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

Itching Frequency and Neuroanatomic Correlates in Frontotemporal Lobar Degeneration

Importance

Itching is common in geriatric populations and is frequently linked to dermatological or systemic conditions. Itching engages specific brain regions that are implicated in the pathogenesis of frontotemporal lobar degeneration spectrum disorders (FTLD-SD). Thus, itching of undetermined origin (IUO) may indicate the presence of a neurodegenerative process.

Objective

To compare the frequency of itching in FTLD-SD and Alzheimer disease (AD) and to determine the neuroanatomical underpinnings of IUO.

Design, Setting, and Participants

This case-control study evaluated data and brain magnetic resonance images (MRIs) for participants with FTLD-SD or AD. Participants of a research study on FTLD-SD at the University of California, San Francisco, Memory and Aging Center were evaluated from May 1, 2002, to December 31, 2021. The exposure group underwent structural brain MRI within 6 months of initial diagnosis. Research visit summaries were reviewed to validate qualitative details and accurately identify itching with undetermined origin (IUO).

Exposures

Symptoms suggestive of FTLD-SD or AD.

Main Outcomes and Measures

Frequency of itching in FTLD-SD and AD and neuroanatomic correlates.

Results

A total of 2091 research visit summaries were reviewed for 1112 patients exhibiting symptoms indicative of FTLD-SD or AD. From 795 records where itching or a related phrase was endorsed, 137 had IUO. A total of 454 participants were included in the study: 137 in the itching group (mean [SD] age, 62.7 [9.9] years; 74 [54%] females and 63 males [46%]) and 317 in the nonitching group (mean [SD] age, 60.7 [10.8] years; 154 [49%] females and 163 males [51%]). Groups were similar in age, sex, and disease severity. More frequent itching was found in FTLD-SD (95/248 patients [38%], of which 44 [46%] had behavioral variant frontotemporal dementia [bvFTD]) compared with the AD group (14/77 patients [18%]; P = .001). The odds of itching were 2.4 (95% CI, 1.48-3.97) times higher for FTLD-SD compared with all other cases of dementia. Compared with healthy controls, the group with IUO exhibited greater gray matter atrophy bilaterally in the amygdala, insula, precentral gyrus, and cingulum, as well as in the right frontal superior gyrus and thalamus. Among patients with bvFTD and itching vs bvFTD without itching, itching was associated with right-lateralized gray matter atrophy affecting the insula, thalamus, superior frontal gyrus, and cingulum.

Conclusions and Relevance

Among individuals with IUO, FTLD-SD was disproportionately represented compared with AD. In FTLD-SD, dysfunction in the right anterior insula and its connected regions, including the right precentral gyrus, cingulum, and bilateral amygdala, contribute to dysregulation of the itching-scratching networks, resulting in uncontrollable itching or skin picking. Awareness among physicians about the relationship between neurodegeneration and itching may help in the management of itch in older individuals. Further studies are needed to determine the best treatments for these symptoms in patients with neurodegenerative disorders.

Pathology-specific patterns of cerebellar atrophy in neurodegenerative disorders

INTRODUCTION

Associations of cerebellar atrophy with specific neuropathologies in Alzheimer's disease and related dementias (ADRD) have not been systematically analyzed. This study examined cerebellar gray matter volume across major pathological subtypes of ADRD.

METHODS

Cerebellar gray matter volume was examined using voxel-based morphometry in 309 autopsy-proven ADRD cases and 80 healthy controls. ADRD subtypes included AD, mixed Lewy body disease and AD (LBD-AD), and frontotemporal lobar degeneration (FTLD). Clinical function was assessed using the Clinical Dementia Rating (CDR) scale.

RESULTS

Distinct patterns of cerebellar atrophy were observed in all ADRD subtypes. Significant cerebellar gray matter changes appeared in the early stages of most subtypes and the very early stages of AD, LBD-AD, FTLD-TDP type A, and progressive supranuclear palsy. Cortical atrophy positively predicted cerebellar atrophy across all subtypes.

DISCUSSION

Our findings establish pathology-specific profiles of cerebellar atrophy in ADRD and propose cerebellar neuroimaging as a non-invasive biomarker for differential diagnosis and disease monitoring.

HIGHLIGHTS

Cerebellar atrophy was examined in 309 patients with autopsy-proven neurodegeneration. Distinct patterns of cerebellar atrophy are found in all pathological subtypes of Alzheimer's disease and related dementias (ADRD). Cerebellar atrophy is seen in early-stage (Clinical Dementia Rating [CDR] ≤1) AD, Lewy body dementia (LBD), frontotemporal lobar degeneration with tau-positive inclusion (FTLD-tau), and FTLD-transactive response DNA binding protein (FTLD-TDP). Cortical atrophy positively predicts cerebellar atrophy across all neuropathologies.

Neurofilament light levels predict clinical progression and death in multiple system atrophy

Disease-modifying treatments are currently being trialled in multiple system atrophy. Approaches based solely on clinical measures are challenged by heterogeneity of phenotype and pathogenic complexity. Neurofilament light chain protein has been explored as a reliable biomarker in several neurodegenerative disorders but data on multiple system atrophy have been limited. Therefore, neurofilament light chain is not yet routinely used as an outcome measure in multiple system atrophy. We aimed to comprehensively investigate the role and dynamics of neurofilament light chain in multiple system atrophy combined with cross-sectional and longitudinal clinical and imaging scales and for subject trial selection. In this cohort study, we recruited cross-sectional and longitudinal cases in a multicentre European set-up. Plasma and CSF neurofilament light chain concentrations were measured at baseline from 212 multiple system atrophy cases, annually for a mean period of 2 years in 44 multiple system atrophy patients in conjunction with clinical, neuropsychological and MRI brain assessments. Baseline neurofilament light chain characteristics were compared between groups. Cox regression was used to assess survival; receiver operating characteristic analysis to assess the ability of neurofilament light chain to distinguish between multiple system atrophy patients and healthy controls. Multivariate linear mixed-effects models were used to analyse longitudinal neurofilament light chain changes and correlated with clinical and imaging parameters. Polynomial models were used to determine the differential trajectories of neurofilament light chain in multiple system atrophy. We estimated sample sizes for trials aiming to decrease neurofilament light chain levels. We show that in multiple system atrophy, baseline plasma neurofilament light chain levels were better predictors of clinical progression, survival and degree of brain atrophy than the neurofilament light chain rate of change. Comparative analysis of multiple system atrophy progression over the course of disease, using plasma neurofilament light chain and clinical rating scales, indicated that neurofilament light chain levels rise as the motor symptoms progress, followed by deceleration in advanced stages. Sample size prediction suggested that significantly lower trial participant numbers would be needed to demonstrate treatment effects when incorporating plasma neurofilament light chain values into multiple system atrophy clinical trials in comparison to clinical measures alone. In conclusion, neurofilament light chain correlates with clinical disease severity, progression and prognosis in multiple system atrophy. Combined with clinical and imaging analysis, neurofilament light chain can inform patient stratification and serve as a reliable biomarker of treatment response in future multiple system atrophy trials of putative disease-modifying agents.

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.

Differences in Multimodal Electroencephalogram and Clinical Correlations Between Early-Onset Alzheimer's Disease and Frontotemporal Dementia

Background

Alzheimer’s disease (AD) and frontotemporal dementia (FTD) are the two main types of dementia. We investigated the electroencephalogram (EEG) difference and clinical correlation in early-onset Alzheimer’s disease (EOAD), and FTD using multimodal EEG analyses. EOAD had more severe EEG abnormalities than late-onset AD (LOAD). Group comparisons between EOAD and LOAD were also performed.

Methods

Thirty patients diagnosed with EOAD, nine patients with LOAD, and 14 patients with FTD (≤65 y) were recruited (2008.1–2020.2), along with 24 healthy controls (≤65 y, n = 18; >65 y, n = 6). Clinical data were reviewed. Visual EEG, EEG microstate, and spectral analyses were performed.

Results

Compared to controls, markedly increased mean microstate duration, reduced mean occurrence, and reduced global field power (GFP) peaks per second were observed in EOAD and FTD. We found increased durations of class B in EOAD and class A in FTD. EOAD had reduced occurrences in classes A, B, and C, while only class C occurrence was reduced in FTD. The visual EEG results did not differ between AD and FTD. Microstate B showed correlations with activities of daily living score (r = 0.780, p = 0.008) and cerebrospinal fluid (CSF) Aβ42 (r = −0.833, p = 0.010) in EOAD. Microstate D occurrence was correlated with the CSF Aβ42 level in FTD (r = 0.786, p = 0.021). Spectral analysis revealed a general slowing EEG, which may contribute to microstate dynamic loss. Power in delta was significantly higher in EOAD than in FTD all over the head. In addition, EOAD had a marked increased duration and decreased occurrence than late-onset AD (LOAD), with no group differences in visual EEG results.

