Citations

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 Background Corticobasal syndrome (CBS) is a neurodegenerative syndrome that often results from a 4-repeat tauopathy. Abnormalities on tau PET, structural MRI, and diffusion MRI (dMRI) have been observed in CBS, although no prior work has systematically compared the relative sensitivity of these modalities. In addition, the relationships between tau uptake, volume loss, and white matter degeneration remain incompletely understood. Objective To compare the sensitivity of tau PET, structural volume, and dMRI metrics to differentiate CBS from controls, and to characterize relationships between regional tau uptake, volume loss, and white matter tract abnormalities. Methods Thirty-two participants meeting criteria for possible or probable CBS and 35 healthy controls underwent standardized 3T dMRI, 18 F-flortaucipir tau PET, and detailed neurologic assessment. Diffusion data were processed using complementary diffusion tensor, free-water, and Neurite Orientation Dispersion and Density Imaging (NODDI) pipelines, with tract-level metrics extracted using the Johns Hopkins University-Eve (JHU EVE) White Matter atlas. Regional gray matter volumes and flortaucipir standardized uptake value ratios (SUVRs) were calculated. Global tau PET uptake, represented by the first principal component (PC1), was removed in a secondary tau analysis. Modality-level discrimination was assessed using area under the curve (AUC) analyses. Cross-modality relationships were evaluated using regional correlations and covariate-adjusted models comparing volume- and tau-related predictors of white matter abnormalities. Results Relative to controls, CBS showed widespread higher mean diffusivity (MD) and lower intracellular volume fraction (ICVF), especially in sensorimotor and projection white matter pathways. Structural volume reductions were most prominent in precentral cortex and subcortical regions including putamen, thalamus, and pallidum, whereas tau PET abnormalities were weaker and less spatially extensive. MD showed the strongest overall discrimination between CBS and controls, followed by ICVF, structural volume, PC1-removed tau PET, and original tau PET. In targeted sensorimotor analyses, higher DTI-MD was most strongly associated with lower gray matter volume. PC1-removed sensorimotor tau uptake was also associated with higher sensorimotor DTI-MD, whereas original tau uptake and broader cortical or subcortical tau measures were not significant predictors. Conclusions White matter microstructural disruption is a dominant imaging signature of CBS and is more closely linked to gray matter volume loss than to measurable uptake on tau PET. dMRI, particularly MD and ICVF, may provide greatest sensitivity for detecting disease-related changes in CBS.

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.

Background TAR DNA-binding protein 43 (TDP-43) proteinopathy contributes to Alzheimer's disease progression, but diagnosis remains autopsy-dependent. Objective This study aimed to develop a predictive model using FDG-PET imaging to identify brain regions associated with TDP-43 pathology in vivo. Methods Penalized logistic regression analyzed data from 294 participants and a subset of 159 with Braak and Thal ≥4. Features included FDG standard uptake value ratios (SUVRs) from 123 brain regions and age. Participants were split into training (90%) and testing (10%) datasets, with significant predictors identified by non-zero coefficients at optimal lambda. Results The model achieved 68% accuracy (AUC = 0.70) in 294 participants, highlighting the middle temporal gyrus, parahippocampal gyrus, and hippocampus. In the subset (n = 159), accuracy was 65% (AUC = 0.71), with the medial amygdala and precentral gyrus as key predictors of TDP-43 pathology. Conclusions This study suggests a moderate predictive accuracy of FDG-PET to identify brain regions associated with Alzheimer's disease-related TDP-43 proteinopathy.

Abstract Background The cerebellar dentate is a known site of iron accumulation and tau deposition in progressive supranuclear palsy (PSP); however, detailed iron distribution and localized volume and shape changes remain unclear across PSP clinical variants. Objective The study aimed to clarify details about regional susceptibility distribution, volume, and shape deformation in the cerebellar dentate across PSP clinical variants. Methods Sixty‐seven PSP patients, including 31 PSP‐Richardson syndrome, 12 PSP‐parkinsonism, 10 PSP‐progressive gait freezing, and 14 PSP‐cortical variants (PSP‐frontal, PSP‐speech/language, and PSP‐corticobasal syndrome), and 31 healthy controls underwent 3 Tesla magnetic resonance imaging to reconstruct quantitative susceptibility maps. Manual dentate segmentation was performed to extract magnetic susceptibility and volume adjusted for total intracranial volume. Shape deformation was assessed using Deformetrica atlas construction. Group comparisons were evaluated with Kruskal–Wallis tests and receiver operating characteristic analysis. Results Patients with PSP‐Richardson syndrome, PSP‐parkinsonism, and PSP‐cortical variants showed significantly increased dentate susceptibility compared with controls ( P < 0.05). Patients with PSP‐progressive gait freezing showed no significant susceptibility differences. Volume loss was most prominent in PSP‐cortical variants, bilaterally, and PSP‐Richardson syndrome, left hemisphere only ( P < 0.05). Shape analysis revealed subregion‐specific deformation patterns, especially in the anterior and posterior deformation in PSP‐progressive gait freezing and the ventroanterior deformation in PSP‐cortical variants. Conclusions The PSP clinical variants had different patterns of susceptibility, volume, and shape metrics, reflecting distinct neurodegenerative patterns of the cerebellar dentate. These findings contribute to our understanding of the neurobiology of PSP and may help to improve phenotypic differentiation of PSP clinical variants. © 2026 International Parkinson and Movement Disorder Society.

