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

Neuroimaging in Dementia

OBJECTIVE

Neurodegenerative diseases are significant health concerns with regard to morbidity and social and economic hardship around the world. This review describes the state of the field of neuroimaging measures as biomarkers for detection and diagnosis of both slowly progressing and rapidly progressing neurodegenerative diseases, specifically Alzheimer disease, vascular cognitive impairment, dementia with Lewy bodies or Parkinson disease dementia, frontotemporal lobar degeneration spectrum disorders, and prion-related diseases. It briefly discusses findings in these diseases in studies using MRI and metabolic and molecular-based imaging (eg, positron emission tomography [PET] and single-photon emission computerized tomography [SPECT]).

LATEST DEVELOPMENTS

Neuroimaging studies with MRI and PET have demonstrated differential patterns of brain atrophy and hypometabolism in different neurodegenerative disorders, which can be useful in differential diagnoses. Advanced MRI sequences, such as diffusion-based imaging, and functional MRI (fMRI) provide important information about underlying biological changes in dementia and new directions for development of novel measures for future clinical use. Finally, advancements in molecular imaging allow clinicians and researchers to visualize dementia-related proteinopathies and neurotransmitter levels.

ESSENTIAL POINTS

Diagnosis of neurodegenerative diseases is primarily based on symptomatology, although the development of in vivo neuroimaging and fluid biomarkers is changing the scope of clinical diagnosis, as well as the research into these devastating diseases. This article will help inform the reader about the current state of neuroimaging in neurodegenerative diseases, as well as how these tools might be used for differential diagnoses.

The Neurodegenerative Elderly Syndrome (NES) hypothesis: Alzheimer and Parkinson are two faces of the same disease

Increasing evidence suggests that Alzheimer's disease (AD) and Parkinson's disease (PD) share monoamine and alpha-synuclein (αSyn) dysfunctions, often beginning years before clinical manifestations onset. The triggers for these impairments and the causes leading these early neurodegenerative processes to become AD or PD remain unclear. We address these issues by proposing a radically new perspective to frame AD and PD: they are different manifestations of one only disease we call "Neurodegenerative Elderly Syndrome (NES)". NES goes through three phases. The seeding stage, which starts years before clinical signs, and where the part of the brain-body affected by the initial αSyn and monoamine dysfunctions, influences the future possible progression of NES towards PD or AD. The compensatory stage, where the clinical symptoms are still silent thanks to compensatory mechanisms keeping monoamine concentrations homeostasis. The bifurcation stage, where NES becomes AD or PD. We present recent literature supporting NES and discuss how this hypothesis could radically change the comprehension of AD and PD comorbidities and the design of novel system-level diagnostic and therapeutic actions.

Genuine high-order interactions in brain networks and neurodegeneration

Brain functional networks have been traditionally studied considering only interactions between pairs of regions, neglecting the richer information encoded in higher orders of interactions. In consequence, most of the connectivity studies in neurodegeneration and dementia use standard pairwise metrics. Here, we developed a genuine high-order functional connectivity (HOFC) approach that captures interactions between 3 or more regions across spatiotemporal scales, delivering a more biologically plausible characterization of the pathophysiology of neurodegeneration. We applied HOFC to multimodal (electroencephalography [EEG], and functional magnetic resonance imaging [fMRI]) data from patients diagnosed with behavioral variant of frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and healthy controls. HOFC revealed large effect sizes, which, in comparison to standard pairwise metrics, provided a more accurate and parsimonious characterization of neurodegeneration. The multimodal characterization of neurodegeneration revealed hypo and hyperconnectivity on medium to large-scale brain networks, with a larger contribution of the former. Regions as the amygdala, the insula, and frontal gyrus were associated with both effects, suggesting potential compensatory processes in hub regions. fMRI revealed hypoconnectivity in AD between regions of the default mode, salience, visual, and auditory networks, while in bvFTD between regions of the default mode, salience, and somatomotor networks. EEG revealed hypoconnectivity in the γ band between frontal, limbic, and sensory regions in AD, and in the δ band between frontal, temporal, parietal and posterior areas in bvFTD, suggesting additional pathophysiological processes that fMRI alone can not capture. Classification accuracy was comparable with standard biomarkers and robust against confounders such as sample size, age, education, and motor artifacts (from fMRI and EEG). We conclude that high-order interactions provide a detailed, EEG- and fMRI compatible, biologically plausible, and psychopathological-specific characterization of different neurodegenerative conditions.

The changing landscape of neuroimaging in frontotemporal lobar degeneration: from group-level observations to single-subject data interpretation

INTRODUCTION

While the imaging signatures of frontotemporal lobar degeneration (FTLD) phenotypes and genotypes are well-characterised based on group-level descriptive analyses, the meaningful interpretation of single MRI scans remains challenging. Single-subject MRI classification frameworks rely on complex computational models and large training datasets to categorise individual patients into diagnostic subgroups based on distinguishing imaging features. Reliable individual subject data interpretation is hugely important in the clinical setting to expedite the diagnosis and classify individuals into relevant prognostic categories.

AREAS COVERED

This article reviews (1) the neuroimaging studies that propose single-subject MRI classification strategies in symptomatic and pre-symptomatic FTLD, (2) potential practical implications and (3) the limitations of current single-subject data interpretation models.

EXPERT OPINION

Classification studies in FTLD have demonstrated the feasibility of categorising individual subjects into diagnostic groups based on multiparametric imaging data. Preliminary data indicate that pre-symptomatic FTLD mutation carriers may also be reliably distinguished from controls. Despite momentous advances in the field, significant further improvements are needed before these models can be developed into viable clinical applications.

Altered Homotopic Functional Connectivity Within White Matter in the Early Stages of Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with memory loss and cognitive impairment. The white matter (WM) BOLD signal has recently been shown to provide an important role in understanding the intrinsic cerebral activity. Although the altered homotopic functional connectivity within gray matter (GM-HFC) has been examined in AD, the abnormal HFC to WM remains unknown. The present study sought to identify changes in the WM-HFC and anatomic characteristics by combining functional magnetic resonance imaging with diffusion tensor imaging (DTI). Resting-state and DTI magnetic resonance images were collected from the OASIS-3 dataset and consisted of 53 mild cognitive impairment (MCI) patients, 90 very MCI (VMCI), and 100 normal cognitive (NC) subjects. Voxel-mirrored HFC was adopted to examine whether WM-HFC was disrupted in VMCI and MCI participants. Moreover, the DTI technique was used to investigate whether specific alterations of WM-HFC were associated with anatomic characteristics. Support vector machine analyses were used to identify the MCI and VMCI participants using the abnormal WM-HFC as the features. Compared with NC, MCI, and VMCI participants showed significantly decreased GM-HFC in the middle occipital gyrus and inferior parietal gyrus and decreased WM-HFC in the bilateral middle occipital and parietal lobe-WM. In addition, specific WM-functional network alteration for the bilateral sub-lobar-WM was found in MCI subjects. MCI subjects showed abnormal anatomic characteristics for bilateral sub-lobar and parietal lobe-WM. Results of GM-HFC mainly showed common neuroimaging features for VMCI and MCI subjects, whereas analysis of WM-HFC showed specific clinical neuromarkers and effectively compensated for the lack of GM-HFC to distinguish NC, VMCI, and MCI subjects.