Conclusion

The current study found that EOAD and FTD had different EEG changes, and microstate had an association with clinical severity and CSF biomarkers. EEG microstate is more sensitive than visual EEG and may be useful for the differentiation between AD and FTD. The observations support that EEG can be a potential biomarker for the diagnosis and assessment of early-onset dementias.

Classification using fractional anisotropy predicts conversion in genetic frontotemporal dementia, a proof of concept

Frontotemporal dementia is a highly heritable and devastating neurodegenerative disease. About 10–20% of all frontotemporal dementia is caused by known pathogenic mutations, but a reliable tool to predict clinical conversion in mutation carriers is lacking. In this retrospective proof-of-concept case-control study, we investigate whether MRI-based and cognition-based classifiers can predict which mutation carriers from genetic frontotemporal dementia families will develop symptoms (‘convert’) within 4 years. From genetic frontotemporal dementia families, we included 42 presymptomatic frontotemporal dementia mutation carriers. We acquired anatomical, diffusion-weighted imaging, and resting-state functional MRI, as well as neuropsychological data. After 4 years, seven mutation carriers had converted to frontotemporal dementia (‘converters’), while 35 had not (‘non-converters’). We trained regularized logistic regression models on baseline MRI and cognitive data to predict conversion to frontotemporal dementia within 4 years, and quantified prediction performance using area under the receiver operating characteristic curves. The prediction model based on fractional anisotropy, with highest contribution of the forceps minor, predicted conversion to frontotemporal dementia beyond chance level (0.81 area under the curve, family-wise error corrected P = 0.025 versus chance level). Other MRI-based and cognitive features did not outperform chance level. Even in a small sample, fractional anisotropy predicted conversion in presymptomatic frontotemporal dementia mutation carriers beyond chance level. After validation in larger data sets, conversion prediction in genetic frontotemporal dementia may facilitate early recruitment into clinical trials.

An update on magnetic resonance imaging markers in AD

The purpose of the present review is to provide an update of the available recent scientific literature on the use of magnetic resonance imaging (MRI) in Alzheimer's disease (AD). MRI is playing an increasingly important role in the characterization of the AD signatures, which can be useful in both the diagnostic process and monitoring of disease progression. Furthermore, this technique is unique in assessing brain structure and function and provides a deep understanding of in vivo evolution of cerebral pathology. In the reviewing process, we established a priori criteria and we thoroughly searched the very recent scientific literature (January 2018-March 2020) for relevant articles on this topic. In summary, we selected 73 articles out of 1654 publications retrieved from PubMed. Based on this selection, this review summarizes the recent application of MRI in clinical trials, defining the predementia stages of AD, the clinical utility of MRI, proposal of novel biomarkers and brain regions of interest, and assessing the relationship between MRI and cognitive features, risk and protective factors of AD. Finally, the value of a multiparametric approach in clinical and preclinical stages of AD is discussed.

Multimodal MRI of grey matter, white matter, and functional connectivity in cognitively healthy mutation carriers at risk for frontotemporal dementia and Alzheimer's disease

BACKGROUND

Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are associated with divergent differences in grey matter volume, white matter diffusion, and functional connectivity. However, it is unknown at what disease stage these differences emerge. Here, we investigate whether divergent differences in grey matter volume, white matter diffusion, and functional connectivity are already apparent between cognitively healthy carriers of pathogenic FTD mutations, and cognitively healthy carriers at increased AD risk.

METHODS

We acquired multimodal magnetic resonance imaging (MRI) brain scans in cognitively healthy subjects with (n=39) and without (n=36) microtubule-associated protein Tau (MAPT) or progranulin (GRN) mutations, and with (n=37) and without (n=38) apolipoprotein E ε4 (APOE4) allele. We evaluated grey matter volume using voxel-based morphometry, white matter diffusion using tract-based spatial statistics (TBSS), and region-to-network functional connectivity using dual regression in the default mode network and salience network. We tested for differences between the respective carriers and controls, as well as for divergence of those differences. For the divergence contrast, we additionally performed region-of-interest TBSS analyses in known areas of white matter diffusion differences between FTD and AD (i.e., uncinate fasciculus, forceps minor, and anterior thalamic radiation).

RESULTS

MAPT/GRN carriers did not differ from controls in any modality. APOE4 carriers had lower fractional anisotropy than controls in the callosal splenium and right inferior fronto-occipital fasciculus, but did not show grey matter volume or functional connectivity differences. We found no divergent differences between both carrier-control contrasts in any modality, even in region-of-interest analyses.

CONCLUSIONS

Concluding, we could not find differences suggestive of divergent pathways of underlying FTD and AD pathology in asymptomatic risk mutation carriers. Future studies should focus on asymptomatic mutation carriers that are closer to symptom onset to capture the first specific signs that may differentiate between FTD and AD.

Rates of Amyloid Imaging Positivity in Patients With Primary Progressive Aphasia

Importance

The ability to predict the pathology underlying different neurodegenerative syndromes is of critical importance owing to the advent of molecule-specific therapies.

Objective

To determine the rates of positron emission tomography (PET) amyloid positivity in the main clinical variants of primary progressive aphasia (PPA).

Design, Setting, and Participants

This prospective clinical-pathologic case series was conducted at a tertiary research clinic specialized in cognitive disorders. Patients were evaluated as part of a prospective, longitudinal research study between January 2002 and December 2015. Inclusion criteria included clinical diagnosis of PPA; availability of complete speech, language, and cognitive testing; magnetic resonance imaging performed within 6 months of the cognitive evaluation; and PET carbon 11-labeled Pittsburgh Compound-B or florbetapir F 18 brain scan results. Of 109 patients referred for evaluation of language symptoms who underwent amyloid brain imaging, 3 were excluded because of incomplete language evaluations, 5 for absence of significant aphasia, and 12 for presenting with significant initial symptoms outside of the language domain, leaving a cohort of 89 patients with PPA.

Main Outcomes and Measures

Clinical, cognitive, neuroimaging, and pathology results.

Results

Twenty-eight cases were classified as imaging-supported semantic variant PPA (11 women [39.3%]; mean [SD] age, 64 [7] years), 31 nonfluent/agrammatic variant PPA (22 women [71.0%]; mean [SD] age, 68 [7] years), 26 logopenic variant PPA (17 women [65.4%]; mean [SD] age, 63 [8] years), and 4 mixed PPA cases. Twenty-four of 28 patients with semantic variant PPA (86%) and 28 of 31 patients with nonfluent/agrammatic variant PPA (90%) had negative amyloid PET scan results, while 25 of 26 patients with logopenic variant PPA (96%) and 3 of 4 mixed PPA cases (75%) had positive scan results. The amyloid positive semantic variant PPA and nonfluent/agrammatic variant PPA cases with available autopsy data (2 of 4 and 2 of 3, respectively) all had a primary frontotemporal lobar degeneration and secondary Alzheimer disease pathologic diagnoses, whereas autopsy of 2 patients with amyloid PET-positive logopenic variant PPA confirmed Alzheimer disease. One mixed PPA patient with a negative amyloid PET scan had Pick disease at autopsy.

Conclusions and Relevance

Primary progressive aphasia variant diagnosis according to the current classification scheme is associated with Alzheimer disease biomarker status, with the logopenic variant being associated with carbon 11-labeled Pittsburgh Compound-B positivity in more than 95% of cases. Furthermore, in the presence of a clinical syndrome highly predictive of frontotemporal lobar degeneration pathology, biomarker positivity for Alzheimer disease may be associated more with mixed pathology rather than primary Alzheimer disease.

An update on advances in magnetic resonance imaging of multiple system atrophy

In this review, we describe how different neuroimaging tools have been used to identify novel MSA biomarkers, highlighting their advantages and limitations. First, we describe the main structural MRI changes frequently associated with MSA including the 'hot cross-bun' and 'putaminal rim' signs as well as putaminal, pontine, and middle cerebellar peduncle (MCP) atrophy. We discuss the sensitivity and specificity of different supra- and infratentorial changes in differentiating MSA from other disorders, highlighting those that can improve diagnostic accuracy, including the MCP width and MCP/superior cerebellar peduncle (SCP) ratio on T1-weighted imaging, raised putaminal diffusivity on diffusion-weighted imaging, and increased T2* signal in the putamen, striatum, and substantia nigra on susceptibility-weighted imaging. Second, we focus on recent advances in structural and functional MRI techniques including diffusion tensor imaging (DTI), resting-state functional MRI (fMRI), and arterial spin labelling (ASL) imaging. Finally, we discuss new approaches for MSA research such as multimodal neuroimaging strategies and how such markers may be applied in clinical trials to provide crucial data for accurately selecting patients and to act as secondary outcome measures.

