Profiles of white matter tract pathology in frontotemporal dementia

NOTCH3 variants of unknown significance underpin vascular dysfunction in neurodegenerative disease: a case series of three nfvPPA-FTD patients

INTRODUCTION

The NOTCH3 gene encodes for an evolutionarily conserved protein, whose functions encompass both embryonic cell proliferation and adult tissue-specific differentiation. Among others, a pivotal role in maintaining functional integrity of neurovascular unit (NVU) is supported by the association of several NOTCH3 gene mutations with neuroimaging markers of cerebral small vessel disease (SVD). Indeed, a pathogenic role of NOTCH3 is recognised in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). However, an increasing number of NOTCH3 variants with unclear pathogenic role have been identified in patients suspected of having CADASIL. The following case series describes three patients under the age of 65 with clinical diagnosis of nonfluent-variant of primary progressive aphasia (nfvPPA), whose genetic analysis revealed the presence of three distinct novel variants of unknown significance (VUS) in NOTCH3 gene.

RESULTS

The diagnostic work-up revealed common features among the patients: clinical presentation -nfvPPA at neuropsychological evaluation with consistent extrapyramidal symptoms; neuroimaging -low brain MR burden of SVD and FDG-PET impairment of cortical areas involved in speech production network; and biomarkers -Cerebrospinal fluid (CSF) analysis negative for Alzheimer's Disease (AD), corroborating suspicion of underlying Frontotemporal Lobe Degeneration (FTLD).

DISCUSSION AND CONCLUSION

The retrieved VUS in NOTCH3 suggest that the involvement of Notch signalling in pathophysiology of neurodegenerative disease is more complex and needs to be fully explored. Rare variants in SVD-associated genes may influence progression of neurodegeneration via the dysfunction of several vascular pathways.

Frontotemporal dementia. How to deal with its diagnostic complexity?

INTRODUCTION

Frontotemporal dementia (FTD) encompasses a group of heterogeneous neurodegenerative disorders. Aside from genetic cases, its diagnosis is challenging, particularly in the early stages when symptoms are ambiguous, and structural neuroimaging does not reveal characteristic patterns.

AREAS COVERED

The authors performed a comprehensive literature search through MEDLINE, Scopus, and Web of Science databases to gather evidence to aid the diagnostic process for suspected FTD patients, particularly in early phases, even in sporadic cases, ranging from established to promising tools. Blood-based biomarkers might help identify very early neuropathological stages and guide further evaluations. Subsequently, neurophysiological measures reflecting functional changes in cortical excitatory/inhibitory circuits, along with functional neuroimaging assessing brain network, connectivity, metabolism, and perfusion alterations, could detect specific changes associated to FTD even decades before symptom onset. As the neuropathological process advances, cognitive-behavioral profiles and atrophy patterns emerge, distinguishing specific FTD subtypes.

EXPERT OPINION

Emerging disease-modifying therapies require early patient enrollment. Therefore, a diagnostic paradigm shift is needed - from relying on typical cognitive and neuroimaging profiles of advanced cases to widely applicable biomarkers, primarily fluid biomarkers, and, subsequently, neurophysiological and functional neuroimaging biomarkers where appropriate. Additionally, exploring subjective complaints and behavioral changes detected by home-based technologies might be crucial for early diagnosis.

Involvement of the left uncinate fasciculus in the amyotrophic lateral sclerosis: an exploratory longitudinal multi-modal neuroimaging and neuropsychological study

To investigate the microstructural integrity, tract volume analysis, and functional connectivity (FC) alterations of the left uncinate fasciculus (UF) in patients with amyotrophic lateral sclerosis (ALS) compared to healthy controls (HCs). Fourteen limb-onset ALS patients were recruited at baseline and ten at follow-up, along with 14 HCs. All participants underwent 3D T1-weighted, diffusion tensor imaging and kurtosis imaging (DTI/DKI), and resting-state functional MRI (rs-fMRI) using a 3 Tesla scanner with 64-channel coils. Eight metrics of diffusion, rs-FC of the left UF, and graph theory analyses were extracted. Statistical group comparisons and correlation analysis for significant diffusion metrics were also conducted. Significantly lower radial kurtosis (RK), mean kurtosis (MK), and higher DTI diffusivity metrics were observed in the left UF of ALS patients than in HCs. RK and MK were correlated with various cognitive scores, particularly executive function and visuospatial ability. The volume of the left UF was positively correlated only with RK and MK at follow-up. While rs-FC analysis did not reveal group differences, a negative functional link between the left UF and cerebellum was observed in HCs but not in patients. Graph theory analysis suggested decreased connectivity in baseline patients and potential compensatory effects during the follow-up. Our study reveals microstructural abnormalities and potential network changes in left UF. DKI metrics, especially RK and MK, may be more sensitive biomarkers than DTI metrics, particularly longitudinally. Diffusion changes appear to precede volume and functional connectivity alterations, suggesting diffusion as a potential early biomarker.

Bidirectional two-sample Mendelian randomization analyses support causal relationships between structural and diffusion imaging-derived phenotypes and the risk of major neurodegenerative diseases

Previous observational investigations suggest that structural and diffusion imaging-derived phenotypes (IDPs) are associated with major neurodegenerative diseases; however, whether these associations are causal remains largely uncertain. Herein we conducted bidirectional two-sample Mendelian randomization analyses to infer the causal relationships between structural and diffusion IDPs and major neurodegenerative diseases using common genetic variants-single nucleotide polymorphism (SNPs) as instrumental variables. Summary statistics of genome-wide association study (GWAS) for structural and diffusion IDPs were obtained from 33,224 individuals in the UK Biobank cohort. Summary statistics of GWAS for seven major neurodegenerative diseases were obtained from the largest GWAS for each disease to date. The forward MR analyses identified significant or suggestively statistical causal effects of genetically predicted three structural IDPs on Alzheimer's disease (AD), frontotemporal dementia (FTD), and multiple sclerosis. For example, the reduction in the surface area of the left superior temporal gyrus was associated with a higher risk of AD. The reverse MR analyses identified significantly or suggestively statistical causal effects of genetically predicted AD, Lewy body dementia (LBD), and FTD on nine structural and diffusion IDPs. For example, LBD was associated with increased mean diffusivity in the right superior longitudinal fasciculus and AD was associated with decreased gray matter volume in the right ventral striatum. Our findings might contribute to shedding light on the prediction and therapeutic intervention for the major neurodegenerative diseases at the neuroimaging level.

Association between Blood Pressure and Post-Stroke Cognitive Impairment: A Meta-Analysis

Background

Post-stroke cognitive impairment (PSCI) represents a serious post-stroke complication with poor cognitive consequences. A vascular consequence after a stroke is that the occurrence and progression of PSCI may be closely related to blood pressure (BP). Thus, we systematically reviewed and performed a meta-analysis of the literature to examine the correlations between BP and PSCI.

Methods

We systematically queried databases, including PubMed, the Cochrane Library, Embase, and Scopus, and conducted meta-analyses on studies reporting odds ratios (ORs) related to the association between BP and PSCI. Two authors autonomously assessed all titles, abstracts, and full texts and extracted data following the Meta-Analysis of Observational Studies in Epidemiology guidelines. The quality of the studies was evaluated using the modified Newcastle-Ottawa scale.

