Distinct Interplay Between Atrophy and Hypometabolism in Alzheimer's Versus Semantic Dementia

Spatial and Temporal Relationships Between Atrophy and Hypometabolism in Behavioral-Variant Frontotemporal Dementia

PURPOSE

Individuals with behavioral-variant frontotemporal dementia (bvFTD) show changes in brain structure as assessed by MRI and brain function assessed by 18FDG-PET hypometabolism. However, current understanding of the spatial and temporal interplay between these measures remains limited.

METHODS

Here, we examined longitudinal atrophy and hypometabolism relationships in 15 bvFTD subjects with 2 to 4 follow-up MRI and PET scans (56 visits total). Subject-specific slopes of atrophy and hypometabolism over time were extracted across brain regions and correlated with baseline measures both locally, via Pearson correlations, and nonlocally, via sparse canonical correlation analyses (SCCA).

RESULTS

Notably, we identified a robust link between initial hypometabolism and subsequent cortical atrophy rate changes in bvFTD subjects. Network-level exploration unveiled alignment between baseline hypometabolism and ensuing atrophy rates in the dorsal attention, language, and default mode networks. SCCA identified 2 significant and highly localized components depicting the connection between baseline hypometabolism and atrophy slope over time. The first centered around bilateral orbitofrontal, frontopolar, and medial prefrontal lobes, whereas the second concentrated in the left temporal lobe and precuneus.

CONCLUSIONS

This study highlights 18FDG-PET as a dependable predictor of forthcoming atrophy in spatially adjacent brain regions for individuals with bvFTD.

Functional and structural network changes related with cognition in semantic dementia longitudinally

Longitudinal changes in the white matter/functional brain networks of semantic dementia (SD), as well as their relations with cognition remain unclear. Using a graph-theoretic method, we examined the neuroimaging (T1, diffusion tensor imaging, functional MRI) network properties and cognitive performance in processing semantic knowledge of general and six modalities (i.e., object form, color, motion, sound, manipulation and function) from 31 patients (at two time points with an interval of 2 years) and 20 controls (only at baseline). Partial correlation analyses were carried out to explore the relationships between the network changes and the declines of semantic performance. SD exhibited aberrant general and modality-specific semantic impairment, and gradually worsened over time. Overall, the brain networks showed a decreased global and local efficiency in the functional network organization but a preserved structural network organization with a 2-year follow-up. With disease progression, both structural and functional alterations were found to be extended to the temporal and frontal lobes. The regional topological alteration in the left inferior temporal gyrus (ITG.L) was significantly correlated with general semantic processing. Meanwhile, the right superior temporal gyrus and right supplementary motor area were identified to be associated with color and motor-related semantic attributes. SD manifested disrupted structural and functional network pattern longitudinally. We proposed a hub region (i.e., ITG.L) of semantic network and distributed modality-specific semantic-related regions. These findings support the hub-and-spoke semantic theory and provide targets for future therapy.

Longitudinal Spatial Relationships Between Atrophy and Hypometabolism Across the Alzheimer's Disease Continuum

BACKGROUND

The A/T/N framework allows for the assessment of pathology-specific markers of MRI-derived structural atrophy and hypometabolism on 18FDG-PET. However, how these measures relate to each other locally and distantly across pathology-defined A/T/N groups is currently unclear.

OBJECTIVE

To determine the regions of association between atrophy and hypometabolism in A/T/N groups both within and across time points.

METHODS

We examined multivariate multimodal neuroimaging relationships between MRI and 18FDG-PET among suspected non-Alzheimer's disease pathology (SNAP) (A-T/N+; n = 14), Amyloid Only (A+T-N-; n = 24) and Probable AD (A+T+N+; n = 77) groups. Sparse canonical correlation analyses were employed to model spatially disjointed regions of association between MRI and 18FDG-PET data. These relationships were assessed at three combinations of time points -cross-sectionally, between baseline visits and between month 12 (M-12) follow-up visits, as well as longitudinally between baseline and M-12 follow-up.

RESULTS

In the SNAP group, spatially overlapping relationships between atrophy and hypometabolism were apparent in the bilateral temporal lobes when both modalities were assessed at the M-12 timepoint. Amyloid-Only subjects showed spatially discordant distributed atrophy-hypometabolism relationships at all time points assessed. In Probable AD subjects, local correlations were evident in the bilateral temporal lobes when both modalities were assessed at baseline and at M-12. Across groups, hypometabolism at baseline correlated with non-local, or distant, atrophy at M-12.

