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Background: Several magnetic resonance imaging (MRI) measures have been suggested as progression biomarkers in progressive supranuclear palsy (PSP), and some PSP staging systems have been recently proposed. Objective: Comparing structural MRI measures and staging systems in tracking atrophy progression in PSP and estimating the sample size to use them as endpoints in clinical trials. Methods: Progressive supranuclear palsy‐Richardson's syndrome (PSP‐RS) patients with one‐year‐follow‐up longitudinal brain MRI were selected from the placebo arms of international trials (NCT03068468, NCT01110720, NCT01049399) and the DescribePSP cohort. The discovery cohort included patients from the NCT03068468 trial; the validation cohort included patients from other sources. Multisite age‐matched healthy controls (HC) were included for comparison. Several MRI measures were compared: automated atlas‐based volumetry (44 regions), automated planimetric measures of brainstem regions, and four previously described staging systems, applied to volumetric data. Results: Of 508 participants, 226 PSP patients including discovery (n = 121) and validation (n = 105) cohorts, and 251 HC were included. In PSP patients, the annualized percentage change of brainstem and midbrain volume, and a combined index including midbrain, frontal lobe, and third ventricle volume change, were the progression biomarkers with the highest effect size in both cohorts (discovery: >1.6; validation cohort: >1.3). These measures required the lowest sample sizes (n < 100) to detect 30% atrophy progression, compared with other volumetric/planimetric measures and staging systems. Conclusions: This evidence may inform the selection of imaging endpoints to assess the treatment efficacy in reducing brain atrophy rate in PSP clinical trials, with automated atlas‐based volumetry requiring smaller sample size than staging systems and planimetry to observe significant treatment effects. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

BackgroundTwo recent, randomized, placebo-controlled phase II/III trials (clinicaltrials.gov: NCT01110720, NCT01049399) of davunetide and tideglusib in progressive supranuclear palsy (PSP) generated prospective, 1-year longitudinal datasets of high-resolution T1-weighted three-dimensional MRI.ObjectiveThe objective of this study was to develop a quantitative MRI disease progression measurement for clinical trials.MethodsThe authors performed a fully automated quantitative MRI analysis employing atlas-based volumetry and provide sample size calculations based on data collected in 99 PSP patients assigned to placebo in these trials. Based on individual volumes of 44 brain compartments and structures at baseline and 52 weeks of follow-up, means and standard deviations of annualized percentage volume changes were used to estimate standardized effect sizes and the required sample sizes per group for future 2-armed, placebo-controlled therapeutic trials.ResultsThe highest standardized effect sizes were found for midbrain, frontal lobes, and the third ventricle. Using the annualized percentage volume change of these structures to detect a 50% change in the 1-year progression (80% power, significance level 5%) required lower numbers of patients per group (third ventricle, n = 32; midbrain, n = 37; frontal lobe, n = 43) than the best clinical scale (PSP rating scale total score, n = 58). A combination of volume changes in these 3 structures reduced the number of required patients to only 20 and correlated best with the progression in the clinical scales.ConclusionsWe propose the 1-year change in the volumes of third ventricle, midbrain, and frontal lobe as combined imaging read-out for clinical trials in PSP that require the least number of patients for detecting efficacy to reduce brain atrophy. © 2017 International Parkinson and Movement Disorder Society.

Objective: We aim to improve focal cortical dysplasia (FCD) detection by combining high‐resolution, three‐dimensional (3D) magnetic resonance fingerprinting (MRF) with voxel‐based morphometric magnetic resonance imaging (MRI) analysis. Methods: We included 37 patients with pharmacoresistant focal epilepsy and FCD (10 IIa, 15 IIb, 10 mild Malformation of Cortical Development [mMCD], and 2 mMCD with oligodendroglial hyperplasia and epilepsy [MOGHE]). Fifty‐nine healthy controls (HCs) were also included. 3D lesion labels were manually created. Whole‐brain MRF scans were obtained with 1 mm3 isotropic resolution, from which quantitative T1 and T2 maps were reconstructed. Voxel‐based MRI postprocessing, implemented with the morphometric analysis program (MAP18), was performed for FCD detection using clinical T1w images, outputting clusters with voxel‐wise lesion probabilities. Average MRF T1 and T2 were calculated in each cluster from MAP18 output for gray matter (GM) and white matter (WM) separately. Normalized MRF T1 and T2 were calculated by z‐scores using HCs. Clusters that overlapped with the lesion labels were considered true positives (TPs); clusters with no overlap were considered false positives (FPs). Two‐sample t‐tests were performed to compare MRF measures between TP/FP clusters. A neural network model was trained using MRF values and cluster volume to distinguish TP/FP clusters. Ten‐fold cross‐validation was used to evaluate model performance at the cluster level. Leave‐one‐patient‐out cross‐validation was used to evaluate performance at the patient level. Results: MRF metrics were significantly higher in TP than FP clusters, including GM T1, normalized WM T1, and normalized WM T2. The neural network model with normalized MRF measures and cluster volume as input achieved mean area under the curve (AUC) of.83, sensitivity of 82.1%, and specificity of 71.7%. This model showed superior performance over direct thresholding of MAP18 FCD probability map at both the cluster and patient levels, eliminating ≥75% FP clusters in 30% of patients and ≥50% of FP clusters in 91% of patients. Significance: This pilot study suggests the efficacy of MRF for reducing FPs in FCD detection, due to its quantitative values reflecting in vivo pathological changes. © 2024 International League Against Epilepsy. [ABSTRACT FROM AUTHOR]

