Meade, Gabriela

Abstract Clinical syndromes of frontotemporal dementia present both distinct and overlapping neuroimaging abnormalities and, consequently, domains of impairment. The aim of this study was to determine how well covariance patterns from multiple neuroimaging modalities discriminate across clinical frontotemporal dementia syndromes. Four-hundred participants with a clinical frontotemporal dementia diagnosis, including behavioral variant of frontotemporal dementia, semantic variant of primary progressive aphasia, right temporal variant of frontotemporal dementia, primary progressive aphasia, apraxia of speech with agrammatic aphasia, primary progressive apraxia of speech, progressive supranuclear palsy and corticobasal syndrome, and 109 cognitively unimpaired participants underwent extensive neurological and neuropsychological assessments, structural MRI, flortaucipir-PET for tau and [18F] fluorodeoxyglucose-PET. Multimodal imaging covariance was investigated at the voxel-level using principal component analysis after adjusting for age and sex effects. Linear regression models were fit to investigate the relationship between principal components and clinical scores. Multinomial logistic regression models investigated the ability of imaging principal components to discriminate across syndromes. The first principal component, which describes the largest source of variability in the data, was a pattern of widespread cortical atrophy (21% variability explained) and of frontoparietal and temporal hypometabolism (21%): scores were lowest in behavioral variant of frontotemporal dementia and correlated with general cognitive impairment. On tau-PET, the first principal component (43% variability) was not significantly different among syndromes and captured a widespread cortical tau uptake, with a focus on the temporal lobe. In all three modalities, the second principal component captured temporal lobe imaging abnormalities, contrasting the motor and semantic clinical syndromes. Subsequent components described smaller variability. On cross-validation, the classifiers based on principal components from MRI (multiclass area under the receiver operating characteristic: 0.76) and [18F]fluorodeoxyglucose-PET (0.79) outperformed tau-PET (0.71), while combining all three modalities did not significantly improve the classifier performance. On cross-validation, the sensitivity of the image-based classifiers was heterogeneous across syndromes and modalities, with highest values for progressive supranuclear palsy and semantic variant of primary progressive aphasia and lowest for primary progressive aphasia and corticobasal syndrome. Our study found that the covariance components of structural and molecular neuroimaging underlying frontotemporal dementia clinical syndromes exist both as a continuum and with syndrome-specific patterns. More than one imaging model was able to correctly classify several frontotemporal dementia clinical syndromes with good specificity and sensitivity, highlighting the value of imaging in aiding patient diagnosis.

Abstract Motor speech disorders (MSDs) are early markers of neurological disease, but expert perceptual analysis is rarely available outside specialized centers. Automated speech analysis offers a scalable alternative, yet prior studies have not systematically compared modeling approaches or assessed clinically relevant metrics in independent datasets. This study compared static acoustic features, articulatory informed Phonet features, and self-supervised pretrained models for binary and multi label MSD classification. We trained and evaluated models on 583 speech samples using speaker level splits. Baseline models included logistic regression and Gated Recurrent Units (GRUs) trained on eGeMAPS and MFCCs. We extracted three types of Phonet derived features and evaluated pretrained HuBERT and SSAST models in frozen, partially fine-tuned, and fully fine-tuned configurations. Binary classification distinguished MSDs from controls, while multi label classification identified six MSD subtypes. Models were assessed using validation AUC, and cut points were tested on two independent datasets. Pretrained and Phonet based models substantially outperformed static acoustic features. In binary classification, HuBERT achieved the highest AUC (0.95), while compact Phonet derived GRUs achieved comparable performance (up to 0.94). These models generalized well to independent datasets, maintaining high sensitivity (0.94) and specificity (0.97). In multi label classification, Phonet models achieved the highest macro average AUC (0.86), but threshold-based subtype performance declined on unseen data. Automated MSD detection is feasible and clinically promising. Binary classification generalized well, whereas multi label classification showed limited threshold stability across datasets.