CONCLUSION

These results support the view that local concordance of atrophy and hypometabolism is the result of a tau-mediated process driving neurodegeneration.

Brain PET Imaging: Frontotemporal Dementia

Brain PET adds value in diagnosing neurodegenerative disorders, especially frontotemporal dementia (FTD) due to its syndromic presentation that overlaps with a variety of other neurodegenerative and psychiatric disorders. 18F-FDG-PET has improved sensitivity and specificity compared with structural MR imaging, with optimal diagnostic results achieved when both techniques are utilized. PET demonstrates superior sensitivity compared with SPECT for FTD diagnosis that is primarily a supplement to other imaging and clinical evaluations. Tau-PET and amyloid-PET primary use in FTD diagnosis is differentiation from Alzheimer disease, although these methods are limited mainly to research settings.

Differential impact of body mass index and leptin on baseline and longitudinal positron emission tomography measurements of the cerebral metabolic rate for glucose in amnestic mild cognitive impairment

Introduction

Several studies have suggested that greater adiposity in older adults is associated with a lower risk of Alzheimer's disease (AD) related cognitive decline, some investigators have postulated that this association may be due to the protective effects of the adipose tissue-derived hormone leptin. In this study we sought to demonstrate that higher body mass indices (BMIs) are associated with greater baseline FDG PET measurements of the regional cerebral metabolic rate for glucose (rCMRgl), a marker of local neuronal activity, slower rCMRgl declines in research participants with amnestic mild cognitive impairment (aMCI). We then sought to clarify the extent to which those relationships are attributable to cerebrospinal fluid (CSF) or plasma leptin concentrations.

Materials and methods

We used baseline PET images from 716 73 ± 8 years-old aMCI participants from the AD Neuroimaging Initiative (ADNI) of whom 453 had follow up images (≥6 months; mean follow up time 3.3 years). For the leptin analyses, we used baseline CSF samples from 81 of the participants and plasma samples from 212 of the participants.

Results

As predicted, higher baseline BMI was associated with greater baseline CMRgl measurements and slower declines within brain regions preferentially affected by AD. In contrast and independently of BMI, CSF, and plasma leptin concentrations were mainly related to less baseline CMRgl within mesocorticolimbic brain regions implicated in energy homeostasis.

Discussion

While higher BMIs are associated with greater baseline CMRgl and slower declines in persons with aMCI, these associations appear not to be primarily attributable to leptin concentrations.

Depressive Symptoms Have Distinct Relationships With Neuroimaging Biomarkers Across the Alzheimer’s Clinical Continuum

Background

Depressive and anxiety symptoms are frequent in Alzheimer’s disease and associated with increased risk of developing Alzheimer’s disease in older adults. We sought to examine their relationships to Alzheimer’s disease biomarkers across the preclinical and clinical stages of the disease.

Method

Fifty-six healthy controls, 35 patients with subjective cognitive decline and 56 amyloid-positive cognitively impaired patients on the Alzheimer’s continuum completed depression and anxiety questionnaires, neuropsychological tests and neuroimaging assessments. We performed multiple regressions in each group separately to assess within group associations of depressive and anxiety symptoms with either cognition (global cognition and episodic memory) or neuroimaging data (gray matter volume, glucose metabolism and amyloid load).

Results

Depressive symptoms, but not anxiety, were higher in patients with subjective cognitive decline and cognitively impaired patients on the Alzheimer’s continuum compared to healthy controls. Greater depressive symptoms were associated with higher amyloid load in subjective cognitive decline patients, while they were related to higher cognition and glucose metabolism, and to better awareness of cognitive difficulties, in cognitively impaired patients on the Alzheimer’s continuum. In contrast, anxiety symptoms were not associated with brain integrity in any group.

Conclusion

These data show that more depressive symptoms are associated with greater Alzheimer’s disease biomarkers in subjective cognitive decline patients, while they reflect better cognitive deficit awareness in cognitively impaired patients on the Alzheimer’s continuum. Our findings highlight the relevance of assessing and treating depressive symptoms in the preclinical stages of Alzheimer’s disease.