Results

Meta-analyses incorporated 12 articles comprising a cumulative participant cohort of 21,732 individuals. The quality assessment indicated good in five studies, fair in one study, and poor in six. Through meta-analyses, we found that hypertension, systolic or diastolic BP (SBP or DBP) was significantly associated with PSCI (OR 1.53, 95% confidence interval (CI), 1.18-1.99; p = 0.001, I 2 = 66%; OR 1.13, 95% CI, 1.05-1.23; p = 0.002, I 2 = 52%; OR 1.38, 95% CI, 1.11-1.72; p = 0.004, I 2 = 90%, respectively). In the subgroup analysis, SBP < 120 mmHg, 120-139 mmHg, 140-159 mmHg, 160-179 mmHg, and DBP ≥ 100 mmHg highly predicted the occurrence of PSCI (OR 1.15, p = 0.0003; OR 1.26, p = 0.010; OR 1.15, p = 0.05; OR 1.02, p = 0.009; OR 1.96, p < 0.00001, respectively). However, the predictive effect of BP for PSCI declines when SBP ≥ 180 mmHg and DBP ≤ 99 mmHg (p > 0.05). Statistical heterogeneity was moderate to high, and publication bias was detected in SBP for PSCI.

Conclusions

Considering the multifactorial etiology of PSCI, it is difficult to conclude that BP is an independent risk factor for PSCI. Given the restricted inclusion of studies, caution is advised when interpreting the findings from this meta-analysis. Subsequent investigations with substantial sample sizes are essential to exploring BP as a prospective target for addressing PSCI.

Trial Registration Number

CRD42023437783 from PROSPERO.

Neuroanatomical and cellular degeneration associated with a social disorder characterized by new ritualistic belief systems in a TDP-C patient vs. a Pick patient

Frontotemporal dementia (FTD) is a spectrum of clinically and pathologically heterogenous neurodegenerative dementias. Clinical and anatomical variants of FTD have been described and associated with underlying frontotemporal lobar degeneration (FTLD) pathology, including tauopathies (FTLD-tau) or TDP-43 proteinopathies (FTLD-TDP). FTD patients with predominant degeneration of anterior temporal cortices often develop a language disorder of semantic knowledge loss and/or a social disorder often characterized by compulsive rituals and belief systems corresponding to predominant left or right hemisphere involvement, respectively. The neural substrates of these complex social disorders remain unclear. Here, we present a comparative imaging and postmortem study of two patients, one with FTLD-TDP (subtype C) and one with FTLD-tau (subtype Pick disease), who both developed new rigid belief systems. The FTLD-TDP patient developed a complex set of values centered on positivity and associated with specific physical and behavioral features of pigs, while the FTLD-tau patient developed compulsive, goal-directed behaviors related to general themes of positivity and spirituality. Neuroimaging showed left-predominant temporal atrophy in the FTLD-TDP patient and right-predominant frontotemporal atrophy in the FTLD-tau patient. Consistent with antemortem cortical atrophy, histopathologic examinations revealed severe loss of neurons and myelin predominantly in the anterior temporal lobes of both patients, but the FTLD-tau patient showed more bilateral, dorsolateral involvement featuring greater pathology and loss of projection neurons and deep white matter. These findings highlight that the regions within and connected to anterior temporal lobes may have differential vulnerability to distinct FTLD proteinopathies and serve important roles in human belief systems.

Structural and microstructural thalamocortical network disruption in sporadic behavioural variant frontotemporal dementia

BACKGROUND

Using multi-block methods we combined multimodal neuroimaging metrics of thalamic morphology, thalamic white matter tract diffusion metrics, and cortical thickness to examine changes in behavioural variant frontotemporal dementia. (bvFTD).

METHOD

Twenty-three patients with sporadic bvFTD and 24 healthy controls underwent structural and diffusion MRI scans. Clinical severity was assessed using the Clinical Dementia Rating scale and behavioural severity using the Frontal Behaviour Inventory by patient caregivers. Thalamic volumes were manually segmented. Anterior and posterior thalamic radiation fractional anisotropy and mean diffusivity were extracted using Tract-Based Spatial Statistics. Finally, cortical thickness was assessed using Freesurfer. We used shape analyses, diffusion measures, and cortical thickness as features in sparse multi-block partial least squares (PLS) discriminatory analyses to classify participants within bvFTD or healthy control groups. Sparsity was tuned with five-fold cross-validation repeated 10 times. Final model fit was assessed using permutation testing. Additionally, sparse multi-block PLS was used to examine associations between imaging features and measures of dementia severity.

RESULTS

Bilateral anterior-dorsal thalamic atrophy, reduction in mean diffusivity of thalamic projections, and frontotemporal cortical thinning, were the main features predicting bvFTD group membership. The model had a sensitivity of 96%, specificity of 68%, and was statistically significant using permutation testing (p = 0.012). For measures of dementia severity, we found similar involvement of regional thalamic and cortical areas as in discrimination analyses, although more extensive thalamo-cortical white matter metric changes.

CONCLUSIONS

Using multimodal neuroimaging, we demonstrate combined structural network dysfunction of anterior cortical regions, cortical-thalamic projections, and anterior thalamic regions in sporadic bvFTD.

Clinical relevance of disrupted topological organization of anatomical connectivity in behavioral variant frontotemporal dementia

Graph theory is a novel approach used to examine the balance of brain connectomes. However, the clinical relevance of white matter (WM) connectome changes in the behavioral variant frontotemporal dementia (bvFTD) is not well understood. We aimed to investigate the clinical relevance of WM topological alterations in bvFTD. Thirty patients with probable bvFTD and 30 healthy controls underwent diffusion tensor imaging, structural MRI, and neuropsychological assessment. WM connectivity between 90 brain regions was calculated and the graph approach was applied to capture the individual characteristics of the anatomical network. Voxel-based morphometry and tract-based spatial statistics were used to present the gray matter atrophy and disrupted WM integrity. The topological organization was disrupted in patients with bvFTD both globally and locally. Compared to controls, bvFTD data showed a different pattern of hub region distributions. Notably, the nodal efficiency of the right superior orbital frontal gyrus was associated with apathy and disinhibition. Topological measures may be potential image markers for early diagnosis and disease severity monitoring of bvFTD.

Disrupted myelin lipid metabolism differentiates frontotemporal dementia caused by GRN and C9orf72 gene mutations

Heterozygous mutations in the GRN gene and hexanucleotide repeat expansions in C9orf72 are the two most common genetic causes of Frontotemporal Dementia (FTD) with TDP-43 protein inclusions. The triggers for neurodegeneration in FTD with GRN (FTD-GRN) or C9orf72 (FTD-C9orf72) gene abnormalities are unknown, although evidence from mouse and cell culture models suggests that GRN mutations disrupt lysosomal lipid catabolism. To determine how brain lipid metabolism is affected in familial FTD with TDP-43 inclusions, and how this is related to myelin and lysosomal markers, we undertook comprehensive lipidomic analysis, enzyme activity assays, and western blotting on grey and white matter samples from the heavily-affected frontal lobe and less-affected parietal lobe of FTD-GRN cases, FTD-C9orf72 cases, and age-matched neurologically-normal controls. Substantial loss of myelin-enriched sphingolipids (sulfatide, galactosylceramide, sphingomyelin) and myelin proteins was observed in frontal white matter of FTD-GRN cases. A less-pronounced, yet statistically significant, loss of sphingolipids was also observed in FTD-C9orf72. FTD-GRN was distinguished from FTD-C9orf72 and control cases by increased acylcarnitines in frontal grey matter and marked accumulation of cholesterol esters in both frontal and parietal white matter, indicative of myelin break-down. Both FTD-GRN and FTD-C9orf72 cases showed significantly increased lysosomal and phagocytic protein markers, however galactocerebrosidase activity, required for lysosomal catabolism of galactosylceramide and sulfatide, was selectively increased in FTD-GRN. We conclude that both C9orf72 and GRN mutations are associated with disrupted lysosomal homeostasis and white matter lipid loss, but GRN mutations cause a more pronounced disruption to myelin lipid metabolism. Our findings support the hypothesis that hyperactive myelin lipid catabolism is a driver of gliosis and neurodegeneration in FTD-GRN. Since FTD-GRN is associated with white matter hyperintensities by MRI, our data provides important biochemical evidence supporting the use of MRI measures of white matter integrity in the diagnosis and management of FTD.