Pain processing in older adults with dementia-related cognitive impairment is associated with frontal neurodegeneration

Experimental pain research has shown that pain processing seems to be heightened in dementia. It is unclear which neuropathological changes underlie these alterations. This study examined whether differences in pressure pain sensitivity and endogenous pain inhibition (conditioned pain modulation (CPM)) between individuals with a dementia-related cognitive impairment (N=23) and healthy controls (N=35) are linked to dementia-related neurodegeneration. Pain was assessed via self-report ratings and by analyzing the facial expression of pain using the Facial Action Coding System. We found that cognitively impaired individuals show decreased CPM inhibition as assessed by facial responses compared to healthy controls, which was mediated by decreased gray matter volume in the medial orbitofrontal and anterior cingulate cortex in the patient group. This study confirms previous findings of intensified pain processing in dementia when pain is assessed using non-verbal responses. Our findings suggest that a loss of pain inhibitory functioning caused by structural changes in prefrontal areas might be one of the underlying mechanisms responsible for amplified pain responses in individuals with a dementia-related cognitive impairment.

Uncovering the prevalence and neural substrates of anhedonia in frontotemporal dementia

Much of human behaviour is motivated by the drive to experience pleasure. The capacity to envisage pleasurable outcomes and to engage in goal-directed behaviour to secure these outcomes depends upon the integrity of frontostriatal circuits in the brain. Anhedonia refers to the diminished ability to experience, and to pursue, pleasurable outcomes, and represents a prominent motivational disturbance in neuropsychiatric disorders. Despite increasing evidence of motivational disturbances in frontotemporal dementia (FTD), no study to date has explored the hedonic experience in these syndromes. Here, we present the first study to document the prevalence and neural correlates of anhedonia in FTD in comparison with Alzheimer's disease, and its potential overlap with related motivational symptoms including apathy and depression. A total of 172 participants were recruited, including 87 FTD, 34 Alzheimer's disease, and 51 healthy older control participants. Within the FTD group, 55 cases were diagnosed with clinically probable behavioural variant FTD, 24 presented with semantic dementia, and eight cases had progressive non-fluent aphasia (PNFA). Premorbid and current anhedonia was measured using the Snaith-Hamilton Pleasure Scale, while apathy was assessed using the Dimensional Apathy Scale, and depression was indexed via the Depression, Anxiety and Stress Scale. Whole-brain voxel-based morphometry analysis was used to examine associations between grey matter atrophy and levels of anhedonia, apathy, and depression in patients. Relative to controls, behavioural variant FTD and semantic dementia, but not PNFA or Alzheimer's disease, patients showed clinically significant anhedonia, representing a clear departure from pre-morbid levels. Voxel-based morphometry analyses revealed that anhedonia was associated with atrophy in an extended frontostriatal network including orbitofrontal and medial prefrontal, paracingulate and insular cortices, as well as the putamen. Although correlated on the behavioural level, the neural correlates of anhedonia were largely dissociable from that of apathy, with only a small region of overlap detected in the right orbitofrontal cortices whilst no overlapping regions were found between anhedonia and depression. This is the first study, to our knowledge, to demonstrate profound anhedonia in FTD syndromes, reflecting atrophy of predominantly frontostriatal brain regions specialized for hedonic tone. Our findings point to the importance of considering anhedonia as a primary presenting feature of behavioural variant FTD and semantic dementia, with distinct neural drivers to that of apathy or depression. Future studies will be essential to address the impact of anhedonia on everyday activities, and to inform the development of targeted interventions to improve quality of life in patients and their families.

Neuroimaging in Frontotemporal Lobar Degeneration: Research and Clinical Utility

Frontotemporal lobar dementia (FTLD) is a clinically and pathologically complex disease. Advances in neuroimaging techniques have provided a specialized set of tools to investigate underlying pathophysiology and identify clinical biomarkers that aid in diagnosis, prognostication, monitoring, and identification of appropriate endpoints in clinical trials. In this chapter, we review data discussing the utility of neuroimaging biomarkers in sporadic FTLD, with an emphasis on current and future clinical applications. Among those modalities readily utilized in clinical settings, T1-weighted structural magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) are best supported in differential diagnosis and as targets for clinical trial endpoints. However, a number of nonclinical neuroimaging modalities, including diffusion tensor imaging and resting-state functional connectivity MRI, show promise as biomarkers to predict progression and as clinical trial endpoints. Other neuroimaging modalities, including amyloid PET, Tau PET, and arterial spin labeling MRI, are also discussed, though more work is required to establish their utility in FTLD in clinical settings.

Cross-sectional and longitudinal medial temporal lobe subregional atrophy patterns in semantic variant primary progressive aphasia

T1-magnetic resonance imaging (MRI) studies report early atrophy in the left anterior temporal lobe, especially the perirhinal cortex, in semantic variant primary progressive aphasia (svPPA). Improved segmentation protocols using high-resolution T2-MRI have enabled fine-grained medial temporal lobe (MTL) subregional measurements, which may provide novel information on the atrophy pattern and disease progression in svPPA. We aimed to investigate the MTL subregional atrophy pattern cross-sectionally and longitudinally in patients with svPPA as compared with controls and patients with Alzheimer's disease (AD). MTL subregional volumes were obtained using the Automated Segmentation for Hippocampal Subfields software from high-resolution T2-MRIs in 15 svPPA, 37 AD, and 23 healthy controls. All MTL volumes were corrected for intracranial volume and parahippocampal cortices for slice number. Longitudinal atrophy rates of all subregions were obtained using an unbiased deformation-based morphometry pipeline in 6 svPPA patients, 9 controls, and 12 AD patients. Cross-sectionally, significant volume loss was observed in svPPA compared with controls in the left MTL, right cornu ammonis 1 (CA1), Brodmann area (BA)35, and BA36 (subdivisions of the perirhinal cortex). Compared with AD patients, svPPA patients had significantly smaller left CA1, BA35, and left and right BA36 volumes. Longitudinally, svPPA patients had significantly greater atrophy rates of left and right BA36 than controls but not relative to AD patients. Fine-grained analysis of MTL atrophy patterns provides information about the evolution of atrophy in svPPA. These results indicate that MTL subregional measures might be useful markers to track disease progression or for clinical trials in svPPA.

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.