Abstract Background Atypical clinical presentations of Alzheimer's disease (AD) are associated with heterogeneous patterns of cortical tau‐PET uptake. The medial‐temporal (MTL) meta‐ROI is typically used to determine tau‐PET abnormality in AD, but this approach may not detect focal uptake in atypical patients. Our goal was to develop regional tau‐PET cut‐points and determine whether the number of positive regions better captures positive tau‐PET signal in atypical AD. Method 127 amyloid‐positive atypical AD (visual=68, language=39, motor=15, others=5) and 62 amyloid‐negative cognitively unimpaired (CU) individuals were recruited by the Neurodegenerative Research Group, Mayo Clinic, and underwent, amyloid‐PET and 18 F‐AV‐1451(tau)‐PET. Images were parcellated using the modified Harvard‐Oxford atlas and we focused on 67 AD‐specific regions. Rather than using the average SUVR across voxels within a region to quantify uptake, we used the 95 th percentile of SUVR values across voxels within a region to capture focal cases. We then used receiver operating characteristic (ROC) methods and a Youden threshold to define regional abnormality. The number of abnormal regions was calculated for each participant and used to discriminate between CU and atypical AD at the individual level. Result Across 64 regions, our approach showed excellent (AUROC>0.90) differentiation between atypical AD and CU. The temporal‐fusiform, parahippocampal gyrus and inferior temporal gyrus showed the best differentiation (Figure 1). All 67 regions showed excellent specificity (>85%), with 63 regions showing excellent sensitivity (≥80%). The lateral occipital cortex, temporal‐fusiform and parahippocampal gyrus showed the best specificity and sensitivity (Figure 2). The distribution of the number of tau‐elevated regions is shown in Figure 3. 74% of CU had no positive regions, while 43% of the atypical AD patients had all 67 regions affected. An optimal threshold of 7 tau‐elevated regions classified all CU below, and 123 (97%) atypical AD above threshold. Using a standard approach based on the average SUVR in the MTL meta‐ROI, only 116 (91%) atypical AD patients were tau‐PET positive. Conclusion Tau uptake in temporal regions showed the greatest group‐level differentiation. However, examining regional tau‐positivity may offer better sensitivity in atypical AD patients compared to the temporal meta‐ROI, likely due to the presence of focal non‐temporal patterns of uptake.

Abstract Background Quantitative susceptibility mapping (QSM) can detect iron deposition or myelin loss in the brain by estimating magnetic susceptibility properties. Iron is an important component in neurofibrillary tangles and is known to co‐localize in regions with tangle burden in Alzheimer's disease (AD). Abnormal magnetic susceptibility measured on QSM has been observed in atypical AD, although it is unclear if susceptibility is regionally related to AV‐1451‐PET uptake in atypical AD. Method Forty atypical AD patients (visual variant=24, language variant=7, others=9) were recruited by the Neurodegenerative Research group from the Department of Neurology, Mayo Clinic, Rochester, MN. They underwent a 3T MRI scan with a five‐echo gradient echo sequence for calculation of QSM ( n = 80), Aβ (Pittsburgh Compound‐B) and a 18 F‐ AV‐1451 PET scan ( n = 73). All patients showed evidence of Aβ positivity on PET. To assess the relationship between QSM and AV‐1451‐PET, two approaches were used i) Voxel‐based regression analysis using VoxelStats for the whole brain, and ii) region‐of‐interest (ROI)‐based Spearman's correlation analyses using cortical and subcortical ROIs. All models were adjusted for age and sex as covariates and were corrected for multiple comparisons, specifically the VoxelStats regression maps were corrected using random field theory and the ROI‐based correlation plots were corrected using false discovery rate. Result At the voxel‐level, positive correlations between AV‐1451‐PET and QSM were only observed in the left caudate (Figure 1). At the ROI‐level, no significant associations were found, although uncorrected data showed a positive association in the occipital lobe (red circle) and a negative association between substantia nigra susceptibility and occipital AV‐1451 uptake (blue circle) (Figure 2). Since these findings did not survive corrections, they should be interpreted cautiously. Conclusion Our data provides little evidence that regional AV‐1451 PET uptake is related to susceptibility changes in patients with atypical AD, suggesting that iron deposition may not be associated with regional tau accumulation in AD.

