Added value of FDG-PET for detection of progressive supranuclear palsy.

BACKGROUND: Diagnostic criteria for progressive supranuclear palsy (PSP) include midbrain atrophy in MRI and hypometabolism in [18F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) as supportive features. Due to limited data regarding their relative and sequential value, there is no recommendation for an algorithm to combine both modalities to increase diagnostic accuracy. This study evaluated the added value of sequential imaging using state-of-the-art methods to analyse the images regarding PSP features. METHODS: The retrospective study included 41 PSP patients, 21 with Richardson's syndrome (PSP-RS), 20 with variant PSP phenotypes (vPSP) and 46 sex- and age-matched healthy controls. A pretrained support vector machine (SVM) for the classification of atrophy profiles from automatic MRI volumetry was used to analyse T1w-MRI (output: MRI-SVM-PSP score). Covariance pattern analysis was applied to compute the expression of a predefined PSP-related pattern in FDG-PET (output: PET-PSPRP expression score). RESULTS: The area under the receiver operating characteristic curve for the detection of PSP did not differ between MRI-SVM-PSP and PET-PSPRP expression score (p≥0.63): about 0.90, 0.95 and 0.85 for detection of all PSP, PSP-RS and vPSP. The MRI-SVM-PSP score achieved about 13% higher specificity and about 15% lower sensitivity than the PET-PSPRP expression score. Decision tree models selected the MRI-SVM-PSP score for the first branching and the PET-PSPRP expression score for a second split of the subgroup with normal MRI-SVM-PSP score, both in the whole sample and when restricted to PSP-RS or vPSP. CONCLUSIONS: FDG-PET provides added value for PSP-suspected patients with normal/inconclusive T1w-MRI, regardless of PSP phenotype and the methods to analyse the images for PSP-typical features.

Magnetic Resonance Imaging Measures to Track Atrophy Progression in Progressive Supranuclear Palsy in Clinical Trials.

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.

Combining magnetic resonance fingerprinting with voxel-based morphometric analysis to reduce false positives for focal cortical dysplasia detection.

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.

Neurofilaments and progranulin are related to atrophy in frontotemporal lobar degeneration - A transdiagnostic study cross-validating atrophy and fluid biomarkers.

INTRODUCTION: Frontotemporal lobar degeneration (FTLD) encompasses behavioral variant frontotemporal dementia (bvFTD), progressive supranuclear palsy, corticobasal syndrome/degeneration, and primary progressive aphasias (PPAs). We cross-validated fluid biomarkers and neuroimaging. METHODS: Seven fluid biomarkers from cerebrospinal fluid and serum were related to atrophy in 428 participants including these FTLD subtypes, logopenic variant PPA (lvPPA), Alzheimer's disease (AD), and healthy subjects. Atrophy was assessed by structural magnetic resonance imaging and atlas-based volumetry. RESULTS: FTLD subtypes, lvPPA, and AD showed specific profiles for neurofilament light chain, phosphorylated heavy chain, tau, phospho-tau, amyloid beta1-42 from serum/cerebrospinal fluid, and brain atrophy. Neurofilaments related to regional atrophy in bvFTD, whereas progranulin was associated with atrophy in semantic variant PPA. Ubiquitin showed no effects. DISCUSSION: Results specify biomarker and atrophy patterns in FTLD and AD supporting differential diagnosis. They identify neurofilaments and progranulin in interaction with structural imaging as promising candidates for monitoring disease progression and therapy. HIGHLIGHTS: Study cross-validated neuroimaging and fluid biomarkers in dementia. Five kinds of frontotemporal lobar degeneration and two variants of Alzheimer's disease. Study identifies disease-specific fluid biomarker and atrophy profiles. Fluid biomarkers and atrophy interact in a disease-specific way. Neurofilaments and progranulin are proposed as biomarkers for diagnosis and therapy.

A novel geometry-based analysis of hippocampal morphometry in mesial temporal lobe epilepsy.

