Bone scan findings of Paget's disease of bone in patients with VCP Multisystem Proteinopathy 1.

Multisystem Proteinopathy 1 (MSP1) disease is a rare genetic disorder caused by mutations in the Valosin-Containing Protein (VCP) gene with clinical features of inclusion body myopathy (IBM), frontotemporal dementia (FTD), and Paget's disease of bone (PDB). We performed bone scan imaging in twelve patients (6 females, 6 males) with confirmed VCP gene mutation six (50%) of which has myopathy alone, four (33%) with both PDB and myopathy, and two (15%) were presymptomatic carriers. We aim to characterize the PDB in diagnosed individuals, and potentially identify PDB in the myopathy and presymptomatic groups. Interestingly, two patients with previously undiagnosed PDB had positive diagnostic findings on the bone scan and subsequent radiograph imaging. Among the individuals with PDB, increased radiotracer uptake of the affected bones were of typical distribution as seen in conventional PDB and those reported in other MSP1 cohorts which are the thoracic spine and ribs (75%), pelvis (75%), shoulder (75%) and calvarium (15%). Overall, we show that technetium-99m bone scans done at regular intervals are a sensitive screening tool in patients with MSP1 associated VCP variants at risk for PDB. However, diagnostic confirmation should be coupled with clinical history, biochemical analysis, and skeletal radiographs to facilitate early treatment and prevention complications, acknowledging its limited specificity.

Narcissistic Personality Disorder as Prodromal Feature of Early-Onset, GRN-Positive bvFTD: A Case Report.

Background: Behavioral variant frontotemporal dementia (bvFTD) typically involves subtle changes in personality that can delay a timely diagnosis. Objective: Here, we report the case of a patient diagnosed of GRN-positive bvFTD at the age of 52 presenting with a 7-year history of narcissistic personality disorder, accordingly to DSM-5 criteria. Methods: The patient was referred to neurological and neuropsychological examination. She underwent 3 Tesla magnetic resonance imaging (MRI) and genetic studies. Results: The neuropsychological examination revealed profound deficits in all cognitive domains and 3T brain MRI showed marked fronto-temporal atrophy. A mutation in the GRN gene further confirmed the diagnosis. Conclusions: The present case documents an unusual onset of bvFTD and highlights the problematic nature of the differential diagnosis between prodromal psychiatric features of the disease and primary psychiatric disorders. Early recognition and diagnosis of bvFTD can lead to appropriate management and support for patients and their families. This case highlights the importance of considering neurodegenerative diseases, such as bvFTD, in the differential diagnosis of psychiatric disorders, especially when exacerbations of behavioral traits manifest in adults.

A 3D convolutional neural network to classify subjects as Alzheimer's disease, frontotemporal dementia or healthy controls using brain 18F-FDG PET.

With the arrival of disease-modifying drugs, neurodegenerative diseases will require an accurate diagnosis for optimal treatment. Convolutional neural networks are powerful deep learning techniques that can provide great help to physicians in image analysis. The purpose of this study is to introduce and validate a 3D neural network for classification of Alzheimer's disease (AD), frontotemporal dementia (FTD) or cognitively normal (CN) subjects based on brain glucose metabolism. Retrospective [18F]-FDG-PET scans of 199 CE, 192 FTD and 200 CN subjects were collected from our local database, Alzheimer's disease and frontotemporal lobar degeneration neuroimaging initiatives. Training and test sets were created using randomization on a 90 %-10 % basis, and training of a 3D VGG16-like neural network was performed using data augmentation and cross-validation. Performance was compared to clinical interpretation by three specialists in the independent test set. Regions determining classification were identified in an occlusion experiment and Gradient-weighted Class Activation Mapping. Test set subjects were age- and sex-matched across categories. The model achieved an overall 89.8 % accuracy in predicting the class of test scans. Areas under the ROC curves were 93.3 % for AD, 95.3 % for FTD, and 99.9 % for CN. The physicians' consensus showed a 69.5 % accuracy, and there was substantial agreement between them (kappa = 0.61, 95 % CI: 0.49-0.73). To our knowledge, this is the first study to introduce a deep learning model able to discriminate AD and FTD based on [18F]-FDG PET scans, and to isolate CN subjects with excellent accuracy. These initial results are promising and hint at the potential for generalization to data from other centers.