Exploring quantitative group-wise differentiation of Alzheimer's disease and behavioural variant frontotemporal dementia using tract-specific microstructural white matter and functional connectivity measures at multiple time points

Objectives

This study explored group-wise quantitative measures of tract-specific white matter (WM) microstructure and functional default mode network (DMN) connectivity to establish an initial indication of their clinical applicability for early-stage and follow-up differential diagnosis of Alzheimer’s disease (AD) and behavioural variant frontotemporal dementia (bvFTD).

Methods

Eleven AD and 12 bvFTD early-stage patients and 18 controls underwent diffusion tensor imaging and resting state functional magnetic resonance imaging at 3 T. All AD and 6 bvFTD patients underwent the same protocol at 1-year follow-up. Functional connectivity measures of DMN and WM tract-specific diffusivity measures were determined for all groups. Exploratory analyses were performed to compare all measures between the three groups at baseline and between patients at follow-up. Additionally, the difference between baseline and follow-up diffusivity measures in AD and bvFTD patients was compared.

Results

Functional connectivity of the DMN was not different between groups at baseline and at follow-up. Diffusion abnormalities were observed widely in bvFTD and regionally in the hippocampal cingulum in AD. The extent of the differences between bvFTD and AD was diminished at follow-up, yet abnormalities were still more pronounced in bvFTD. The rate of change was similar in bvFTD and AD.

Conclusions

This study provides a tentative indication that quantitative tract-specific microstructural WM abnormalities, but not quantitative functional connectivity of the DMN, may aid early-stage and follow-up differential diagnosis of bvFTD and AD. Specifically, pronounced microstructural changes in anterior WM tracts may characterise bvFTD, whereas microstructural abnormalities of the hippocampal cingulum may characterise AD.

Key Points

• The clinical applicability of quantitative brain imaging measures for early-stage and follow-up differential diagnosis of dementia subtypes was explored using a group-wise approach.

• Quantitative tract-specific microstructural white matter abnormalities, but not quantitative functional connectivity of the default mode network, may aid early-stage and follow-up differential diagnosis of behavioural variant frontotemporal dementia and Alzheimer’s disease.

• Pronounced microstructural white matter (WM) changes in anterior WM tracts characterise behavioural variant frontotemporal dementia, whereas microstructural WM abnormalities of the hippocampal cingulum in the absence of other WM changes characterise Alzheimer’s disease.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06061-7) contains supplementary material, which is available to authorized users.

Single-subject classification of presymptomatic frontotemporal dementia mutation carriers using multimodal MRI

BACKGROUND

Classification models based on magnetic resonance imaging (MRI) may aid early diagnosis of frontotemporal dementia (FTD) but have only been applied in established FTD cases. Detection of FTD patients in earlier disease stages, such as presymptomatic mutation carriers, may further advance early diagnosis and treatment. In this study, we aim to distinguish presymptomatic FTD mutation carriers from controls on an individual level using multimodal MRI-based classification.

METHODS

Anatomical MRI, diffusion tensor imaging (DTI) and resting-state functional MRI data were collected in 55 presymptomatic FTD mutation carriers (8 microtubule-associated protein Tau, 35 progranulin, and 12 chromosome 9 open reading frame 72) and 48 familial controls. We calculated grey and white matter density features from anatomical MRI scans, diffusivity features from DTI, and functional connectivity features from resting-state functional MRI. These features were applied in a recently introduced multimodal behavioural variant FTD (bvFTD) classification model, and were subsequently used to train and test unimodal and multimodal carrier-control models. Classification performance was quantified using area under the receiver operator characteristic curves (AUC).

RESULTS

The bvFTD model was not able to separate presymptomatic carriers from controls beyond chance level (AUC = 0.582, p = 0.078). In contrast, one unimodal and several multimodal carrier-control models performed significantly better than chance level. The unimodal model included the radial diffusivity feature and had an AUC of 0.642 (p = 0.032). The best multimodal model combined radial diffusivity and white matter density features (AUC = 0.684, p = 0.004).

CONCLUSIONS

FTD mutation carriers can be separated from controls with a modest AUC even before symptom-onset, using a newly created carrier-control classification model, while this was not possible using a recent bvFTD classification model. A multimodal MRI-based classification score may therefore be a useful biomarker to aid earlier FTD diagnosis. The exclusive selection of white matter features in the best performing model suggests that the earliest FTD-related pathological processes occur in white matter.

Primary progressive aphasia and the FTD-MND spectrum disorders: clinical, pathological, and neuroimaging correlates

Objective: Behavioral variant frontotemporal dementia (bvFTD), is commonly considered the cognitive presentation of the frontotemporal dementia-motor neuron disease (FTD-MND) spectrum disorder. We evaluated the prevalence of primary progressive aphasia in a series of pathologically confirmed cases of FTD-MND spectrum. Methods: Pathologically confirmed cases of frontotemporal lobar degeneration-motor neuron disease (FTLD-MND) were obtained from the UCSF brain bank. Cases were analyzed for presence of language impairment via retrospective chart review of research visits that include neurologic exam, in-depth cognitive testing and magnetic resonance imaging (MRI) imaging. Forty one cases were included. Thirty two were diagnosed with FTD-MND, while nine cases were diagnosed as MND-only from clinical evaluation. Results: Ten FTLD-MND cases (31%) presented with prominent or isolated language involvement consistent with a diagnosis of primary progressive aphasia (PPA), which we called progressive aphasia with motor neuron disease (PA-MND). Of these, three cases that mirrored the non-fluent variant of PPA (nfvPPA) were named nfvPA-MND. The imaging pattern of these nfvPA-MND showed atrophy strictly confined to the frontal and anterior temporal language cortical areas. Another group of seven cases that resembled patients with the semantic variant PPA (svPPA) were named svPA-MND. The group of svPPA-MND on imaging analysis showed selective atrophy of the temporal lobe and orbitofrontal cortex. Conclusions: Language impairment was a frequent phenotype of FTD-MND associated with focal atrophy patterns within the language networks. This data suggest patients with FTD-MND can present quite often with language phenotype of nfvPPA and svPPA, as opposed to exclusive bvFTD symptoms.

Longitudinal multimodal MRI as prognostic and diagnostic biomarker in presymptomatic familial frontotemporal dementia

Developing and validating sensitive biomarkers for the presymptomatic stage of familial frontotemporal dementia is an important step in early diagnosis and for the design of future therapeutic trials. In the longitudinal Frontotemporal Dementia Risk Cohort, presymptomatic mutation carriers and non-carriers from families with familial frontotemporal dementia due to microtubule-associated protein tau (MAPT) and progranulin (GRN) mutations underwent a clinical assessment and multimodal MRI at baseline, 2-, and 4-year follow-up. Of the cohort of 73 participants, eight mutation carriers (three GRN, five MAPT) developed clinical features of frontotemporal dementia ('converters'). Longitudinal whole-brain measures of white matter integrity (fractional anisotropy) and grey matter volume in these converters (n = 8) were compared with healthy mutation carriers ('non-converters'; n = 35) and non-carriers (n = 30) from the same families. We also assessed the prognostic performance of decline within white matter and grey matter regions of interest by means of receiver operating characteristic analyses followed by stepwise logistic regression. Longitudinal whole-brain analyses demonstrated lower fractional anisotropy values in extensive white matter regions (genu corpus callosum, forceps minor, uncinate fasciculus, and superior longitudinal fasciculus) and smaller grey matter volumes (prefrontal, temporal, cingulate, and insular cortex) over time in converters, present from 2 years before symptom onset. White matter integrity loss of the right uncinate fasciculus and genu corpus callosum provided significant classifiers between converters, non-converters, and non-carriers. Converters' within-individual disease trajectories showed a relatively gradual onset of clinical features in MAPT, whereas GRN mutations had more rapid changes around symptom onset. MAPT converters showed more decline in the uncinate fasciculus than GRN converters, and more decline in the genu corpus callosum in GRN than MAPT converters. Our study confirms the presence of spreading predominant frontotemporal pathology towards symptom onset and highlights the value of multimodal MRI as a prognostic biomarker in familial frontotemporal dementia.

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.

Single-subject classification of presymptomatic frontotemporal dementia mutation carriers using multimodal MRI

Background

Classification models based on magnetic resonance imaging (MRI) may aid early diagnosis of frontotemporal dementia (FTD) but have only been applied in established FTD cases. Detection of FTD patients in earlier disease stages, such as presymptomatic mutation carriers, may further advance early diagnosis and treatment. In this study, we aim to distinguish presymptomatic FTD mutation carriers from controls on an individual level using multimodal MRI-based classification.

