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Adrian Danek

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YNICL Journal 2026 Journal Article

Additive value of early-phase β-Amyloid-PET for the differential diagnosis of non-Alzheimer’s disease dementia

  • Sebastian Eckenweber
  • Friederike Völter
  • Nicolai Franzmeier
  • Carla Palleis
  • Olivia Wagemann
  • Endy Weidinger
  • Sabrina Katzdobler
  • Elisabeth Wlasich

PURPOSE: F]FDG-PET, indicating the potential of early-phase β-amyloid-PET as a surrogate biomarker of neuronal injury. We therefore aimed to investigate the additive value of early-phase β-amyloid-PET for the differential diagnosis of non-Alzheimer's disease dementia syndromes in clinical routine. MATERIALS AND METHODS: F]flutemetamol-PET scans (n = 379) performed between July 2013 and July 2021 were analyzed for their amyloid status and the presence of a neurodegenerative hypoperfusion pattern using visual assessment and z-score maps. In patients visually rated as amyloid-negative/neurodegeneration-positive (A-N+), the most likely diagnosis based on perfusion patterns was compared to the final clinical diagnosis, i.e. frontotemporal dementia or psychiatric disorders, suspected 4R-tauopathy, and suspected non-Alzheimer pathophysiology. Logistic regression models based on a data-driven selection of cerebral regions of hypoperfusion by principal component analysis were used to predict neurodegenerative disease and clinical diagnoses. Diagnostic accuracy was compared between visual assessment and the regression models. RESULTS: Neurodegeneration status was correctly identified in 78.8% (119/151) of amyloid-negative patients through visual rating, compared to 67.5% (102/151) using logistic regression. Visual assessment assigned 75.3% (67/89) of A-N+ patients to the correct diagnostic category. In contrast, the regression model classified 69.7% (62/89) of patients. CONCLUSIONS: The current study demonstrates an additive value of early-phase β-amyloid-PET for the differential diagnosis of dementia syndromes. While visual assessment of early-phase β-amyloid-PET already provides substantial diagnostic accuracy, a data-driven analysis approach could aid in cases of uncertainty.

YNICL Journal 2023 Journal Article

Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging

  • Leonie Lampe
  • Hans-Jürgen Huppertz
  • Sarah Anderl-Straub
  • Franziska Albrecht
  • Tommaso Ballarini
  • Sandrine Bisenius
  • Karsten Mueller
  • Sebastian Niehaus

INTRODUCTION: Dementia syndromes can be difficult to diagnose. We aimed at building a classifier for multiple dementia syndromes using magnetic resonance imaging (MRI). METHODS: Atlas-based volumetry was performed on T1-weighted MRI data of 426 patients and 51 controls from the multi-centric German Research Consortium of Frontotemporal Lobar Degeneration including patients with behavioral variant frontotemporal dementia, Alzheimer's disease, the three subtypes of primary progressive aphasia, i.e., semantic, logopenic and nonfluent-agrammatic variant, and the atypical parkinsonian syndromes progressive supranuclear palsy and corticobasal syndrome. Support vector machine classification was used to classify each patient group against controls (binary classification) and all seven diagnostic groups against each other in a multi-syndrome classifier (multiclass classification). RESULTS: The binary classification models reached high prediction accuracies between 71 and 95% with a chance level of 50%. Feature importance reflected disease-specific atrophy patterns. The multi-syndrome model reached accuracies of more than three times higher than chance level but was far from 100%. Multi-syndrome model performance was not homogenous across dementia syndromes, with better performance in syndromes characterized by regionally specific atrophy patterns. Whereas diseases generally could be classified vs controls more correctly with increasing severity and duration, differentiation between diseases was optimal in disease-specific windows of severity and duration. DISCUSSION: Results suggest that automated methods applied to MR imaging data can support physicians in diagnosis of dementia syndromes. It is particularly relevant for orphan diseases beside frequent syndromes such as Alzheimer's disease.