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.

The role of neurofilament light in genetic frontotemporal lobar degeneration

Genetic frontotemporal lobar degeneration caused by autosomal dominant gene mutations provides an opportunity for targeted drug development in a highly complex and clinically heterogeneous dementia. These neurodegenerative disorders can affect adults in their middle years, progress quickly relative to other dementias, are uniformly fatal and have no approved disease-modifying treatments. Frontotemporal dementia, caused by mutations in the GRN gene which encodes the protein progranulin, is an active area of interventional drug trials that are testing multiple strategies to restore progranulin protein deficiency. These and other trials are also examining neurofilament light as a potential biomarker of disease activity and disease progression and as a therapeutic endpoint based on the assumption that cerebrospinal fluid and blood neurofilament light levels are a surrogate for neuroaxonal damage. Reports from genetic frontotemporal dementia longitudinal studies indicate that elevated concentrations of blood neurofilament light reflect disease severity and are associated with faster brain atrophy. To better inform patient stratification and treatment response in current and upcoming clinical trials, a more nuanced interpretation of neurofilament light as a biomarker of neurodegeneration is now required, one that takes into account its relationship to other pathophysiological and topographic biomarkers of disease progression from early presymptomatic to later clinically symptomatic stages.

Posttraumatic Stress and Traumatic Brain Injury: Cognition, Behavior, and Neuroimaging Markers in Vietnam Veterans

BACKGROUND

Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are common in Veterans and linked to behavioral disturbances, increased risk of cognitive decline, and Alzheimer's disease.

OBJECTIVE

We studied the synergistic effects of PTSD and TBI on behavioral, cognitive, and neuroimaging measures in Vietnam war Veterans.

METHODS

Data were acquired at baseline and after about one-year from male Veterans categorized into: PTSD, TBI, PTSD+TBI, and Veteran controls without PTSD or TBI. We applied manual tractography to examine white matter microstructure of three fiber tracts: uncinate fasciculus (N = 91), cingulum (N = 87), and inferior longitudinal fasciculus (N = 95). ANCOVAs were used to compare Veterans' baseline behavioral and cognitive functioning (N = 285), white matter microstructure, amyloid-β (N = 230), and tau PET (N = 120). Additional ANCOVAs examined scores' differences from baseline to follow-up.

RESULTS

Veterans with PTSD and PTSD+TBI, but not Veterans with TBI only, exhibited poorer behavioral and cognitive functioning at baseline than controls. The groups did not differ in baseline white matter, amyloid-β, or tau, nor in behavioral and cognitive functioning, and tau accumulation change. Progression of white matter abnormalities of the uncinate fasciculus in Veterans with PTSD compared to controls was observed; analyses in TBI and PTSD+TBI were not run due to insufficient sample size.

CONCLUSIONS

PTSD and PTSD+TBI negatively affect behavioral and cognitive functioning, while TBI does not contribute independently. Whether progressive decline in uncinate fasciculus microstructure in Veterans with PTSD might account for cognitive decline should be further studied. Findings did not support an association between PTSD, TBI, and Alzheimer's disease pathology based on amyloid and tau PET.

Functional Imaging for Neurodegenerative Diseases

Diagnosis and monitoring of neurodegenerative diseases has changed profoundly over the past twenty years. Biomarkers are now included in most diagnostic procedures as well as in clinical trials. Neuroimaging biomarkers provide access to brain structure and function over the course of neurodegenerative diseases. They have brought new insights into a wide range of neurodegenerative diseases and have made it possible to describe some of the imaging challenges in clinical populations. MRI mainly explores brain structure while molecular imaging, functional MRI and electro- and magnetoencephalography examine brain function. In this paper, we describe and analyse the current and potential contribution of MRI and molecular imaging in the field of neurodegenerative diseases.

Right uncinate fasciculus supports socioemotional sensitivity in health and neurodegenerative disease

The uncinate fasciculus (UF) connects fronto-insular and temporal gray matter regions involved in visceral emotional reactivity and semantic appraisal, but the precise role of this tract in socioemotional functioning is not well-understood. Using the Revised-Self Monitoring (RSMS) informant questionnaire, we examined whether fractional anisotropy (FA) in the right UF corresponded to socioemotional sensitivity during face-to-face interactions in 145 individuals (40 healthy older adults [NC], and 105 patients with frontotemporal lobar degeneration [FTLD] syndromes in whom this tract is selectively vulnerable, including 31 behavioral variant frontotemporal dementia [bvFTD], 39 semantic variant primary progressive aphasia [svPPA], and 35 nonfluent variant primary progressive aphasia [nfvPPA]). Voxelwise and region-of-interest-based DWI analyses revealed that FA in the right but not left UF significantly predicted RSMS score in the full sample, and in NC and svPPA subgroups alone. Right UF integrity did not predict RSMS score in the bvFTD group, but gray matter volume in the right orbitofrontal cortex adjacent to the UF was a significant predictor. Our results suggest that better socioemotional sensitivity is specifically supported by right UF white matter, highlighting a key neuro-affective relationship found in both healthy aging and neurologically affected individuals. The finding that poorer socioemotional sensitivity corresponded to right UF damage in svPPA but was more robustly influenced by gray matter atrophy adjacent to the UF in bvFTD may have important implications for endpoint selection in clinical trial design for patients with FTLD.

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.

White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation

BACKGROUND

Frontotemporal dementias (FTD) include a genetically heterogeneous group of conditions with distinctive molecular, radiological and clinical features. The majority of radiology studies in FTD compare FTD subgroups to healthy controls to describe phenotype- or genotype-associated imaging signatures. While the characterization of group-specific imaging traits is academically important, the priority of clinical imaging is the meaningful interpretation of individual datasets.

METHODS

To demonstrate the feasibility of single-subject magnetic resonance imaging (MRI) interpretation, we have evaluated the white matter profile of 60 patients across the clinical spectrum of FTD. A z-score-based approach was implemented, where the diffusivity metrics of individual patients were appraised with reference to demographically matched healthy controls. Fifty white matter tracts were systematically evaluated in each subject with reference to normative data.

RESULTS

The z-score-based approach successfully detected white matter pathology in single subjects, and group-level inferences were analogous to the outputs of standard track-based spatial statistics.

CONCLUSIONS

Our findings suggest that it is possible to meaningfully evaluate the diffusion profile of single FTD patients if large normative datasets are available. In contrast to the visual review of FLAIR and T2-weighted images, computational imaging offers objective, quantitative insights into white matter integrity changes even at single-subject level.