Sleep and circadian rhythm disruptions in behavioral variant frontotemporal dementia.

INTRODUCTION: Sleep and rest-activity rhythm alterations are common in neurodegenerative diseases. However, their characterization in patients with behavioral variant frontotemporal dementia (bvFTD) has proven elusive. We investigated rest-activity rhythm alterations, sleep disturbances, and their neural correlates in bvFTD. METHODS: Twenty-seven bvFTD patients and 25 healthy controls completed sleep questionnaires and underwent 7 days of actigraphy while concurrently maintaining a sleep diary. Cortical complexity and thickness were calculated from T1-weighted magnetic resonance (MR) images. RESULTS: Compared to controls, bvFTD patients showed longer time in bed (95% confidence interval [CI]: 79.31, 321.83) and total sleep time (95% CI: 24.38, 321.88), lower sleep efficiency (95% CI: -12.58, -95.54), and rest-activity rhythm alterations in the morning and early afternoon. Increased sleep duration was associated with reduced cortical thickness in frontal regions. DISCUSSION: Patients with bvFTD showed longer sleep duration, lower sleep quality, and rest-activity rhythm alterations. Actigraphy could serve as a cost-effective and accessible tool for ecologically monitoring changes in sleep duration in bvFTD patients. HIGHLIGHTS: We assessed sleep and circadian rhythms in behavioral variant frontotemporal dementia (bvFTD) using actigraphy. Patients with bvFTD show increased sleep duration and reduced sleep quality. Patients with bvFTD show rest-activity alterations in the morning and early afternoon. Sleep duration is associated with reduced cortical thickness in frontal regions. These alterations may represent an early sign of neurodegeneration.

Cortical thickness modeling and variability in Alzheimer's disease and frontotemporal dementia.

BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) and frontotemporal dementia (FTD) show different patterns of cortical thickness (CTh) loss compared with healthy controls (HC), even though there is relevant heterogeneity between individuals suffering from each of these diseases. Thus, we developed CTh models to study individual variability in AD, FTD, and HC. METHODS: We used the baseline CTh measures of 379 participants obtained from the structural MRI processed with FreeSurfer. A total of 169 AD patients (63 ± 9 years, 65 men), 88 FTD patients (64 ± 9 years, 43 men), and 122 HC (62 ± 10 years, 47 men) were studied. We fitted region-wise temporal models of CTh using Support Vector Regression. Then, we studied associations of individual deviations from the model with cerebrospinal fluid levels of neurofilament light chain (NfL) and 14-3-3 protein and Mini-Mental State Examination (MMSE). Furthermore, we used real longitudinal data from 144 participants to test model predictivity. RESULTS: We defined CTh spatiotemporal models for each group with a reliable fit. Individual deviation correlated with MMSE for AD and with NfL for FTD. AD patients with higher deviations from the trend presented higher MMSE values. In FTD, lower NfL levels were associated with higher deviations from the CTh prediction. For AD and HC, we could predict longitudinal visits with the presented model trained with baseline data. For FTD, the longitudinal visits had more variability. CONCLUSION: We highlight the value of CTh models for studying AD and FTD longitudinal changes and variability and their relationships with cognitive features and biomarkers.

Behavioral Variant Frontotemporal Dementia With the Dominantly Affected Caudate Nucleus in 18 F-FP-CIT PET/CT.