Quantitative and qualitative features of executive dysfunction in frontotemporal and Alzheimer's dementia

Behavioral variant fronto-temporal degeneration (bvFTD) is typically distinguished from Alzheimer's disease (AD) by early, prominent dysexecutive findings, in addition to other clinical features. However, differences in executive functioning between these groups are not consistently found. The current study sought to investigate quantitative and qualitative differences in executive functioning between those with bvFTD and AD in a large sample, while controlling for dementia severity and demographic variables. Secondary data analyses were completed on a subset of cases from the National Alzheimer's Coordinating Center collected from 36 Alzheimer's Disease Research Centers and consisting of 1,577 individuals with AD and 406 individuals with bvFTD. Groups were compared on 1) ability to complete three commonly administered executive tasks (letter fluency, Trail Making Test Part B [TMTB], and digits backward); 2) quantitative test performance; and 3) errors on these tasks. Findings suggested that individuals with bvFTD were less likely to complete letter fluency, χ²(2) = 178.62, p < .001, and number span tasks, χ²(1) = 11.49, p < .001), whereas individuals with AD were less likely to complete TMTB, χ²(2) = 460.38, p < .001. Individuals with bvFTD performed more poorly on letter fluency, F(1) = 28.06, p = .013, but there were not group differences in TMTB lines per second or number span backwards. Errors generally did not differentiate the diagnostic groups. In summary, there is substantial overlap in executive dysfunction between those with bvFTD and AD, though individuals with bvFTD tend to demonstrate worse letter fluency performance.

FTD spectrum: Neuroimaging across the FTD spectrum

Frontotemporal dementia is a complex and heterogeneous neurodegenerative disease that encompasses many clinical syndromes, pathological diseases, and genetic mutations. Neuroimaging has played a critical role in our understanding of the underlying pathophysiology of frontotemporal dementia and provided biomarkers to aid diagnosis. Early studies defined patterns of neurodegeneration and hypometabolism associated with the clinical, pathological and genetic aspects of frontotemporal dementia, with more recent studies highlighting how the breakdown of structural and functional brain networks define frontotemporal dementia. Molecular positron emission tomography ligands allowing the in vivo imaging of tau proteins have also provided important insights, although more work is needed to understand the biology of the currently available ligands.

Gray and white matter changes in presymptomatic genetic frontotemporal dementia: a longitudinal MRI study

In genetic frontotemporal dementia, cross-sectional studies have identified profiles of presymptomatic neuroanatomical loss for C9orf72 repeat expansion, MAPT, and GRN mutations. In this study, we characterize longitudinal gray matter (GM) and white matter (WM) brain changes in presymptomatic frontotemporal dementia. We included healthy carriers of C9orf72 repeat expansion (n = 12), MAPT (n = 15), GRN (n = 33) mutations, and related noncarriers (n = 53), that underwent magnetic resonance imaging at baseline and 2-year follow-up. We analyzed cross-sectional baseline, follow-up, and longitudinal GM and WM changes using voxel-based morphometry and cortical thickness analysis in SPM and tract-based spatial statistics in FSL. Compared with noncarriers, C9orf72 repeat expansion carriers showed lower GM volume in the cerebellum and insula, and WM differences in the anterior thalamic radiation, at baseline and follow-up. MAPT mutation carriers showed emerging GM temporal lobe changes and longitudinal WM degeneration of the uncinate fasciculus. GRN mutation carriers did not show presymptomatic neurodegeneration. This study shows distinct presymptomatic cross-sectional and longitudinal patterns of GM and WM changes across C9orf72 repeat expansion, MAPT, and GRN mutation carriers compared with noncarriers.

Frontotemporal dementia

Frontotemporal dementia (FTD) is the second commonest cause of young onset dementia. Our understanding of FTD and its related syndromes has advanced significantly in recent years. Among the most prominent areas of progress is the overlap between FTD, MND, and other neurodegenerative conditions at a clinicopathologic and genetic level. In parallel major advances in neuroimaging techniques, the discovery of new genetic mutations as well as the development of potential biomarkers may serve to further expand knowledge of the biologic processes at play in FTD and may in turn propel research toward identifying curative and preventative pharmacologic therapies. The aim of this chapter is to discuss the clinical, pathologic, and genetic complexities of FTD and related disorders.

Neuroimaging in aging and neurologic diseases

Neuroimaging biomarkers for neurologic diseases are important tools, both for understanding pathology associated with cognitive and clinical symptoms and for differential diagnosis. This chapter explores neuroimaging measures, including structural and functional measures from magnetic resonance imaging (MRI) and molecular measures primarily from positron emission tomography (PET), in healthy aging adults and in a number of neurologic diseases. The spectrum covers neuroimaging measures from normal aging to a variety of dementias: late-onset Alzheimer's disease [AD; including mild cognitive impairment (MCI)], familial and nonfamilial early-onset AD, atypical AD syndromes, posterior cortical atrophy (PCA), logopenic aphasia (lvPPA), cerebral amyloid angiopathy (CAA), vascular dementia (VaD), sporadic and familial behavioral-variant frontotemporal dementia (bvFTD), semantic dementia (SD), progressive nonfluent aphasia (PNFA), frontotemporal dementia with motor neuron disease (FTD-MND), frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS), corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with and without dementia, and multiple systems atrophy (MSA). We also include a discussion of the appropriate use criteria (AUC) for amyloid imaging and conclude with a discussion of differential diagnosis of neurologic dementia disorders in the context of neuroimaging.

A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers

Alzheimer’s disease (AD) is a progressive and fatal neurodegenerative disease, with no effective treatment or cure. A gold standard therapy would be treatment to slow or halt disease progression; however, knowledge of causation in the early stages of AD is very limited. In order to determine effective endpoints for possible therapies, a number of quantitative surrogate markers of disease progression have been suggested, including biochemical and imaging biomarkers. The dynamics of these various surrogate markers over time, particularly in relation to disease development, are, however, not well characterized. We reviewed the literature for studies that measured cerebrospinal fluid or plasma amyloid-β and tau, or took magnetic resonance image or fluorodeoxyglucose/Pittsburgh compound B-positron electron tomography scans, in longitudinal cohort studies. We summarized the properties of the major cohort studies in various countries, commonly used diagnosis methods and study designs. We have concluded that additional studies with repeat measures over time in a representative population cohort are needed to address the gap in knowledge of AD progression. Based on our analysis, we suggest directions in which research could move in order to advance our understanding of this complex disease, including repeat biomarker measurements, standardization and increased sample sizes.

