changes in Alzheimer's disease patients

Magnetic resonance imaging (MRI) allows the assessment of structural changes in subjects with Alzheimer's disease (AD). Early studies used visual assessments of MRI or manual measurements of structures of interest, although these methods were limited by inter-rater variability. Techniques have now been developed which allow automated analysis of both cross-sectional and longitudinal MRI data and have provided valuable information concerning the patterns and progression of atrophy in subjects with AD. It is also now possible using machine learning-based techniques to provide individual-level diagnostic information from MRI scans. Various analysis techniques have been applied to validate the use of MRI to capture subtle structural changes due to atrophy in AD and its usefulness in providing diagnostic and prognostic information, as well as tracking the disease progression in AD.

Differential pharmacological responses of catatonia-like signs in frontotemporal dementia

Sequential therapeutic trials for catatonoid frontal signs in clinically-evident frontotemporal dementia (n = 2) revealed differential benefits for lorazepam, amantadine, memantine, pramipexole, aripiprazole, quetiapine, citalopram, and donepezil, although certain signs also worsened. Citalopram and donepezil were poorly tolerated. Ramelteon was without effect. While memantine appeared to improve cognition in case 1, this remains to be established by more reliable neuropsychological testing. Parkinsonism (case 2) responded to pramipexole, but not amantadine or levodopa. Possible relationships of catatonoid signs requiring future confirmation include insufficient GABA-A (multiple signs) and D2 (mutism) and excessive NMDA (immobility, rigidity), D2/D3 (mannerisms, verbal perseveration), and 5HT1a (staring) receptor stimulation. Low-dose lorazepam and quetiapine required close monitoring.

Distinct cerebral perfusion patterns in FTLD and AD

OBJECTIVE

We examined the utility of distinguishing between patients with frontotemporal lobar degeneration (FTLD) and Alzheimer disease (AD) using quantitative cerebral blood flow (CBF) imaging with arterial spin labeled (ASL) perfusion MRI.

METHODS

Forty-two patients with FTLD and 18 patients with AD, defined by autopsy or CSF-derived biomarkers for AD, and 23 matched controls were imaged with a continuous ASL method to quantify CBF maps covering the entire brain.

RESULTS

Patients with FTLD and AD showed distinct patterns of hypoperfusion and hyperperfusion. Compared with controls, patients with FTLD showed significant hypoperfusion in regions of the frontal lobe bilaterally, and hyperperfusion in posterior cingulate and medial parietal/precuneus regions. Compared with controls, patients with AD showed significant hypoperfusion in the medial parietal/precuneus and lateral parietal cortex, and hyperperfusion in regions of the frontal lobe. Direct comparison of patient groups showed significant inferior, medial, and dorsolateral frontal hypoperfusion in FTLD, and significant hypoperfusion in bilateral lateral temporal-parietal and medial parietal/precuneus regions in AD.

CONCLUSIONS

Doubly dissociated areas of hypoperfusion in FTLD and AD are consistent with areas of significant histopathologic burden in these groups. ASL is a potentially useful biomarker for distinguishing patients with these neurodegenerative diseases.

Longitudinal rates of lobar atrophy in frontotemporal dementia, semantic dementia, and Alzheimer's disease

This study compared rates of regional atrophy in Alzheimer disease (AD), frontotemporal dementia (FTD), and semantic dementia (SD). Cross-sectional studies have shown that different dementia syndromes are associated with different patterns of regional brain tissue loss. Rates of atrophy over time may be useful for differential diagnosis, and could be used to monitor disease progression, serving as an outcome measure for clinical trials. We studied patients with AD (n=12), FTD (n=13), SD (n=20), and normal controls (n=23) longitudinally with structural magnetic resonance imaging, using BRAINS2 software to measure frontal, temporal, and parietal lobe volumes. In FTD the rate of frontal lobe atrophy over 1 year was greater than in any other group, whereas SD showed the highest rate in the temporal lobes. Atrophy in these regions progressed twice as quickly in FTD and SD compared with AD. Atrophy was not significantly faster for AD in any brain region compared with the other groups. Regional atrophy over time was significantly faster in FTD and SD compared with AD, and the regions of greatest atrophy were specific for each syndrome. Measuring specific regions of cerebral volume changes by serial neuroimaging may serve as a useful biomarker outcome measure for clinical trials in neurodegenerative diseases.