Methods

Anatomical MRI, diffusion tensor imaging (DTI) and resting-state functional MRI data were collected in 55 presymptomatic FTD mutation carriers (8 microtubule-associated protein Tau, 35 progranulin, and 12 chromosome 9 open reading frame 72) and 48 familial controls. We calculated grey and white matter density features from anatomical MRI scans, diffusivity features from DTI, and functional connectivity features from resting-state functional MRI. These features were applied in a recently introduced multimodal behavioural variant FTD (bvFTD) classification model, and were subsequently used to train and test unimodal and multimodal carrier-control models. Classification performance was quantified using area under the receiver operator characteristic curves (AUC).

Results

The bvFTD model was not able to separate presymptomatic carriers from controls beyond chance level (AUC = 0.570, p = 0.11). In contrast, one unimodal and several multimodal carrier-control models performed significantly better than chance level. The unimodal model included the radial diffusivity feature and had an AUC of 0.646 (p = 0.021). The best multimodal model combined radial diffusivity and white matter density features (AUC = 0.680, p = 0.005).

Conclusions

FTD mutation carriers can be separated from controls with a modest AUC even before symptom-onset, using a newly created carrier-control classification model, while this was not possible using a recent bvFTD classification model. A multimodal MRI-based classification score may therefore be a useful biomarker to aid earlier FTD diagnosis. The exclusive selection of white matter features in the best performing model suggests that the earliest FTD-related pathological processes occur in white matter.

Using simultaneous PET/MRI to compare the accuracy of diagnosing frontotemporal dementia by arterial spin labelling MRI and FDG-PET

Purpose

The clinical utility of FDG-PET in diagnosing frontotemporal dementia (FTD) has been well demonstrated over the past decades. On the contrary, the diagnostic value of arterial spin labelling (ASL) MRI - a relatively new technique - in clinical diagnosis of FTD has yet to be confirmed. Using simultaneous PET/MRI, we evaluated the diagnostic performance of ASL in identifying pathological abnormalities in FTD (FTD) to determine whether ASL can provide similar diagnostic value as FDG-PET.

Methods

ASL and FDG-PET images were compared in 10 patients with FTD and 10 healthy older adults. Qualitative and quantitative measures of diagnostic equivalency were used to determine the diagnostic utility of ASL compared to FDG-PET. Sensitivity, specificity, and inter-rater reliability were calculated for each modality from scores of subjective visual ratings and from analysis of regional mean values in thirteen a priori regions of interest (ROI). To determine the extent of concordance between modalities in each patient, individual statistical maps generated from comparison of each patient to controls were compared between modalities using the Jaccard similarity index (JI).

Results

Visual assessments revealed lower sensitivity, specificity and inter-rater reliability for ASL (66.67%/62.12%/0.2) compared to FDG-PET (88.43%/90.91%/0.61). Across all regions, ASL performed lower than FDG-PET in discriminating patients from controls (areas under the receiver operating curve: ASL = 0.75 and FDG-PET = 0.87). In all patients, ASL identified patterns of reduced perfusion consistent with FTD, but areas of hypometabolism exceeded hypoperfused areas (group-mean JI = 0.30 ± 0.22).

Conclusion

This pilot study demonstrated that ASL can detect similar spatial patterns of abnormalities in individual FTD patients compared to FDG-PET, but its sensitivity and specificity for discriminant diagnosis of a patient from healthy individuals remained unmatched to FDG-PET. Further studies at the individual level are required to confirm the clinical role of ASL in FTD management.

Aberrant pattern of regional cerebral blood flow in Alzheimer's disease: a voxel-wise meta-analysis of arterial spin labeling MR imaging studies

Many studies have applied arterial spin labeling (ASL) to characterize cerebral perfusion patterns of Alzheimer's disease (AD). However, findings across studies are not conclusive. A quantitatively voxel-wise meta-analysis to pool the resting-state ASL studies that measure regional cerebral blood flow (rCBF) alterations in AD was conducted to identify the most consistent and replicable perfusion pattern using seed-based d mapping. The meta-analysis, including 17 ASL studies encompassing 327 AD patients and 357 healthy controls, demonstrated that decreased rCBF in AD patients relative to healthy controls were consistently identified in the bilateral posterior cingulate cortices (PCC)/precuneus, bilateral inferior parietal lobules (IPLs), and left dorsolateral prefrontal cortex. The meta-regression analysis showed that more severe cognitive impairment in the AD samples correlated with greater decreases of rCBF in the bilateral PCC and left IPL. This study characterizes an aberrant ASL-rCBF perfusion pattern of AD involving the posterior default mode network and executive network, which are implicated in its pathophysiology and hold promise for developing imaging biomarkers.

Feature selective temporal prediction of Alzheimer's disease progression using hippocampus surface morphometry

INTRODUCTION

Prediction of Alzheimer's disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end, we combine a predictive multi-task machine learning method (cFSGL) with a novel MR-based multivariate morphometric surface map of the hippocampus (mTBM) to predict future cognitive scores of patients.

METHODS

Previous work has shown that a multi-task learning framework that performs prediction of all future time points simultaneously (cFSGL) can be used to encode both sparsity as well as temporal smoothness. The authors showed that this method is able to predict cognitive outcomes of ADNI subjects using FreeSurfer-based baseline MRI features, MMSE score demographic information and ApoE status. Whilst volumetric information may hold generalized information on brain status, we hypothesized that hippocampus specific information may be more useful in predictive modeling of AD. To this end, we applied a multivariate tensor-based parametric surface analysis method (mTBM) to extract features from the hippocampal surfaces.

RESULTS

We combined mTBM features with traditional surface features such as middle axis distance, the Jacobian determinant as well as 2 of the Jacobian principal eigenvalues to yield 7 normalized hippocampal surface maps of 300 points each. By combining these 7 × 300 = 2100 features together with the previous ~350 features, we illustrate how this type of sparsifying method can be applied to an entire surface map of the hippocampus that yields a feature space that is 2 orders of magnitude larger than what was previously attempted.

CONCLUSIONS

By combining the power of the cFSGL multi-task machine learning framework with the addition of AD sensitive mTBM feature maps of the hippocampus surface, we are able to improve the predictive performance of ADAS cognitive scores 6, 12, 24, 36 and 48 months from baseline.

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.

Multiparametric MRI to distinguish early onset Alzheimer's disease and behavioural variant of frontotemporal dementia

This prospective study explored whether an approach combining structural [cortical thickness and white matter (WM) microstructure] and resting state functional MRI can aid differentiation between 62 early onset Alzheimer's disease (EOAD) and 27 behavioural variant of frontotemporal dementia (bvFTD) patients. Random forest and receiver operator characteristic curve analyses assessed the ability of MRI in classifying the two clinical syndromes. All patients showed a distributed pattern of brain alterations relative to controls. Compared to bvFTD, EOAD patients showed bilateral inferior parietal cortical thinning and decreased default mode network functional connectivity. Compared to EOAD, bvFTD patients showed bilateral orbitofrontal and temporal cortical thinning, and WM damage of the corpus callosum, bilateral uncinate fasciculus, and left superior longitudinal fasciculus. Random forest analysis revealed that left inferior parietal cortical thickness (accuracy 0.78, specificity 0.76, sensitivity 0.83) and WM integrity of the right uncinate fasciculus (accuracy 0.81, specificity 0.96, sensitivity 0.43) were the best predictors of clinical diagnosis. The combination of cortical thickness and DT MRI measures was able to distinguish patients with EOAD and bvFTD with accuracy 0.82, specificity 0.76, and sensitivity 0.96. The diagnostic ability of MRI models was confirmed in a subsample of patients with biomarker-based clinical diagnosis. Multiparametric MRI is useful to identify brain alterations which are specific to EOAD and bvFTD. A severe cortical involvement is suggestive of EOAD, while a prominent WM damage is indicative of bvFTD.

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Multimodal MRI distinguishes in vivo EOAD and bvFTD patients

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EOAD and bvFTD show a distributed pattern of structural brain alterations

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A severe cortical involvement is suggestive of EOAD relative to bvFTD

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A prominent WM damage is indicative of bvFTD relative to EOAD

Features of Patients With Nonfluent/Agrammatic Primary Progressive Aphasia With Underlying Progressive Supranuclear Palsy Pathology or Corticobasal Degeneration

IMPORTANCE

We provide novel evidence of specific clinical and neuroimaging features that may help for the in vivo prediction of underlying pathology in patients with nonfluent/agrammatic primary progressive aphasia (nfvPPA) and progressive supranuclear palsy (PSP) or corticobasal degeneration (CBD) proved by autopsy.

OBJECTIVE

To characterize the neurological, cognitive, and neuroimaging features of patients with nfvPPA-in whom either PSP or CBD was eventually confirmed at autopsy-at initial presentation and at 1-year follow-up.