Recommandations de Swiss Memory Clinics pour le diagnostic des démences

Résumé. Le diagnostic précoce des atteintes cognitives, ressenties subjectivement ou rapportées par un tiers, est essentiel pour détecter des maladies neurodégénératives ou exclure des causes traitables telles que des pathologies de médecine interne, neurologiques ou psychiatriques. C’est la seule façon de garantir un traitement anticipé. Dans le cadre du projet 3.1 de la stratégie nationale en matière de démences 2014–2019 («Mise en place et extension d’un réseau de centres de compétences régionaux pour le diagnostic»), l’association Swiss Memory Clinics (SMC) s’est fixé pour objectif d’améliorer les normes de qualité en matière de diagnostic des démences et de soins de proximité dans ce domaine. Ces recommandations contiennent des directives d’ordre général sur le diagnostic et les différentes possibilités d’examens, et proposent des normes pour les procédures à appliquer. Elles expliquent en détail les différents éléments du diagnostic standard, tels que l’anamnèse, l’examen clinique, l’analyse de laboratoire, les tests neuropsychologiques et les procédures neuroradiologiques, et présentent des examens complémentaires pouvant alimenter les réflexions sur le diagnostic différentiel. Les principaux objectifs des recommandations SMC pour le diagnostic des démences sont les suivants: assurer l’accès à un diagnostic de haute qualité à un maximum de personnes atteintes, améliorer le diagnostic précoce de la démence, ainsi que proposer aux médecins de premier recours et aux collaborateurs de Memory Clinics un outil d’investigations diagnostiques utile.

Die Empfehlungen der Swiss Memory Clinics für die Diagnostik der Demenzerkrankungen

Zusammenfassung. Die Frühdiagnostik subjektiv wahrgenommener oder fremdanamnestisch beobachteter kognitiver Beeinträchtigungen ist essenziell, um neurodegenerative Erkrankungen nachzuweisen oder behandelbare Ursachen wie internistische, neurologische oder psychiatrische Störungen auszuschliessen. Nur dadurch wird eine frühzeitige Behandlung ermöglicht. Im Rahmen des Projekts 3.1 der Nationalen Demenzstrategie 2014–2019 («Auf- und Ausbau regionaler und vernetzter Kompetenzzentren für die Diagnostik») hat sich der Verein Swiss Memory Clinics (SMC) zum Ziel gesetzt, Qualitätsstandards für die Demenzabklärung zu entwickeln und die wohnortsnahe Versorgung in diesem Bereich zu verbessern. In den vorliegenden Empfehlungen werden allgemeine Richtlinien der Diagnostik und einzelne Untersuchungsmöglichkeiten vorgestellt, sowie Standards für die diesbezüglichen Abläufe vorgeschlagen. Einzelne Bereiche wie Anamneseerhebung, klinische Untersuchung, Laborparameter, neuropsychologische Testung und neuroradiologische Verfahren werden als Teil der Standarddiagnostik ausführlich diskutiert, ergänzende Untersuchungsmethoden für differenzialdiagnostische Überlegungen abgebildet. Die wichtigsten Ziele der SMC-Empfehlungen zur Diagnostik der Demenzerkrankungen sind, möglichst allen Betroffenen Zugang zu einer qualitativ hochstehenden Diagnostik zu ermöglichen, die Frühdiagnostik der Demenz zu verbessern und den Grundversorgern sowie den Mitarbeitenden der Memory Clinics ein nützliches Instrument für die Abklärung anzubieten.

A Longitudinal Study on Resting State Functional Connectivity in Behavioral Variant Frontotemporal Dementia and Alzheimer's Disease

BACKGROUND/OBJECTIVE

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. We applied longitudinal resting state functional magnetic resonance imaging (fMRI) to delineate functional brain connections relevant for disease progression and diagnostic accuracy.

METHODS

We used two-center resting state fMRI data of 20 AD patients (65.1±8.0 years), 12 bvFTD patients (64.7±5.4 years), and 22 control subjects (63.8±5.0 years) at baseline and 1.8-year follow-up. We used whole-network and voxel-based network-to-region analyses to study group differences in functional connectivity at baseline and follow-up, and longitudinal changes in connectivity within and between groups.

RESULTS

At baseline, connectivity between paracingulate gyrus and executive control network, between cuneal cortex and medial visual network, and between paracingulate gyrus and salience network was higher in AD compared with controls. These differences were also present after 1.8 years. At follow-up, connectivity between angular gyrus and right frontoparietal network, and between paracingulate gyrus and default mode network was lower in bvFTD compared with controls, and lower compared with AD between anterior cingulate gyrus and executive control network, and between lateral occipital cortex and medial visual network. Over time, connectivity decreased in AD between precuneus and right frontoparietal network and in bvFTD between inferior frontal gyrus and left frontoparietal network. Longitudinal changes in connectivity between supramarginal gyrus and right frontoparietal network differ between both patient groups and controls.

CONCLUSION

We found disease-specific brain regions with longitudinal connectivity changes. This suggests the potential of longitudinal resting state fMRI to delineate regions relevant for disease progression and for diagnostic accuracy, although no group differences in longitudinal changes in the direct comparison of AD and bvFTD were found.

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.

Enhanced Feedback-Related Negativity in Alzheimer's Disease

Alzheimer’s disease (AD), the most common cause of dementia in the elderly, results in the impairment of executive function, including that of performance monitoring. Feedback-related negativity (FRN) is an electrophysiological measure reflecting the activity of this monitoring system via feedback signals, and is generated from the anterior cingulate cortex. However, there have been no reports on FRN in AD. Based on prior aging studies, we hypothesized that FRN would decrease in AD patients. To assess this, FRN was measured in healthy individuals and those with AD during a simple gambling task involving positive and negative feedback stimuli. Contrary to our hypothesis, FRN amplitude increased in AD patients, compared with the healthy elderly. We speculate that this may reflect the existence of a compensatory mechanism against the decline in executive function. Also, there was a significant association between FRN amplitude and depression scores in AD, and the FRN amplitude tended to increase insomuch as the Self-rating Depression Scale (SDS) was higher. This result suggests the existence of a negative bias in the affective state in AD. Thus, the impaired functioning monitoring system in AD is a more complex phenomenon than we thought.

Data-driven regions of interest for longitudinal change in three variants of frontotemporal lobar degeneration

INTRODUCTION

Longitudinal imaging of neurodegenerative disorders is a potentially powerful biomarker for use in clinical trials. In Alzheimer's disease, studies have demonstrated that empirically derived regions of interest (ROIs) can provide more reliable measurement of disease progression compared with anatomically defined ROIs.

METHODS

We set out to derive ROIs with optimal effect size for quantifying longitudinal change in a hypothetical clinical trial by comparing atrophy rates in 44 patients with behavioral variant of frontotemporal dementia (bvFTD), 30 with the semantic variant primary progressive aphasia (svPPA), and 26 with the nonfluent variant PPA (nfvPPA) to atrophy in 97 cognitively healthy controls.

RESULTS

The regions identified for each variant were generally what would be expected from prior studies of frontotemporal lobar degeneration (FTLD). Sample size estimates for detecting a 40% reduction in annual rate of ROI atrophy varied substantially across groups, being 103 per arm in bvFTD, 31 in nfvPPA, and 10 in svPPA, but in all groups were less than those estimated for a priori ROIs and clinical measures. The variability in location of peak regions of atrophy across individuals was highest in bvFTD and lowest in svPPA, likely relating to the differences in effect size.