Background Frontotemporal dementia is an umbrella term that encompasses several clinical syndromes with impaired behavioral, language, and motor functions. These syndromes show considerable overlap in clinical features and imaging patterns. Therefore, there is a need to investigate the syndromic heterogeneity in FTD using unbiased data-driven approaches. Methods We used data-driven clustering analysis of structural magnetic resonance imaging (MRI) data on 400 patients with clinical FTD diagnoses [behavioral variant of frontotemporal dementia (bvFTD), semantic variant of primary progressive aphasia (svPPA), right temporal variant of frontotemporal dementia (rtvFTD), apraxia of speech with agrammatic aphasia (AOS-PAA), primary progressive apraxia of speech (PPAOS), progressive supranuclear palsy (PSP), corticobasal syndrome (CBS) and primary progressive aphasia who did not fit into the other diagnostic categories (PPA-other)]. MR images were w-scored relative to cognitively unimpaired individuals, and principal component analysis was performed. A clustering ensemble approach, including hierarchical algorithms, was applied to the MR-based principal components, and imaging and clinical characteristics of the clusters were investigated. Various numbers of clusters ( K = 2, 3, or 4) were evaluated. Results The K = 3 solution offered the most clinically meaningful separation of FTD syndromes. The first cluster captured mostly frontal MRI abnormalities related to the speech, language and behavioral clinical dimensions, including patients with AOS-PAA, PPAOS, PPA-other, and bvFTD. The second cluster captured mostly temporal abnormalities and included mainly patients with svPPA and rtvFTD, but also bvFTD, AOS-PAA, and PPA-other. The third cluster captured cortical and subcortical atrophy, particularly in the midbrain, and included atypical Parkinsonian syndromes, with all PSP and CBS patients captured in this cluster, as well as most PPAOS patients. Considerable overlap of clinical syndromes was noted across these clusters, whereby patients with AOS-PAA, svPPA, PPA-other, and bvFTD were captured in more than one cluster. Discussion Our findings highlight heterogeneity in FTD, which mainly exists along three axes: speech, language and behavioral deficits reflecting frontal atrophy, language deficits reflecting temporal atrophy, and motor and motor speech deficits reflecting mostly midbrain and subcortical atrophy, with cortical involvement.

Purpose: This viewpoint addresses the complexity of the nomenclature of progressive speech-language disorders, which often exists at the intersection of descriptive symptoms, clinical syndromes, and underlying neuropathology. Using primary progressive apraxia of speech (PPAOS) as an example, we explore how overlapping diagnostic frameworks employed by speech-language pathologists, neurologists, and other clinicians and researchers can lead to different diagnostic labels that may evolve throughout disease progression. These discrepancies and changes can complicate patient understanding, clinical care, and affect eligibility for clinical trials. We highlight the importance of diagnostic specificity, flexibility, and multidisciplinary collaboration in improving patient counseling, prognostication, treatment planning, and clinical research alignment, particularly in the context of the growing number of clinical trials and specialized, multidisciplinary clinics. Conclusions: This viewpoint explores how symptom-based, syndrome-based, and pathology-based diagnoses can work together to support patient care and research. Accurate and specific diagnosis of speech-language disorders has important implications for patient understanding of their condition, identity, prognostic accuracy, access to care, clinical trial enrollment, and treatment planning and efficacy. Misdiagnosis or vague labeling can result in inappropriate interventions, delayed support, and skewed research findings. We argue that multidisciplinary collaboration and flexibility in recognizing evolving symptom-based and syndrome-based labels over the disease course—and as the fields learn more—is essential to empower patients with accurate, actionable information. Embracing both the specificity and the complexity of progressive speech-language disorders can both enhance communication and facilitate research.

Abstract Background Primary progressive apraxia of speech (PPAOS) is a frontotemporal lobar degeneration spectrum disorder characterized by progressive speech motor planning/programming decline. Patients often develop neurological symptoms, frequently evolving into progressive supranuclear palsy (PSP)/corticobasal syndrome (CBS) overlap syndromes. Requests for information about disease progression and causes of death are common amongst our clinical and research encounters; however, empiric evidence to guide these discussions is lacking. Understanding causes of death may enhance counseling and support targeted interventions to delay fatal outcomes. This study aimed to describe causes of death in PPAOS. Methods Data from 29 deceased PPAOS patients (16 males) seen in research studies (July 2010–May 2023) were reviewed. Causes of death were established from medical charts and family reports. Fifteen had prosodic and 12 had phonetic‐predominant PPAOS; two had no clear predominance. Median age at onset was 67.08 years, disease duration 9.78 years, and age at death 76.25 years. 28 patients were white and one was Asian Indian. Results Overall, fifteen (52%) patients died from overall deterioration (cachexia/dehydration), nine (31%) from aspiration pneumonia, and the remainder from falls (10%), asphyxiation (3%), or medical aid in dying (3%). There was no clear association with AOS subtype and cause of death. Conclusions Most deaths in PPAOS resulted from systemic failure or dysphagia‐related complications. Half of the patients died without a clear precipitating event, described by family members as “shutting down,” similar to other prior studies that have shown central nervous system deterioration associated with dementia as cause of death. Aspiration pneumonia caused 34% of deaths, highlighting the need for early swallowing management, including assessments, dietary adjustments, and caregiver education. Falls underscore the importance of addressing balance and motor impairments through proactive prevention strategies. Other factors, such as access to healthcare and medical and psychiatric comorbidities were not analyzed but may influence outcomes. Future research should validate these findings in larger, diverse cohorts and compare outcomes to motor‐onset presentations of PSP and CBS. A comprehensive, multidisciplinary approach addressing motor speech impairments, dysphagia, and fall risks is essential to improve care and potentially extend survival for patients with PPAOS.