Hippocampal volumetry is an essential tool in researching and diagnosing mesial temporal lobe epilepsy (mTLE). However, it has a limited ability to detect subtle alterations in hippocampal morphometry. Here, we establish and apply a novel geometry-based tool that enables point-wise morphometric analysis based on an intrinsic coordinate system of the hippocampus. We hypothesized that this point-wise analysis uncovers structural alterations not measurable by volumetry, but associated with histological underpinnings and the neuropsychological profile of mTLE. We conducted a retrospective study in 204 individuals with mTLE and 57 age- and gender-matched healthy subjects. FreeSurfer-based segmentations of hippocampal subfields in 3T-MRI were subjected to a geometry-based analysis that resulted in a coordinate system of the hippocampal mid-surface and allowed for point-wise measurements of hippocampal thickness and other features. Using point-wise analysis, we found significantly lower thickness and higher FLAIR signal intensity in the entire affected hippocampus of individuals with hippocampal sclerosis (HS-mTLE). In the contralateral hippocampus of HS-mTLE and the affected hippocampus of MRI-negative mTLE, we observed significantly lower thickness in the presubiculum. Impaired verbal memory was associated with lower thickness in the left presubiculum. In HS-mTLE histological subtype 3, we observed higher curvature than in subtypes 1 and 2 (all p < .05). These findings could not be observed using conventional volumetry (Bonferroni-corrected p < .05). We show that point-wise measures of hippocampal morphometry can uncover structural alterations not measurable by volumetry while also reflecting histological underpinnings and verbal memory. This substantiates the prospect of their clinical application.

Automatic covariance pattern analysis outperforms visual reading of 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in variant progressive supranuclear palsy.

BACKGROUND: To date, studies on positron emission tomography (PET) with 18 F-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.

Brain MRI in Progressive Supranuclear Palsy with Richardson's Syndrome and Variant Phenotypes.

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.

Artificial intelligence for the detection of focal cortical dysplasia: Challenges in translating algorithms into clinical practice.

Focal cortical dysplasias (FCDs) are malformations of cortical development and one of the most common pathologies causing pharmacoresistant focal epilepsy. Resective neurosurgery yields high success rates, especially if the full extent of the lesion is correctly identified and completely removed. The visual assessment of magnetic resonance imaging does not pinpoint the FCD in 30%-50% of cases, and half of all patients with FCD are not amenable to epilepsy surgery, partly because the FCD could not be sufficiently localized. Computational approaches to FCD detection are an active area of research, benefitting from advancements in computer vision. Automatic FCD detection is a significant challenge and one of the first clinical grounds where the application of artificial intelligence may translate into an advance for patients' health. The emergence of new methods from the combination of health and computer sciences creates novel challenges. Imaging data need to be organized into structured, well-annotated datasets and combined with other clinical information, such as histopathological subtypes or neuroimaging characteristics. Algorithmic output, that is, model prediction, requires a technically correct evaluation with adequate metrics that are understandable and usable for clinicians. Publication of code and data is necessary to make research accessible and reproducible. This critical review introduces the field of automatic FCD detection, explaining underlying medical and technical concepts, highlighting its challenges and current limitations, and providing a perspective for a novel research environment.

Relationship of serum beta-synuclein with blood biomarkers and brain atrophy.

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).

Relationship of Genotype, Phenotype, and Treatment in Dopa-Responsive Dystonia: MDSGene Review.