CONCLUSIONS

These findings suggest that, while cross-validated maps of change can improve sensitivity to change in FTLD compared with a priori regions, the reliability of these maps differs considerably across syndromes. Future studies can utilize these maps to design clinical trials, and should try to identify factors accounting for the variability in patterns of atrophy across individuals, particularly those with bvFTD.

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data

Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with a very high accuracy paving the road for its application in clinical settings.

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Aim was to evaluate the potential of multi-center MRI data for individual PPA diagnosis.

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We used support vector machine classification in PPA variants and healthy controls.

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We compared a whole brain approach with a ROI (taken from meta-analyses) approach.

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Accuracies were overall quite high, for both, the whole brain and the ROI approach.

Altered Gray Matter Volume in Stable Chronic Obstructive Pulmonary Disease with Subclinical Cognitive Impairment: an Exploratory Study

Gray matter volume deficits have been identified in cognitively impaired patients with chronic obstructive pulmonary disease (COPD). However, it remains unknown whether the gray matter volume is altered in COPD patients with subclinical cognitive impairment. To determine whether any gray matter abnormalities are present in these patients, neuropsychological tests and structural MRI data were analyzed from 60 patients with COPD and 60 age-, gender-, education-, and handedness-matched normal controls (NCs). The COPD patients had similar Mini-Mental State Examination (MMSE) scores compared with the NCs. However, they had reduced Montreal Cognitive Assessment (MoCA) scores for visuospatial and executive and naming and memory functions (P < 0.001). Voxel-based morphometry (VBM) analysis revealed that the COPD patients had significantly lowered gray matter volumes in several brain regions, including the left precuneus (PrCU), bilateral calcarine (CAL), right superior temporal gyrus/middle temporal gyrus (STG/MTG), bilateral fusiform gyrus (FG), and right inferior parietal lobule (IPL) (P < 0.01, corrected). Importantly, the forced vital capacity (FVC) was found to be associated with the gray matter volume in the calcarine. The present study confirmed that brain structural changes were present in stable COPD patients with subclinical cognitive impairment. These findings may provide new insights into the pathogenesis of COPD.

Gray matter network differences between behavioral variant frontotemporal dementia and Alzheimer's disease

We set out to study whether single-subject gray matter (GM) networks show disturbances that are specific for Alzheimer's disease (AD; n = 90) or behavioral variant frontotemporal dementia (bvFTD; n = 59), and whether such disturbances would be related to cognitive deficits measured with mini-mental state examination and a neuropsychological battery, using subjective cognitive decline subjects as reference. AD and bvFTD patients had a lower degree, connectivity density, clustering, path length, betweenness centrality, and small world values compared with subjective cognitive decline. AD patients had a lower connectivity density than bvFTD patients (F = 5.79, p = 0.02; mean ± standard deviation bvFTD 16.10 ± 1.19%; mean ± standard deviation AD 15.64 ± 1.02%). Lasso logistic regression showed that connectivity differences between bvFTD and AD were specific to 23 anatomical areas, in terms of local GM volume, degree, and clustering. Lower clustering values and lower degree values were specifically associated with worse mini-mental state examination scores and lower performance on the neuropsychological tests. GM showed disease-specific alterations, when comparing bvFTD with AD patients, and these alterations were associated with cognitive deficits.

Volumetric and fiber-tracing MRI methods for gray and white matter

Magnetic resonance imaging (MRI) is capable of generating high-resolution brain images with fine anatomic detail and unique tissue contrasts that reveal structures that are not visible to the eye. Sharply defined gray- and white-matter interfaces allow for quantitative anatomic analysis that can be accurately performed with largely automated segmentation methods. In an analogous fashion, diffusion MRI in the brain provides structural information based on contrasts derived from the diffusivity of water in brain tissue, which can highlight the orientation of neuronal axons. Also using largely automated methods, diffusion MRI can be used to generate models of white-matter tracts throughout the brain, a method known as tractography, as well as characterize the microstructural integrity of neuronal axons. Tractographic analysis has helped to define connectivity in the brain that powerfully informs understanding of brain function, and, together with other diffusion metrics, is useful in evaluation of the normal and diseased brain. The quantitative methods of brain segmentation, tractography, and diffusion MRI extend MRI into a realm beyond visual inspection and provide otherwise unachievable sensitivity and specificity in the analysis of brain structure and function.

Differences in structural covariance brain networks between behavioral variant frontotemporal dementia and Alzheimer's disease

Disease-specific patterns of gray matter atrophy in Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) overlap with distinct structural covariance networks (SCNs) in cognitively healthy controls. This suggests that both types of dementia target specific structural networks. Here, we study SCNs in AD and bvFTD. We used structural magnetic resonance imaging data of 31 AD patients, 24 bvFTD patients, and 30 controls from two centers specialized in dementia. Ten SCNs were defined based on structural covariance of gray matter density using independent component analysis. We studied group differences in SCNs using F-tests, with Bonferroni corrected t-tests, adjusted for age, gender, and study center. Associations with cognitive performance were studied using linear regression analyses. Cross-sectional group differences were found in three SCNs (all P < 0.0025). In bvFTD, we observed decreased anterior cingulate network integrity compared with AD and controls. Patients with AD showed decreased precuneal network integrity compared with bvFTD and controls, and decreased hippocampal network and anterior cingulate network integrity compared with controls. In AD, we found an association between precuneal network integrity and global cognitive performance (P = 0.0043). Our findings show that AD and bvFTD target different SCNs. The comparison of both types of dementia showed decreased precuneal (i.e., default mode) network integrity in AD and decreased anterior cingulate (i.e., salience) network integrity in bvFTD. This confirms the hypothesis that AD and bvFTD have distinct anatomical networks of degeneration and shows that structural covariance gives valuable insights in the understanding of network pathology in dementia.

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.

Resting state functional connectivity differences between behavioral variant frontotemporal dementia and Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. Early differentiation between both types of dementia may be challenging due to heterogeneity and overlap of symptoms. Here, we apply resting state functional magnetic resonance imaging (fMRI) to study functional brain connectivity differences between AD and bvFTD.

METHODS

We used resting state fMRI data of 31 AD patients, 25 bvFTD patients, and 29 controls from two centers specialized in dementia. We studied functional connectivity throughout the entire brain, applying two different analysis techniques, studying network-to-region and region-to-region connectivity. A general linear model approach was used to study group differences, while controlling for physiological noise, age, gender, study center, and regional gray matter volume.