DESIGN, SETTING, AND PARTICIPANTS

A prospective longitudinal clinical-pathological study was conducted in a tertiary research clinic that specialized in cognitive disorders. Fourteen patients were evaluated between January 2002 and December 2014. Inclusion criteria for the study were a clinical diagnosis of nfvPPA; the availability of speech, language, and cognitive testing for at least 1 evaluation; magnetic resonance imaging within 6 months of initial evaluation; and a postmortem pathological diagnosis of PSP or CBD. Ten matched healthy control participants were also included.

MAIN OUTCOMES AND MEASURES

Clinical, cognitive, and neuroimaging longitudinal data were analyzed to characterize the whole nfvPPA-4-repeat-tau group and identify differences between nfvPPA-PSP and nfvPPA-CBD both at presentation and longitudinally.

RESULTS

Patient groups did not differ significantly in age, sex, or handedness (nfvPPA-PSP group: median [interquartile range (IQR)] age, 74 [67-76] years; 1 of 5 male [20%]; 1 of 5 left-handed [20%]; and nfvPPA-CBD group: mean [IQR] age, 65 [54-81] years; 3 of 9 male [33%]; 0 left-handed). Motor speech impairment and left frontal white matter atrophy were the most prominent common features. At presentation, dysarthria (Motor Speech Examination median [IQR] score: nfvPPA-PSP, 4 [2-7]; nfvPPA-CBD, 0 [0-4]; P = .02), depression (Geriatric Depression Scale median [IQR] score: nfvPPA-PSP, 19 [3-28]; nfvPPA-CBD, 4 [0-16]; P = .04), and relatively selective white matter atrophy were typical of the nfvPPA-PSP group, while greater gray matter atrophy and a trend toward greater sentence comprehension deficits (median [IQR] sentence comprehension correct: nfvPPA-PSP, 98% [80-100]; nfvPPA-CBD, 81% [65-98]; P = .08) were found in the nfvPPA-CBD group. At follow-up after 1 year, we observed no significant differences in any speech or language measures. Furthermore, atrophy in patients with PSP progressed within the subcortical/brainstem motor system generating greater oculomotors deficits and swallowing difficulty; atrophy in patients with CBD spread anteriorly in prefrontal regions consistent with their greater working memory impairment and development of behavioral symptoms.

CONCLUSIONS AND RELEVANCE

In patients presenting with nfvPPA, presence of early severe dysarthria, relatively selective white matter atrophy at presentation, and a greater rate of change in the brainstem measured by longitudinal imaging may be useful for differentiating underlying PSP from CBD pathology during life.

Typical and atypical pathology in primary progressive aphasia variants

OBJECTIVE

To characterize in vivo signatures of pathological diagnosis in a large cohort of patients with primary progressive aphasia (PPA) variants defined by current diagnostic classification.

METHODS

Extensive clinical, cognitive, neuroimaging, and neuropathological data were collected from 69 patients with sporadic PPA, divided into 29 semantic (svPPA), 25 nonfluent (nfvPPA), 11 logopenic (lvPPA), and 4 mixed PPA. Patterns of gray matter (GM) and white matter (WM) atrophy at presentation were assessed and tested as predictors of pathological diagnosis using support vector machine (SVM) algorithms.

RESULTS

A clinical diagnosis of PPA was associated with frontotemporal lobar degeneration (FTLD) with transactive response DNA-binding protein (TDP) inclusions in 40.5%, FTLD-tau in 40.5%, and Alzheimer disease (AD) pathology in 19% of cases. Each variant was associated with 1 typical pathology; 24 of 29 (83%) svPPA showed FTLD-TDP type C, 22 of 25 (88%) nfvPPA showed FTLD-tau, and all 11 lvPPA had AD. Within FTLD-tau, 4R-tau pathology was commonly associated with nfvPPA, whereas Pick disease was observed in a minority of subjects across all variants except for lvPPA. Compared with pathologically typical cases, svPPA-tau showed significant extrapyramidal signs, greater executive impairment, and severe striatal and frontal GM and WM atrophy. nfvPPA-TDP patients lacked general motor symptoms or significant WM atrophy. Combining GM and WM volumes, SVM analysis showed 92.7% accuracy to distinguish FTLD-tau and FTLD-TDP pathologies across variants.

INTERPRETATION

Each PPA clinical variant is associated with a typical and most frequent cognitive, neuroimaging, and neuropathological profile. Specific clinical and early anatomical features may suggest rare and atypical pathological diagnosis in vivo. Ann Neurol 2017;81:430-443.

Multiparametric computer-aided differential diagnosis of Alzheimer's disease and frontotemporal dementia using structural and advanced MRI

Objectives

To investigate the added diagnostic value of arterial spin labelling (ASL) and diffusion tensor imaging (DTI) to structural MRI for computer-aided classification of Alzheimer's disease (AD), frontotemporal dementia (FTD), and controls.

Methods

This retrospective study used MRI data from 24 early-onset AD and 33 early-onset FTD patients and 34 controls (CN). Classification was based on voxel-wise feature maps derived from structural MRI, ASL, and DTI. Support vector machines (SVMs) were trained to classify AD versus CN (AD-CN), FTD-CN, AD-FTD, and AD-FTD-CN (multi-class). Classification performance was assessed by the area under the receiver-operating-characteristic curve (AUC) and accuracy. Using SVM significance maps, we analysed contributions of brain regions.

Results

Combining ASL and DTI with structural MRI resulted in higher classification performance for differential diagnosis of AD and FTD (AUC = 84%; p = 0.05) than using structural MRI by itself (AUC = 72%). The performance of ASL and DTI themselves did not improve over structural MRI. The classifications were driven by different brain regions for ASL and DTI than for structural MRI, suggesting complementary information.

Conclusions

ASL and DTI are promising additions to structural MRI for classification of early-onset AD, early-onset FTD, and controls, and may improve the computer-aided differential diagnosis on a single-subject level.

Key points

• Multiparametric MRI is promising for computer-aided diagnosis of early-onset AD and FTD.

• Diagnosis is driven by different brain regions when using different MRI methods.

• Combining structural MRI, ASL, and DTI may improve differential diagnosis of dementia.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-016-4691-x) contains supplementary material, which is available to authorized users.

Diagnostic utility of ASL-MRI and FDG-PET in the behavioral variant of FTD and AD

Objective

To compare the values of arterial spin‐labeled (ASL) MRI and fluorodeoxyglucose (FDG) PET in the diagnosis of behavioral variant of frontotemporal dementia (bvFTD) and Alzheimer's disease (AD).

Methods

Partial least squares logistic regression was used to identify voxels with diagnostic value in cerebral blood flow (CBF) and cerebral metabolic rate of glucose (CMRgl) maps from patients with bvFTD (n = 32) and AD (n = 28), who were compared with each other and with cognitively normal controls (CN, n = 15). Diagnostic values of these maps were compared with each other.

Results

Regions that differentiated each disorder from controls were similar for CBF and CMRgl. For differentiating AD from CN, the areas under the curve (AUC) for CBF (0.89) and CMRgl (0.91) were similar, with similar sensitivity (CBF: 86%, CMRgl: 78%) and specificity (CBF: 92%, CMRgl: 100%). Likewise, for differentiating bvFTD from CN performances of CBF (AUC = 0.83) and CMRgl (AUC = 0.85) were equivalent, with similar sensitivity (CBF: 78%, CMRgl: 79%) and specificity (CBF: 92%, CMRgl: 100%). In differentiating bvFTD from AD, classification was again similar for CBF (AUC = 0.87) and CMRgl (AUC = 0.79), as were sensitivity (CBF: 83%, CMRgl: 89%) and specificity (CBF: 93%, CMRgl: 78%). None of the differences in any performance measure were statistically significant.

Interpretation

ASL‐MRI has similar diagnostic utility as FDG‐PET in the diagnosis of AD and bvFTD. Continued development of ASL‐MRI as a diagnostic tool for neurodegenerative dementias is warranted.

Cerebral blood flow in presymptomatic MAPT and GRN mutation carriers: A longitudinal arterial spin labeling study

Objective

Frontotemporal dementia (FTD) is characterized by behavioral disturbances and language problems. Familial forms can be caused by genetic defects in microtubule-associated protein tau (MAPT), progranulin (GRN), and C9orf72. In light of upcoming clinical trials with potential disease-modifying agents, the development of sensitive biomarkers to evaluate such agents in the earliest stage of FTD is crucial. In the current longitudinal study we used arterial spin labeling MRI (ASL) in presymptomatic carriers of MAPT and GRN mutations to investigate early changes in cerebral blood flow (CBF).

Methods

Healthy first-degree relatives of patients with a MAPT or GRN mutation underwent ASL at baseline and follow-up after two years. We investigated cross-sectional and longitudinal differences in CBF between mutation carriers (n = 34) and controls without a mutation (n = 31).