Impact of long- and short-range fiber depletion on the cognitive deficits of fronto-temporal dementia

Recent studies suggest a framework where white-matter (WM) atrophy plays an important role in fronto-temporal dementia (FTD) pathophysiology. However, these studies often overlook the fact that WM tracts bridging different brain regions may have different vulnerabilities to the disease and the relative contribution of grey-matter (GM) atrophy to this WM model, resulting in a less comprehensive understanding of the relationship between clinical symptoms and pathology. Using a common factor analysis to extract a semantic and an executive factor, we aimed to test the relative contribution of WM and GM of specific tracts in predicting cognition in the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI). We found that semantic symptoms were mainly dependent on short-range WM fibre disruption, while damage to long-range WM fibres was preferentially associated to executive dysfunction with the GM contribution to cognition being predominant for local processing. These results support the importance of the disruption of specific WM tracts to the core cognitive symptoms associated with FTD. As large-scale WM tracts, which are particularly vulnerable to vascular disease, were highly associated with executive dysfunction, our findings highlight the importance of controlling for risk factors associated with deep WM disease, such as vascular risk factors, in patients with FTD in order not to potentiate underlying executive dysfunction.

Speech and language impairments in behavioral variant frontotemporal dementia: A systematic review

Although behavioral variant frontotemporal dementia (bvFTD) is classically defined by behavioral and socio-emotional changes, impairments often extend to other cognitive functions. These include early speech and language deficits related to the disease's core neural disruptions. Yet, their scope and clinical relevance remains poorly understood. This systematic review characterizes such disturbances in bvFTD, considering clinically, neuroanatomically, genetically, and neuropathologically defined subgroups. We included 181 experimental studies, with at least 5 bvFTD patients diagnosed using accepted criteria, comparing speech and language outcomes between bvFTD patients and healthy controls or between bvFTD subgroups. Results reveal extensive and heterogeneous deficits across cohorts, with (a) consistent lexico-semantic, reading & writing, and prosodic impairments; (b) inconsistent deficits in motor speech and grammar; and (c) relative preservation of phonological skills. Also, preliminary findings suggest that the severity of speech and language deficits might be associated with global cognitive impairment, predominantly temporal or fronto-temporal atrophy and MAPT mutations (vs C9orf72). Although under-recognized, these impairments contribute to patient characterization and phenotyping, while potentially informing diagnosis and management.

Exploring Signatures of Neurodegeneration in Early-Onset Older-Age Bipolar Disorder and Behavioral Variant Frontotemporal Dementia

Introduction: Older-age bipolar disorder (OABD) may involve neurocognitive decline and behavioral disturbances that could share features with the behavioral variant of frontotemporal dementia (bvFTD), making the differential diagnosis difficult in cases of suspected dementia. Objective: To compare the neuropsychological profile, brain morphometry, and structural connectivity patterns between patients diagnosed with bvFTD, patients classified as OABD with an early onset of the disease (EO-OABD), and healthy controls (HC). Methods: bvFTD patients (n = 25, age: 66 ± 7, female: 64%, disease duration: 6 ± 4 years), EO-OABD patients (n = 17, age: 65 ± 9, female: 71%, disease duration: 38 ± 8 years), and HC (n = 28, age: 62 ± 7, female: 64%) were evaluated through neuropsychological tests concerning attention, memory, executive function, praxis, and language. Brain morphometry was analyzed through surface-based morphometry (SBM), while structural brain connectivity was assessed through diffusion tensor imaging (DTI). Results: Both bvFTD and EO-OABD patients showed lower performance in neuropsychological tests of attention, verbal fluency, working memory, verbal memory, and praxis than HC. Comparisons between EO-OABD and bvFTD showed differences limited to cognitive flexibility delayed recall and intrusion errors in the memory test. SBM analysis demonstrated that several frontal, temporal, and parietal regions were altered in both bvFTD and EO-OABD compared to HC. In contrast, comparisons between bvFTD and EO-OABD evidenced differences exclusively in the right temporal pole and the left entorhinal cortex. DTI analysis showed alterations in association and projection fibers in both EO-OABD and bvFTD patients compared to HC. Commissural fibers were found to be particularly affected in EO-OABD. The middle cerebellar peduncle and the pontine crossing tract were exclusively altered in bvFTD. There were no significant differences in DTI analysis between EO-OABD and bvFTD. Discussion: EO-OABD and bvFTD may share an overlap in cognitive, brain morphometry, and structural connectivity profiles that could reflect common underlying mechanisms, even though the etiology of each disease can be different and multifactorial.

Changes in local brain function in mild cognitive impairment due to semantic dementia

AIMS

Mild cognitive impairment due to semantic dementia represents the preclinical stage, involving cognitive decline dominated by semantic impairment below the semantic dementia standard. Therefore, studying mild cognitive impairment due to semantic dementia may identify changes in patients before progression to dementia. However, whether changes in local functional activity occur in preclinical stages of semantic dementia remains unknown. Here, we explored local functional changes in patients with mild cognitive impairment due to semantic dementia using resting-state functional MRI.

METHODS

We administered a battery of neuropsychological tests to twenty-two patients with mild cognitive impairment due to semantic dementia (MCI-SD group) and nineteen healthy controls (HC group). We performed structural MRI to compare gray matter volumes, and resting-state functional MRI with multiple sub-bands and indicators to evaluate functional activity.

RESULTS

Neuropsychological tests revealed a significant decline in semantic performance in the MCI-SD group, but no decline in other cognitive domains. Resting-state functional MRI revealed local functional changes in multiple brain regions in the MCI-SD group, distributed in different sub-bands and indicators. In the normal band, local functional changes were only in the gray matter atrophic area. In the other sub-bands, more regions with local functional changes outside atrophic areas were found across various indicators. Among these, the degree centrality of the left precuneus in the MCI-SD group was positively correlated with general semantic tasks (oral sound naming, word-picture verification).

CONCLUSION

Our study revealed local functional changes in mild cognitive impairment due to semantic dementia, some of which were located outside the atrophic gray matter. Driven by functional connectivity changes, the left precuneus might play a role in preclinical semantic dementia. The study proved the value of frequency-dependent sub-bands, especially the slow-2 and slow-3 sub-bands.

MRI data-driven algorithm for the diagnosis of behavioural variant frontotemporal dementia

INTRODUCTION

Structural brain imaging is paramount for the diagnosis of behavioural variant of frontotemporal dementia (bvFTD), but it has low sensitivity leading to erroneous or late diagnosis.

METHODS

A total of 515 subjects from two different bvFTD cohorts (training and independent validation cohorts) were used to perform voxel-wise morphometric analysis to identify regions with significant differences between bvFTD and controls. A random forest classifier was used to individually predict bvFTD from deformation-based morphometry differences in isolation and together with semantic fluency. Tenfold cross validation was used to assess the performance of the classifier within the training cohort. A second held-out cohort of genetically confirmed bvFTD cases was used for additional validation.

RESULTS

Average 10-fold cross-validation accuracy was 89% (82% sensitivity, 93% specificity) using only MRI and 94% (89% sensitivity, 98% specificity) with the addition of semantic fluency. In the separate validation cohort of definite bvFTD, accuracy was 88% (81% sensitivity, 92% specificity) with MRI and 91% (79% sensitivity, 96% specificity) with added semantic fluency scores.

CONCLUSION

Our results show that structural MRI and semantic fluency can accurately predict bvFTD at the individual subject level within a completely independent validation cohort coming from a different and independent database.

