Patterns of brain atrophy in clinical variants of frontotemporal lobar degeneration

Phenotypically concordant distribution of pick bodies in aphasic versus behavioral dementias

Pick's disease (PiD) is a subtype of the tauopathy form of frontotemporal lobar degeneration (FTLD-tau) characterized by intraneuronal 3R-tau inclusions. PiD can underly various dementia syndromes, including primary progressive aphasia (PPA), characterized by an isolated and progressive impairment of language and left-predominant atrophy, and behavioral variant frontotemporal dementia (bvFTD), characterized by progressive dysfunction in personality and bilateral frontotemporal atrophy. In this study, we investigated the neocortical and hippocampal distributions of Pick bodies in bvFTD and PPA to establish clinicopathologic concordance between PiD and the salience of the aphasic versus behavioral phenotype. Eighteen right-handed cases with PiD as the primary pathologic diagnosis were identified from the Northwestern University Alzheimer's Disease Research Center brain bank (bvFTD, N = 9; PPA, N = 9). Paraffin-embedded sections were stained immunohistochemically with AT8 to visualize Pick bodies, and unbiased stereological analysis was performed in up to six regions bilaterally [middle frontal gyrus (MFG), superior temporal gyrus (STG), inferior parietal lobule (IPL), anterior temporal lobe (ATL), dentate gyrus (DG) and CA1 of the hippocampus], and unilateral occipital cortex (OCC). In bvFTD, peak neocortical densities of Pick bodies were in the MFG, while the ATL was the most affected in PPA. Both the IPL and STG had greater leftward pathology in PPA, with the latter reaching significance (p < 0.01). In bvFTD, Pick body densities were significantly right-asymmetric in the STG (p < 0.05). Hippocampal burden was not clinicopathologically concordant, as both bvFTD and PPA cases demonstrated significant hippocampal pathology compared to neocortical densities (p < 0.0001). Inclusion-to-neuron analyses in a subset of PPA cases confirmed that neurons in the DG are disproportionately burdened with inclusions compared to neocortical areas. Overall, stereological quantitation suggests that the distribution of neocortical Pick body pathology is concordant with salient clinical features unique to PPA vs. bvFTD while raising intriguing questions about the selective vulnerability of the hippocampus to 3R-tauopathies.

Abnormalities of Hippocampal Subfield and Amygdalar Nuclei Volumes and Clinical Correlates in Behavioral Variant Frontotemporal Dementia with Obsessive-Compulsive Behavior-A Pilot Study

(1) Background: The hippocampus (HP) and amygdala are essential structures in obsessive-compulsive behavior (OCB); however, the specific role of the HP in patients with behavioral variant frontotemporal dementia (bvFTD) and OCB remains unclear. (2) Objective: We investigated the alterations of hippocampal and amygdalar volumes in patients with bvFTD and OCB and assessed the correlations of clinical severity with hippocampal subfield and amygdalar nuclei volumes in bvFTD patients with OCB. (3) Materials and methods: Eight bvFTD patients with OCB were recruited and compared with eight age- and sex-matched healthy controls (HCs). Hippocampal subfield and amygdalar nuclei volumes were analyzed automatically using a 3T magnetic resonance image and FreeSurfer v7.1.1. All participants completed the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Neuropsychiatric Inventory (NPI), and Frontal Behavioral Inventory (FBI). (4) Results: We observed remarkable reductions in bilateral total hippocampal volumes. Compared with the HCs, reductions in the left hippocampal subfield volume over the cornu ammonis (CA)1 body, CA2/3 body, CA4 body, granule cell layer, and molecular layer of the dentate gyrus (GC-ML-DG) body, molecular layer of the HP body, and hippocampal tail were more obvious in patients with bvFTD and OCB. Right subfield volumes over the CA1 body and molecular layer of the HP body were more significantly reduced in bvFTD patients with OCB than in those in HCs. We observed no significant difference in amygdalar nuclei volume between the groups. Among patients with bvFTD and OCB, Y-BOCS score was negatively correlated with left CA2/3 body volume (τb = -0.729, p < 0.001); total NPI score was negatively correlated with left GC-ML-DG body (τb = -0.648, p = 0.001) and total bilateral hippocampal volumes (left, τb = -0.629, p = 0.002; right, τb = -0.455, p = 0.023); and FBI score was negatively correlated with the left molecular layer of the HP body (τb = -0.668, p = 0.001), CA4 body (τb = -0.610, p = 0.002), and hippocampal tail volumes (τb = -0.552, p < 0.006). Mediation analysis confirmed these subfield volumes as direct biomarkers for clinical severity, independent of medial and lateral orbitofrontal volumes. (5) Conclusions: Alterations in hippocampal subfield volumes appear to be crucial in the pathophysiology of OCB development in patients with bvFTD.