Results

GRN mutation carriers showed significant frontoparietal hypoperfusion compared with controls at follow-up, whereas we found no cross-sectional group differences in the total study group or the MAPT subgroup. Longitudinal analyses revealed a significantly stronger decrease in CBF in frontal, temporal, parietal, and subcortical areas in the total group of mutation carriers and the GRN subgroup, with the strongest decrease in two mutation carriers who converted to clinical FTD during follow-up.

Interpretation

We demonstrated longitudinal alterations in CBF in presymptomatic FTD independent of grey matter atrophy, with the strongest decrease in individuals that developed symptoms during follow-up. Therefore, ASL could have the potential to serve as a sensitive biomarker of disease progression in the presymptomatic stage of FTD in future clinical trials.

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Longitudinal alterations in cerebral blood flow in presymptomatic FTD

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Larger decline in cerebral blood flow during conversion to symptomatic FTD

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Arterial spin labeling might provide a useful biomarker for therapeutic trials.

Structural and functional brain abnormalities place phenocopy frontotemporal dementia (FTD) in the FTD spectrum

Purpose

‘Phenocopy’ frontotemporal dementia (phFTD) patients may clinically mimic the behavioral variant of FTD (bvFTD), but do not show functional decline or abnormalities upon visual inspection of routine neuroimaging. We aimed to identify abnormalities in gray matter (GM) volume and perfusion in phFTD and to assess whether phFTD belongs to the FTD spectrum. We compared phFTD patients with both healthy controls and bvFTD patients.

Materials & methods

Seven phFTD and 11 bvFTD patients, and 20 age-matched controls underwent structural T1-weighted magnetic resonance imaging (MRI) and 3D pseudo-continuous arterial spin labeling (pCASL) at 3T. Normalized GM (nGM) volumes and perfusion, corrected for partial volume effects, were quantified regionally as well as in the entire supratentorial cortex, and compared between groups taking into account potential confounding effects of gender and scanner.

Results

PhFTD patients showed cortical atrophy, most prominently in the right temporal lobe. Apart from this regional atrophy, GM volume was generally not different from either controls or from bvFTD. BvFTD however showed extensive frontotemporal atrophy. Perfusion was increased in the left prefrontal cortex compared to bvFTD and to a lesser extent to controls.

Conclusion

PhFTD and bvFTD show overlapping cortical structural abnormalities indicating a continuum of changes especially in the frontotemporal regions. Together with functional changes suggestive of a compensatory response to incipient pathology in the left prefrontal regions, these findings are the first to support a possible neuropathological etiology of phFTD and suggest that phFTD may be a neurodegenerative disease on the FTD spectrum.

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Both phFTD and bvFTD show frontotemporal cortical structural abnormalities.

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PhFTD shows left frontal hyperperfusion, suggestive of functional compensation.

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Overlapping findings in phFTD and bvFTD findings suggest a common disease spectrum.

A brain stress test: Cerebral perfusion during memory encoding in mild cognitive impairment

Arterial spin labeled perfusion magnetic resonance imaging (ASL MRI) provides non-invasive quantification of cerebral blood flow, which can be used as a biomarker of brain function due to the tight coupling between cerebral blood flow (CBF) and brain metabolism. A growing body of literature suggests that regional CBF is altered in neurodegenerative diseases. Here we examined ASL MRI CBF in subjects with amnestic mild cognitive impairment (n = 65) and cognitively normal healthy controls (n = 62), both at rest and during performance of a memory-encoding task. As compared to rest, task-enhanced ASL MRI improved group discrimination, which supports the notion that physiologic measures during a cognitive challenge, or "stress test", may increase the ability to detect subtle functional changes in early disease stages. Further, logistic regression analysis demonstrated that ASL MRI and concomitantly acquired structural MRI provide complementary information of disease status. The current findings support the potential utility of task-enhanced ASL MRI as a biomarker in early Alzheimer's disease.

Joint assessment of white matter integrity, cortical and subcortical atrophy to distinguish AD from behavioral variant FTD: A two-center study

We investigated the ability of cortical and subcortical gray matter (GM) atrophy in combination with white matter (WM) integrity to distinguish behavioral variant frontotemporal dementia (bvFTD) from Alzheimer's disease (AD) and from controls using voxel-based morphometry, subcortical structure segmentation, and tract-based spatial statistics. To determine which combination of MR markers differentiated the three groups with the highest accuracy, we conducted discriminant function analyses. Adjusted for age, sex and center, both types of dementia had more GM atrophy, lower fractional anisotropy (FA) and higher mean (MD), axial (L1) and radial diffusivity (L23) values than controls. BvFTD patients had more GM atrophy in orbitofrontal and inferior frontal areas than AD patients. In addition, caudate nucleus and nucleus accumbens were smaller in bvFTD than in AD. FA values were lower; MD, L1 and L23 values were higher, especially in frontal areas of the brain for bvFTD compared to AD patients. The combination of cortical GM, hippocampal volume and WM integrity measurements, classified 97-100% of controls, 81-100% of AD and 67-75% of bvFTD patients correctly. Our results suggest that WM integrity measures add complementary information to measures of GM atrophy, thereby improving the classification between AD and bvFTD.

Early-stage differentiation between presenile Alzheimer's disease and frontotemporal dementia using arterial spin labeling MRI

Objective

To investigate arterial spin labeling (ASL)-MRI for the early diagnosis of and differentiation between the two most common types of presenile dementia: Alzheimer’s disease (AD) and frontotemporal dementia (FTD), and for distinguishing age-related from pathological perfusion changes.

Methods

Thirteen AD and 19 FTD patients, and 25 age-matched older and 22 younger controls underwent 3D pseudo-continuous ASL-MRI at 3 T. Gray matter (GM) volume and cerebral blood flow (CBF), corrected for partial volume effects, were quantified in the entire supratentorial cortex and in 10 GM regions. Sensitivity, specificity and diagnostic performance were evaluated in regions showing significant CBF differences between patient groups or between patients and older controls.

Results

AD compared with FTD patients had hypoperfusion in the posterior cingulate cortex, differentiating these with a diagnostic performance of 74 %. Compared to older controls, FTD patients showed hypoperfusion in the anterior cingulate cortex, whereas AD patients showed a more widespread regional hypoperfusion as well as atrophy. Regional atrophy was not different between AD and FTD. Diagnostic performance of ASL to differentiate AD or FTD from controls was good (78-85 %). Older controls showed global hypoperfusion compared to young controls.

Conclusion

ASL-MRI contributes to early diagnosis of and differentiation between presenile AD and FTD.

Key Points

• ASL-MRI facilitates differentiation of early Alzheimer’s disease and frontotemporal dementia.

• Posterior cingulate perfusion is lower in Alzheimer’s disease than frontotemporal dementia.

• Compared to controls, Alzheimer’s disease patients show hypoperfusion in multiple regions.

• Compared to controls, frontotemporal dementia patients show focal anterior cingulate hypoperfusion.

• Global decreased perfusion in older adults differs from hypoperfusion in dementia.

White matter disease contributes to apathy and disinhibition in behavioral variant frontotemporal dementia

OBJECTIVE

To relate changes in fractional anisotropy associated with behavioral variant frontotemporal dementia to measures of apathy and disinhibition.

BACKGROUND

Apathy and disinhibition are the 2 most common behavioral features of behavioral variant frontotemporal dementia, and these symptoms are associated with accelerated patient decline and caregiver stress. However, little is known about how white matter disease contributes to these symptoms.

METHODS

We collected neuropsychiatric data, volumetric magnetic resonance imaging, and diffusion-weighted imaging in 11 patients who met published criteria for behavioral variant frontotemporal dementia and had an autopsy-validated cerebrospinal fluid profile consistent with frontotemporal lobar degeneration. We also collected imaging data on 34 healthy seniors for analyses defining regions of disease in the patients. We calculated and analyzed fractional anisotropy with a white matter tract-specific method. This approach uses anatomically guided data reduction to increase sensitivity, and localizes results within canonically defined tracts. We used nonparametric, cluster-based statistical analysis to relate fractional anisotropy to neuropsychiatric measures of apathy and disinhibition.

RESULTS

The patients with behavioral variant frontotemporal dementia had widespread reductions in fractional anisotropy in anterior portions of frontal and temporal white matter, compared to the controls. Fractional anisotropy correlated with apathy in the left uncinate fasciculus and with disinhibition in the right corona radiata.

CONCLUSIONS

In patients with behavioral variant frontotemporal dementia, apathy and disinhibition are associated with distinct regions of white matter disease. The implicated fiber tracts likely support frontotemporal networks that are involved in goal-directed behavior.