The Role of White Matter Dysfunction and Leukoencephalopathy/Leukodystrophy Genes in the Aetiology of Frontotemporal Dementias: Implications for Novel Approaches to Therapeutics

Frontotemporal dementia (FTD) is a common cause of presenile dementia and is characterized by behavioural and/or language changes and progressive cognitive deficits. Genetics is an important component in the aetiology of FTD, with positive family history of dementia reported for 40% of cases. This review synthesizes current knowledge of the known major FTD genes, including C9orf72 (chromosome 9 open reading frame 72), MAPT (microtubule-associated protein tau) and GRN (granulin), and their impact on neuronal and glial pathology. Further, evidence for white matter dysfunction in the aetiology of FTD and the clinical, neuroimaging and genetic overlap between FTD and leukodystrophy/leukoencephalopathy are discussed. The review highlights the role of common variants and mutations in genes such as CSF1R (colony-stimulating factor 1 receptor), CYP27A1 (cytochrome P450 family 27 subfamily A member 1), TREM2 (triggering receptor expressed on myeloid cells 2) and TMEM106B (transmembrane protein 106B) that play an integral role in microglia and oligodendrocyte function. Finally, pharmacological and non-pharmacological approaches for enhancing remyelination are discussed in terms of future treatments of FTD.

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.

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.

Plasma neurofilament light protein correlates with diffusion tensor imaging metrics in frontotemporal dementia

Neurofilaments are structural components of neurons and are particularly abundant in highly myelinated axons. The levels of neurofilament light chain (NfL) in both cerebrospinal fluid (CSF) and plasma have been related to degeneration in several neurodegenerative conditions including frontotemporal dementia (FTD) and NfL is currently considered as the most promising diagnostic and prognostic fluid biomarker in FTD. Although the location and function of filaments in the healthy nervous system suggests a link between increased NfL and white matter degeneration, such a claim has not been fully elucidated in vivo, especially in the context of FTD. The present study provides evidence of an association between the plasma levels of NfL and white matter involvement in behavioral variant FTD (bvFTD) by relating plasma concentration of NfL to diffusion tensor imaging (DTI) metrics in a group of 20 bvFTD patients. The results of both voxel-wise and tract specific analysis showed that increased plasma NfL concentration is associated with a reduction in fractional anisotropy (FA) in a widespread set of white matter tracts including the superior longitudinal fasciculus, the fronto-occipital fasciculus the anterior thalamic radiation and the dorsal cingulum bundle. Plasma NfL concentration also correlated with cortical thinning in a portion of the right medial prefrontal cortex and of the right lateral orbitofrontal cortex. These results support the hypothesis that blood NfL levels reflect the global level of neurodegeneration in bvFTD and help to advance our understanding of the association between this blood biomarker for FTD and the disease process.

Neuroimaging in genetic frontotemporal dementia and amyotrophic lateral sclerosis

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) have a strong clinical, genetic and pathological overlap. This review focuses on the current understanding of structural, functional and molecular neuroimaging signatures of genetic FTD and ALS. We overview quantitative neuroimaging studies on the most common genes associated with FTD (MAPT, GRN), ALS (SOD1), and both (C9orf72), and summarize visual observations of images reported in the rarer genes (CHMP2B, TARDBP, FUS, OPTN, VCP, UBQLN2, SQSTM1, TREM2, CHCHD10, TBK1).

Microglial burden, activation and dystrophy patterns in frontotemporal lobar degeneration

Background

Microglial dysfunction is implicated in frontotemporal lobar degeneration (FTLD). Although studies have reported excessive microglial activation or senescence (dystrophy) in Alzheimer’s disease (AD), few have explored this in FTLD. We examined regional patterns of microglial burden, activation and dystrophy in sporadic and genetic FTLD, sporadic AD and controls.

Methods

Immunohistochemistry was performed in frontal and temporal grey and white matter from 50 pathologically confirmed FTLD cases (31 sporadic, 19 genetic: 20 FTLD-tau, 26 FTLD-TDP, four FTLD-FUS), five AD cases and five controls, using markers to detect phagocytic (CD68-positive) and antigen-presenting (CR3/43-positive) microglia, and microglia in general (Iba1-positive). Microglial burden and activation (morphology) were assessed quantitatively for each microglial phenotype. Iba1-positive microglia were assessed semi-quantitatively for dystrophy severity and qualitatively for rod-shaped and hypertrophic morphology. Microglia were compared in each region between FTLD, AD and controls, and between different pathological subtypes of FTLD, including its main subtypes (FTLD-tau, FTLD-TDP, FTLD-FUS), and subtypes of FTLD-tau, FTLD-TDP and genetic FTLD. Microglia were also compared between grey and white matter within each lobe for each group.

Results

There was a higher burden of phagocytic and antigen-presenting microglia in FTLD and AD cases than controls, but activation was often not increased. Burden was generally higher in white matter than grey matter, but activation was greater in grey matter. However, microglia varied regionally according to FTLD subtype and disease mechanism. Dystrophy was more severe in FTLD and AD than controls, and more severe in white than grey matter, but this also varied regionally and was particularly extensive in FTLD due to progranulin (GRN) mutations. Presence of rod-shaped and hypertrophic microglia also varied by FTLD subtype.

Conclusions

This study demonstrates regionally variable microglial involvement in FTLD and links this to underlying disease mechanisms. This supports investigation of microglial dysfunction in disease models and consideration of anti-senescence therapies in clinical trials.

The path to biomarker-based diagnostic criteria for the spectrum of neurodegenerative diseases

Introduction: The postmortem examination still represents the reference standard for detecting the pathological nature of chronic neurodegenerative diseases (NDD). This approach displays intrinsic conceptual limitations since NDD represent a dynamic spectrum of partially overlapping phenotypes, shared pathomechanistic alterations that often give rise to mixed pathologies.Areas covered: We scrutinized the international clinical diagnostic criteria of NDD and the literature to provide a roadmap toward a biomarker-based classification of the NDD spectrum. A few pathophysiological biomarkers have been established for NDD. These are time-consuming, invasive, and not suitable for preclinical detection. Candidate screening biomarkers are gaining momentum. Blood neurofilament light-chain represents a robust first-line tool to detect neurodegeneration tout court and serum progranulin helps detect genetic frontotemporal dementia. Ultrasensitive assays and retinal scans may identify Aβ pathology early, in blood and the eye, respectively. Ultrasound also represents a minimally invasive option to investigate the substantia nigra. Protein misfolding amplification assays may accurately detect α-synuclein in biofluids.Expert opinion: Data-driven strategies using quantitative rather than categorical variables may be more reliable for quantification of contributions from pathophysiological mechanisms and their spatial-temporal evolution. A systems biology approach is suitable to untangle the dynamics triggering loss of proteostasis, driving neurodegeneration and clinical evolution.

Diffusion tensor imaging evidence of corticospinal pathway involvement in frontotemporal lobar degeneration

Motor neuron dysfunctions (MNDys) in Frontotemporal Lobar Degeneration (FTLD) have been consistently reported. Clinical and neurophysiological findings proved a variable range of pathological changes, also affecting the corticospinal tract (CST). This study aims to assess white-matter microstructural alterations in a sample of patients with FTLD, and to evaluate the relationship with MNDys. Fifty-four FTLD patients (21 bvFTD, 16 PPA, 17 CBS) and 36 healthy controls participated in a Diffusion Tensor Imaging (DTI) study. We analyzed distinctive and common microstructural alteration patterns across FTLD subtypes, including those affecting the CST, and performed an association analysis between CST integrity and the presence of clinical and/or neurophysiological signs of MNDys. The majority of FTLD patients showed microstructural changes in the motor pathway with a high prevalence of CST alterations also in patients not displaying clinical and/or neurophysiological signs of MNDys. Our results suggest that subtle CST alterations characterize FTLD patients regardless to the subtype. This may be due to the spread of the pathological process to the motor system, even without a clear clinical manifestation of MNDys.