Characterizing Differences in Functional Connectivity Between Posterior Cortical Atrophy and Semantic Dementia by Seed-Based Approach

Background

Posterior cortical atrophy (PCA) and semantic dementia (SD) are focal syndromes involving different cerebral regions. This study aimed to demonstrate the existence of abnormal functional connectivity (FC) with an affected network in PCA and SD.

Methods

A total of 10 patients with PCA, 12 patients with SD, and 11 controls were recruited to undergo a detailed clinical history interview and physical examination, neuropsychological assessments, and PET/MRI scan. Seed-based FC analyses were conducted to construct FC in language network, visual network, and salience network. The two-sample t-test was performed to reveal distinct FC patterns in PCA and SD, and we further related the FC difference to cognition. Meanwhile, the uptake value of fluorodeoxyglucose in regions with FC alteration was also extracted for comparison.

Results

We found a global cognitive impairment in patients with PCA and SD. The results of FC analyses showed that patients with PCA present decreased FC in left precentral gyrus to left V1 and increased FC in right inferior frontal gyrus to right V1 in the visual network, right medial frontal gyrus and left fusiform to left anterior temporal lobe and post-superior temporal gyrus in the language network, and left superior temporal gyrus to left anterior insula in the salience network, which were related to cognitive function. Patients with SD had decreased FC from right superior frontal gyrus, right middle frontal gyrus and right superior frontal gyrus to left anterior temporal lobe, or post-superior temporal gyrus in the language network, as well as left superior frontal gyrus to right anterior insula in the salience network, positively relating to cognitive function, but increased FC in the right superior temporal gyrus to left anterior temporal lobe in the language network, and right insula and left anterior cingulum to right anterior insula in the salience network, negatively relating to cognitive function. Most of the regions with FC change in patients with PCA and SD had abnormal metabolism simultaneously.

Conclusion

Abnormal connectivity spread over the cortex involving language and salience networks was common in patients with PCA and SD, whereas FC change involving the visual network was unique to patients with PCA. The FC changes were matched for cognitive deficits.

Network-wise concordance of multimodal neuroimaging features across the Alzheimer's disease continuum

Background

Concordance between cortical atrophy and cortical glucose hypometabolism within distributed brain networks was evaluated among cerebrospinal fluid (CSF) biomarker-defined amyloid/tau/neurodegeneration (A/T/N) groups.

Method

We computed correlations between cortical thickness and fluorodeoxyglucose metabolism within 12 functional brain networks. Differences among A/T/N groups (biomarker normal [BN], Alzheimer's disease [AD] continuum, suspected non-AD pathologic change [SNAP]) in network concordance and relationships to longitudinal change in cognition were assessed.

Results

Network-wise markers of concordance distinguish SNAP subjects from BN subjects within the posterior multimodal and language networks. AD-continuum subjects showed increased concordance in 9/12 networks assessed compared to BN subjects, as well as widespread atrophy and hypometabolism. Baseline network concordance was associated with longitudinal change in a composite memory variable in both SNAP and AD-continuum subjects.

Conclusions

Our novel study investigates the interrelationships between atrophy and hypometabolism across brain networks in A/T/N groups, helping disentangle the structure-function relationships that contribute to both clinical outcomes and diagnostic uncertainty in AD.

Sex-specificities in anxiety and depressive symptoms across the lifespan and their links with multimodal neuroimaging

BACKGROUND

Anxiety and depressive symptoms are associated with impaired well-being, higher risk of developing psychoaffective disorders and are risk factors for Alzheimer's disease (AD). To further understand their relevance and the mechanisms underlying their link with AD, our aims were to assess how anxiety and depressive symptoms changed with age and related to AD neuroimaging biomarkers across the adult lifespan, while also exploring sex specificities.

METHODS

210 cognitively normal participants aged 19-86 years (101 men, 109 women) completed assessments of anxiety and depressive symptoms with the STAI-A and MADRS respectively, and neuroimaging measurements including structural MRI, FDG-PET and amyloid-PET. 167 of those were followed-up over 1.5-3 years. Multiple regressions were performed to assess the links between anxiety or depressive symptoms versus age, global cognition or each imaging modality, both cross-sectionally and longitudinally; and general linear models we used to test the interactive effect of sex on these associations.