BACKGROUND: Pathogenic variants in 5 genes (GCH1, TH, PTS, SPR, and QDPR), involved in dopamine/tetrahydrobiopterin biosynthesis or recycling, have been linked to Dopa-responsive dystonia (DRD). Diagnosis and treatment are often delayed due to high between- and within-group variability. OBJECTIVES: Comprehensively analyzed individual genotype, phenotype, treatment response, and biochemistry information. METHODS: 734 DRD patients and 151 asymptomatic GCH1 mutation carriers were included using an MDSGene systematic literature review and an automated classification approach to distinguish between different forms of monogenic DRDs. RESULTS: Whereas dystonia, L-Dopa responsiveness, early age at onset, and diurnal fluctuations were identified as red flags, parkinsonism without dystonia was rarely reported (11%) and combined with dystonia in only 18% of patients. While sex was equally distributed in autosomal recessive DRD, there was female predominance in autosomal dominant DYT/PARK-GCH1 patients accompanied by a lower median age at onset and more dystonia in females compared to males. Accordingly, the majority of asymptomatic heterozygous GCH1 mutation carriers (>8 years of age) were males. Multiple other subgroup-specific characteristics were identified, showing high accuracy in the automated classification approach: Seizures and microcephaly were mostly seen in DYT/PARK-PTS, autonomic symptoms appeared commonly in DYT/PARK-TH and DYT/PARK-PTS, and sleep disorders and oculogyric crises in DYT/PARK-SPR. Biochemically, homovanillic acid and 5-hydroxyindoleacetic acid in CSF were reduced in most DRDs, but neopterin and biopterin were increased only in DYT/PARK-PTS and DYT/PARK-SPR. Hyperphenylalaninemia was seen in DYT/PARK-PTS, DYT/PARK-QDPR, and rarely reported in autosomal recessive DYT/PARK-GCH1. CONCLUSIONS: Our indicators will help to specify diagnosis and accelerate start of treatment. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Fully automated detection of focal cortical dysplasia: Comparison of MPRAGE and MP2RAGE sequences.

OBJECTIVE: The detection of focal cortical dysplasia (FCD) in magnetic resonance imaging is challenging. Voxel-based morphometric analysis and automated FCD detection using an artificial neural network (ANN) integrated into the Morphometric Analysis Program (MAP18) have been shown to facilitate FCD detection. This study aimed to evaluate whether the detection of FCD can be further improved by feeding this approach with magnetization prepared two rapid acquisition gradient echoes (MP2RAGE) instead of magnetization-prepared rapid acquisition gradient echo (MPRAGE) datasets. METHODS: MPRAGE and MP2RAGE datasets were acquired in a consecutive sample of 32 patients with FCD and postprocessed using MAP18. Visual analysis and, if available, histopathology served as the gold standard for assessing the sensitivity and specificity of FCD detection. Out-of-sample specificity was evaluated in a cohort of 32 healthy controls. RESULTS: The sensitivity and specificity of FCD detection were 82.4% and 62.5% for the MPRAGE and 97.1% and 34.4% for the MP2RAGE sequences, respectively. Median volumes of true-positive voxel clusters were .16 ml for the MPRAGE and .52 ml for the MP2RAGE sequences compared to .08- and .04-ml volumes of false-positive clusters. With regard to cluster volumes, FCD detection was substantially improved for the MP2RAGE data when the estimated optimal threshold of .23 ml was applied (sensitivity = 72.9%, specificity = 83.0%). In contrast, the estimated optimal threshold of .37 ml for the MPRAGE data did not improve FCD lesion detection (sensitivity = 42.9%, specificity = 79.5%). SIGNIFICANCE: In this study, the sensitivity of FCD detection by morphometric analysis and an ANN integrated into MAP18 was higher for MP2RAGE than for MPRAGE sequences. Additional usage of cluster volume information helped to discriminate between true- and false-positive MP2RAGE results.

Genotype-Phenotype Relations for the Atypical Parkinsonism Genes: MDSGene Systematic Review.