RESULTS

Given gray matter differences, we observed decreased network-to-region connectivity in bvFTD between (a) lateral visual cortical network and lateral occipital and cuneal cortex, and (b) auditory system network and angular gyrus. In AD, we found decreased network-to-region connectivity between the dorsal visual stream network and lateral occipital and parietal opercular cortex. Region-to-region connectivity was decreased in bvFTD between superior temporal gyrus and cuneal, supracalcarine, intracalcarine cortex, and lingual gyrus.

CONCLUSION

We showed that the pathophysiology of functional brain connectivity is different between AD and bvFTD. Our findings support the hypothesis that resting state fMRI shows disease-specific functional connectivity differences and is useful to elucidate the pathophysiology of AD and bvFTD. However, the group differences in functional connectivity are less abundant than has been shown in previous studies.

Data-driven regions of interest for longitudinal change in frontotemporal lobar degeneration

Current research is investigating the potential utility of longitudinal measurement of brain structure as a marker of drug effect in clinical trials for neurodegenerative disease. Recent studies in Alzheimer's disease (AD) have shown that measurement of change in empirically derived regions of interest (ROIs) allows more reliable measurement of change over time compared with regions chosen a-priori based on known effects of AD on brain anatomy. Frontotemporal lobar degeneration (FTLD) is a devastating neurodegenerative disorder for which there are no approved treatments. The goal of this study was to identify an empirical ROI that maximizes the effect size for the annual rate of brain atrophy in FTLD compared with healthy age matched controls, and to estimate the effect size and associated power estimates for a theoretical study that would use change within this ROI as an outcome measure. Eighty six patients with FTLD were studied, including 43 who were imaged twice at 1.5 T and 43 at 3 T, along with 105 controls (37 imaged at 1.5 T and 67 at 3 T). Empirically-derived maps of change were generated separately for each field strength and included the bilateral insula, dorsolateral, medial and orbital frontal, basal ganglia and lateral and inferior temporal regions. The extent of regions included in the 3 T map was larger than that in the 1.5 T map. At both field strengths, the effect sizes for imaging were larger than for any clinical measures. At 3 T, the effect size for longitudinal change measured within the empirically derived ROI was larger than the effect sizes derived from frontal lobe, temporal lobe or whole brain ROIs. The effect size derived from the data-driven 1.5 T map was smaller than at 3 T, and was not larger than the effect size derived from a-priori ROIs. It was estimated that measurement of longitudinal change using 1.5 T MR systems requires approximately a 3-fold increase in sample size to obtain effect sizes equivalent to those seen at 3 T. While the results should be confirmed in additional datasets, these results indicate that empirically derived ROIs can reduce the number of subjects needed for a longitudinal study of drug effects in FTLD compared with a-priori ROIs. Field strength may have a significant impact on the utility of imaging for measuring longitudinal change.

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.

Neuroimaging in dementia

Over the last few years, advances in neuroimaging have generated biomarkers, which increase diagnostic certainty, provide valuable information about prognosis, and suggest a particular pathology underlying the clinical dementia syndrome. We aim to review the evidence for use of already established imaging modalities, along with selected techniques that have a great potential to guide clinical decisions in the future. We discuss structural, functional and molecular imaging, focusing on the most common dementias: Alzheimer's disease, fronto-temporal dementia, dementia with Lewy bodies and vascular dementia. Finally, we stress the importance of conducting research using representative cohorts and in a naturalistic set up, in order to build a strong evidence base for translating imaging methods for a National Health Service. If we assess a broad range of patients referred to memory clinic with a variety of imaging modalities, we will make a step towards accumulating robust evidence and ultimately closing the gap between the dramatic advances in neurosciences and meaningful clinical applications for the maximum benefit of our patients.

Longitudinal grey and white matter changes in frontotemporal dementia and Alzheimer's disease

Behavioural variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) dementia are characterised by progressive brain atrophy. Longitudinal MRI volumetry may help to characterise ongoing structural degeneration and support the differential diagnosis of dementia subtypes. Automated, observer-independent atlas-based MRI volumetry was applied to analyse 102 MRI data sets from 15 bvFTD, 14 AD, and 10 healthy elderly control participants with consecutive scans over at least 12 months. Anatomically defined targets were chosen a priori as brain structures of interest. Groups were compared regarding volumes at clinic presentation and annual change rates. Baseline volumes, especially of grey matter compartments, were significantly reduced in bvFTD and AD patients. Grey matter volumes of the caudate and the gyrus rectus were significantly smaller in bvFTD than AD. The bvFTD group could be separated from AD on the basis of caudate volume with high accuracy (79% cases correct). Annual volume decline was markedly larger in bvFTD and AD than controls, predominantly in white matter of temporal structures. Decline in grey matter volume of the lateral orbitofrontal gyrus separated bvFTD from AD and controls. Automated longitudinal MRI volumetry discriminates bvFTD from AD. In particular, greater reduction of orbitofrontal grey matter and temporal white matter structures after 12 months is indicative of bvFTD.

Sequential distribution of pTDP-43 pathology in behavioral variant frontotemporal dementia (bvFTD)

We examined regional distribution patterns of phosphorylated 43-kDa TAR DNA-binding protein (pTDP-43) intraneuronal inclusions in frontotemporal lobar degeneration (FTLD). Immunohistochemistry was performed on 70 μm sections from FTLD-TDP autopsy cases (n = 39) presenting with behavioral variant frontotemporal dementia. Two main types of cortical pTDP-43 pathology emerged, characterized by either predominantly perikaryal pTDP-43 inclusions (cytoplasmic type, cFTLD) or long aggregates in dendrites (neuritic type, nFTLD). Cortical involvement in nFTLD was extensive and frequently reached occipital areas, whereas cases with cFTLD often involved bulbar somatomotor neurons and the spinal cord. We observed four patterns indicative of potentially sequential dissemination of pTDP-43: cases with the lowest burden of pathology (pattern I) were characterized by widespread pTDP-43 lesions in the orbital gyri, gyrus rectus, and amygdala. With increasing burden of pathology (pattern II) pTDP-43 lesions emerged in the middle frontal and anterior cingulate gyrus as well as in anteromedial temporal lobe areas, the superior and medial temporal gyri, striatum, red nucleus, thalamus, and precerebellar nuclei. More advanced cases showed a third pattern (III) with involvement of the motor cortex, bulbar somatomotor neurons, and the spinal cord anterior horn, whereas cases with the highest burden of pathology (pattern IV) were characterized by pTDP-43 lesions in the visual cortex. We interpret the four neuropathological patterns in bvFTD to be consistent with the hypothesis that pTDP-43 pathology can spread sequentially and may propagate along axonal pathways.