RESULTS

Depressive symptoms decreased with age, while anxiety symptoms increased only among women. Higher anxiety symptoms were associated with lower grey matter (GM) volume and glucose metabolism, with an interaction of sex, this relationship being significant only in women. Longitudinally, only low baseline GM volume predicted an increase in anxiety symptoms with time.

LIMITATIONS

Only 43% of participants reported depressive symptoms. Despite additional analyses, the low variability in the measure might have prevented us from detecting subtle changes.

CONCLUSIONS

This study emphasizes the need to consider anxiety symptoms in assessments for dementia risk, particularly in women.

rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data

The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smoothing of amyloid-PET scans performed with any of the FDA-approved radiotracers (¹⁸F-florbetapir/FBP, ¹⁸F-florbetaben/FBB or ¹⁸F-flutemetamol/FLUTE). Each image undergoes spatial normalization based on weighted PET templates and data-driven differential smoothing, then allowing users to perform their quantification of choice. Prior to normalization, users can choose whether to automatically reset the origin of the image to the center of mass or proceed with the pipeline with the image as it is. We validate rPOP with n = 740 (514 FBP, 182 FBB, 44 FLUTE) amyloid-PET scans from the Imaging Dementia-Evidence for Amyloid Scanning - Brain Health Registry sub-study (IDEAS-BHR) and n = 1,518 scans from the Alzheimer's Disease Neuroimaging Initiative (n = 1,249 FBP, n = 269 FBB), including heterogeneous acquisition and reconstruction protocols. After running rPOP, a standard quantification to extract Standardized Uptake Value ratios and the respective Centiloids conversion was performed. rPOP-based amyloid status (using an independent pathology-based threshold of ≥24.4 Centiloid units) was compared with either local visual reads (IDEAS-BHR, n = 663 with complete valid data and reads available) or with amyloid status derived from an MRI-based PET processing pipeline (ADNI, thresholds of >20/>18 Centiloids for FBP/FBB). Finally, within the ADNI dataset, we tested the linear associations between rPOP- and MRI-based Centiloid values. rPOP achieved accurate warping for N = 2,233/2,258 (98.9%) in the first pass. Of the N = 25 warping failures, 24 were rescued with manual reorientation and origin reset prior to warping. We observed high concordance between rPOP-based amyloid status and both visual reads (IDEAS-BHR, Cohen's k = 0.72 [0.7-0.74], ∼86% concordance) or MRI-pipeline based amyloid status (ADNI, k = 0.88 [0.87-0.89], ∼94% concordance). rPOP- and MRI-pipeline based Centiloids were strongly linearly related (R²:0.95, p<0.001), with this association being significantly modulated by estimated PET resolution (β= -0.016, p<0.001). rPOP provides reliable MRI-free amyloid-PET warping and quantification, leveraging widely available software and only requiring an attenuation-corrected amyloid-PET image as input. The rPOP pipeline enables the comparison and merging of heterogeneous datasets and is publicly available at https://github.com/leoiacca/rPOP.

Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer's disease

Posterior cortical hypometabolism measured with [18F]-Fluorodeoxyglucose (FDG)-PET is a well-known marker of Alzheimer's disease-related neurodegeneration, but its associations with underlying neuropathological processes are unclear. We assessed cross-sectionally the relative contributions of three potential mechanisms causing hypometabolism in the retrosplenial and inferior parietal cortices: local molecular (amyloid and tau) pathology and atrophy, distant factors including contributions from the degenerating medial temporal lobe or molecular pathology in functionally connected regions, and the presence of the apolipoprotein E (APOE) ε4 allele. Two hundred and thirty-two amyloid-positive cognitively impaired patients from two cohorts (University of California, San Francisco, UCSF, and Alzheimer's Disease Neuroimaging Initiative, ADNI) underwent MRI and PET with FDG, amyloid-PET using [11C]-Pittsburgh Compound B, [18F]-Florbetapir, or [18F]-Florbetaben, and [18F]-Flortaucipir tau-PET within one year. Standard uptake value ratios (SUVR) were calculated using tracer-specific reference regions. Regression analyses were run within cohorts to identify variables associated with retrosplenial or inferior parietal FDG SUVR. On average, ADNI patients were older and were less impaired than UCSF patients. Regional patterns of hypometabolism were similar between cohorts, though there were cohort differences in regional gray matter atrophy. Local cortical thickness and tau-PET (but not amyloid-PET) were independently associated with both retrosplenial and inferior parietal FDG SUVR (ΔR2 = .09 to .21) across cohorts in models that also included age and disease severity (local model). Including medial temporal lobe volume improved the retrosplenial FDG model in ADNI (ΔR2 = .04, p = .008) but not UCSF (ΔR2 < .01, p = .52), and did not improve the inferior parietal models (ΔR2s < .01, ps > .37). Interaction analyses revealed that medial temporal volume was more strongly associated with retrosplenial FDG SUVR at earlier disease stages (p = .06 in UCSF, p = .046 in ADNI). Exploratory analyses across the cortex confirmed overall associations between hypometabolism and local tau pathology and thickness and revealed associations between medial temporal degeneration and hypometabolism in retrosplenial, orbitofrontal, and anterior cingulate cortices. Finally, our data did not support hypotheses of a detrimental effect of pathology in connected regions or of an effect of the APOE ε4 allele in impaired participants. Overall, in two independent groups of patients at symptomatic stages of Alzheimer's disease, cortical hypometabolism mainly reflected structural neurodegeneration and tau, but not amyloid, pathology.