ABSTRACT: Frontotemporal dementia is a clinical syndrome that is characterized by a progressive deterioration in behavior, personality, and/or language, with relative preservation of memory, and its phenotype and molecular basis are heterogeneous. We present a case of a 62-year-old female patient who underwent 18 F-FDG PET/CT and 18 F-FP-CIT PET/CT for differential diagnosis of psychiatric disease and types of dementia. 18 F-FDG PET/CT image showed a compatible finding for frontotemporal dementia, and 18 F-FP-CIT PET/CT image showed dominantly decreased dopamine transporter activity in the bilateral caudate nucleus.

Assessing network degeneration and phenotypic heterogeneity in genetic frontotemporal lobar degeneration by decoding FDG-PET.

Genetic mutations causative of frontotemporal lobar degeneration (FTLD) are highly predictive of a specific proteinopathy, but there exists substantial inter-individual variability in their patterns of network degeneration and clinical manifestations. We collected clinical and 18Fluorodeoxyglucose-positron emission tomography (FDG-PET) data from 39 patients with genetic FTLD, including 11 carrying the C9orf72 hexanucleotide expansion, 16 carrying a MAPT mutation and 12 carrying a GRN mutation. We performed a spectral covariance decomposition analysis between FDG-PET images to yield unbiased latent patterns reflective of whole brain patterns of metabolism ("eigenbrains" or EBs). We then conducted linear discriminant analyses (LDAs) to perform EB-based predictions of genetic mutation and predominant clinical phenotype (i.e., behavior/personality, language, asymptomatic). Five EBs were significant and explained 58.52 % of the covariance between FDG-PET images. EBs indicative of hypometabolism in left frontotemporal and temporo-parietal areas distinguished GRN mutation carriers from other genetic mutations and were associated with predominant language phenotypes. EBs indicative of hypometabolism in prefrontal and temporopolar areas with a right hemispheric predominance were mostly associated with predominant behavioral phenotypes and distinguished MAPT mutation carriers from other genetic mutations. The LDAs yielded accuracies of 79.5 % and 76.9 % in predicting genetic status and predominant clinical phenotype, respectively. A small number of EBs explained a high proportion of covariance in patterns of network degeneration across FTLD-related genetic mutations. These EBs contained biological information relevant to the variability in the pathophysiological and clinical aspects of genetic FTLD, and for offering valuable guidance in complex clinical decision-making, such as decisions related to genetic testing.

Novel data-driven subtypes and stages of brain atrophy in the ALS-FTD spectrum.

BACKGROUND: TDP-43 proteinopathies represent a spectrum of neurological disorders, anchored clinically on either end by amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). The ALS-FTD spectrum exhibits a diverse range of clinical presentations with overlapping phenotypes, highlighting its heterogeneity. This study was aimed to use disease progression modeling to identify novel data-driven spatial and temporal subtypes of brain atrophy and its progression in the ALS-FTD spectrum. METHODS: We used a data-driven procedure to identify 13 anatomic clusters of brain volume for 57 behavioral variant FTD (bvFTD; with either autopsy-confirmed TDP-43 or TDP-43 proteinopathy-associated genetic variants), 103 ALS, and 47 ALS-FTD patients with likely TDP-43. A Subtype and Stage Inference (SuStaIn) model was trained to identify subtypes of individuals along the ALS-FTD spectrum with distinct brain atrophy patterns, and we related subtypes and stages to clinical, genetic, and neuropathological features of disease. RESULTS: SuStaIn identified three novel subtypes: two disease subtypes with predominant brain atrophy in either prefrontal/somatomotor regions or limbic-related regions, and a normal-appearing group without obvious brain atrophy. The limbic-predominant subtype tended to present with more impaired cognition, higher frequencies of pathogenic variants in TBK1 and TARDBP genes, and a higher proportion of TDP-43 types B, E and C. In contrast, the prefrontal/somatomotor-predominant subtype had higher frequencies of pathogenic variants in C9orf72 and GRN genes and higher proportion of TDP-43 type A. The normal-appearing brain group showed higher frequency of ALS relative to ALS-FTD and bvFTD patients, higher cognitive capacity, higher proportion of lower motor neuron onset, milder motor symptoms, and lower frequencies of genetic pathogenic variants. The overall SuStaIn stages also correlated with evidence for clinical progression including longer disease duration, higher King's stage, and cognitive decline. Additionally, SuStaIn stages differed across clinical phenotypes, genotypes and types of TDP-43 pathology. CONCLUSIONS: Our findings suggest distinct neurodegenerative subtypes of disease along the ALS-FTD spectrum that can be identified in vivo, each with distinct brain atrophy, clinical, genetic and pathological patterns.