YNICL Journal 2023 Journal Article

Symptomatology in 4-repeat tauopathies is associated with data-driven topology of [18F]-PI-2620 tau-PET signal

  • Sonja Schönecker
  • Carla Palleis
  • Nicolai Franzmeier
  • Sabrina Katzdobler
  • Christian Ferschmann
  • Sebastian Schuster
  • Anika Finze
  • Maximilian Scheifele

In recent years in vivo visualization of tau deposits has become possible with various PET radiotracers. The tau tracer [18F]PI-2620 proved high affinity both to 3-repeat/4-repeat tau in Alzheimer’s disease as well as to 4-repeat tau in progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). However, to be clinically relevant, biomarkers should not only correlate with pathological changes but also with disease stage and progression. Therefore, we aimed to investigate the correlation between topology of [18F]PI-2620 uptake and symptomatology in 4-repeat tauopathies. 72 patients with possible or probable 4-repeat tauopathy, i. e. 31 patients with PSP-Richardson’s syndrome (PSP-RS), 30 with amyloid-negative CBS and 11 with PSP-non-RS/CBS, underwent [18F]PI-2620-PET. Principal component analysis was performed to identify groups of similar brain regions based on 20–40 min p. i. regional standardized uptake value ratio z-scores. Correlations between component scores and the items of the PSP Rating Scale were explored. Motor signs like gait, arising from chair and postural instability showed a positive correlation with tracer uptake in mesial frontoparietal lobes and the medial superior frontal gyrus and adjacent anterior cingulate cortex. While the signs disorientation and bradyphrenia showed a positive correlation with tracer uptake in the parietooccipital junction, the signs disorientation and arising from chair were negatively correlated with tau-PET signal in the caudate nucleus and thalamus. Total PSP Rating Scale Score showed a trend towards a positive correlation with mesial frontoparietal lobes and a negative correlation with caudate nucleus and thalamus. While in CBS patients, the main finding was a negative correlation of tracer binding in the caudate nucleus and thalamus and a positive correlation of tracer binding in medial frontal cortex with gait and motor signs, in PSP-RS patients various correlations of clinical signs with tracer binding in specific cerebral regions could be detected. Our data reveal [18F]PI-2620 tau-PET topology to correlate with symptomatology in 4-repeat tauopathies. Longitudinal studies will be needed to address whether a deterioration of signs and symptoms over time can be monitored by [18F]PI-2620 in 4-repeat tauopathies and whether [18F]PI-2620 may serve as a marker of disease progression in future therapeutic trials. The detected negative correlation of tracer binding in the caudate nucleus and thalamus with the signs disorientation and arising from chair may be due to an increasing atrophy in these regions leading to partial volume effects and a relative decrease of tracer uptake in the disease course. As cerebral regions correlating with symptomatology differ depending on the clinical phenotype, a precise knowledge of clinical signs and symptoms is necessary when interpreting [18F]PI-2620 PET results.

YNICL Journal 2021 Journal Article

Cognitive reserve hypothesis in frontotemporal dementia: A FDG-PET study

  • Leonie Beyer
  • Johanna Meyer-Wilmes
  • Sonja Schönecker
  • Jonas Schnabel
  • Julia Sauerbeck
  • Maximilian Scheifele
  • Catharina Prix
  • Marcus Unterrainer

BACKGROUND AND OBJECTIVE: F]-fluorodeoxyglucose positron-emission-tomography (FDG-PET) hypometabolism in FTD. METHODS: Sixty-six FTD subjects (age 67 ± 8 years) and twenty-four cognitively healthy controls (HC) were evaluated. Brain regions with FTD-related glucose hypometabolism in the contrast against HC and brain regions that correlate with the cognitive function were defined by a voxel-based analysis and individual FDG-PET values were extracted from all frontotemporal brain areas. Linear regression analysis served to test if education is associated with residualized cognitive performance and regional FDG-PET hypometabolism after controlling for global cognition. RESULTS: Compared to healthy controls, patients with FTD showed glucose hypometabolism in bilateral frontal and temporal brain areas whereas cognition was only associated with deteriorated glucose metabolism in the left temporal lobe. The education level was significantly correlated with the residualized cognitive performance (residuals from regression analysis between hypometabolism and cognitive function as a quantitative index of reserve) and also negatively correlated with left temporal FDG-PET hypometabolism after controlling for cognition. CONCLUSIONS: In patients with FTD, the education level predicts the existing left temporal FDG-PET hypometabolism at the same cognition level, supporting the cognitive reserve hypothesis in FTD.