Biphasic cortical macro- and microstructural changes in autosomal dominant Alzheimer's disease

INTRODUCTION

A biphasic model for brain structural changes in preclinical Alzheimer's disease (AD) could reconcile some conflicting and paradoxical findings in observational studies and anti-amyloid clinical trials.

METHODS

In this study we tested this model fitting linear versus quadratic trajectories and computed the timing of the inflection points vertexwise of cortical thickness and cortical diffusivity-a novel marker of cortical microstructure-changes in 389 participants from the Dominantly Inherited Alzheimer Network.

RESULTS

In early preclinical AD, between 20 and 15 years before estimated symptom onset, we found increases in cortical thickness and decreases in cortical diffusivity followed by cortical thinning and cortical diffusivity increases in later preclinical and symptomatic stages. The inflection points 16 to 19 years before estimated symptom onset are in agreement with the start of tau biomarker alterations.

DISCUSSION

These findings confirm a biphasic trajectory for brain structural changes and have direct implications when interpreting magnetic resonance imaging measures in preventive AD clinical trials.

Neuroimaging in Frontotemporal Dementia: Heterogeneity and Relationships with Underlying Neuropathology

Frontotemporal dementia encompasses a group of clinical syndromes defined pathologically by degeneration of the frontal and temporal lobes. Historically, these syndromes have been challenging to diagnose, with an average of about three years between the time of symptom onset and the initial evaluation and diagnosis. Research in the field of neuroimaging has revealed numerous biomarkers of the various frontotemporal dementia syndromes, which has provided clinicians with a method of narrowing the differential diagnosis and improving diagnostic accuracy. As such, neuroimaging is considered a core investigative tool in the evaluation of neurodegenerative disorders. Furthermore, patterns of neurodegeneration correlate with the underlying neuropathological substrates of the frontotemporal dementia syndromes, which can aid clinicians in determining the underlying etiology and improve prognostication. This review explores the advancements in neuroimaging and discusses the phenotypic and pathologic features of behavioral variant frontotemporal dementia, semantic variant primary progressive aphasia, and nonfluent variant primary progressive aphasia, as seen on structural magnetic resonance imaging and positron emission tomography.

Automatic analysis of integrated magnetic resonance and positron emission tomography images improves the accuracy of detection of focal cortical dysplasia type IIb lesions

We aimed to develop an efficient and objective pre-evaluation method to identify the precise location of a focal cortical dysplasia lesion before surgical resection to reduce medication use and decrease the post-operative frequency of seizure attacks. We developed a novel machine learning-based approach using cortical surface-based features by integrating MRI and metabolic PET to identify focal cortical dysplasia lesions. Significant surface-based features of 22 patients with histopathologically proven FCD IIb lesions were extracted from PET and MRI images using FreeSurfer. We modified significant parameters, trained and tested the XGBoost model using these surface-based features, and made predictions. We detected lesions in all 20 patients using the XGBoost model, with an accuracy of 91%. We used one-way chi-squared test to test the null hypothesis that the population proportion was 50% (p = 0.0001), indicating that our classification of the algorithm was statistically significant. The sensitivity, specificity, and false-positive rates were 93%, 91%, and 9%, respectively. We developed an objective, quantitative XGBoost classifier that combined MRI and PET imaging features to locate focal cortical dysplasia. This automated method yielded better outcomes than conventional visual analysis and single modality quantitative analysis for surgical pre-evaluation, especially in subtle or visually unidentifiable FCD lesions. This time-efficient method would also help doctors identify otherwise overlooked details.