Neuropsychiatric symptoms and imbalance of atrophy in behavioral variant frontotemporal dementia

Behavioral variant frontotemporal dementia is characterized by heterogeneous frontal, insular, and anterior temporal atrophy patterns that vary along left-right and dorso-ventral axes. Little is known about how these structural imbalances impact clinical symptomatology. The goal of this study was to assess the frequency of frontotemporal asymmetry (right- or left-lateralization) and dorsality (ventral or dorsal predominance of atrophy) and to investigate their clinical correlates. Neuropsychiatric symptoms and structural images were analyzed for 250 patients with behavioral variant frontotemporal dementia. Frontotemporal atrophy was most often symmetric while left-lateralized (9%) and right-lateralized (17%) atrophy were present in a minority of patients. Atrophy was more often ventral (32%) than dorsal (3%) predominant. Patients with right-lateralized atrophy were characterized by higher severity of abnormal eating behavior and hallucinations compared to those with left-lateralized atrophy. Subsequent analyses clarified that eating behavior was associated with right atrophy to a greater extent than a lack of left atrophy, and hallucinations were driven mainly by right atrophy. Dorsality analyses showed that anxiety, euphoria, and disinhibition correlated with ventral-predominant atrophy. Agitation, irritability, and depression showed greater severity with a lack of regional atrophy, including in dorsal regions. Aberrant motor behavior and apathy were not explained by asymmetry or dorsality. This study provides additional insight into how anatomical heterogeneity influences the clinical presentation of patients with behavioral variant frontotemporal dementia. Behavioral symptoms can be associated not only with the presence or absence of focal atrophy, but also with right/left or dorsal/ventral imbalance of gray matter volume.

Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementia

Alzheimer's disease and Frontotemporal dementia are common forms of neurodegenerative dementia. Behavioral alterations and cognitive impairments are found in the clinical courses of both diseases, and their differential diagnosis can sometimes pose challenges for physicians. Therefore, an accurate tool dedicated to this diagnostic challenge can be valuable in clinical practice. However, current structural imaging methods mainly focus on the detection of each disease but rarely on their differential diagnosis. In this paper, we propose a deep learning-based approach for both disease detection and differential diagnosis. We suggest utilizing two types of biomarkers for this application: structure grading and structure atrophy. First, we propose to train a large ensemble of 3D U-Nets to locally determine the anatomical patterns of healthy people, patients with Alzheimer's disease and patients with Frontotemporal dementia using structural MRI as input. The output of the ensemble is a 2-channel disease's coordinate map, which can be transformed into a 3D grading map that is easily interpretable for clinicians. This 2-channel disease's coordinate map is coupled with a multi-layer perceptron classifier for different classification tasks. Second, we propose to combine our deep learning framework with a traditional machine learning strategy based on volume to improve the model discriminative capacity and robustness. After both cross-validation and external validation, our experiments, based on 3319 MRIs, demonstrated that our method produces competitive results compared to state-of-the-art methods for both disease detection and differential diagnosis.

Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging

Neurodegenerative diseases afflict a large number of persons worldwide, with the prevalence and incidence of dementia rapidly increasing. Despite their prevalence, clinical diagnosis of dementia syndromes remains imperfect with limited specificity. Conventional structural-based imaging techniques also lack the accuracy necessary for confident diagnosis. Multiparametric magnetic resonance imaging and molecular imaging provide the promise of improving specificity and sensitivity in the diagnosis of neurodegenerative disease as well as therapeutic monitoring of monoclonal antibody therapy. This educational review will briefly focus on the epidemiology, clinical presentation, and pathologic findings of common and uncommon neurodegenerative diseases. Imaging features of each disease spanning from conventional magnetic resonance sequences to advanced multiparametric methods such as resting-state functional magnetic resonance imaging and arterial spin labeling imaging will be described in detail. Additionally, the review will explore the findings of each diagnosis on molecular imaging including single-photon emission computed tomography and positron emission tomography with a variety of clinically used and experimental radiotracers. The literature and clinical cases provided demonstrate the power of advanced magnetic resonance imaging and molecular techniques in the diagnosis of neurodegenerative diseases and areas of future and ongoing research. With the advent of combined positron emission tomography/magnetic resonance imaging scanners, hybrid protocols utilizing both techniques are an attractive option for improving the evaluation of neurodegenerative diseases.

Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference

Characterizing a particular neurodegenerative condition against others possible diseases remains a challenge along clinical, biomarker, and neuroscientific levels. This is the particular case of frontotemporal dementia (FTD) variants, where their specific characterization requires high levels of expertise and multidisciplinary teams to subtly distinguish among similar physiopathological processes. Here, we used a computational approach of multimodal brain networks to address simultaneous multiclass classification of 298 subjects (one group against all others), including five FTD variants: behavioral variant FTD, corticobasal syndrome, nonfluent variant primary progressive aphasia, progressive supranuclear palsy, and semantic variant primary progressive aphasia, with healthy controls. Fourteen machine learning classifiers were trained with functional and structural connectivity metrics calculated through different methods. Due to the large number of variables, dimensionality was reduced, employing statistical comparisons and progressive elimination to assess feature stability under nested cross-validation. The machine learning performance was measured through the area under the receiver operating characteristic curves, reaching 0.81 on average, with a standard deviation of 0.09. Furthermore, the contributions of demographic and cognitive data were also assessed via multifeatured classifiers. An accurate simultaneous multiclass classification of each FTD variant against other variants and controls was obtained based on the selection of an optimum set of features. The classifiers incorporating the brain's network and cognitive assessment increased performance metrics. Multimodal classifiers evidenced specific variants' compromise, across modalities and methods through feature importance analysis. If replicated and validated, this approach may help to support clinical decision tools aimed to detect specific affectations in the context of overlapping diseases.

Allostatic-Interoceptive Overload in Frontotemporal Dementia

BACKGROUND

The predictive coding theory of allostatic-interoceptive load states that brain networks mediating autonomic regulation and interoceptive-exteroceptive balance regulate the internal milieu to anticipate future needs and environmental demands. These functions seem to be distinctly compromised in behavioral variant frontotemporal dementia (bvFTD), including alterations of the allostatic-interoceptive network (AIN). Here, we hypothesize that bvFTD is typified by an allostatic-interoceptive overload.

METHODS

We assessed resting-state heartbeat evoked potential (rsHEP) modulation as well as its behavioral and multimodal neuroimaging correlates in patients with bvFTD relative to healthy control subjects and patients with Alzheimer's disease (N = 94). We measured 1) resting-state electroencephalography (to assess the rsHEP, prompted by visceral inputs and modulated by internal body sensing), 2) associations between rsHEP and its neural generators (source location), 3) cognitive disturbances (cognitive state, executive functions, facial emotion recognition), 4) brain atrophy, and 5) resting-state functional magnetic resonance imaging functional connectivity (AIN vs. control networks).

RESULTS

Relative to healthy control subjects and patients with Alzheimer's disease, patients with bvFTD presented more negative rsHEP amplitudes with sources in critical hubs of the AIN (insula, amygdala, somatosensory cortex, hippocampus, anterior cingulate cortex). This exacerbated rsHEP modulation selectively predicted the patients' cognitive profile (including cognitive decline, executive dysfunction, and emotional impairments). In addition, increased rsHEP modulation in bvFTD was associated with decreased brain volume and connectivity of the AIN. Machine learning results confirmed AIN specificity in predicting the bvFTD group.

CONCLUSIONS

Altogether, these results suggest that bvFTD may be characterized by an allostatic-interoceptive overload manifested in ongoing electrophysiological markers, brain atrophy, functional networks, and cognition.

Cortical and subcortical pathological burden and neuronal loss in an autopsy series of FTLD-TDP-type C

The TDP-43 type C pathological form of frontotemporal lobar degeneration is characterized by the presence of immunoreactive TDP-43 short and long dystrophic neurites, neuronal cytoplasmic inclusions, neuronal loss and gliosis and the absence of neuronal intranuclear inclusions. Frontotemporal lobar degeneration-TDP-type C cases are commonly associated with the semantic variant of primary progressive aphasia or behavioural variant frontotemporal dementia. Here, we provide detailed characterization of regional distributions of pathological TDP-43 and neuronal loss and gliosis in cortical and subcortical regions in 10 TDP-type C cases and investigate the relationship between inclusions and neuronal loss and gliosis. Specimens were obtained from the first 10 TDP-type C cases accessioned from the Northwestern Alzheimer's Disease Research Center (semantic variant of primary progressive aphasia, n = 7; behavioural variant frontotemporal dementia, n = 3). A total of 42 cortical (majority bilateral) and subcortical regions were immunostained with a phosphorylated TDP-43 antibody and/or stained with haematoxylin-eosin. Regions were evaluated for atrophy, and for long dystrophic neurites, short dystrophic neurites, neuronal cytoplasmic inclusions, and neuronal loss and gliosis using a semiquantitative 5-point scale. We calculated a 'neuron-to-inclusion' score (TDP-type C mean score - neuronal loss and gliosis mean score) for each region per case to assess the relationship between TDP-type C inclusions and neuronal loss and gliosis. Primary progressive aphasia cases demonstrated leftward asymmetry of cortical atrophy consistent with the aphasic phenotype. We also observed abundant inclusions and neurodegeneration in both cortical and subcortical regions, with certain subcortical regions emerging as particularly vulnerable to dystrophic neurites (e.g. amygdala, caudate and putamen). Interestingly, linear mixed models showed that regions with lowest TDP-type C pathology had high neuronal dropout, and conversely, regions with abundant pathology displayed relatively preserved neuronal densities (P < 0.05). This inverse relationship between the extent of TDP-positive inclusions and neuronal loss may reflect a process whereby inclusions disappear as their associated neurons are lost. Together, these findings offer insight into the putative substrates of neurodegeneration in unique dementia syndromes.