YNICL Journal 2021 Journal Article

Differential early subcortical involvement in genetic FTD within the GENFI cohort

  • Martina Bocchetta
  • Emily G. Todd
  • Georgia Peakman
  • David M. Cash
  • Rhian S. Convery
  • Lucy L. Russell
  • David L. Thomas
  • Juan Eugenio Iglesias

BACKGROUND: Studies have previously shown evidence for presymptomatic cortical atrophy in genetic FTD. Whilst initial investigations have also identified early deep grey matter volume loss, little is known about the extent of subcortical involvement, particularly within subregions, and how this differs between genetic groups. METHODS: 480 mutation carriers from the Genetic FTD Initiative (GENFI) were included (198 GRN, 202 C9orf72, 80 MAPT), together with 298 non-carrier cognitively normal controls. Cortical and subcortical volumes of interest were generated using automated parcellation methods on volumetric 3 T T1-weighted MRI scans. Mutation carriers were divided into three disease stages based on their global CDR® plus NACC FTLD score: asymptomatic (0), possibly or mildly symptomatic (0.5) and fully symptomatic (1 or more). RESULTS: In all three groups, subcortical involvement was seen at the CDR 0.5 stage prior to phenoconversion, whereas in the C9orf72 and MAPT mutation carriers there was also involvement at the CDR 0 stage. In the C9orf72 expansion carriers the earliest volume changes were in thalamic subnuclei (particularly pulvinar and lateral geniculate, 9-10%) cerebellum (lobules VIIa-Crus II and VIIIb, 2-3%), hippocampus (particularly presubiculum and CA1, 2-3%), amygdala (all subregions, 2-6%) and hypothalamus (superior tuberal region, 1%). In MAPT mutation carriers changes were seen at CDR 0 in the hippocampus (subiculum, presubiculum and tail, 3-4%) and amygdala (accessory basal and superficial nuclei, 2-4%). GRN mutation carriers showed subcortical differences at CDR 0.5 in the presubiculum of the hippocampus (8%). CONCLUSIONS: C9orf72 expansion carriers show the earliest and most widespread changes including the thalamus, basal ganglia and medial temporal lobe. By investigating individual subregions, changes can also be seen at CDR 0 in MAPT mutation carriers within the limbic system. Our results suggest that subcortical brain volumes may be used as markers of neurodegeneration even prior to the onset of prodromal symptoms.

YNICL Journal 2021 Journal Article

Disease-related cortical thinning in presymptomatic granulin mutation carriers

  • Sergi Borrego-Écija
  • Roser Sala-Llonch
  • John van Swieten
  • Barbara Borroni
  • Fermín Moreno
  • Mario Masellis
  • Carmela Tartaglia
  • Caroline Graff

Mutations in the granulin gene (GRN) cause familial frontotemporal dementia. Understanding the structural brain changes in presymptomatic GRN carriers would enforce the use of neuroimaging biomarkers for early diagnosis and monitoring. We studied 100 presymptomatic GRN mutation carriers and 94 noncarriers from the Genetic Frontotemporal dementia initiative (GENFI), with MRI structural images. We analyzed 3T MRI structural images using the FreeSurfer pipeline to calculate the whole brain cortical thickness (CTh) for each subject. We also perform a vertex-wise general linear model to assess differences between groups in the relationship between CTh and diverse covariables as gender, age, the estimated years to onset and education. We also explored differences according to TMEM106B genotype, a possible disease modifier. Whole brain CTh did not differ between carriers and noncarriers. Both groups showed age-related cortical thinning. The group-by-age interaction analysis showed that this age-related cortical thinning was significantly greater in GRN carriers in the left superior frontal cortex. TMEM106B did not significantly influence the age-related cortical thinning. Our results validate and expand previous findings suggesting an increased CTh loss associated with age and estimated proximity to symptoms onset in GRN carriers, even before the disease onset.