This Movement Disorder Society Genetic mutation database Systematic Review focuses on monogenic atypical parkinsonism with mutations in the ATP13A2, DCTN1, DNAJC6, FBXO7, SYNJ1, and VPS13C genes. We screened 673 citations and extracted genotypic and phenotypic data for 140 patients (73 families) from 77 publications. In an exploratory fashion, we applied an automated classification procedure via an ensemble of bootstrap-aggregated ("bagged") decision trees to distinguish these 6 forms of monogenic atypical parkinsonism and found a high accuracy of 86.5% (95%CI, 86.3%-86.7%) based on the following 10 clinical variables: age at onset, spasticity and pyramidal signs, hypoventilation, decreased body weight, minimyoclonus, vertical gaze palsy, autonomic symptoms, other nonmotor symptoms, levodopa response quantification, and cognitive decline. Comparing monogenic atypical with monogenic typical parkinsonism using 2063 data sets from Movement Disorder Society Genetic mutation database on patients with SNCA, LRRK2, VPS35, Parkin, PINK1, and DJ-1 mutations, the age at onset was earlier in monogenic atypical parkinsonism (24 vs 40 years; P = 1.2647 × 10-12) and levodopa response less favorable than in patients with monogenic typical presentations (49% vs 93%). In addition, we compared monogenic to nonmonogenic atypical parkinsonism using data from 362 patients with progressive supranuclear gaze palsy, corticobasal degeneration, multiple system atrophy, or frontotemporal lobar degeneration. Although these conditions share many clinical features with the monogenic atypical forms, they can typically be distinguished based on their later median age at onset (64 years; IQR, 57-70 years). In conclusion, age at onset, presence of specific signs, and degree of levodopa response inform differential diagnostic considerations and genetic testing indications in atypical forms of parkinsonism. © 2021 International Parkinson and Movement Disorder Society.

External validation of automated focal cortical dysplasia detection using morphometric analysis.

OBJECTIVE: Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magnetic resonance imaging (MRI) assessment. The visual detection can be facilitated by morphometric analysis of T1-weighted images, for example, using the Morphometric Analysis Program (v2018; MAP18), which was introduced in 2005, independently validated for its clinical benefits, and successfully integrated in standard presurgical workflows of numerous epilepsy centers worldwide. Here we aimed to develop an artificial neural network (ANN) classifier for robust automated detection of FCDs based on these morphometric maps and probe its generalization performance in a large, independent data set. METHODS: In this retrospective study, we created a feed-forward ANN for FCD detection based on the morphometric output maps of MAP18. The ANN was trained and cross-validated on 113 patients (62 female, mean age ± SD =29.5 ± 13.6 years) with manually segmented FCDs and 362 healthy controls (161 female, mean age ± SD =30.2 ± 9.6 years) acquired on 13 different scanners. In addition, we validated the performance of the trained ANN on an independent, unseen data set of 60 FCD patients (28 female, mean age ± SD =30 ± 15.26 years) and 70 healthy controls (42 females, mean age ± SD = 40.0 ± 12.54 years). RESULTS: In the cross-validation, the ANN achieved a sensitivity of 87.4% at a specificity of 85.4% on the training data set. On the independent validation data set, our method still reached a sensitivity of 81.0% at a comparably high specificity of 84.3%. SIGNIFICANCE: Our method shows a robust automated detection of FCDs and performance generalizability, largely independent of scanning site or MR-sequence parameters. Taken together with the minimal input requirements of a standard T1 image, our approach constitutes a clinically viable and useful tool in the presurgical diagnostic routine for drug-resistant focal epilepsy.

Quantifying progression in primary progressive aphasia with structural neuroimaging.

INTRODUCTION: The term primary progressive aphasia (PPA) sums up the non-fluent (nfv), the semantic (sv), and the logopenic (lv) variant. Up to now, there is only limited data available concerning magnetic resonance imaging volumetry to monitor disease progression. METHODS: Structural brain imaging and an extensive assessment were applied at baseline and up to 4-year(s) follow-up in 269 participants. With automated atlas-based volumetry 56 brain regions were assessed. Atrophy progression served to calculate sample sizes for therapeutic trials. RESULTS: At baseline highest atrophy appeared in parts of the left frontal lobe for nfvPPA (-17%) and of the left temporal lobe for svPPA (-34%) and lvPPA (-24%). Severest progression within 1-year follow-up occurred in the basal ganglia in nfvPPA (-7%), in the hippocampus/amygdala in svPPA (-9%), and in (medial) temporal regions in lvPPA (-6%). CONCLUSION: PPA presents as a left-dominant, mostly gray matter sensitive disease with considerable atrophy at baseline that proceeds variant-specific.

Longitudinal brain atrophy distribution in advanced Parkinson's disease: What makes the difference in "cognitive status" converters?