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.

Frontotemporal Dementia-Parkinsonism Due to MAPT Gene Variant Presenting with Rest and Action Tremor.

A 50-year-old male presented with a four-year history of gradually progressive rest tremor in the distal right lower limb and then spreading to the left lower limb in last 10-12 months. He developed right arm rest and action tremor two years later. Magnetic resonance imaging scans showed progressive frontotemporal and asymmetrical mesial temporal atrophy. Genetic testing revealed a heterozygous c.915+16C>T pathogenic variant in intron 9 of the MAPT gene. Presentation with rest tremor should not exclude frontotemporal dementia-parkinsonism due to a MAPT variant as a differential diagnosis though rest tremor is a rare presentation.

The involvement of language-associated networks, tracts, and cortical regions in frontotemporal dementia and amyotrophic lateral sclerosis: Structural and functional alterations.

BACKGROUND: Language deficits are cardinal manifestations of some frontotemporal dementia (FTD) phenotypes and also increasingly recognized in sporadic and familial amyotrophic lateral sclerosis (ALS). They have considerable social and quality-of-life implications, and adaptive strategies are challenging to implement. While the neuropsychological profiles of ALS-FTD phenotypes are well characterized, the neuronal underpinnings of language deficits are less well studied. METHODS: A multiparametric, quantitative neuroimaging study was conducted to characterize the involvement of language-associated networks, tracts, and cortical regions with a panel of structural, diffusivity, and functional magnetic resonance imaging (MRI) metrics. Seven study groups were evaluated along the ALS-FTD spectrum: healthy controls (HC), individuals with ALS without cognitive impairment (ALSnci), C9orf72-negative ALS-FTD, C9orf72-positive ALS-FTD, behavioral-variant FTD (bvFTD), nonfluent variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA). The integrity of the Broca's area, Wernicke's area, frontal aslant tract (FAT), arcuate fascicle (AF), inferior occipitofrontal fascicle (IFO), inferior longitudinal fascicle (ILF), superior longitudinal fascicle (SLF), and uncinate fascicle (UF) was quantitatively evaluated. The functional connectivity (FC) between Broca's and Wernicke' areas and FC along the FAT was also specifically assessed. RESULTS: Patients with nfvPPA and svPPA exhibit distinctive patterns of gray and white matter degeneration in language-associated brain regions. Individuals with bvFTD exhibit Broca's area, right FAT, right IFO, and UF degeneration. The ALSnci group exhibits Broca's area atrophy and decreased FC along the FAT. Both ALS-FTD cohorts, irrespective of C9orf72 status, show bilateral FAT, AF, and IFO pathology. Interestingly, only C9orf72-negative ALS-FTD patients exhibit bilateral uncinate and right ILF involvement, while C9orf72-positive ALS-FTD patients do not. CONCLUSIONS: Language-associated tracts and networks are not only affected in language-variant FTD phenotypes but also in ALS and bvFTD. Language domains should be routinely assessed in ALS irrespective of the genotype.

Coexistence of Amyotrophic Lateral Sclerosis and Alzheimer's Disease: Case Report and Review of the Literature.