Background: Brain magnetic resonance imaging (MRI) is used to support the diagnosis of progressive supranuclear palsy (PSP). However, the value of visual descriptive, manual planimetric, automatic volumetric MRI markers and fully automatic categorization is unclear, particularly regarding PSP predominance types other than Richardson's syndrome (RS). Objectives: To compare different visual reading strategies and automatic classification of T1‐weighted MRI for detection of PSP in a typical clinical cohort including PSP‐RS and (non‐RS) variant PSP (vPSP) patients. Methods: Forty‐one patients (21 RS, 20 vPSP) and 46 healthy controls were included. Three readers using three strategies performed MRI analysis: exclusively visual reading using descriptive signs (hummingbird, morning‐glory, Mickey‐Mouse), visual reading supported by manual planimetry measures, and visual reading supported by automatic volumetry. Fully automatic classification was performed using a pre‐trained support vector machine (SVM) on the results of atlas‐based volumetry. Results: All tested methods achieved higher specificity than sensitivity. Limited sensitivity was driven to large extent by false negative vPSP cases. Support by automatic volumetry resulted in the highest accuracy (75.1% ± 3.5%) among the visual strategies, but performed not better than the midbrain area (75.9%), the best single planimetric measure. Automatic classification by SVM clearly outperformed all other methods (accuracy, 87.4%), representing the only method to provide clinically useful sensitivity also in vPSP (70.0%). Conclusions: Fully automatic classification of volumetric MRI measures using machine learning methods outperforms visual MRI analysis without and with planimetry or volumetry support, particularly regarding diagnosis of vPSP, suggesting the use in settings with a broad phenotypic PSP spectrum. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Background: To date, studies on positron emission tomography (PET) with 18F‐fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP‐RS). Objectives: To evaluate FDG‐PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice. Methods: This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non‐RS variants of PSP (vPSP), and 46 age‐matched healthy controls. Two state‐of‐the art methods for the interpretation of FDG‐PET were compared: visual analysis supported by voxel‐based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP‐related pattern. Results: Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false‐negative cases was 10% in the PSP‐RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false‐negative cases was 0% in the PSP‐RS subsample and 15% in the vPSP subsample. Conclusions: Visual interpretation of FDG‐PET supported by voxel‐based testing provides good accuracy for the detection of PSP‐RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP‐RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false‐positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel‐based testing of FDG‐PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Background: Recent data support beta‐synuclein as a blood biomarker to study synaptic degeneration in Alzheimer's disease (AD). Methods: We provide a detailed comparison of serum beta‐synuclein immunoprecipitation – mass spectrometry (IP‐MS) with the established blood markers phosphorylated tau 181 (p‐tau181) (Simoa) and neurofilament light (NfL) (Ella) in the German FTLD consortium cohort (n = 374) and its relation to brain atrophy (magnetic resonance imaging) and cognitive scores. Results: Serum beta‐synuclein was increased in AD but not in frontotemporal lobar degeneration (FTLD) syndromes. Beta‐synuclein correlated with atrophy in temporal brain structures and was associated with cognitive impairment. Serum p‐tau181 showed the most specific changes in AD but the lowest correlation with structural alterations. NfL was elevated in all diseases and correlated with frontal and temporal brain atrophy. Discussion: Serum beta‐synuclein changes differ from those of NfL and p‐tau181 and are strongly related to AD, most likely reflecting temporal synaptic degeneration. Beta‐synuclein can complement the existing panel of blood markers, thereby providing information on synaptic alterations. Highlights: Blood beta‐synuclein is increased in Alzheimer's disease (AD) but not in frontotemporal lobar degeneration (FTLD) syndromes.Blood beta‐synuclein correlates with temporal brain atrophy in AD.Blood beta‐synuclein correlates with cognitive impairment in AD.The pattern of blood beta‐synuclein changes in the investigated diseases is different to phosphorylated tau 181 (p‐tau181) and neurofilament light (NfL). [ABSTRACT FROM AUTHOR]