Cognitive and Behavioral Profiles of Left and Right Semantic Dementia: Differential Diagnosis with Behavioral Variant Frontotemporal Dementia and Alzheimer's Disease

BACKGROUND

Semantic dementia (SD) is a subtype of frontotemporal dementia (FTD) characterized by semantic memory loss and preserved abilities of other cognitive functions. The clinical manifestations of SD require a differential diagnosis with Alzheimer's disease (AD), especially those with early onset, and behavioral variant FTD (bvFTD).

OBJECTIVE

The present study aimed to compare cognitive performances and neuropsychiatric symptoms in a population of AD, bvFTD, and left and right SD defined with the support of molecular imaging (amyloid and 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography) and assessed the accuracy of different neuropsychological markers in distinguishing these neurodegenerative diseases.

METHODS

Eighty-seven participants (32 AD, 20 bvFTD, and 35 SD (17 Left-SD and 18 Right-SD) completed a comprehensive neuropsychological battery that included memory, language, attention and executive functions, visuospatial function, visuoconstructional skills, and tasks designed specifically to evaluate prosopagnosia and facial emotions recognition. The Neuropsychiatric Inventory was administered to assess neuropsychiatric symptoms.

RESULTS

An episodic memory test that included semantic cues, a visuospatial test (both impaired in AD), a naming test and a prosopagnosia task (both impaired in SD) were the four most valuable cognitive metrics for the differential diagnosis between groups. Several behavioral abnormalities were differentially present, of which aggression, self-care (both more frequent in bvFTD), and eating habits, specifically overeating and altered dietary preference (more frequent in SD), were the most valuable in group discrimination.

CONCLUSION

Our study highlights the value of a comprehensive neuropsychological and neuropsychiatric evaluation for the differential diagnosis between FTD syndromes and AD.

Altered functional connectivity of cortical networks in semantic variant Primary Progressive Aphasia

As their illness progresses, patients with the semantic variant of Primary Progressive Aphasia (svPPA) frequently exhibit peculiar behaviors indicative of altered visual attention or an increased interest in artistic endeavors. In the present study, we examined changes within and between large-scale functional brain networks that may explain this altered visual behavior. We first examined the connectivity of the visual association network, the dorsal attention network, and the default mode network in healthy young adults (n = 89) to understand the typical architecture of these networks in the healthy brain. We then compared the large-scale functional connectivity of these networks in a group of svPPA patients (n = 12) to a group of age-matched cognitively normal controls (n = 30). Our results showed that the between-network connectivity of the dorsal attention and visual association networks was elevated in svPPA patients relative to controls. We further showed that this heightened between-network connectivity was associated with a decrease in the within-network connectivity of the default mode network, possibly due to progressive degeneration of the anterior temporal lobes in svPPA. These results suggest that focal neurodegeneration can lead to the reorganization of large-scale cognitive networks beyond the primarily affected network(s), possibly contributing to cognitive or behavioral changes that are commonly present as part of the clinical phenotype of svPPA.

Cortical microstructure in the amyotrophic lateral sclerosis-frontotemporal dementia continuum

OBJECTIVE

To characterize the cortical macrostructure and microstructure of behavioral and cognitive changes along the amyotrophic lateral sclerosis (ALS)-frontotemporal dementia (FTD) continuum.

METHODS

We prospectively recruited 88 participants with a 3T MRI structural and diffusion-weighted imaging sequences: 31 with ALS, 20 with the behavioral variant of FTD (bvFTD), and 37 cognitively normal controls. Participants with ALS underwent a comprehensive cognitive and behavioral assessment and were dichotomized into ALS without cognitive or behavioral impairment (ALSno-cbi; n = 12) and ALS with cognitive or behavioral impairment (ALScbi; n = 19). We computed cortical thickness and cortical mean diffusivity using a surface-based approach and explored the cortical correlates of cognitive impairment with the Edinburgh Cognitive and Behavioral ALS Screen.