We investigated the brain atrophy distribution pattern and rate of regional atrophy change in Parkinson's disease (PD) in association with the cognitive status to identify the morphological characteristics of conversion to mild cognitive impairment (MCI) and dementia (PDD). T1-weighted longitudinal 3T MRI data (up to four follow-up assessments) from neuropsychologically well-characterized advanced PD patients (n = 172, 8.9 years disease duration) and healthy elderly controls (n = 85) enrolled in the LANDSCAPE study were longitudinally analyzed using a linear mixed effect model and atlas-based volumetry and cortical thickness measures. At baseline, PD patients presented with cerebral atrophy and cortical thinning including striatum, temporoparietal regions, and primary/premotor cortex. The atrophy was already observed in "cognitively normal" PD patients (PD-N) and was considerably more pronounced in cognitively impaired PD patients. Linear mixed effect modeling revealed almost similar rates of atrophy change in PD and controls. The group comparison at baseline between those PD-N whose cognitive performance remained stable (n = 42) and those PD-N patients who converted to MCI/PDD ("converter" cPD-N, n = 26) indicated suggested cortical thinning in the anterior cingulate cortex in cPD-N patients which was correlated with cognitive performance. Our results suggest that cortical brain atrophy has been already expanded in advanced PD patients without overt cognitive deficits while atrophy progression in late disease did not differ from "normal" aging regardless of the cognitive status. It appears that cortical atrophy begins early and progresses already in the initial disease stages emphasizing the need for therapeutic interventions already at disease onset.

Social cognition in an adult epilepsy patient with developmental amnesia.

Reports on social cognition in patients with developmental amnesia resulting from bilateral hippocampal lesions are rare, although the link between social cognition and temporal lobe structures is well established. We present the case of a 23-year-old male epilepsy patient, BM, with developmental amnesia due to perinatal cerebral hypoxia. The patient was examined with neuroimaging and neuropsychological methods and compared to IQ-matched patients with epilepsy to control for effects of epilepsy. In addition, we used a test battery that evaluates emotion recognition and theory of mind to study his social cognition abilities. Structural high-resolution magnetic resonance imaging showed bilateral hippocampal atrophy. The comparison to controls showed that, in addition to the well-documented memory disorders in developmental amnesia, BM showed remarkable deficits in 9 out of 17 social cognitive tasks assessing emotion recognition and theory of mind. In contrast, BM's performance on tasks of executive functions was largely preserved. The relevance of deficits in social cognition for patients with developmental amnesia is discussed.

Ultrasonographic features of focal cortical dysplasia and their relevance for epilepsy surgery.

OBJECTIVE Surgery has proven to be the best therapeutic option for drug-refractory cases of focal cortical dysplasia (FCD)-associated epilepsy. Seizure outcome primarily depends on the completeness of resection, rendering the intraoperative FCD identification and delineation particularly important. This study aims to assess the diagnostic yield of intraoperative ultrasound (IOUS) in surgery for FCD-associated drug-refractory epilepsy. METHODS The authors prospectively enrolled 15 consecutive patients with drug-refractory epilepsy who underwent an IOUS-assisted microsurgical resection of a radiologically suspected FCD between January 2013 and July 2016. The findings of IOUS were compared with those of presurgical MRI postprocessing and the sonographic characteristics were analyzed in relation to the histopathological findings. The authors investigated the added value of IOUS in achieving completeness of resection and improving postsurgical seizure outcome. RESULTS The neurosurgeon was able to identify the dysplastic tissue by IOUS in all cases. The visualization of FCD type I was more challenging compared to FCD II and the demarcation of its borders was less clear. Postsurgical MRI showed residual dysplasia in 2 of the 3 patients with FCD type I. In all FCD type II cases, IOUS allowed for a clear intraoperative visualization and demarcation, strongly correlating with presurgical MRI postprocessing. Postsurgical MRI confirmed complete resection in all FCD type II cases. Sonographic features correlated with the histopathological classification of dysplasia (sonographic abnormalities increase continuously in the following order: FCD IA/IB, FCD IC, FCD IIA, FCD IIB). In 1 patient with IOUS features atypical for FCD, histopathological investigation showed nonspecific gliosis. CONCLUSIONS Morphological features of FCD, as identified by IOUS, correlate well with advanced presurgical imaging. The resolution of IOUS was superior to MRI in all FCD types. The appreciation of distinct sonographic features on IOUS allows the intraoperative differentiation between FCD and non-FCD lesions as well as the discrimination of different histological subtypes of FCD. Sonographic demarcation depends on the underlying degree of dysplasia. IOUS allows for more tailored resections by facilitating the delineation of the dysplastic tissue.