Idiopathic normal pressure hydrocephalus-like MRI features in patients with progressive supranuclear palsy: a comparative case-control study

BACKGROUND

The occurrence of neurodegenerative disease in patients with normal pressure hydrocephalus (NPH) is emphasized in recent reports. Based on this common co-occurrence, some of the hydrocephalic disorders appearing in late adulthood have been hypothesized to result from initially unapparent parenchymal abnormalities of neurodegenerative origin. Among these diseases, progressive supranuclear palsy (PSP) has been specifically remarked on. We aimed to comparatively investigate the neuroimaging clues of iNPH in our PSP subjects.

METHODS

Eighteen patients with a clinical diagnosis of PSP, 44 with Parkinson's disease (PD), and 44 healthy control (HC) individuals were enrolled. The disproportionately enlarged subarachnoid space hydrocephalus (DESH) score, the Evans' index (EI), and the callosal angle (CA) were measured on the conventional magnetic resonance imaging (MRI). The comparative analyses were performed using IBM SPSS Statistics 26.

RESULTS

We found that dilated Sylvian fissures score (p = 0.016) and focal sulcal dilatation score (p = 0.037) were higher in the PSP group in comparison to HC whereas the CA score was higher in PSP subjects in comparison to both PD patients and HC (p = 0.000). Remarkably, the DESH score was also found to be higher in the PSP group in comparison to the age-matched HC group (p = 0.024).

CONCLUSIONS

We found that the NPH-like MRI features were more common in PSP subjects in comparison to PD subjects and age-matched HC. These results may provide critical contributions to the literature regarding the overlap between PSP and NPH.

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.

Quantified Brain Magnetic Resonance Imaging Volumes Differentiate Behavioral Variant Frontotemporal Dementia from Early-Onset Alzheimer's Disease

BACKGROUND

The differentiation of behavioral variant frontotemporal dementia (bvFTD) from early-onset Alzheimer's disease (EOAD) by clinical criteria can be inaccurate. The volumetric quantification of clinically available magnetic resonance (MR) brain scans may facilitate early diagnosis of these neurodegenerative dementias.

OBJECTIVE

To determine if volumetric quantification of brain MR imaging can identify persons with bvFTD from EOAD.

METHODS

3D T1 MR brain scans of 20 persons with bvFTD and 45 with EOAD were compared using Neuroreader to measure subcortical, and lobar volumes, and Volbrain for hippocampal subfields. Analyses included: 1) discriminant analysis with leave one out cross-validation; 2) input of predicted probabilities from this process into a receiver operator characteristic (ROC) analysis; and 3) Automated linear regression to identify predictive regions.

RESULTS

Both groups were comparable in age and sex with no statistically significant differences in symptom duration. bvFTD had lower volume percentiles in frontal lobes, thalamus, and putamen. EOAD had lower parietal lobe volumes. ROC analyses showed 99.3% accuracy with Neuroreader percentiles and 80.2% with subfields. The parietal lobe was the most predictive percentile. Although there were differences in hippocampal (particularly left CA2-CA3) subfields, it did not add to the discriminant analysis.

CONCLUSION

Percentiles from an MR based volumetric quantification can help differentiate between bvFTD from EOAD in routine clinical care. Use of hippocampal subfield volumes does not enhance the diagnostic separation of these two early-onset dementias.

Neurocognitive factorial structure of executive functions: Evidence from neurotypicals and frontotemporal dementia

The latent structure of executive functions (EFs) remains controversial. Confirmatory factorial analysis (CFA) has provided support for both multidimensional (assumes EFs to be functionally separable but related components) and bifactor (proposes all components are nested within a common factor) models. However, these CFA models have never been compared in patient samples, nor regarding their neuroanatomical correlates. Here, we systematically contrast both approaches in neurotypicals and in a neurodegenerative lesion model (patients with the behavioral variant frontotemporal dementia, bvFTD), characterized by executive deficits associated with frontal neurodegeneration. First, CFA was used to test the models' fit in a sample of 341 neurotypicals and 29 bvFTD patients based on performance in an executive frontal screening battery which assesses working memory, motor inhibition, verbal inhibition, and abstraction capacity. Second, we compared EFs factor and observed scores between patients and matched controls. Finally, we used voxel-based morphometry (VBM) to compare the grey matter correlates of factor and observed scores. CFA results showed that both models fit the data well. The multidimensional model, however, was more sensitive than the bifactor model and the observed scores to detect EFs impairments in bvFTD patients. VBM results for the multidimensional model revealed common and unique grey matter correlates for EFs components across prefrontal-insular, posterior, and temporal cortices. Regarding the bifactor model, only the common factor was associated with prefrontal-insular hubs. Observed scores presented scant, non-frontal grey matter associations. Converging behavioral and neuroanatomical evidence from healthy populations and a neurodegenerative model of EFs supports an underlying multidimensional structure.