Structural Brain Changes in Pre-Clinical FTD MAPT Mutation Carriers

BACKGROUND

Frontotemporal dementia (FTD) is the second most common cause of early-onset neurodegenerative dementia. Several studies have focused on early imaging changes in FTD patients, but once subjects meet full criteria for FTD diagnosis, structural changes are generally widespread.

OBJECTIVE

This study aims to determine the earliest structural brain changes in asymptomatic MAPT MUTATION carriers.

METHODS

This is a cross-sectional multicenter study comparing global and regional brain volume and white matter integrity in a group of MAPT mutation preclinical carriers and controls. Participants belong to multiple generations of six families with five MAPT mutations. All participants underwent a medical examination, neuropsychological tests, genetic analysis, and a magnetic resonance scan (3T, scout, T1-weighted image followed by EPI (BOLD), MPRAGE, DTI, FLAIR, and ASL sequences).

RESULTS

Volumes of five cortical and subcortical areas were strongly correlated with mutation status: temporal lobe (left amygdala, left temporal pole), cingulate cortex (left rostral anterior cingulate gyrus, right posterior cingulate), and the lingual gyrus in the occipital lobe. We did not find significant differences in whole brain volume, white matter hyperintensities volume, and white matter integrity using DTI analysis.

CONCLUSION

Temporal lobe, cingulate cortex and the lingual gyrus seem to be early targets of the disease and may serve as biomarkers for FTD prior to overt symptom onset.

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.

Effects of Blood Pressure on Cognitive Performance: A Systematic Review

Background: High blood pressure has been associated with an increased risk of developing cognitive impairment. However, this relationship is unclear. This study aims to systematically review the effects of blood pressure on executive functioning, language, memory, attention and processing speed. Methods: The review process was conducted according to the PRISMA-Statement, using the PubMed, PsycINFO, PsycARTICLES and MEDLINE databases. Restrictions were made by selecting studies, which included one or more cognitive measures and reported blood pressure recordings. Studies that included participants with medical conditions or people diagnosed with dementia, psychiatric disorders, stroke and head trauma were excluded. The review allows selecting fifty studies that included 107,405 participants. The results were reported considering different cognitive domains separately: global cognitive functioning, attention, processing speed, executive functions, memory and visuospatial abilities. Results: Higher blood pressure appears to influence cognitive performance in different domains in the absence of dementia and severe cardiovascular diseases, such as strokes. This relationship seems to be independent of demographic factors (gender and education), medical co-morbidity (diabetes), and psychiatric disorders (depression). Furthermore, it presents different patterns considering ageing. In the elderly, a sort of “cardiovascular paradox” is highlighted, which allows considering higher blood pressure as a protective factor for cognitive functioning. Conclusions: The results underline that higher blood pressure is associated with a higher risk of cognitive decline in people without dementia or stroke. These findings highlight the need to introduce early management of blood pressure, even in the absence of clinical hypertension, to prevent the risk of a decline of cognitive functioning typically associated with ageing.

Cognitive and Neuroanatomic Accounts of Referential Communication in Focal Dementia

The primary function of language is to communicate—that is, to make individuals reach a state of mutual understanding about a particular thought or idea. Accordingly, daily communication is truly a task of social coordination. Indeed, successful interactions require individuals to (1) track and adopt a partner’s perspective and (2) continuously shift between the numerous elements relevant to the exchange. Here, we use a referential communication task to study the contributions of perspective taking and executive function to effective communication in nonaphasic human patients with behavioral variant frontotemporal dementia (bvFTD). Similar to previous work, the task was to identify a target object, embedded among an array of competitors, for an interlocutor. Results indicate that bvFTD patients are impaired relative to control subjects in selecting the optimal, precise response. Neuropsychological testing related this performance to mental set shifting, but not to working memory or inhibition. Follow-up analyses indicated that some bvFTD patients perform equally well as control subjects, while a second, clinically matched patient group performs significantly worse. Importantly, the neuropsychological profiles of these subgroups differed only in set shifting. Finally, structural MRI analyses related patient impairment to gray matter disease in orbitofrontal, medial prefrontal, and dorsolateral prefrontal cortex, all regions previously implicated in social cognition and overlapping those related to set shifting. Complementary white matter analyses implicated uncinate fasciculus, which carries projections between orbitofrontal and temporal cortices. Together, these findings demonstrate that impaired referential communication in bvFTD is cognitively related to set shifting, and anatomically related to a social-executive network including prefrontal cortices and uncinate fasciculus.

Diagnostic Value of Diffusion Tensor Imaging and Positron Emission Tomography in Early Stages of Frontotemporal Dementia

BACKGROUND

Due to suboptimal sensitivity and specificity of structural and molecular neuroimaging tools, the diagnosis of behavioral variant frontotemporal dementia (bvFTD) remains challenging.

OBJECTIVE

Investigation of the sensitivity of diffusion tensor imaging (DTI) and fluorodeoxyglucose positron emission tomography (FDG-PET) to detect cerebral alterations in early stages of bvFTD despite inconspicuous conventional MRI.

METHODS

Thirty patients with early stages of bvFTD underwent a detailed neuropsychological examination, cerebral 3T MRI with DTI analysis, and FDG-PET. After 12 months of follow-up, all patients finally fulfilled the diagnosis of bvFTD. Individual FDG-PET data analyses showed that 20 patients exhibited a "typical" pattern for bvFTD with bifrontal and/or temporal hypometabolism (bvFTD/PET+), and that 10 patients showed a "non-typical"/normal pattern (bvFTD/PET-). DTI data were compared with 42 healthy controls in an individual and voxel-based group analysis. To examine the clinical relevance of the findings, associations between pathologically altered voxels of DTI or FDG-PET results and behavioral symptoms were estimated by linear regression analyses.

RESULTS

DTI voxel-based group analyses revealed microstructural degeneration in bifrontal and bitemporal areas in bvFTD/PET+ and bvFTD/PET- groups. However, when comparing the sensitivity of individual DTI data analysis with FDG-PET, DTI appeared to be less sensitive. Neuropsychological symptoms were considerably related to neurodegeneration within frontotemporal areas identified by DTI and FDG-PET.

CONCLUSION

DTI seems to be an interesting tool for detection of functionally relevant neurodegenerative alterations in early stages of bvFTD, even in bvFTD/PET- patients. However, at a single subject level, it seems to be less sensitive than FDG-PET. Thus, improvement of individual DTI analysis is necessary.

Networks Disrupted in Linguistic Variants of Frontotemporal Dementia

The non-fluent/agrammatic variant of primary progressive aphasia (nfvPPA) and semantic variant (svPPA) of frontotemporal dementia (FTD) are neurodegenerative diseases. Previous works have shown alterations of fractional anisotropy (FA) and mean diffusivity (MD) from diffusion tensor images (DTIs). This manuscript is aimed at using DTI images to build a global tractography and to identify atrophy patterns of white matter in each variant. Twenty patients with svPPA, 20 patients with nfvPPA, 26 patients with behavioral variant of FTD (bvFTD) and, 33 controls were included. An analysis based on the connectivity of structural networks showed changes in FA and MD in svPPA and nfvPPA with respect to bvFTD. Much damage in the internal networks of the left temporal lobe was found in svPPA patients; in contrast, patients with nfvPPA showed atrophy in networks from the basal ganglia to motor and premotor areas. Those findings support the dual stream model of speech and language.