Progression of atrophy in Alzheimer's disease and related disorders

Longitudinal MRI is a powerful tool that allows the assessment of progression of brain changes over multiple imaging time-points and has been increasingly employed in the study of neurodegenerative dementias, particularly Alzheimer's disease (AD). Early studies demonstrated that AD was associated with increased rates of whole brain loss and hippocampal atrophy. A number of sophisticated voxel-level techniques have now been developed that have provided additional information describing regional atrophy over time in the temporal, parietal, and frontal lobes in AD. Studies have also focused on subjects in the prodromal phase of AD in order to describe the earliest changes that are occurring in the brain. Atrophy has been shown to start in the medial temporal lobes and fusiform gyrus at least 3 years before subjects reach a diagnosis of AD, and then spread to the posterior temporal lobes and parietal lobes, and then eventually the frontal lobes. These patterns of atrophy correlate well with the progression of neurofibrillary tangles observed on pathology. Rates of atrophy have also been shown to accelerate over the course of the disease as a subject progresses from cognitively normal to a diagnosis of AD. Similar techniques have also been applied to other neurodegenerative diseases, such as frontotemporal dementia which show higher rates of atrophy and different patterns of progression to those observed in AD. Hence, longitudinal MRI shows promise as a biomarker of disease progression in neurodegenerative disease.

Modeling and Estimating Recall Processing Capacity: Sensitivity and Diagnostic Utility in Application to Mild Cognitive Impairment

We investigate the potential for using latency-based measures of retrieval processing capacity to assess changes in perfomance specific to individuals with mild cognitive impairment (MCI), a reliable precursor state to Alzheimer's Disease. Use of these capacity measures is motivated in part by exploration of the effects of atrophy on a computational model of a basic hippocampal circuit. We use this model to suggest that capacity may be a more sensitive indicator of undelying atrophy than speed of processing, and test this hypothesis by adapting a standard behavioral measure of memory (the free and cued selective reminding test, FCSRT) to allow for the collection of cued recall latencies. Participants were drawn from five groups: college-aged, middle-aged, healthy elderly, those with a diagnosis of MCI, and a sample of MCI control participants. The measure of capacity is shown to offer increased classificatory sensitivity relative to the standard behavioral measures, and is also shown to be the behavioral measure that correlated most strongly with hippocampal volume.

Dementia induces correlated reductions in white matter integrity and cortical thickness: a multivariate neuroimaging study with sparse canonical correlation analysis

We use a new, unsupervised multivariate imaging and analysis strategy to identify related patterns of reduced white matter integrity, measured with the fractional anisotropy (FA) derived from diffusion tensor imaging (DTI), and decreases in cortical thickness, measured by high resolution T1-weighted imaging, in Alzheimer's disease (AD) and frontotemporal dementia (FTD). This process is based on a novel computational model derived from sparse canonical correlation analysis (SCCA) that allows us to automatically identify mutually predictive, distributed neuroanatomical regions from different imaging modalities. We apply the SCCA model to a dataset that includes 23 control subjects that are demographically matched to 49 subjects with autopsy or CSF-biomarker-diagnosed AD (n=24) and FTD (n=25) with both DTI and T1-weighted structural imaging. SCCA shows that the FTD-related frontal and temporal degeneration pattern is correlated across modalities with permutation corrected p<0.0005. In AD, we find significant association between cortical thinning and reduction in white matter integrity within a distributed parietal and temporal network (p<0.0005). Furthermore, we show that-within SCCA identified regions-significant differences exist between FTD and AD cortical-connective degeneration patterns. We validate these distinct, multimodal imaging patterns by showing unique relationships with cognitive measures in AD and FTD. We conclude that SCCA is a potentially valuable approach in image analysis that can be applied productively to distinguishing between neurodegenerative conditions.