Using structural and diffusion magnetic resonance imaging to differentiate the dementias

Dementia is one of the major causes of personal, societal and financial dependence in older people and in today's ageing society there is a pressing need for early and accurate markers of cognitive decline. There are several subtypes of dementia but the four most common are Alzheimer's disease, Lewy body dementia, vascular dementia and frontotemporal dementia. These disorders can only be diagnosed at autopsy, and ante-mortem assessments of "probable dementia (e.g. of Alzheimer type)" are traditionally driven by clinical symptoms of cognitive or behavioural deficits. However, owing to the overlapping nature of symptoms and age of onset, a significant proportion of dementia cases remain incorrectly diagnosed. Misdiagnosis can have an extensive impact, both at the level of the individual, who may not be offered the appropriate treatment, and on a wider scale, by influencing the entry of patients into relevant clinical trials. Magnetic resonance imaging (MRI) may help to improve diagnosis by providing non-invasive and detailed disease-specific markers of cognitive decline. MRI-derived measurements of grey and white matter structural integrity are potential surrogate markers of disease progression, and may also provide valuable diagnostic information. This review summarises the latest evidence on the use of structural and diffusion MRI in differentiating between the four major dementia subtypes.

Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography

Introduction

Group comparisons demonstrate greater visuospatial and memory deficits and temporoparietal-predominant degeneration on neuroimaging in patients with corticobasal syndrome (CBS) found to have Alzheimer’s disease (AD) pathology versus those with underlying frontotemporal lobar degeneration (FTLD). The value of these features in predicting underlying AD pathology in individual patients is unknown. The goal of this study is to evaluate the utility of modified clinical criteria and visual interpretations of magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) for predicting amyloid deposition (as a surrogate of Alzheimer’s disease neuropathology) in patients presenting with CBS.

Methods

In total, 25 patients meeting CBS core criteria underwent amyloid (Pittsburgh compound B; PIB) PET scans. Clinical records, MRI, and FDG scans were reviewed blinded to PIB results. Modified clinical criteria were used to classify CBS patients as temporoparietal variant CBS (tpvCBS) or frontal variant CBS (fvCBS). MRI and FDG-PET were classified based on the predominant atrophy/hypometabolism pattern (frontal or temporoparietal).

Results

A total of 9 out of 13 patients classified as tpvCBS were PIB+, compared to 2out of 12 patients classified as fvCBS (P < 0.01, sensitivity 82%, specificity 71% for PIB+ status). Visual MRI reads had 73% sensitivity and 46% specificity for PIB+ status with moderate intra-rater reliability (Cohen’s kappa = 0.42). Visual FDG reads had higher sensitivity (91%) for PIB+ status with perfect intra-rater reliability (kappa = 1.00), though specificity was low (50%). PIB results were confirmed in all 8 patients with available histopathology (3 PIB+ with confirmed AD, 5 PIB- with FTLD).

Conclusions

Splitting CBS patients into frontal or temporoparietal clinical variants can help predict the likelihood of underlying AD, but criteria require further refinement. Temporoparietal-predominant neuroimaging patterns are sensitive but not specific for AD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-014-0093-y) contains supplementary material, which is available to authorized users.

Neuroimaging of dementia

Dementia, whether secondary to Alzheimer disease or another process, is a significant cause of morbidity and mortality worldwide. Although dementia remains a clinical diagnosis, for many years imaging has served as a key component in the assessment of patients with cognitive impairment. There have been tremendous advancements in the neuroimaging of dementia over the past decade, moving the field past the rule-out dogma toward ruling in specific pathophysiologic processes. This article is written for the practicing clinician, to provide a review of neuroimaging findings associated with selected degenerative and nondegenerative forms of dementia.

Profiles of white matter tract pathology in frontotemporal dementia

Despite considerable interest in improving clinical and neurobiological characterisation of frontotemporal dementia and in defining the role of brain network disintegration in its pathogenesis, information about white matter pathway alterations in frontotemporal dementia remains limited. Here we investigated white matter tract damage using an unbiased, template-based diffusion tensor imaging (DTI) protocol in a cohort of 27 patients with the behavioral variant of frontotemporal dementia (bvFTD) representing both major genetic and sporadic forms, in relation both to healthy individuals and to patients with Alzheimer's disease. Widespread white matter tract pathology was identified in the bvFTD group compared with both healthy controls and Alzheimer's disease group, with prominent involvement of uncinate fasciculus, cingulum bundle and corpus callosum. Relatively discrete and distinctive white matter profiles were associated with genetic subgroups of bvFTD associated with MAPT and C9ORF72 mutations. Comparing diffusivity metrics, optimal overall separation of the bvFTD group from the healthy control group was signalled using radial diffusivity, whereas optimal overall separation of the bvFTD group from the Alzheimer's disease group was signalled using fractional anisotropy. Comparing white matter changes with regional grey matter atrophy (delineated using voxel based morphometry) in the bvFTD cohort revealed co-localisation between modalities particularly in the anterior temporal lobe, however white matter changes extended widely beyond the zones of grey matter atrophy. Our findings demonstrate a distributed signature of white matter alterations that is likely to be core to the pathophysiology of bvFTD and further suggest that this signature is modulated by underlying molecular pathologies.

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.

The power of neuroimaging biomarkers for screening frontotemporal dementia

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative disease that can result from either frontotemporal lobar degeneration (FTLD) or Alzheimer's disease (AD) pathology. It is critical to establish statistically powerful biomarkers that can achieve substantial cost-savings and increase the feasibility of clinical trials. We assessed three broad categories of neuroimaging methods to screen underlying FTLD and AD pathology in a clinical FTD series: global measures (e.g., ventricular volume), anatomical volumes of interest (VOIs) (e.g., hippocampus) using a standard atlas, and data-driven VOIs using Eigenanatomy. We evaluated clinical FTD patients (N = 93) with cerebrospinal fluid, gray matter (GM) magnetic resonance imaging (MRI), and diffusion tensor imaging (DTI) to assess whether they had underlying FTLD or AD pathology. Linear regression was performed to identify the optimal VOIs for each method in a training dataset and then we evaluated classification sensitivity and specificity in an independent test cohort. Power was evaluated by calculating minimum sample sizes required in the test classification analyses for each model. The data-driven VOI analysis using a multimodal combination of GM MRI and DTI achieved the greatest classification accuracy (89% sensitive and 89% specific) and required a lower minimum sample size (N = 26) relative to anatomical VOI and global measures. We conclude that a data-driven VOI approach using Eigenanatomy provides more accurate classification, benefits from increased statistical power in unseen datasets, and therefore provides a robust method for screening underlying pathology in FTD patients for entry into clinical trials.

Handedness and language learning disability differentially distribute in progressive aphasia variants

Primary progressive aphasia is a neurodegenerative clinical syndrome that presents in adulthood with an isolated, progressive language disorder. Three main clinical/anatomical variants have been described, each associated with distinctive pathology. A high frequency of neurodevelopmental learning disability in primary progressive aphasia has been reported. Because the disorder is heterogeneous with different patterns of cognitive, anatomical and biological involvement, we sought to identify whether learning disability had a predilection for one or more of the primary progressive aphasia subtypes. We screened the University of California San Francisco Memory and Aging Center's primary progressive aphasia cohort (n = 198) for history of language-related learning disability as well as hand preference, which has associations with learning disability. The study included logopenic (n = 48), non-fluent (n = 54) and semantic (n = 96) variant primary progressive aphasias. We investigated whether the presence of learning disability or non-right-handedness was associated with differential effects on demographic, neuropsychological and neuroimaging features of primary progressive aphasia. We showed that a high frequency of learning disability was present only in the logopenic group (χ(2) = 15.17, P < 0.001) and (χ(2) = 11.51, P < 0.001) compared with semantic and non-fluent populations. In this group, learning disability was associated with earlier onset of disease, more isolated language symptoms, and more focal pattern of left posterior temporoparietal atrophy. Non-right-handedness was instead over-represented in the semantic group, at nearly twice the prevalence of the general population (χ(2) = 6.34, P = 0.01). Within semantic variant primary progressive aphasia the right-handed and non-right-handed cohorts appeared homogeneous on imaging, cognitive profile, and structural analysis of brain symmetry. Lastly, the non-fluent group showed no increase in learning disability or non-right-handedness. Logopenic variant primary progressive aphasia and developmental dyslexia both manifest with phonological disturbances and posterior temporal involvement. Learning disability might confer vulnerability of this network to early-onset, focal Alzheimer's pathology. Left-handedness has been described as a proxy for atypical brain hemispheric lateralization. As non-right-handedness was increased only in the semantic group, anomalous lateralization mechanisms might instead be related to frontotemporal lobar degeneration with abnormal TARDBP. Taken together, this study suggests that neurodevelopmental signatures impart differential trajectories towards neurodegenerative disease.