Hypothalamic atrophy is related to body mass index and age at onset in amyotrophic lateral sclerosis.

OBJECTIVE: Our objective was to study the hypothalamic volume in a cohort of patients with amyotrophic lateral sclerosis (ALS) including symptomatic and presymptomatic ALS mutation carriers. METHODS: High-resolution three-dimensional T1-weighted MRI datasets from 251 patients with sporadic ALS, 19 symptomatic and 32 presymptomatic ALS mutation carriers and 112 healthy controls (HC) were retrospectivally registered for manual delineation of the hypothalamus. The volume of the hypothalamus, in total or subdivided, was normalised to the intracranial volume and adjusted to age. Correlation analyses were performed with clinical and metabolic outcomes. Pathologically defined ALS stages were determined in vivo by diffusion tensor imaging (DTI). RESULTS: We observed a severe atrophy of the hypothalamus both in patients with sporadic ALS (-21.8%, p<0.0001) and symptomatic ALS mutation carriers (-13.4%, p<0.001). The atrophy in patients with sporadic ALS was observed in both the anterior (-27.6% p<0.0001) and the posterior parts of the hypothalamus (-17.7%, p<0.0001). Notably, this atrophy was also observed in presymptomatic ALS mutation carriers (-15.5%, p<0.001) and was unrelated to whole brain volume atrophy or disease stage as assessed using DTI or functional status. Hypothalamic volume was correlated with body mass index (BMI) in patients with sporadic ALS (p=0.0434, ρ=+0.1579), and this correlation was much stronger in patients with familial ALS (fALS) (p=0.0060, ρ=+0.6053). Anterior hypothalamic volume was correlated with age at onset, but not with survival after MRI. CONCLUSIONS: Hypothalamus is atrophied in ALS, even in premorbid stages, and correlates with BMI, especially in fALS. Decreased anterior hypothalamic volume is associated with earlier onset of disease.

Longitudinal magnetic resonance imaging in progressive supranuclear palsy: A new combined score for clinical trials.

BACKGROUND: Two 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. OBJECTIVE: The objective of this study was to develop a quantitative MRI disease progression measurement for clinical trials. METHODS: The 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. RESULTS: The 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. CONCLUSIONS: We 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.

Manual MRI morphometry in Parkinsonian syndromes.

BACKGROUND: Several morphometric magnetic resonance imaging parameters may serve for differential diagnosis of parkinsonism. The objective of this study was to identify which performs best in clinical routine. METHODS: We acquired multicentric magnetization-prepared rapid gradient echo sequences in patients with Parkinson's disease (n=204), progressive supranuclear palsy (n=106), multiple system atrophy-cerebellar, (n = 21); multiple system atrophy-parkinsonian (n = 60), and healthy controls (n = 73), performed manual planimetric measurements, and calculated receiver operator characteristics with leave-one-out cross-validation to propose cutoff values. RESULTS: The midsagittal midbrain area was reduced in PSP versus all other groups (P < 0.001). The midsagittal pons area was reduced in MSA-cerebellar, MSA-parkinsonian, and PSP versus PD patients and healthy controls (P < 0.001). The midbrain/pons area ratio was lower in PSP (P < 0.001) and higher in MSA-cerebellar and MSA-parkinsonian versus PD and PSP (P < 0.001). CONCLUSIONS: The midsagittal midbrain area most reliably identified PSP, the midsagittal pons area MSA-cerebellar. The midbrain/pons area ratio differentiated MSA-cerebellar and PSP better than the magnetic resonance-Parkinson index. © 2017 International Parkinson and Movement Disorder Society.