Interactive effects of chronic cigarette smoking and age on brain volumes in controls and alcohol-dependent individuals in early abstinence

Chronic alcohol-use disorders (AUDs) have been shown to interact with normal age-related volume loss to exacerbate brain atrophy with increasing age. However, chronic cigarette smoking, a highly co-morbid condition in AUD and its influence on age-related brain atrophy have not been evaluated. We performed 1.5 T quantitative magnetic resonance imaging in non-smoking controls [non-smoking light drinking controls (nsCONs); n = 54], smoking light drinking controls (sCONs, n = 34), and one-week abstinent, treatment-seeking alcohol-dependent (ALC) non-smokers (nsALCs, n = 35) and smokers (sALCs, n = 43), to evaluate the independent and interactive effects of alcohol dependence and chronic smoking on regional cortical and subcortical brain volumes, emphasizing the brain reward/executive oversight system (BREOS). The nsCONs and sALCs showed greater age-related volume losses than the nsALCs in the dorsal prefrontal cortex (DPFC), total cortical BREOS, superior parietal lobule and putamen. The nsALCs and sALCs demonstrated smaller volumes than the nsCONs in most cortical region of interests (ROIs). The sCONs had smaller volumes than the nsCONs in the DPFC, insula, inferior parietal lobule, temporal pole/parahippocampal region and all global cortical measures. The nsALCs and sALCs had smaller volumes than the sCONs in the DPFC, superior temporal gyrus, inferior and superior parietal lobules, precuneus and all global cortical measures. Volume differences between the nsALCs and sALCs were observed only in the putamen. Alcohol consumption measures were not related to volumes in any ROI for ALC; smoking severity measures were related to corpus callosum volume in the sCONs and sALCs. The findings indicate that consideration of smoking status is necessary for a better understanding of the factors contributing to regional brain atrophy in AUD.

Neuroimaging biomarkers of neurodegenerative diseases and dementia

Neurodegenerative disorders leading to dementia are common diseases that affect many older and some young adults. Neuroimaging methods are important tools for assessing and monitoring pathological brain changes associated with progressive neurodegenerative conditions. In this review, the authors describe key findings from neuroimaging studies (magnetic resonance imaging and radionucleotide imaging) in neurodegenerative disorders, including Alzheimer's disease (AD) and prodromal stages, familial and atypical AD syndromes, frontotemporal dementia, amyotrophic lateral sclerosis with and without dementia, Parkinson's disease with and without dementia, dementia with Lewy bodies, Huntington's disease, multiple sclerosis, HIV-associated neurocognitive disorder, and prion protein associated diseases (i.e., Creutzfeldt-Jakob disease). The authors focus on neuroimaging findings of in vivo pathology in these disorders, as well as the potential for neuroimaging to provide useful information for differential diagnosis of neurodegenerative disorders.

Complexity and schizophrenia

Complexity estimators have been broadly utilized in schizophrenia investigation. Early studies reported increased complexity in schizophrenia patients, associated with a higher variability or "irregularity" of their brain signals. However, further investigations showed reduced complexities, thus introducing a clear divergence. Nowadays, both increased and reduced complexity values are reported. The explanation of such divergence is a critical issue to understand the role of complexity measures in schizophrenia research. Considering previous arguments a complementary hypothesis is advanced: if the increased irregularity of schizophrenia patients' neurophysiological activity is assumed, a "natural" tendency to increased complexity in EEG and MEG scans should be expected, probably reflecting an abnormal neuronal firing pattern in some critical regions such as the frontal lobes. This "natural" tendency to increased complexity might be modulated by the interaction of three main factors: medication effects, symptomatology, and age effects. Therefore, young, medication-naïve, and highly symptomatic (positive symptoms) patients are expected to exhibit increased complexities. More importantly, the investigation of these interacting factors by means of complexity estimators might help to elucidate some of the neuropathological processes involved in schizophrenia.

Using the revised diagnostic criteria for frontotemporal dementia in India: evidence of an advanced and florid disease

BACKGROUND

The International Consortium (FTDC) that revised the diagnostic criteria for behavioural variant frontotemporal dementia (bvFTD) did not have an Asian representation. Whether the revised criteria are equally useful in the early detection of Asian bvFTD patients therefore remains largely unexplored. Earlier studies have indicated differences in clinical manifestations in Indian and other Asian bvFTD patients when compared to western groups. There is an urgent need for clarification, given the projected exponential rise in dementia in these countries and the imminent clinical trials on bvFTD.

OBJECTIVE

To assess how Indian bvFTD patients fulfil the FTDC criteria, hypothesizing that our patients might present differently early in the illness.

METHOD

In a hospital-based retrospective observational study, we assessed 48 probable bvFTD patients, diagnosed according to the FTDC criteria, for the speed with which these criteria were fulfilled, the frequency of individual symptoms and their order of appearance during the illness.

RESULTS

Most of our patients presented with moderate to severe dementia, in spite of having relatively short onset to diagnosis times. Patients on average took 1.4 years from onset to meet the FTDC criteria, with 90% of them presenting with four or more symptoms at diagnosis. Disinhibition was the commonest symptom and the first symptom in most patients.

CONCLUSION

With most patients presenting with advanced and florid disease, the FTDC criteria have little additional impact in early identification of bvFTD in India. Modifying the criteria further could allow detection of Indian patients early enough for their inclusion in future clinical trials.

Recent advances in the imaging of frontotemporal dementia

Neuroimaging has played an important role in the characterization of the frontotemporal dementia (FTD) syndromes, demonstrating neurodegenerative signatures that can aid in the differentiation of FTD from other neurodegenerative disorders. Recent advances have been driven largely by the refinement of the clinical syndromes that underlie FTD, and by the discovery of new genetic and pathological features associated with FTD. Many new imaging techniques and modalities are also now available that allow the assessment of other aspects of brain structure and function, such as diffusion tensor imaging and resting-state functional MRI. Studies have used these recent techniques, as well as traditional volumetric MRI, to provide further insight into disease progression across the many clinical, genetic, and pathological variants of FTD. Importantly, neuroimaging signatures have been identified that will improve the clinician's ability to predict underlying genetic and pathological features, and hence ultimately improve patient diagnosis.

Neuroimaging in dementias

PURPOSE OF REVIEW

To critically review data on the use of neuroimaging tools in the clinical diagnostic investigation of dementias.

RECENT FINDINGS

For many years, the use of neuroimaging tools in the evaluation of dementias has been restricted to excluding neurosurgical lesions that may account for the cognitive decline. However, modern neuroimaging extends beyond this traditional role of excluding other conditions and has a key role in the clinical investigation of Alzheimer's disease and of other degenerative cortical dementias. MRI, PET with fluorodeoxyglucose, and single-photon emission computed tomography are topographic markers of neural damage and enable the identification of specific lesional patterns that characterize Alzheimer's disease and other cortical dementias. More recently, PET amyloid markers have enabled the in-vivo assessment of amyloid load, a key feature in the physiopathology of Alzheimer's disease.