We describe a case of amyotrophic lateral sclerosis (ALS) associated with Alzheimer's disease (AD) and review the literature about the coexistence of the two entities, highlighting the following: mean age at onset is 63.8 years, with slight female predominance; ALS tends to manifest after cognitive impairment and often begins in the bulbar region; average disease duration is 3 years; cognitive phenotype is mostly amnestic; the pattern of brain involvement is, in most cases, consistent with AD. Our case and the reviewed ones suggest that patients with ALS and dementia lacking unequivocal features of FTD should undergo additional examinations in order to recognize AD.

Diagnostic accuracy of brain age prediction in a memory clinic population and comparison with clinically available volumetric measures.

The aim of this study was to assess the diagnostic validity of a deep learning-based method estimating brain age based on magnetic resonance imaging (MRI) and to compare it with volumetrics obtained using NeuroQuant (NQ) in a clinical cohort. Brain age prediction was performed on minimally processed MRI data using deep convolutional neural networks and an independent training set. The brain age gap (difference between chronological and biological age) was calculated, and volumetrics were performed in 110 patients with dementia (Alzheimer's disease, frontotemporal dementia (FTD), and dementia with Lewy bodies), and 122 with non-dementia (subjective and mild cognitive impairment). Area-under-the-curve (AUC) based on receiver operating characteristics and logistic regression analyses were performed. The mean age was 67.1 (9.5) years and 48.7% (113) were females. The dementia versus non-dementia sensitivity and specificity of the volumetric measures exceeded 80% and yielded higher AUCs compared to BAG. The explained variance of the prediction of diagnostic stage increased when BAG was added to the volumetrics. Further, BAG separated patients with FTD from other dementia etiologies with > 80% sensitivity and specificity. NQ volumetrics outperformed BAG in terms of diagnostic discriminatory power but the two methods provided complementary information, and BAG discriminated FTD from other dementia etiologies.

The use of neuroimaging techniques in the early and differential diagnosis of dementia.

Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.

Genetic and Neuroimaging Analysis of SIGMAR1 for Frontotemporal Dementia.

BACKGROUND: Recently, Sigma nonopioid intracellular receptor 1 (SIGMAR1) variants have been shown harboring C9orf72 pathogenic repeat expansions in some frontotemporal dementia (FTD) cases. However, no SIGMAR1 genotype analysis has been reported in a cohort absent of C9orf72 pathogenic repeat expansions to date. OBJECTIVE: The present study investigated the contribution of SIGMAR1 independent of C9orf72 gene status to FTD spectrum syndromes. METHODS: We directly sequencing the entire coding region and a minimum of 50 bp from each of the flanking introns of SIGMAR1 gene in 82 sporadic FTD patients (female: male = 42 : 40) and 417 controls. For the patient carrying SIGMAR1 variant, a follow-up 3T MR imaging was performed in the study. RESULTS: Gene sequencing of SIGMAR1 revealed a rare 3'UTR nucleotide variation rs192856872 in a male patient with semantic dementia independent of C9orf72 gene status. The MR imaging showed asymmetrical atrophy in the anterior temporal lobes and the degeneration extends caudally into the posterior temporal lobes as the disease progresses. ESEFinder analysis showed new SRSF1 and SRSF1-IgM-BRCA1 binding sites with significant scores, which is predicted to affect normal splicing. CONCLUSION: We found a novel SIGMAR1 variant independent of C9orf72 gene status associated with semantic dementia phenotype.

Clinical Value of Longitudinal Serum Neurofilament Light Chain in Prodromal Genetic Frontotemporal Dementia.