The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications

Within the wide range of neurodegenerative brain diseases, the differential diagnosis of frontotemporal dementia (FTD) frequently poses a challenge. Often, signs and symptoms are not characteristic of the disease and may instead reflect atypical presentations. Consequently, the use of disease biomarkers is of importance to correctly identify the patients. Here, we describe how neuropsychological characteristics, neuroimaging and neurochemical biomarkers and screening for causal gene mutations can be used to differentiate FTD from other neurodegenerative diseases as well as to distinguish between FTD subtypes. Summarizing current evidence, we propose a stepwise approach in the diagnostic evaluation. Clinical consensus criteria that take into account a full neuropsychological examination have relatively good accuracy (sensitivity [se] 75–95%, specificity [sp] 82–95%) to diagnose FTD, although misdiagnosis (mostly AD) is common. Structural brain MRI (se 70–94%, sp 89–99%) and FDG PET (se 47–90%, sp 68–98%) or SPECT (se 36–100%, sp 41–100%) brain scans greatly increase diagnostic accuracy, showing greater involvement of frontal and anterior temporal lobes, with sparing of hippocampi and medial temporal lobes. If these results are inconclusive, we suggest detecting amyloid and tau cerebrospinal fluid (CSF) biomarkers that can indicate the presence of AD with good accuracy (se 74–100%, sp 82–97%). The use of P-tau₁₈₁ and the Aβ_1–42/Aβ_1–40 ratio significantly increases the accuracy of correctly identifying FTD vs. AD. Alternatively, an amyloid brain PET scan can be performed to differentiate FTD from AD. When autosomal dominant inheritance is suspected, or in early onset dementia, mutation screening of causal genes is indicated and may also be offered to at-risk family members. We have summarized genotype–phenotype correlations for several genes that are known to cause familial frontotemporal lobar degeneration, which is the neuropathological substrate of FTD. The genes most commonly associated with this disease (C9orf72, MAPT, GRN, TBK1) are discussed, as well as some less frequent ones (CHMP2B, VCP). Several other techniques, such as diffusion tensor imaging, tau PET imaging and measuring serum neurofilament levels, show promise for future implementation as diagnostic biomarkers.

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.

Single Subject Classification of Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia Using Anatomical, Diffusion Tensor, and Resting-State Functional Magnetic Resonance Imaging

BACKGROUND/OBJECTIVE

Overlapping clinical symptoms often complicate differential diagnosis between patients with Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). Magnetic resonance imaging (MRI) reveals disease specific structural and functional differences that aid in differentiating AD from bvFTD patients. However, the benefit of combining structural and functional connectivity measures to-on a subject-basis-differentiate these dementia-types is not yet known.

METHODS

Anatomical, diffusion tensor (DTI), and resting-state functional MRI (rs-fMRI) of 30 patients with early stage AD, 23 with bvFTD, and 35 control subjects were collected and used to calculate measures of structural and functional tissue status. All measures were used separately or selectively combined as predictors for training an elastic net regression classifier. Each classifier's ability to accurately distinguish dementia-types was quantified by calculating the area under the receiver operating characteristic curves (AUC).

RESULTS

Highest AUC values for AD and bvFTD discrimination were obtained when mean diffusivity, full correlations between rs-fMRI-derived independent components, and fractional anisotropy (FA) were combined (0.811). Similarly, combining gray matter density (GMD), FA, and rs-fMRI correlations resulted in highest AUC of 0.922 for control and bvFTD classifications. This, however, was not observed for control and AD differentiations. Classifications with GMD (0.940) and a GMD and DTI combination (0.941) resulted in similar AUC values (p = 0.41).

CONCLUSION

Combining functional and structural connectivity measures improve dementia-type differentiations and may contribute to more accurate and substantiated differential diagnosis of AD and bvFTD patients. Imaging protocols for differential diagnosis may benefit from also including DTI and rs-fMRI.

Cortical microstructure in the behavioural variant of frontotemporal dementia: looking beyond atrophy

Cortical mean diffusivity has been proposed as a novel biomarker for the study of the cortical microstructure in Alzheimer's disease. In this multicentre study, we aimed to assess the cortical microstructural changes in the behavioural variant of frontotemporal dementia (bvFTD); and to correlate cortical mean diffusivity with clinical measures of disease severity and CSF biomarkers (neurofilament light and the soluble fraction beta of the amyloid precursor protein). We included 148 participants with a 3 T MRI and appropriate structural and diffusion weighted imaging sequences: 70 patients with bvFTD and 78 age-matched cognitively healthy controls. The modified frontotemporal lobar degeneration clinical dementia rating was obtained as a measure of disease severity. A subset of patients also underwent a lumbar puncture for CSF biomarker analysis. Two independent raters blind to the clinical data determined the presence of significant frontotemporal atrophy to dichotomize the participants into possible or probable bvFTD. Cortical thickness and cortical mean diffusivity were computed using a surface-based approach. We compared cortical thickness and cortical mean diffusivity between bvFTD (both using the whole sample and probable and possible bvFTD subgroups) and controls. Then we computed the Cohen's d effect size for both cortical thickness and cortical mean diffusivity. We also performed correlation analyses with the modified frontotemporal lobar degeneration clinical dementia rating score and CSF neuronal biomarkers. The cortical mean diffusivity maps, in the whole cohort and in the probable bvFTD subgroup, showed widespread areas with increased cortical mean diffusivity that partially overlapped with cortical thickness, but further expanded to other bvFTD-related regions. In the possible bvFTD subgroup, we found increased cortical mean diffusivity in frontotemporal regions, but only minimal loss of cortical thickness. The effect sizes of cortical mean diffusivity were notably higher than the effect sizes of cortical thickness in the areas that are typically involved in bvFTD. In the whole bvFTD group, both cortical mean diffusivity and cortical thickness correlated with measures of disease severity and CSF biomarkers. However, the areas of correlation with cortical mean diffusivity were more extensive. In the possible bvFTD subgroup, only cortical mean diffusivity correlated with the modified frontotemporal lobar degeneration clinical dementia rating. Our data suggest that cortical mean diffusivity could be a sensitive biomarker for the study of the neurodegeneration-related microstructural changes in bvFTD. Further longitudinal studies should determine the diagnostic and prognostic utility of this novel neuroimaging biomarker.

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.

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.

Atrophy, metabolism and cognition in the posterior cortical atrophy spectrum based on Alzheimer's disease cerebrospinal fluid biomarkers

INTRODUCTION

In vivo clinical, anatomical and metabolic differences between posterior cortical atrophy (PCA) patients presenting with different Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers profiles are still unknown.

METHODS

Twenty-seven PCA patients underwent CSF examination and were classified as 1) PCA with a typical CSF AD profile (PCA-tAD; abnormal amyloid and T-tau/P-tau biomarkers, n = 13); 2) PCA with an atypical AD CSF profile (PCA-aAD; abnormal amyloid biomarker only, n = 9); and 3) PCA not associated with AD (PCA-nonAD; normal biomarkers, n = 5). All patients underwent clinical and cognitive assessment, structural MRI, and a subset of them underwent brain 18F-FDG PET.