Multi-Modal Segmentation of 3D Brain Scans Using Neural Networks

Anatomical segmentation of brain scans is highly relevant for diagnostics and neuroradiology research. Conventionally, segmentation is performed on T₁-weighted MRI scans, due to the strong soft-tissue contrast. In this work, we report on a comparative study of automated, learning-based brain segmentation on various other contrasts of MRI and also computed tomography (CT) scans and investigate the anatomical soft-tissue information contained in these imaging modalities. A large database of in total 853 MRI/CT brain scans enables us to train convolutional neural networks (CNNs) for segmentation. We benchmark the CNN performance on four different imaging modalities and 27 anatomical substructures. For each modality we train a separate CNN based on a common architecture. We find average Dice scores of 86.7 ± 4.1% (T₁-weighted MRI), 81.9 ± 6.7% (fluid-attenuated inversion recovery MRI), 80.8 ± 6.6% (diffusion-weighted MRI) and 80.7 ± 8.2% (CT), respectively. The performance is assessed relative to labels obtained using the widely-adopted FreeSurfer software package. The segmentation pipeline uses dropout sampling to identify corrupted input scans or low-quality segmentations. Full segmentation of 3D volumes with more than 2 million voxels requires <1s of processing time on a graphical processing unit.

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.

Predementia Brain Changes in Progranulin Mutation: A Systematic Review of Neuroimaging Evidence

BACKGROUND

Mutations in the progranulin (GRN) gene are a major cause of familial frontotemporal dementia. They result in a loss of progranulin levels and in GRN-related brain degenerative changes that unfold over years if not decades. The aim of our review was to summarize the evidence on emerging functional and structural brain abnormalities in carriers of GRN mutations.

SUMMARY

We performed a systematic search for studies that used at least one modality (structural MRI, fMRI, fluorodeoxyglucose positron emission tomography, diffusion tensor imaging) to compare mutation carriers to non-carrier controls. Our search produced 13 studies published between 2008 and 2017, the majority cross-sectional, with carrier sample sizes ranging from 5 to 65. Key Messages: The aggregate findings suggest that (1) measurable brain changes are detectable in at least some mutation carriers 20-25 years prior to disease onset; (2) functional/metabolic changes progress more consistently over time than structural changes; (3) the topographic pattern is anterior to posterior, not always asymmetric, and maps onto known functional networks.

MR fingerprinting as a diagnostic tool in patients with frontotemporal lobe degeneration: A pilot study

Several very rare forms of dementia are associated with characteristic focal atrophy predominantly of the frontal and/or temporal lobes and currently lack imaging solutions to monitor disease. Magnetic resonance fingerprinting (MRF) is a recently developed technique providing quantitative relaxivity maps and images with various tissue contrasts out of a single sequence acquisition. This pilot study explores the utility of MRF-based T1 and T2 mapping to discover focal differences in relaxation times between patients with frontotemporal lobe degenerative dementia and healthy controls. 8 patients and 30 healthy controls underwent a 3 T MRI including an axial 2D spoiled gradient echo MRF sequence. T1 and T2 relaxation maps were generated based on an extended phase graphs algorithm-founded dictionary involving inner product pattern matching. A region of interest (ROI)-based analysis of T1 and T2 relaxation times was performed with FSL and ITK-SNAP. Depending on the brain region analyzed, T1 relaxation times were up to 10.28% longer in patients than in controls reaching significant differences in cortical gray matter (P = .047) and global white matter (P = .023) as well as in both hippocampi (P = .001 left; P = .027 right). T2 relaxation times were similarly longer in the hippocampus by up to 19.18% in patients compared with controls. The clinically most affected patient had the most control-deviant relaxation times. There was a strong correlation of T1 relaxation time in the amygdala with duration of the clinically manifest disease (Spearman Rho = .94; P = .001) and of T1 relaxation times in the left hippocampus with disease severity (Rho = .90, P = .002). In conclusion, MRF-based relaxometry is a promising and time-saving new MRI tool to study focal cerebral alterations and identify patients with frontotemporal lobe degeneration. To validate the results of this pilot study, MRF is worth further exploration as a diagnostic tool in neurodegenerative diseases.