Sparse unbiased analysis of anatomical variance in longitudinal imaging

We present a new algorithm for reliable, unbiased, multivariate longitudinal analysis of cortical and white matter atrophy rates with penalized statistical methods. The pipeline uses a step-wise approach to transform and personalize template information first to a single-subject template (SST) and then to the individual's time series data. The first stream of information flows from group template to the SST; the second flows from the SST to the individual time-points and provides unbiased, prior-based segmentation and measurement of cortical thickness. MRI-bias correction, consistent longitudinal segmentation, cortical parcellation and cortical thickness estimation are all based on strong use of the subject-specific priors built from initial diffeomorphic mapping between the SST and optimal group template. We evaluate our approach with both test-retest data and with application to a driving biological problem. We use test-retest data to show that this approach produces (a) zero change when the retest data contains the same image content as the test data and (b) produces normally distributed, low variance estimates of thickness change centered at zero when test-retest data is collected near in time to test data. We also show that our approach--when combined with sparse canonical correlation analysis--reveals plausible, significant, annualized decline in cortical thickness and white matter volume when contrasting frontotemporal dementia and normal aging.

Brain and ventricular volumetric changes in frontotemporal lobar degeneration over 1 year

BACKGROUND

Measurement of volumetric changes with MR might be a useful surrogate endpoint for clinical trials in frontotemporal lobar degeneration (FTLD). Because there is only limited longitudinal imaging data currently available, we measured the rate of change over 1 year of whole brain volume (WBV) and ventricular volume (VV) in patients with FTLD.

METHODS

Subjects with an FTLD cognitive syndrome were recruited from five centers using standard clinical diagnostic criteria for behavioral variant frontotemporal dementia (bvFTD), progressive nonfluent aphasia (PNFA), semantic dementia (SMD), and progressive logopenic aphasia. Structural brain imaging, using three-dimensional T1-weighted sequences at 1.5 teslas, and cognitive, behavioral, and functional assessments were performed at baseline and approximately 1 year later. The boundary shift integral algorithm was used to determine change in WBV and VV.

RESULTS

There were 76 patients (mean age 64 years; 41 men and 35 women) who had usable baseline and annual scans. The group-wise annualized change was -1.62% (SD 1.03, range +0.69 to -3.6) for WBV and 11.6% (SD 5.9, range -1.3 to 23.9) for VV. Rates of change were similar among bvFTD, PNFA, and SMD groups. Longitudinal changes in WBV and VV were correlated with decline on clinical global and cognitive measures.

CONCLUSIONS

Multicenter, serial measurements of whole brain volume (WBV) and ventricular volume (VV) from magnetic resonance scans were feasible in patients with frontotemporal lobar degeneration (FTLD). Using WBV or VV as outcome measures would require recruiting (at 80% power) 139 or 55 subjects per group to detect a small (25%) or medium-sized (40%) effect in a randomized, placebo-controlled trial of a putative agent for FTLD.

Longitudinal imaging: change and causality

PURPOSE OF REVIEW

Longitudinal studies that use MRI scans performed over multiple time-points have been increasingly employed in the study of different neurological disorders, including degenerative dementia, multiple sclerosis, and epilepsy.

RECENT FINDINGS

Although it is well established that increased rates of brain atrophy occur in degenerative dementia and multiple sclerosis, recent data have further described these changes and demonstrated that they correlate with both cognitive and functional decline. Advanced voxel-level techniques have also provided detailed descriptions of regional patterns of change, and a few studies have started to investigate changes over multiple MRI enabling the trajectories of brain loss over time to be determined. Researchers have also started to more thoroughly investigate the underlying causes of brain atrophy. Correlations have been observed between rate of brain atrophy and the presence of abnormal protein deposits in the brain in dementia, and the lesion burden in multiple sclerosis. However, longitudinal studies on epilepsy have been inconsistent, with very little recent data.

SUMMARY

Recent data further support the suggestion that longitudinal MRI provides a good biomarker of disease progression in dementia and multiple sclerosis, though more work needs to be performed to define the role of longitudinal imaging in epilepsy.