BACKGROUND AND OBJECTIVES: Elevated serum neurofilament light chain (NfL) is used to identify carriers of genetic frontotemporal dementia (FTD) pathogenic variants approaching prodromal conversion. Yet, the magnitude and timeline of NfL increase are still unclear. Here, we investigated the predictive and early diagnostic value of longitudinal serum NfL for the prodromal conversion in genetic FTD. METHODS: In a longitudinal observational cohort study of genetic FTD pathogenic variant carriers, we examined the diagnostic accuracy and conversion risk associated with cross-sectional and longitudinal NfL. Time periods relative to prodromal conversion (>3, 3-1.5, 1.5-0 years before; 0-1.5 years after) were compared with values of participants who did not convert. Next, we modeled longitudinal NfL and MRI volume trajectories to determine their timeline. RESULTS: We included 21 participants who converted (5 chromosome 9 open-reading frame 72 [C9orf72], 10 progranulin [GRN], 5 microtubule-associated protein tau [MAPT], and 1 TAR DNA-binding protein [TARDBP]) and 61 who did not (20 C9orf72, 30 GRN, and 11 MAPT). Participants who converted had higher NfL levels at all examined periods before prodromal conversion (median values 14.0-18.2 pg/mL; betas = 0.4-0.7, standard error [SE] = 0.1, p < 0.046) than those who did not (6.5 pg/mL) and showed further increase 0-1.5 years after conversion (28.4 pg/mL; beta = 1.0, SE = 0.1, p < 0.001). Annualized longitudinal NfL change was only significantly higher in participants who converted (vs. participants who did not) 0-1.5 years after conversion (beta = 1.2, SE = 0.3, p = 0.001). Diagnostic accuracy of cross-sectional NfL for prodromal conversion (vs. nonconversion) was good-to-excellent at time periods before conversion (area under the curve range: 0.72-0.92), improved 0-1.5 years after conversion (0.94-0.97), and outperformed annualized longitudinal change (0.76-0.84). NfL increase in participants who converted occurred earlier than frontotemporal MRI volume change and differed by genetic group and clinical phenotypes. Higher NfL corresponded to increased conversion risk (hazard ratio: cross-sectional = 6.7 [95% CI 3.3-13.7]; longitudinal = 13.0 [95% CI 4.0-42.8]; p < 0.001), but conversion-free follow-up time varied greatly across participants. DISCUSSION: NfL increase discriminates individuals who convert to prodromal FTD from those who do not, preceding significant frontotemporal MRI volume loss. However, NfL alone is limited in predicting the exact timing of prodromal conversion. NfL levels also vary depending on underlying variant-carrying genes and clinical phenotypes. These findings help to guide participant recruitment for clinical trials targeting prodromal genetic FTD.

Sex influences clinical phenotype in valosin-containing protein mutations: A case family report and systematic literature review.

OBJECTIVE: Mutations in the valosin-containing protein (VCP) gene cause autosomal dominant multisystem proteinopathy 1 (MSP1), characterized by a variable combination of inclusion body myopathy (IBM), Paget's disease of bone (PDB), and frontotemporal dementia (FTD). Here we report a novel VCP missense mutations in an Italian family with FTD as the prevalent manifestation and compare our results with those described in the literature. METHODS: We described the clinical, molecular, and imaging data of the studied family. We also conducted a systematic literature search with the aim of comparing our findings with previously reported VCP-related phenotypes. RESULTS: A novel heterozygous VCP missense mutation (c 0.473 T > C/p.Met158Thr) was found in all the affected family members. The proband is a 69-year-old man affected by progressive muscle weakness since the age of 49. Muscle MRI showed patchy fatty infiltration in most muscles, and STIR sequences revealed an unusual signal increase in distal leg muscles. At age 65, he presented a cognitive disorder suggestive of behavioral variant FTD. A bone scintigraphy also revealed PDB. The patient's mother, his maternal aunt and her daughter had died following a history of cognitive deterioration consistent with FTD; the mother also had PDB. No relatives had any muscular impairments. Reviewing the literature data, we observed a different sex distribution of VCP-related phenotypes, being FTD prevalence higher among women as compared to men (51.2 % vs 31.2 %) and IBM prevalence higher among men as compared to women (92.1 % vs 72.8 %). DISCUSSION: This study broadened our clinical, genetic, and imaging knowledge of VCP-related disorders.

Cortical signature of depressive symptoms in frontotemporal dementia: A surface-based analysis.