Behavioral Variant Frontotemporal Dementia Performance on a Range of Saccadic Tasks

BACKGROUND

Saccadic paradigms display changes across a number of degenerative conditions reflecting changes in the oculomotor pathway which in some conditions have been linked to disease presentation.

OBJECTIVE

To examine a novel range of saccadic paradigms in behavioral variant frontotemporal dementia (bvFTD).

METHODS

Prosaccade, predictive, self-paced, memory-guided, and anti-saccade tasks were examined in bvFTD patients and controls.

RESULTS

A significant increase in latency for the bvFTD group was seen in all tasks. Self-paced saccades are reduced in number, memory-guided saccades display an increase in errors. Predictive saccades show an increased latency that does not remain when prosaccade latency changes are accounted for. While changes were seen across a range of paradigms, no individual task completely separated bvFTD from control participants.

CONCLUSION

bvFTD patients as a group display a number of changes on saccadic testing which may reflect the frontal lobe changes seen in this condition.

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.

Prolonged Visual Facial Grasp in Frontotemporal Dementia

BACKGROUND

Gaze and eye contact is a critical aspect of social interaction. Patients with behavioral variant frontotemporal dementia (bvFTD) may exhibit abnormally prolonged stare toward human faces.

OBJECTIVE

To study characteristics of social gaze in patients with bvFTD compared to age and education matched-patients with early-onset Alzheimer's disease (eAD) and healthy controls (HC).

METHOD

Fifty picture stimuli were presented to each participant (bvFTD = 12, eAD = 18, HC = 13). Each stimuli contained two properties: face (facial versus non-facial) and valence (positive, negative, and neutral). The "facial" stimuli contained human faces. The participants Visual Fixation Time (VFT) was measured for each picture stimuli of interest (per facial expressions on the Facial Action Coding System). A linear mixed-effects regression model with participant-level of random effects was used to compare VFTs between groups.

RESULTS

The patients with bvFTD showed significantly prolonged VFTs to faces than the patients with eAD and the HC, regardless of valence (all p < 0.01). There were no differences in VFTs for non-facial stimuli between patients with bvFTD and eAD. However, patients with bvFTD and eAD had significantly prolonged VFTs to negative non-facial stimuli than the HC (p = 0.006 and 0.019, respectively).

CONCLUSION

Patients with bvFTD exhibited a prolonged stare toward human faces. This prolonged visual facial grasp may contribute to the disturbed social interactions of patients with bvFTD and can help distinguish them from those with Alzheimer's disease and other conditions. Additionally, both dementia groups tended to stare at negative stimuli whether faces or non-faces.

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

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

[Emotional, affective and behavioral disorders in a behavioral variant of frontotemporal dementia]

AIM

To determine the prevalence and severity of non-cognitive nervous and psychiatric disorders (NNPD) in a behavioral variant of frontotemporal dementia.

MATERIAL AND METHODS

Twenty-nine patients with BVFTD, aged from 41 to 73 years (mean 60.7±8.1 years), were studied. All patients underwent neurological and neuropsychological examinations. NNPD were assessed using the Neuropsychiatric Inventory (J. Cummings et al). Twenty-seven patients underwent brain MRI with T1, T2 and FLAIR sequences.

RESULTS

The most clinically significant symptoms of NNPD were apathy, behavioral disinhibition, eating disorders, abnormal motor activity and euphoria. Irritability, sleep disorders and excitement were less frequent. Anxiety and depression were identified in 13.8 and 20.7% of the patients, respectively. The severity of NNPD can increase and their spectrum can be qualitatively changed with the disease progression that indicates the spread of the neurodegenerative process.

CONCLUSION

Patients with BVFTD had all NNPD with the exception of delusion and hallucinations. The character and degree of severity of some emotional, affective and behavioral disorders are associated with the predominant localization of the pathological process in frontal and temporal brain regions.

An advanced white matter tract analysis in frontotemporal dementia and early-onset Alzheimer's disease