YNICL Journal 2019 Journal Article

Neuronal injury biomarkers for assessment of the individual cognitive reserve in clinically suspected Alzheimer's disease

  • Leonie Beyer
  • Jonas Schnabel
  • Philipp Kazmierczak
  • Michael Ewers
  • Sonja Schönecker
  • Catharina Prix
  • Johanna Meyer-Wilmes
  • Marcus Unterrainer

OBJECTIVES: ), all according to the A/T/N-classification. The aim of this study was to calculate residual cognitive performance based on neuronal injury biomarkers as a surrogate of cognitive reserve, and to test the predictive value of this index for the individual clinical course. METHODS: . All neuronal injury markers were tested for an association with clinical MMSE and the resulting residuals were correlated with years of education. We used multiple regression analysis to calculate the expected MMSE score based on neuronal injury biomarkers and covariates. The residuals of the partial correlation for each biomarker and the predicted residualized memory function were correlated with individual cognitive changes measured during clinical follow-up (27 ± 13 months). RESULTS: (R = -0.12, p = .22) showed only weak correlations. Residuals of all neuronal injury biomarker regressions correlated significantly with education level, indicating them to be surrogates of cognitive reserve. A positive residual was associated with faster cognitive deterioration at follow-up for the residuals of stand-alone FDG-PET (R = -0.36, p = .01) and the combined residualized memory function model (R = -0.35, p = .02). CONCLUSIONS: These findings suggest that subjects with higher cognitive reserve had accumulated more pathology, which subsequently caused a faster cognitive decline over time. Together with previous findings suggesting that higher reserve is associated with slower cognitive decline, we propose a biphasic reserve effect, with an initially protective phase followed by more rapid decompensation once the protection is overwhelmed.

YNIMG Journal 2019 Journal Article

The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint

  • Enrico Premi
  • Vince D. Calhoun
  • Matteo Diano
  • Stefano Gazzina
  • Maura Cosseddu
  • Antonella Alberici
  • Silvana Archetti
  • Donata Paternicò

Frontotemporal Dementia (FTD) is preceded by a long period of subtle brain changes, occurring in the absence of overt cognitive symptoms, that need to be still fully characterized. Dynamic network analysis based on resting-state magnetic resonance imaging (rs-fMRI) is a potentially powerful tool for the study of preclinical FTD. In the present study, we employed a "chronnectome" approach (recurring, time-varying patterns of connectivity) to evaluate measures of dynamic connectivity in 472 at-risk FTD subjects from the Genetic Frontotemporal dementia research Initiative (GENFI) cohort. We considered 249 subjects with FTD-related pathogenetic mutations and 223 mutation non-carriers (HC). Dynamic connectivity was evaluated using independent component analysis and sliding-time window correlation to rs-fMRI data, and meta-state measures of global brain flexibility were extracted. Results show that presymptomatic FTD exhibits diminished dynamic fluidity, visiting less meta-states, shifting less often across them, and travelling through a narrowed meta-state distance, as compared to HC. Dynamic connectivity changes characterize preclinical FTD, arguing for the desynchronization of the inner fluctuations of the brain. These changes antedate clinical symptoms, and might represent an early signature of FTD to be used as a biomarker in clinical trials.

YNICL Journal 2019 Journal Article

White matter hyperintensities in progranulin-associated frontotemporal dementia: A longitudinal GENFI study

  • Carole H. Sudre
  • Martina Bocchetta
  • Carolin Heller
  • Rhian Convery
  • Mollie Neason
  • Katrina M. Moore
  • David M. Cash
  • Ione O.C. Woollacott