Background: Posterior cortical atrophy (PCA) patients typically show progressive visual decline, although language impairment can be a prominent feature. Previous studies have explored language connectivity impairment in PCA; not much is known about the exact nature of language processing disruptions in PCA. Methods: Thirty-seven PCA patients were compared with 39 cognitively unimpaired (CU) individuals. Functional connectivity was evaluated for the language processing system, which consisted of language, perceptual, motor, and cognitive networks. Linear regression was performed to compare within- and between-network connectivity across networks and within the language network in PCA compared to CU individuals. Relationships between language network connectivity, clinical performance, and gray matter volumes were also evaluated. Results: PCA showed reduced connectivity within the language and perceptual networks, along with reduced between-network connectivity compared to CU individuals. Regional connectivity breakdown within the language network was also noted. Language processing system connectivity was not associated with clinical performance on language processing tests. However, a breakdown in Broca-Wernicke, Wernicke-middle frontal gyrus, and Wernicke-frontal orbital gyrus connectivity was related to worse performance on sentence repetition. Lastly, gray matter volume was not associated with language network connectivity. Discussion: Together, these results reiterate the breakdown of language network connectivity in PCA and highlight the disruption in connectivity at the regional level within the language network. Reduced connectivity within the perceptual network and associations between reduced language network connectivity and worse performance on sentence repetition imply a breakdown within the language processing systems in PCA.

Abstract Background Quantitative susceptibility mapping ( QSM ) is a promising neuroimaging biomarker for detecting abnormal iron deposition in progressive supranuclear palsy ( PSP ); however, the QSM profile and its accuracy in autopsy‐confirmed PSP remain unexplored. Objective The aim of the study was to elucidate and validate the QSM profiles in autopsy‐confirmed PSP. Methods Eight patients with a clinically diagnosed PSP syndrome ( PSPS ) underwent antemortem 3 T magnetic resonance imaging ( MRI) scanning and subsequent pathological diagnosis, confirming 6 PSP pathology and 2 multiple system atrophy ( MSA ) pathology cases. QSM analysis and Prussian blue staining were performed across subcortical regions. Results PSP cases showed higher susceptibility than age‐matched controls in the pallidum, subthalamic nucleus, substantia nigra, and cerebellar dentate (false discovery rate [ FDR] ‐corrected P < 0.05). PSP had higher susceptibility in the subthalamic nucleus and lower susceptibility in the putamen than the clinically atypical MSA ( P = 0.08). Subcortical susceptibilities correlated with Prussian blue–stained areas ( r = 0.63, P < 0.001). Conclusions QSM could be a reliable measure to evaluate abnormal iron accumulation patterns in PSP.

Background: Progressive apraxia of speech (PAOS) is a neurodegenerative disorder most commonly arising from a 4-repeat tauopathy that affects the programming or planning of speech, although many patients develop a Parkinson-plus syndrome. The role of neuroinflammation as a disease mechanism is unknown. We investigated the spatial pattern of neuroinflammation in PAOS using PET and evaluated whether it is associated with disease severity, presence of Parkinson-plus features, and tau PET uptake. Patients and Methods: Twenty-five PAOS patients (13 with Parkinson-plus features) and 30 controls underwent inflammatory 11C-ER176 and tau 18F-flortaucipir PET scans as well as detailed clinical assessments. Multiple linear regression analyses compared the inflammatory standardized uptake value ratio (SUVR) between PAOS and controls and assessed the relationship with clinical test scores. Pearson correlation analysis examined the relationship between inflammatory and tau SUVRs. Results: PAOS had greater neuroinflammatory SUVR than controls in the precentral, supplementary motor area, frontal gyri, putamen, pallidum, subthalamic nucleus, and red nucleus (adjusted P < 0.05). Greater neuroinflammation was associated with worse parkinsonism, and patients who had developed Parkinson-plus features showed a broader pattern of neuroinflammation, extending to prefrontal, temporal and parietal cortices. Neuroinflammation correlated with tau uptake in most (96%) PAOS patients (r > 0.3, P < 0.05). The higher correlation was associated with worse parkinsonism (r = 0.61, P < 0.05) and disease severity (r = 0.54, P < 0.05). Conclusions: 11C-ER176 PET analysis demonstrates neuroinflammation in frontal and subcortical regions in PAOS which is particularly severe and widespread with the development of Parkinson-plus clinical features. The colocalization of neuroinflammation and tau may support a relationship between these disease mechanisms.