SUMMARY

The combined use of neuroimaging examinations with clinical, neuropsychological, and cerebrospinal fluid markers can improve the specificity of the diagnosis of Alzheimer's disease, even at early stages of the disease. In the following years, progress in research will provide standardized and validated imaging markers of Alzheimer's disease and other dementias, which may increase their application in clinical settings.

Social Cognition and Emotional Assessment (SEA) is a marker of medial and orbital frontal functions: a voxel-based morphometry study in behavioral variant of frontotemporal degeneration

The aim of this study was to explore the cerebral correlates of functional deficits that occur in behavioral variant frontotemporal dementia (bvFTD). A specific neuropsychological battery, the Social cognition & Emotional Assessment (SEA; Funkiewiez et al., 2012), was used to assess impaired social and emotional functions in 20 bvFTD patients who also underwent structural MRI scanning. The SEA subscores of theory of mind, reversal-learning tests, facial emotion identification, and apathy evaluation were entered as covariates in a voxel-based morphometry analysis. The results revealed that the gray matter volume in the rostral part of the medial prefrontal cortex [mPFC, Brodmann area (BA) 10] was associated with scores on the theory of mind subtest, while gray matter volume within the orbitofrontal (OFC) and ventral mPFC (BA 11 and 47) was related to the scores observed in the reversal-learning subtest. Gray matter volume within BA 9 in the mPFC was correlated with scores on the emotion recognition subtest, and the severity of apathetic symptoms in the Apathy scale covaried with gray matter volume in the lateral PFC (BA 44/45). Among these regions, the mPFC and OFC cortices have been shown to be atrophied in the early stages of bvFTD. In addition, SEA and its abbreviated version (mini-SEA) have been demonstrated to be sensitive to early impairments in bvFTD (Bertoux et al., 2012). Taken together, these results suggest a differential involvement of orbital and medial prefrontal subregions in SEA subscores and support the use of the SEA to evaluate the integrity of these regions in the early stages of bvFTD.

Greater regional brain atrophy rate in healthy elderly subjects with a history of cigarette smoking

BACKGROUND

Little is known about the effects of cigarette smoking on longitudinal brain morphological changes in the elderly. This study investigated the effects of a history of cigarette smoking on changes in regional brain volumes over 2 years in healthy, cognitively intact elderly individuals. We predicted that individuals with a history of cigarette smoking, compared with never smokers, demonstrate greater rate of atrophy over 2 years in regions that manifest morphological abnormalities in the early stages of Alzheimer's disease (AD), as well as in the extended brain reward/executive oversight system (BREOS), which is implicated in the development and maintenance of substance use disorders.

METHODS

Participants were healthy, cognitively normal elderly control subjects (75.9 ± 4.8 years of age) with any lifetime history of cigarette smoking (n = 68) or no history of smoking (n = 118). Data were obtained through the Alzheimer Disease Neuroimaging Initiative from 2005 to 2010. Participants completed four magnetic resonance scans over 2 years. A standardized protocol using high-resolution three-dimensional T1-weighted sequences at 1.5 T was used for structural imaging and regional brain volumetric analyses.

RESULTS

Smokers demonstrated a significantly greater atrophy rate over 2 years than nonsmokers in multiple brain regions associated with the early stages of AD, as well as in the BREOS system. Groups did not differ on the rate of global cortical atrophy.

CONCLUSIONS

A history of cigarette smoking in this healthy elderly cohort was associated with decreased structural integrity of multiple brain regions, which manifested as a greater rate of atrophy over 2 years in regions specifically affected by incipient AD as well as chronic substance abuse.

Rates of hemispheric and lobar atrophy in the language variants of frontotemporal lobar degeneration

Frontotemporal lobar degeneration (FTLD) is a neurodegenerative disorder which presents with either behavioral or language impairment. The two language syndromes are known as progressive nonfluent aphasia (PNFA) and semantic dementia (SEMD). While cross-sectional imaging patterns of brain atrophy are well-described in FTLD, fewer studies have investigated longitudinal imaging changes. We measured longitudinal hemispheric and lobar atrophy rates using serial MRI in a cohort of 18 patients with PNFA and 17 patients with SEMD as well as 14 cognitively-normal control subjects. We subsequently calculated sample size estimates for clinical trials. Rates of left hemisphere atrophy were greater than rates of right hemisphere atrophy in both PNFA and SEMD with no significant differences between the groups. The disease groups showed asymmetrical atrophy (more severe on the left) at baseline with significantly increasing asymmetry over time. Within a hemisphere, the fastest rate of atrophy varied between lobes: in SEMD temporal > frontal > parietal > occipital, while in PNFA frontal > temporal/parietal > occipital. In SEMD, using temporal lobe measures of atrophy in clinical trials would provide the lowest sample sizes necessary, while in PNFA left hemisphere atrophy measures provided the lowest sample size. These patterns provide information about disease evolution in the FTLD language variants that is of both clinical and neurobiological relevance.

Linking white matter integrity loss to associated cortical regions using structural connectivity information in Alzheimer's disease and fronto-temporal dementia: the Loss in Connectivity (LoCo) score

It is well known that gray matter changes occur in neurodegenerative diseases like Alzheimer's (AD) and fronto-temporal dementia (FTD), and several studies have investigated their respective patterns of atrophy progression. Recent work, however, has revealed that diffusion MRI that is able to detect white matter integrity changes may be an earlier or more sensitive biomarker in both diseases. However, studies that examine white matter changes only are limited in that they do not provide the functional specificity of GM region-based analysis. In this study, we develop a new metric called the Loss in Connectivity (LoCo) score that gives the amount of structural network disruption incurred by a gray matter region for a particular pattern of white matter integrity loss. Leveraging the relative strengths of WM and GM markers, this metric links areas of WM integrity loss to their connected GM regions as a first step in understanding their functional implications. The LoCo score is calculated for three groups: 18AD, 18 FTD, and 19 age-matched normal controls. We show significant correlations of the LoCo with the respective atrophy patterns in AD (R=0.51, p=2.2 × 10(-9)) and FTD (R=0.49, p=2.5 × 10(-8)) for a standard 116 region gray matter atlas. In addition, we demonstrate that the LoCo outperforms a measure of gray matter atrophy when classifying individuals into AD, FTD, and normal groups.

Semantic dementia: a specific network-opathy

Semantic dementia (SD) is a unique syndrome in the frontotemporal lobar degeneration spectrum. Typically presenting as a progressive, fluent anomic aphasia, SD is the paradigmatic disorder of semantic memory with a characteristic anatomical profile of asymmetric, selective antero-inferior temporal lobe atrophy. Histopathologically, most cases show a specific pattern of abnormal deposition of protein TDP-43. This relatively close clinical, anatomical and pathological correspondence suggests SD as a promising target for future therapeutic trials. Here, we discuss outstanding nosological and neurobiological challenges posed by the syndrome and propose a pathophysiological model of SD based on sequential, regionally determined disintegration of a vulnerable neural network.