Cortical and subcortical nuclei degenerate in the dementias, but less is known about changes in the white matter tracts that connect them. To better understand white matter changes in behavioral variant frontotemporal dementia (bvFTD) and early-onset Alzheimer’s disease (EOAD), we used a novel approach to extract full 3D profiles of fiber bundles from diffusion-weighted MRI (DWI) and map white matter abnormalities onto detailed models of each pathway. The result is a spatially complex picture of tract-by-tract microstructural changes. Our atlas of tracts for each disease consists of 21 anatomically clustered and recognizable white matter tracts generated from whole-brain tractography in 20 patients with bvFTD, 23 with age-matched EOAD, and 33 healthy elderly controls. To analyze the landscape of white matter abnormalities, we used a point-wise tract correspondence method along the 3D profiles of the tracts and quantified the pathway disruptions using common diffusion metrics – fractional anisotropy, mean, radial, and axial diffusivity. We tested the hypothesis that bvFTD and EOAD are associated with preferential degeneration in specific neural networks. We mapped axonal tract damage that was best detected with mean and radial diffusivity metrics, supporting our network hypothesis, highly statistically significant and more sensitive than widely studied fractional anisotropy reductions. From white matter diffusivity, we identified abnormalities in bvFTD in all 21 tracts of interest but especially in the bilateral uncinate fasciculus, frontal callosum, anterior thalamic radiations, cingulum bundles and left superior longitudinal fasciculus. This network of white matter alterations extends beyond the most commonly studied tracts, showing greater white matter abnormalities in bvFTD versus controls and EOAD patients. In EOAD, network alterations involved more posterior white matter – the parietal sector of the corpus callosum and parahipoccampal cingulum bilaterally. Widespread but distinctive white matter alterations are a key feature of the pathophysiology of these two forms of dementia.

Neuroimaging in Dementia

Although the diagnosis of dementia still is primarily based on clinical criteria, neuroimaging is playing an increasingly important role. This is in large part due to advances in techniques that can assist with discriminating between different syndromes. Magnetic resonance imaging remains at the core of differential diagnosis, with specific patterns of cortical and subcortical changes having diagnostic significance. Recent developments in molecular PET imaging techniques have opened the door for not only antemortem but early, even preclinical, diagnosis of underlying pathology. This is vital, as treatment trials are underway for pharmacological agents with specific molecular targets, and numerous failed trials suggest that earlier treatment is needed. This article provides an overview of classic neuroimaging findings as well as new and cutting-edge research techniques that assist with clinical diagnosis of a range of dementia syndromes, with an emphasis on studies using pathologically proven cases.

Tackling variability: A multicenter study to provide a gold-standard network approach for frontotemporal dementia

Biomarkers represent a critical research area in neurodegeneration disease as they can contribute to studying potential disease-modifying agents, fostering timely therapeutic interventions, and alleviating associated financial costs. Functional connectivity (FC) analysis represents a promising approach to identify early biomarkers in specific diseases. Yet, virtually no study has tested whether potential FC biomarkers prove to be reliable and reproducible across different centers. As such, their implementation remains uncertain due to multiple sources of variability across studies: the numerous international centers capable conducting FC research vary in their scanning equipment and their samples' socio-cultural background, and, more troublingly still, no gold-standard method exists to analyze FC. In this unprecedented study, we aim to address both issues by performing the first multicenter FC research in the behavioral-variant frontotemporal dementia (bvFTD), and by assessing multiple FC approaches to propose a gold-standard method for analysis. We enrolled 52 bvFTD patients and 60 controls from three international clinics (with different fMRI recording parameters), and three additional neurological patient groups. To evaluate FC, we focused on seed analysis, inter-regional connectivity, and several graph-theory approaches. Only graph-theory analysis, based on weighted-matrices, yielded consistent differences between bvFTD and controls across centers. Also, graph metrics robustly discriminated bvFTD from the other neurological conditions. The consistency of our findings across heterogeneous contexts highlights graph-theory as a potential gold-standard approach for brain network analysis in bvFTD. Hum Brain Mapp 38:3804-3822, 2017. © 2017 Wiley Periodicals, Inc.

Behavioral Evolution of Progressive Semantic Aphasia in Comparison with Nonfluent Aphasia

BACKGROUND

Patients with primary progressive aphasia (PPA) usually develop significant behavioral disturbances with progression of the disease. We tested our clinical observation that development of disruptive agitation is more likely in semantic than in nonfluent PPA and examined which clinical variables could be associated with this behavior.

METHODS

We retrospectively analyzed neuropsychiatric scores and the need for behavioral treatments in semantic PPA (n = 41) and nonfluent PPA (n = 39) cases and compared first (1-3 years since the onset of symptoms) and last (5-13 years since the onset) evaluations. Clinical variables and laterality of temporal atrophy were associated with symptoms in semantic PPA cases.

RESULTS

The semantic PPA group developed more frequent (p = 0.03) and intense agitation (p = 0.0008) and had a greater need for antipsychotic drugs (p = 0.001) than the nonfluent PPA group. Presence of agitation was clearly associated with psychotic symptoms (delusions/hallucinations) but was not associated with gender, age at onset, duration of the disease, or laterality of temporal atrophy. In contrast, nonfluent PPA cases were more frequently depressed and treated with antidepressants (p = 0.0007). There were no differences in anxiety, irritability, apathy, perseverations, hyperorality, or abnormal motor behavior.