Abstract Background Primary progressive apraxia of speech (PPAOS) is a neurodegenerative disorder affecting speech motor planning/programming. Current interventions for PPAOS are limited and often adapted from treatments for nondegenerative AOS, which rely on intensive practice to maintain speech accuracy for practiced items. Systematic interventions for PPAOS are scarce, and no studies have explored differential effects across AOS subtypes. PPAOS subtypes include those with predominant phonetic (articulatory distortions and substitutions) or prosodic (slow speech rate, segmentation) speech changes. These subtypes likely differ in their neural underpinnings and may respond variably to intervention. Delayed auditory feedback (DAF), which introduces a slight delay in hearing one's speech, has shown promise in altering speech rate and fluency for stuttering and hypokinetic dysarthria, though its effects on stroke‐related AOS have been mixed. Recent studies suggest DAF can increase speech rate in patients with AOS in the context of nonfluent/agrammatic primary progressive aphasia. We hypothesized DAF would improve speech clarity and fluency in PPAOS, with subtype‐specific effects: phonetic PPAOS may see slower, more accurate speech, while prosodic PPAOS may produce faster, less segmented speech. Method Four PPAOS patients (3 prosodic, 1 phonetic) completed a web‐based speech battery with and without DAF. Feedback delay was calibrated individually using the DAF Pro app. Speech metrics were analyzed acoustically, and blinded perceptual ratings of deviant speech features were conducted. Results Key data are summarized in Table 1. Three out of four patients found the DAF helpful and two re‐recorded with DAF to allow for quantitative analysis. Patient 1 produced words faster with DAF but had slower total sentence production times; he did not find it helpful. Patient 2 spoke slower with DAF. Both patients produced AMRs faster with DAF, while SMRs were faster for Patient 1 and slower for Patient 2. Blinded perceptual judgments of speech clarity and prosody revealed mixed effects of DAF across participants. Conclusions Preliminary results suggest DAF may differentially benefit phonetic and prosodic PPAOS, particularly in sentences compared to word production. Further research is needed to assess clinical significance, refine DAF calibration, and explore patient‐perceived improvements with guided practice in a larger, more diverse sample.

ABSTRACTIndividuals with primary progressive apraxia of speech (PPAOS) often develop parkinsonism and dysphagia. To evaluate the clinical correlates and impact of dysphagia in this population, we compared enrollment visit data between individuals with (n = 12) versus individuals without (n = 44) dysphagia symptoms. The group with dysphagia had more motor speech symptoms and parkinsonism. Longitudinal analysis revealed that almost everyone developed dysphagia before dying; the average time to death after developing dysphagia was 5.43 years and complications of dysphagia resulted in mortality for 35% of the individuals for whom data were available. These results emphasize the need for dysphagia management and provide useful prognostic estimates.

Abstract Tau aggregation in early affected regions in the asymptomatic stage of Alzheimer’s disease marks a transitional phase between stable asymptomatic amyloid positivity and the clinically manifest stage. How this early region tau aggregation covertly affects brain function during this asymptomatic stage remains unclear. In this study, 83 participants underwent a 128 electrodes resting-state EEG, a dynamic 100 min tau PET scan (18F-MK6240), an amyloid PET scan, a structural T1 MRI scan and neuropsychological assessment. Tau PET data quality control led to a final sample of 66 subjects. Based on the clinical and cognitive status, amyloid and tau PET biomarkers, the group was composed of 37 cognitively unimpaired amyloid negative subjects, 14 cognitively unimpaired amyloid positive subjects and 15 patients with prodromal Alzheimer’s disease. We calculated the average undirected weighted Phase Lag Index in the alpha frequency band with eyes closed and used this as weights for the graph and analysed the global clustering coefficient and characteristic path length in sensor space. As a primary objective, we assessed how these global graph measures correlated with tau PET values, in an a priori defined early metaVOI, comprised of the entorhinal and perirhinal cortex, hippocampus, parahippocampus and fusiform cortex. As secondary analyses, we investigated which specific brain regions were mainly implicated, what the contribution was of amyloid, the effect of electrode density and the relation to cognitive performance. In the overall group and within the cognitively unimpaired amyloid positive subgroup, tau aggregation was associated with a decrease in global clustering coefficient and an increase in characteristic path length. These changes reflect the initial disintegration of the small-world brain network during the transitional phase, even before clinical symptoms are apparent. The correlations are most prominent in the perirhinal cortex, indicating that global deterioration of the network is already present early in the Alzheimer’s disease pathology. We obtained similar results with only taking 64 electrodes into account. To conclude, we found that in the asymptomatic stage of Alzheimer’s disease, tau PET load in medial temporal cortex is associated with global electrophysiological measures of network disintegration. The study demonstrates the potential value of high-density EEG in the era of biologically defined Alzheimer’s disease for characterizing brain function in the asymptomatic stage.