RESULTS

The ALSno-cbi and ALScbi groups showed different patterns of reduced cortical thickness and increased cortical mean diffusivity. In the ALSno-cbi group, cortical thinning was restricted mainly to the dorsal motor cortex. In contrast, in the ALScbi group, cortical thinning was observed primarily on frontoinsular and temporal regions bilaterally. There were progressive cortical mean diffusivity changes along the ALSno-cbi, ALScbi, and bvFTD clinical continuum. Participants with ALS with either cognitive or behavioral impairment showed increased cortical mean diffusivity in the prefrontal cortex in the absence of cortical thickness.

CONCLUSIONS

Cortical mean diffusivity might be a useful biomarker for the study of extramotor cortical neurodegeneration in the ALS-FTD clinical spectrum.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that the cortical microstructure correlates with cognitive impairment in the ALS-FTD continuum.

Longitudinal structural and metabolic changes in frontotemporal dementia

OBJECTIVE

To compare the sensitivity of structural MRI and 18F-fludeoxyglucose PET (18FDG-PET) to detect longitudinal changes in frontotemporal dementia (FTD).

METHODS

Thirty patients with behavioral variant FTD (bvFTD), 7 with nonfluent/agrammatic variant primary progressive aphasia (nfvPPA), 16 with semantic variant primary progressive aphasia (svPPA), and 43 cognitively normal controls underwent 2-4 MRI and 18FDG-PET scans (total scans/visit = 270) as part of the Frontotemporal Lobar Degeneration Neuroimaging Initiative study. Linear mixed-effects models were carried out voxel-wise and in regions of interest to identify areas showing decreased volume or metabolism over time in patients as compared to controls.

RESULTS

At baseline, patients with bvFTD showed bilateral temporal, dorsolateral, and medial prefrontal atrophy/hypometabolism that extended with time into adjacent structures and parietal lobe. In nfvPPA, baseline atrophy/hypometabolism in supplementary motor cortex extended with time into left greater than right precentral, dorsolateral, and dorsomedial prefrontal cortex. In svPPA, baseline atrophy/hypometabolism encompassed the anterior temporal and medial prefrontal cortex and longitudinal changes were found in temporal, orbitofrontal, and lateral parietal cortex. Across syndromes, there was substantial overlap in the brain regions showing volume and metabolism loss. Even though the pattern of metabolic decline was more extensive, metabolic changes were also more variable and sample size estimates were similar or higher for 18FDG-PET compared to MRI.

CONCLUSION

Our findings demonstrated the sensitivity of 18FDG-PET and structural MRI for tracking disease progression in FTD. Both modalities showed highly overlapping patterns of longitudinal change and comparable sample size estimates to detect longitudinal changes in future clinical trials.

Prospective longitudinal atrophy in Alzheimer's disease correlates with the intensity and topography of baseline tau-PET

β-Amyloid plaques and tau-containing neurofibrillary tangles are the two neuropathological hallmarks of Alzheimer's disease (AD) and are thought to play crucial roles in a neurodegenerative cascade leading to dementia. Both lesions can now be visualized in vivo using positron emission tomography (PET) radiotracers, opening new opportunities to study disease mechanisms and improve patients' diagnostic and prognostic evaluation. In a group of 32 patients at early symptomatic AD stages, we tested whether β-amyloid and tau-PET could predict subsequent brain atrophy measured using longitudinal magnetic resonance imaging acquired at the time of PET and 15 months later. Quantitative analyses showed that the global intensity of tau-PET, but not β-amyloid-PET, signal predicted the rate of subsequent atrophy, independent of baseline cortical thickness. Additional investigations demonstrated that the specific distribution of tau-PET signal was a strong indicator of the topography of future atrophy at the single patient level and that the relationship between baseline tau-PET and subsequent atrophy was particularly strong in younger patients. These data support disease models in which tau pathology is a major driver of local neurodegeneration and highlight the relevance of tau-PET as a precision medicine tool to help predict individual patient's progression and design future clinical trials.