BACKGROUND AND OBJECTIVES: Depressive symptoms are frequently reported in patients affected by frontotemporal dementia (FTD). At structural MRI, cortical features of depressed FTD patients have been poorly described. Our objective was to investigate correlations between cortical measures and depression severity in FTD patients. METHODS: Data were obtained from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) database. We included 98 controls and 92 FTD patients, n = 38 behavioral variant FTD (bvFTD), n = 26 non-fluent variant Primary Progressive Aphasia (nfvPPA), and n = 28 semantic variant Primary Progressive Aphasia (svPPA). Patients underwent clinical and cognitive evaluations, as well as a 3D T1-weighted MRI on a 3 Tesla scanner (Siemens, Trio Tim system). Depression was evaluated by means of Geriatric Depression Scale (GDS). Surface-based analysis was performed on T1-weighted images to evaluate cortical thickness, a measure of gray matter integrity, and local gyrification index (lGI), a quantitative metric of cortical folding. RESULTS: Patients affected by svPPA were more depressed than controls at NPI and depression severity at GDS was higher in svPPA and bvFTD. Severity of depression correlated with a decrease in lGI in left precentral and superior frontal gyrus, supramarginal and postcentral gyrus and right precentral, supramarginal, superior parietal and superior frontal gyri. Furthermore, depression severity correlated positively with cortical thickness in the left medial orbitofrontal cortex. DISCUSSION: We found that lGI was associated with depressive symptoms over brain regions involved in the pathophysiology of major depressive disorder. This finding provides novel insights into the mechanisms underlying psychiatric symptoms in FTD.

Expressive Prosody in Patients With Focal Anterior Temporal Neurodegeneration.

BACKGROUND AND OBJECTIVES: Progressive focal anterior temporal lobe (ATL) neurodegeneration has been historically called semantic dementia. More recently, semantic variant primary progressive aphasia (svPPA) and semantic behavioral variant frontotemporal dementia (sbvFTD) have been linked with predominant left and right ATL neurodegeneration, respectively. Nonetheless, clinical tools for an accurate diagnosis of sbvFTD are still lacking. Expressive prosody refers to the modulation of pitch, loudness, tempo, and quality of voice used to convey emotional and linguistic information and has been linked to bilateral but right-predominant frontotemporal functioning. Changes in expressive prosody can be detected with semiautomated methods and could represent a useful diagnostic marker of socioemotional functioning in sbvFTD. METHODS: Participants underwent a comprehensive neuropsychological and language evaluation and a 3T MRI at the University of California San Francisco. Each participant provided a verbal description of the picnic scene from the Western Aphasia Battery. The fundamental frequency (f0) range, an acoustic measure of pitch variability, was extracted for each participant. We compared the f0 range between groups and investigated associations with an informant-rated measure of empathy, a facial emotion labeling task, and gray matter (GM) volumes using voxel-based morphometry. RESULTS: Twenty-eight patients with svPPA, 18 with sbvFTD, and 18 healthy controls (HCs) were included. f0 range was significantly different across groups: patients with sbvFTD showed reduced f0 range in comparison with both patients with svPPA (mean difference of -1.4 ± 2.4 semitones; 95% CI -2.4 to -0.4]; p < 0.005) and HCs (mean difference of -1.9 ± 3.0 semitones; 95% CI -3.0 to -0.7]; p < 0.001). A higher f0 range was correlated with a greater informant-rated empathy (r = 0.355; p ≤ 0.05), but not facial emotion labeling. Finally, the lower f0 range was correlated with lower GM volume in the right superior temporal gyrus, encompassing anterior and posterior portions (p < 0.05 FWE cluster corrected). DISCUSSION: Expressive prosody may be a useful clinical marker of sbvFTD. Reduced empathy is a core symptom in sbvFTD; the present results extend this to prosody, a core component of social interaction, at the intersection of speech and emotion. They also inform the long-standing debate on the lateralization of expressive prosody in the brain, highlighting the critical role of the right superior temporal lobe.

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.