Frontotemporal dementia (FTD) is a heterogeneous group of neurodegenerative disorders with both sporadic and genetic forms. Mutations in the progranulin gene (GRN) are a common cause of genetic FTD, causing either a behavioural presentation or, less commonly, language impairment. Presence on T2-weighted images of white matter hyperintensities (WMH) has been previously shown to be more commonly associated with GRN mutations rather than other forms of FTD. The aim of the current study was to investigate the longitudinal change in WMH and the associations of WMH burden with grey matter (GM) loss, markers of neurodegeneration and cognitive function in GRN mutation carriers. 336 participants in the Genetic FTD Initiative (GENFI) study were included in the analysis: 101 presymptomatic and 32 symptomatic GRN mutation carriers, as well as 203 mutation-negative controls. 39 presymptomatic and 12 symptomatic carriers, and 73 controls also had longitudinal data available. Participants underwent MR imaging acquisition including isotropic 1 mm T1-weighted and T2-weighted sequences. WMH were automatically segmented and locally subdivided to enable a more detailed representation of the pathology distribution. Log-transformed WMH volumes were investigated in terms of their global and regional associations with imaging measures (grey matter volumes), biomarker concentrations (plasma neurofilament light chain, NfL, and glial fibrillary acidic protein, GFAP), genetic status (TMEM106B risk genotype) and cognition (tests of executive function). Analyses revealed that WMH load was higher in both symptomatic and presymptomatic groups compared with controls and this load increased over time. In particular, lesions were seen periventricularly in frontal and occipital lobes, progressing to medial layers over time. However, there was variability in the WMH load across GRN mutation carriers - in the symptomatic group 25.0% had none/mild load, 37.5% had medium and 37.5% had a severe load - a difference not fully explained by disease duration. GM atrophy was strongly associated with WMH load both globally and in separate lobes, and increased WMH burden in the frontal, periventricular and medial regions was associated with worse executive function. Furthermore, plasma NfL and to a lesser extent GFAP concentrations were seen to be associated with increased lesion burden. Lastly, the presence of the homozygous TMEM106B rs1990622 TT risk genotypic status was associated with an increased accrual of WMH per year. In summary, WMH occur in GRN mutation carriers and accumulate over time, but are variable in their severity. They are associated with increased GM atrophy and executive dysfunction. Furthermore, their presence is associated with markers of WM damage (NfL) and astrocytosis (GFAP), whilst their accrual is modified by TMEM106B genetic status. WMH load may represent a target marker for trials of disease modifying therapies in individual patients but the variability across the GRN population would prevent use of such markers as a global outcome measure across all participants in a trial.

YNICL Journal 2017 Journal Article

Evaluation of early-phase [18F]-florbetaben PET acquisition in clinical routine cases

  • Sonja Daerr
  • Matthias Brendel
  • Christian Zach
  • Erik Mille
  • Dorothee Schilling
  • Mathias Johannes Zacherl
  • Katharina Bürger
  • Adrian Danek

OBJECTIVES: F]-fluorodeoxyglucose (FDG) PET in a clinical setting. METHODS: All subjects were recruited with clinical suspicion of dementia due to neurodegenerative disease. FDG PET was undertaken by conventional methods, and amyloid PET was performed with FBB, with early recordings for the initial 10 min (early-phase FBB), and late recordings at 90-110 min p.i. (late-phase FBB). Regional SUVR with cerebellar and global mean normalization were calculated for early-phase FBB and FDG PET. Pearson correlation coefficients between FDG and early-phase FBB were calculated for predefined cortical brain regions. Furthermore, a visual interpretation of disease pattern using 3-dimensional stereotactic surface projections (3D-SSP) was performed, with assessment of intra-reader agreement. RESULTS: Among a total of 33 patients (mean age 67.5 ± 11.0 years) included in the study, 18 were visually rated amyloid-positive, and 15 amyloid-negative based on late-phase FBB scans. Correlation coefficients for early-phase FBB vs. FDG scans displayed excellent agreement in all target brain regions for global mean normalization. Cerebellar normalization gave strong, but significantly lower correlations. 3D representations of early-phase FBB visually resembled the corresponding FDG PET images, irrespective of the amyloid-status of the late FBB scans. CONCLUSIONS: Early-phase FBB acquisitions correlate on a relative quantitative and visual level with FDG PET scans, irrespective of the amyloid plaque density assessed in late FBB imaging. Thus, early-phase FBB uptake depicts a metabolism-like image, suggesting it as a valid surrogate marker for synaptic dysfunction, which could ultimately circumvent the need for additional FDG PET investigation in diagnosis of dementia.

YNICL Journal 2017 Journal Article

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data

  • Sandrine Bisenius
  • Karsten Mueller
  • Janine Diehl-Schmid
  • Klaus Fassbender
  • Timo Grimmer
  • Frank Jessen
  • Jan Kassubek
  • Johannes Kornhuber

Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with a very high accuracy paving the road for its application in clinical settings.

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