Patient-Tailored, Connectivity-Based Forecasts of Spreading Brain Atrophy

Neurodegenerative diseases appear to progress by spreading via brain connections. Here we evaluated this transneuronal degeneration hypothesis by attempting to predict future atrophy in a longitudinal cohort of patients with behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA). We determined patient-specific "epicenters" at baseline, located each patient's epicenters in the healthy functional connectome, and derived two region-wise graph theoretical metrics to predict future atrophy: (1) shortest path length to the epicenter and (2) nodal hazard, the cumulative atrophy of a region's first-degree neighbors. Using these predictors and baseline atrophy, we could accurately predict longitudinal atrophy in most patients. The regions most vulnerable to subsequent atrophy were functionally connected to the epicenter and had intermediate levels of baseline atrophy. These findings provide novel, longitudinal evidence that neurodegeneration progresses along connectional pathways and, further developed, could lead to network-based clinical tools for prognostication and disease monitoring.

Cross-sectional and longitudinal characterization of SCD patients recruited from the community versus from a memory clinic: subjective cognitive decline, psychoaffective factors, cognitive performances, and atrophy progression over time

Background

Subjective cognitive decline (SCD) defines a heterogeneous population, part of which having Alzheimer’s disease (AD). We aimed at characterizing SCD populations according to whether or not they referred to a memory clinic, by assessing the factors associated with increased AD risk.

Methods

Seventy-eight cognitively unimpaired older adults from the IMAP+ study (Caen) were included, amongst which 28 healthy controls (HC) and 50 SCD recruited from the community (SCD-community; n = 23) or from a memory clinic (SCD-clinic; n = 27). Participants underwent cognitive, psychoaffective, structural MRI, FDG-PET, and amyloid-PET assessments. They were followed up over a mean period of 2.4 ± 0.8 years. The groups were compared in terms of baseline and follow-up levels of SCD (self- and informant-reported), cognition, subclinical anxiety and depression, and atrophy progression over time. We also investigated SCD substrates within each SCD group through the correlations between self-reported SCD and other psychometric and brain measures.

Results

Compared to HC, both SCD groups showed similar cognitive performances but higher informant-reported SCD and anxiety. Compared to SCD-community, SCD-clinic showed higher informant-reported SCD, depression score, and atrophy progression over time but similar brain amyloid load. A significant increase over time was found for depression in the SCD-community and for self-reported praxis-domestic activities SCD factor in the SCD-clinic. Higher self-reported SCD correlated with (i) lower grey matter volume and higher anxiety in SCD-community, (ii) greater informant-reported SCD in SCD-clinic, and (iii) lower glucose metabolism in both SCD groups.

Conclusions

Higher subclinical depression and informant-reported SCD specifically characterize the SCD group that refers to a memory clinic. The same group appears as a frailer population than SCD-community as they show greater atrophy progression over time. Yet, both the SCD groups were quite similar otherwise including for brain amyloid load and the SCD-community showed increased depression score over time. Altogether, our findings highlight the relevance of assessing psychoaffective factors and informant-reported SCD in SCD populations and point to both differences and similarities in SCD populations referring or not to a memory clinic.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0514-z) contains supplementary material, which is available to authorized users.

White Matter Damage in the Semantic Variant of Primary Progressive Aphasia

BACKGROUND

The semantic variant of primary progressive aphasia (svPPA) is a form of dementia, mainly featuring language impairment, for which the extent of white matter (WM) damage is less described than its associated grey matter (GM) atrophy. Our study aimed to characterise the extent of this damage using a sensitive and unbiased approach.

METHODS

We conducted a between-group study comparing 10 patients with a clinical diagnosis of svPPA, recruited between 2011 and 2014 at a tertiary reference centre, with 9 cognitively healthy, age-matched controls. From diffusion tensor imaging (DTI) data, we extracted fractional anisotropy (FA) values using a tract-based spatial statistics approach. We further obtained GM volumetric data using the Freesurfer automated segmentation tool. We compared both groups using non-parametric Wilcoxon rank-sum tests, correcting for multiple comparisons.

RESULTS

Demographic data showed that patients and controls were comparable. As expected, clinical data showed lower results in svPPA than controls on cognitive screening tests. Tractography showed impaired diffusion in svPPA patients, with FA mostly decreased in the longitudinal, uncinate, cingulum and external capsule fasciculi. Volumetric data show significant atrophy in svPPA patients, mostly in the left entorhinal, amygdala, inferior temporal, middle temporal, superior temporal and temporal pole cortices, and bilateral fusiform gyri.

CONCLUSIONS

This syndrome appears to be associated not only with GM but also significant WM degeneration. Thus, DTI could play a role in the differential diagnosis of atypical dementia by specifying WM damage specific to svPPA.

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.