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.

Modular reorganization of brain resting state networks and its independent validation in Alzheimer's disease patients

Previous studies have demonstrated disruption in structural and functional connectivity occurring in the Alzheimer's Disease (AD). However, it is not known how these disruptions alter brain network reorganization. With the modular analysis method of graph theory, and datasets acquired by the resting-state functional connectivity MRI (R-fMRI) method, we investigated and compared the brain organization patterns between the AD group and the cognitively normal control (CN) group. Our main finding is that the largest homotopic module (defined as the insula module) in the CN group was broken down to the pieces in the AD group. Specifically, it was discovered that the eight pairs of the bilateral regions (the opercular part of inferior frontal gyrus, area triangularis, insula, putamen, globus pallidus, transverse temporal gyri, superior temporal gyrus, and superior temporal pole) of the insula module had lost symmetric functional connection properties, and the corresponding gray matter concentration (GMC) was significant lower in AD group. We further quantified the functional connectivity changes with an index (index A) and structural changes with the GMC index in the insula module to demonstrate their great potential as AD biomarkers. We further validated these results with six additional independent datasets (271 subjects in six groups). Our results demonstrated specific underlying structural and functional reorganization from young to old, and for diseased subjects. Further, it is suggested that by combining the structural GMC analysis and functional modular analysis in the insula module, a new biomarker can be developed at the single-subject level.

Diffusion tensor tractography versus volumetric imaging in the diagnosis of behavioral variant frontotemporal dementia

MRI diffusion tensor imaging (DTI) studies of white matter integrity in behavioral variant frontotemporal dementia have consistently shown involvement of frontal and temporal white matter, corresponding to regional loss of cortical volume. Volumetric imaging has a suboptimal sensitivity as a diagnostic tool and thus we wanted to explore if DTI is a better method to discriminate patients and controls than volumetric imaging. We examined the anterior cingulum bundle in 14 patients with behavioral variant frontotemporal dementia and 22 healthy controls using deterministic manual diffusion tensor tractography, and compared DTI parameters with two measures of cortical atrophy, VBM and cortical thickness, of the anterior cingulate cortex (ACC). Statistically significant changes between patients and controls were detected in all DTI parameters, with large effect sizes. ROC-AUC was for the best DTI parameters: 0.92 (fractional anisotropy) to 0.97 (radial diffusivity), 0.82 for the best cortical parameter, VBM of the ACC. Results from the AUC were confirmed with binary logistic regression analysis including demographic variables, but only for fractional anisotropy and mean diffusivity. Ability to classify patient/nonpatient status was significantly better for mean diffusivity vs. VBM (p=0.031), and borderline significant for fractional anisotropy vs. VBM (p=0.062). The results indicate that DTI could offer advantages in comparison with the assessment of cortical volume in differentiating patients with behavioral variant frontotemporal dementia and controls.

White Matter Lesion Assessment in Patients with Cognitive Impairment and Healthy Controls: Reliability Comparisons between Visual Rating, a Manual, and an Automatic Volumetrical MRI Method-The Gothenburg MCI Study

Age-related white matter lesions (WML) are a risk factor for stroke, cognitive decline, and dementia. Different requirements are imposed on methods for the assessment of WML in clinical settings and for research purposes, but reliability analysis is of major importance. In this study, WML assessment with three different methods was evaluated. In the Gothenburg mild cognitive impairment study, MRI scans from 152 participants were used to assess WML with the Fazekas visual rating scale on T2 images, a manual volumetric method on FLAIR images, and FreeSurfer volumetry on T1 images. Reliability was acceptable for all three methods. For low WML volumes (2/3 of the patients), reliability was overall lower and nonsignificant for the manual volumetric method. Unreliability in the assessment of patients with low WML with manual volumetry may mainly be due to intensity variation in the FLAIR sequence used; hence, intensity standardization and normalization methods must be used for more accurate assessments. The FreeSurfer segmentations resulted in smaller WML volumes than the volumes acquired with the manual method and showed deviations from visible hypointensities in the T1 images, which quite likely reduces validity.

Can MRI screen for CSF biomarkers in neurodegenerative disease?

OBJECTIVE

Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD) may have overlapping clinical presentations despite distinct underlying neuropathologies, thus making in vivo diagnosis challenging. In this study, we evaluate the utility of MRI as a noninvasive screening procedure for the differential diagnosis of AD and FTLD.

METHODS

We recruited 185 patients with a clinically diagnosed neurodegenerative disease consistent with AD or FTLD who had a lumbar puncture and a volumetric MRI. A subset of 32 patients had genetic or autopsy-confirmed AD or FTLD. We used singular value decomposition to decompose MRI volumes and linear regression and cross-validation to predict CSF total tau (tt) and β-amyloid (Aβ(1-42)) ratio (tt/Aβ) in patients with AD and patients with FTLD. We then evaluated accuracy of MRI-based predicted tt/Aβ using 4 converging sources including neuroanatomic visualization and categorization of a subset of patients with genetic or autopsy-confirmed AD or FTLD.

RESULTS

Regression analyses showed that MRI-predicted tt/Aβ is highly related to actual CSF tt/Aβ. In each group, both predicted and actual CSF tt/Aβ have extensively overlapping neuroanatomic correlates: low tt/Aβ consistent with FTLD is related to ventromedial prefrontal regions while high tt/Aβ consistent with AD is related to posterior cortical regions. MRI-predicted tt/Aβ is 75% accurate at identifying underlying diagnosis in patients with known pathology and in clinically diagnosed patients with known CSF tt/Aβ levels.

CONCLUSION

MRI may serve as a noninvasive procedure that can screen for AD and FTLD pathology as a surrogate for CSF biomarkers.

Frontotemporal dementia due to C9ORF72 mutations: clinical and imaging features

OBJECTIVE

To describe the phenotype of patients with C9FTD/ALS (C9ORF72) hexanucleotide repeat expansion.

METHODS

A total of 648 patients with frontotemporal dementia (FTD)-related clinical diagnoses and Alzheimer disease (AD) dementia were tested for C9ORF72 expansion and 31 carried expanded repeats (C9+). Clinical and neuroimaging data were compared between C9+ (15 behavioral variant FTD [bvFTD], 11 FTD-motor neuron disease [MND], 5 amyotrophic lateral sclerosis [ALS]) and sporadic noncarriers (48 bvFTD, 19 FTD-MND, 6 ALS).

RESULTS

All C9+ patients displayed clinical syndromes of bvFTD, ALS, or FTD-MND. At first evaluation, C9+ bvFTD patients had more delusions and greater impairment of working memory, but milder eating dysregulation compared to bvFTD noncarriers. C9+FTD-MND patients had a trend for longer survival and had an earlier age at onset than FTD-MND noncarriers. Voxel-based morphometry demonstrated more thalamic atrophy in FTD and FTD-MND carriers than in noncarriers.

CONCLUSIONS

Patients with the C9ORF72 hexanucleotide repeat expansion develop bvFTD, ALS, or FTD-MND with similar clinical and imaging features to sporadic cases. Other FTD spectrum diagnoses and AD dementia appear rare or absent among C9+ individuals. Longer survival in C9+ FTD-MND suggests slower disease progression and thalamic atrophy represents a novel and unexpected feature.

White matter imaging contributes to the multimodal diagnosis of frontotemporal lobar degeneration

OBJECTIVE

To evaluate the distribution of white matter (WM) disease in frontotemporal lobar degeneration (FTLD) and Alzheimer disease (AD) and to evaluate the relative usefulness of WM and gray matter (GM) for distinguishing these conditions in vivo.

METHODS

Patients were classified as having FTLD (n = 50) or AD (n = 42) using autopsy-validated CSF values of total-tau:β-amyloid (t-tau:Aβ(1-42)) ratios. Patients underwent WM diffusion tensor imaging (DTI) and volumetric MRI of GM. We employed tract-specific analyses of WM fractional anisotropy (FA) and whole-brain GM density analyses. Individual patient classification was performed using receiver operator characteristic (ROC) curves with FA, GM, and a combination of the 2 modalities.

RESULTS

Regional FA and GM were significantly reduced in FTLD and AD relative to healthy seniors. Direct comparisons revealed significantly reduced FA in the corpus callosum in FTLD relative to AD. GM analyses revealed reductions in anterior temporal cortex for FTLD relative to AD, and in posterior cingulate and precuneus for AD relative to FTLD. ROC curves revealed that a multimodal combination of WM and GM provide optimal classification (area under the curve = 0.938), with 87% sensitivity and 83% specificity.

CONCLUSIONS

FTLD and AD have significant WM and GM defects. A combination of DTI and volumetric MRI modalities provides a quantitative method for distinguishing FTLD and AD in vivo.

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.