RESULTS

All patients' groups showed a common pattern of posterior GM atrophy and hypometabolism typical of PCA, as well as equivalent demographics and clinical/cognitive profiles. PCA-tAD patients showed a group-specific pattern of hypometabolism in the left fusiform gyrus and inferior temporal gyrus. PCA-aAD did not present a group-specific atrophy pattern. Finally, group-specific gray matter atrophy in the right dorsolateral prefrontal cortex, left caudate nucleus and right medial temporal regions and hypometabolism in the right supplementary motor area and paracentral lobule were observed in PCA-nonAD patients.

CONCLUSION

Our findings suggest that both PCA-tAD and PCA-aAD patients are on the AD continuum, in agreement with the recently suggested A/T/N model. Furthermore, in PCA, the underlying pathology has an impact at least on the anatomo-functional presentation. Brain damage observed in PCA-tAD and PCA-aAD was mostly consistent with the well-described presentation of the disease, although it was more widespread in PCA-tAD group, especially in the left temporal lobe. Additional fronto-temporal (especially dorsolateral prefrontal) damage seems to be a clue to underlying non-AD pathology in PCA, which warrants the need for longitudinal follow-ups to investigate frontal symptoms in these patients.

Presymptomatic white matter integrity loss in familial frontotemporal dementia in the GENFI cohort: A cross-sectional diffusion tensor imaging study

Objective

We aimed to investigate mutation-specific white matter (WM) integrity changes in presymptomatic and symptomatic mutation carriers of the C9orf72,MAPT, and GRN mutations by use of diffusion-weighted imaging within the Genetic Frontotemporal dementia Initiative (GENFI) study.

Methods

One hundred and forty mutation carriers (54 C9orf72, 30 MAPT, 56 GRN), 104 presymptomatic and 36 symptomatic, and 115 noncarriers underwent 3T diffusion tensor imaging. Linear mixed effects models were used to examine the association between diffusion parameters and years from estimated symptom onset in C9orf72,MAPT, and GRN mutation carriers versus noncarriers. Post hoc analyses were performed on presymptomatic mutation carriers only, as well as left-right asymmetry analyses on GRN mutation carriers versus noncarriers.

Results

Diffusion changes in C9orf72 mutation carriers are present significantly earlier than both MAPT and GRN mutation carriers - characteristically in the posterior thalamic radiation and more posteriorly located tracts (e.g., splenium of the corpus callosum, posterior corona radiata), as early as 30 years before estimated symptom onset. MAPT mutation carriers showed early involvement of the uncinate fasciculus and cingulum, sparing the internal capsule, whereas involvement of the anterior and posterior internal capsule was found in GRN. Restricting analyses to presymptomatic mutation carriers only, similar - albeit less extensive - patterns were found: posteriorly located WM tracts (e.g., posterior thalamic radiation, splenium of the corpus callosum, posterior corona radiata) in presymptomatic C9orf72, the uncinate fasciculus in presymptomatic MAPT, and the internal capsule (anterior and posterior limbs) in presymptomatic GRN mutation carriers. In GRN, most tracts showed significant left-right differences in one or more diffusion parameter, with the most consistent results being found in the UF, EC, RPIC, and ALIC.

Interpretation

This study demonstrates the presence of early and widespread WM integrity loss in presymptomatic FTD, and suggests a clear genotypic "fingerprint." Our findings corroborate the notion of FTD as a network-based disease, where changes in connectivity are some of the earliest detectable features, and identify diffusion tensor imaging as a potential neuroimaging biomarker for disease-tracking and -staging in presymptomatic to early-stage familial FTD.

The cingulum bundle: Anatomy, function, and dysfunction

The cingulum bundle is a prominent white matter tract that interconnects frontal, parietal, and medial temporal sites, while also linking subcortical nuclei to the cingulate gyrus. Despite its apparent continuity, the cingulum's composition continually changes as fibres join and leave the bundle. To help understand its complex structure, this review begins with detailed, comparative descriptions of the multiple connections comprising the cingulum bundle. Next, the impact of cingulum bundle damage in rats, monkeys, and humans is analysed. Despite causing extensive anatomical disconnections, cingulum bundle lesions typically produce only mild deficits, highlighting the importance of parallel pathways and the distributed nature of its various functions. Meanwhile, non-invasive imaging implicates the cingulum bundle in executive control, emotion, pain (dorsal cingulum), and episodic memory (parahippocampal cingulum), while clinical studies reveal cingulum abnormalities in numerous conditions, including schizophrenia, depression, post-traumatic stress disorder, obsessive compulsive disorder, autism spectrum disorder, Mild Cognitive Impairment, and Alzheimer's disease. Understanding the seemingly diverse contributions of the cingulum will require better ways of isolating pathways within this highly complex tract.

Morphometric MRI as a diagnostic biomarker of frontotemporal dementia: A systematic review to determine clinical applicability

Frontotemporal dementia (FTD) is difficult to diagnose, due to its heterogeneous nature and overlap in symptoms with primary psychiatric disorders. Brain MRI for atrophy is a key biomarker but lacks sensitivity in the early stage. Morphometric MRI-based measures and machine learning techniques are a promising tool to improve diagnostic accuracy. Our aim was to review the current state of the literature using morphometric MRI to classify FTD and assess its applicability for clinical practice. A search was completed using Pubmed and PsychInfo of studies which conducted a classification of subjects with FTD from non-FTD (controls or another disorder) using morphometric MRI metrics on an individual level, using single or combined approaches. 28 relevant articles were included and systematically reviewed following PRISMA guidelines. The studies were categorized based on the type of FTD subjects included and the group(s) against which they were classified. Studies varied considerably in subject selection, MRI methodology, and classification approach, and results are highly heterogeneous. Overall many studies indicate good diagnostic accuracy, with higher performance when differentiating FTD from controls (highest result was accuracy of 100%) than other dementias (highest result was AUC of 0.874). Very few machine learning algorithms have been tested in prospective replication. In conclusion, morphometric MRI with machine learning shows potential as an early diagnostic biomarker of FTD, however studies which use rigorous methodology and validate findings in an independent real-life cohort are necessary before this method can be recommended for use clinically.

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.

Regional structural hypo- and hyperconnectivity of frontal-striatal and frontal-thalamic pathways in behavioral variant frontotemporal dementia

Behavioral variant frontotemporal dementia (bvFTD) has been predominantly considered as a frontotemporal cortical disease, with limited direct investigation of frontal-subcortical connections. We aim to characterize the grey and white matter components of frontal-thalamic and frontal-striatal circuits in bvFTD. Twenty-four patients with bvFTD and 24 healthy controls underwent morphological and diffusion imaging. Subcortical structures were manually segmented according to published protocols. Probabilistic pathways were reconstructed separately from the dorsolateral, orbitofrontal and medial prefrontal cortex to the striatum and thalamus. Patients with bvFTD had smaller cortical and subcortical volumes, lower fractional anisotropy, and higher mean diffusivity metrics, which is consistent with disruptions in frontal-striatal-thalamic pathways. Unexpectedly, regional volumes of the striatum and thalamus connected to the medial prefrontal cortex were significantly larger in bvFTD (by 135% in the striatum, p = .032, and 217% in the thalamus, p = .004), despite smaller dorsolateral prefrontal cortex connected regional volumes (by 67% in the striatum, p = .002, and 65% in the thalamus, p = .020), and inconsistent changes in orbitofrontal cortex connected regions. These unanticipated findings may represent compensatory or maladaptive remodeling in bvFTD networks. Comparisons are made to other neuropsychiatric disorders suggesting a common mechanism of changes in frontal-subcortical networks; however, longitudinal studies are necessary to test this hypothesis.