CONCLUSIONS

Semantic PPA in advanced disease is frequently associated with agitation and psychotic symptoms with fewer mood symptoms, while nonfluent PPA maintains a high prevalence of depression. This implies different treatment and care and support needs for each group.

Lack of Frank Agrammatism in the Nonfluent Agrammatic Variant of Primary Progressive Aphasia

Background/Aims

Frank agrammatism, defined as the omission and/or substitution of grammatical morphemes with associated grammatical errors, is variably reported in patients with nonfluent variant primary progressive aphasia (nfPPA). This study addressed whether frank agrammatism is typical in agrammatic nfPPA patients when this feature is not required for diagnosis.

Method

We assessed grammatical production in 9 patients who satisfied current diagnostic criteria. Although the focus was agrammatism, motor speech skills were also evaluated to determine whether dysfluency arose primarily from apraxia of speech (AOS), instead of, or in addition to, agrammatism. Volumetric MRI analyses provided impartial imaging-supported diagnosis.

Results

The majority of cases exhibited neither frank agrammatism nor AOS.

Conclusion

There are nfPPA patients with imaging-supported diagnosis and preserved motor speech skills who do not exhibit frank agrammatism, and this may persist beyond the earliest stages of the illness. Because absence of frank agrammatism is a subsidiary diagnostic feature in the logopenic variant of PPA, this result has implications for differentiation of the nonfluent and logopenic variants, and indicates that PPA patients with nonfluent speech in the absence of frank agrammatism or AOS do not necessarily have the logopenic variant.

Magnetic resonance elastography of frontotemporal dementia

Purpose

To investigate the feasibility of utilizing brain stiffness as a potential biomarker for behavioral variant frontotemporal dementia (bvFTD) patients. Magnetic resonance elastography (MRE) is a noninvasive technique for evaluating the mechanical properties of brain tissue in vivo. MRE has demonstrated decreased brain stiffness in patients with Alzheimer's disease.

Materials and Methods

We examined five male subjects with bvFTD and nine cognitively normal age‐matched male controls (NC) with brain 3T MRE. Stiffness was calculated in nine regions of interest (ROIs): whole brain (entire cerebrum excluding cerebellum), frontal lobes, occipital lobes, parietal lobes, temporal lobes, deep gray matter / white matter (GM/WM; insula, deep gray nuclei and white matter tracts), cerebellum, sensorimotor cortex (pre‐ and postcentral gyri), and a composite region labeled FT (frontal and temporal lobes excluding the pre‐ and postcentral gyri).

Results

Significantly lower stiffness values were observed in the whole brain (P = 0.007), frontal lobe (P = 0.001), and temporal lobes (P = 0.005) of bvFTD patients compared to NC. No significant stiffness differences were observed in any other ROIs of bvFTD patients compared to NC (P > 0.05). These results demonstrate that statistically significant brain softening occurs in the frontal and temporal lobes of bvFTD patients, which corresponds to the expected pathophysiology of bvFTD.

Conclusion

Future studies evaluating the feasibility of brain MRE for early disease detection and monitoring disease progression could shed new insights into understanding the mechanisms involved in bvFTD. J. Magn. Reson. Imaging 2016;43:474–478.

Regional differences in white matter breakdown between frontotemporal dementia and early-onset Alzheimer's disease

BACKGROUND

White matter abnormalities have been associated with both behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD).

OBJECTIVE

Using MRI diffusion tensor imaging (DTI) measures, we compared white matter integrity between patients with bvFTD and those with early-onset AD and correlated these biomarkers with behavioral symptoms involving emotional blunting.

METHODS

We studied 8 bvFTD and 12 AD patients as well as 12 demographically-matched healthy controls (NCs). Using four DTI metrics (fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity), we assessed the frontal lobes (FWM) and genu of the corpus callosum (GWM), which are vulnerable late-myelinating regions, and a contrasting early-myelinating region (splenium of the corpus callosum). The Scale for Emotional Blunting Scale (SEB) was used to assess emotional functioning of the study participants.

RESULTS

Compared to AD patients and NCs, the bvFTD subjects exhibited significantly worse FWM and GWM integrity on all four DTI metrics sensitive to myelin and axonal integrity. In contrast, AD patients showed a numerical trend toward worse splenium of the corpus callosum integrity than bvFTD and NC groups. Significant associations between SEB ratings and GWM DTI measures were demonstrated in the combined bvFTD and AD sample. When examined separately, these relationships remained robust for the bvFTD group but not the AD group.

CONCLUSIONS

The regional DTI alterations suggest that FTD and AD are each associated with a characteristic distribution of white matter degradation. White matter breakdown in late-myelinating regions was associated with symptoms of emotional blunting, particularly within the bvFTD group.