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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., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

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., (© 2023 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

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)., (© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

Background: ALS patients with hexanucleotide expansion in C9orf72 are characterized by a specific clinical phenotype, including more aggressive disease course and cognitive decline. Computerized multiparametric MRI with gray matter volumetry and diffusion tensor imaging (DTI) to analyze white matter structural connectivity is a potential in vivo biomarker., Objective: The objective of this study was to develop a multiparametric MRI signature in a large cohort of ALS patients with C9orf72 mutations. The aim was to investigate how morphological features of C9orf72-associated ALS differ in structural MRI and DTI compared to healthy controls and ALS patients without C9orf72 mutations., Methods: Atlas-based volumetry (ABV) and whole brain-based DTI-based analyses were performed in a cohort of n = 51 ALS patients with C9orf72 mutations and compared with both n = 51 matched healthy controls and n = 51 C9orf72 negative ALS patients, respectively. Subsequently, Spearman correlation analysis of C9orf72 ALS patients' data with clinical parameters (age of onset, sex, ALS-FRS-R, progression rate, survival) as well as ECAS and p-NfH in CSF was performed., Results: The whole brain voxel-by-voxel comparison of fractional anisotropy (FA) maps between C9orf72 ALS patients and controls showed significant bilateral alterations in axonal structures of the white matter at group level, primarily along the corticospinal tracts and in fibers projecting to the frontal lobes. For the frontal lobes, these alterations were also significant between C9orf72 positive and C9orf72 negative ALS patients. In ABV, patients with C9orf72 mutations showed lower volumes of the frontal, temporal, and parietal lobe, with the lowest values in the gray matter of the superior frontal and the precentral gyrus, but also in hippocampi and amygdala. Compared to C9orf72 negative ALS, the differences were shown to be significant for cerebral gray matter (p = 0.04), especially in the frontal (p = 0.01) and parietal lobe (p = 0.01), and in the thalamus (p = 0.004). A correlation analysis between ECAS and averaged regional FA values revealed significant correlations between cognitive performance in ECAS and frontal association fibers. Lower FA values in the frontal lobes were associated with worse performance in all cognitive domains measured (language, verbal fluency, executive functions, memory and spatial perception). In addition, there were significant negative correlations between age of onset and atlas-based volumetry results for gray matter., Conclusions: This study demonstrates a distinct pattern of DTI alterations of the white matter and ubiquitous volume reductions of the gray matter early in the disease course of C9orf72-associated ALS. Alterations were closely linked to a more aggressive cognitive phenotype. These results are in line with an expected pTDP43 propagation pattern of cortical affection and thus strengthen the hypothesis that an underlying developmental disorder is present in ALS with C9orf72 expansions. Thus, multiparametric MRI could contribute to the assessment of the disease as an in vivo biomarker even in the early phase of the disease., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Importance: The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context., Objective: Multi-class prediction is key for building computational aid systems for differential diagnosis. We compared support vector machine, random forest, gradient boosting, and deep feed-forward neural networks for the classification of different neurodegenerative syndromes based on structural magnetic resonance imaging., Design, Setting, and Participants: Atlas-based volumetry was performed on multi-centric T1-weighted MRI data from 940 subjects, i.e., 124 healthy controls and 816 patients with ten different neurodegenerative diseases, leading to a multi-diagnostic multi-class classification task with eleven different classes., Interventions: N.A., Main Outcomes and Measures: Cohen's kappa, accuracy, and F1-score to assess model performance., Results: Overall, the neural network produced both the best performance measures and the most robust results. The smaller classes however were better classified by either the ensemble learning methods or the support vector machine, while performance measures for small classes were comparatively low, as expected. Diseases with regionally specific and pronounced atrophy patterns were generally better classified than diseases with widespread and rather weak atrophy., Conclusions and Relevance: Our study furthermore underlines the necessity of larger data sets but also calls for a careful consideration of different machine learning methods that can handle the type of data and the classification task best., (© 2022. The Author(s).)

Introduction: The behavioral variant of frontotemporal dementia (bvFTD) is a rare neurodegenerative disease. Reliable predictors of disease progression have not been sufficiently identified. We investigated multivariate magnetic resonance imaging (MRI) biomarker profiles for their predictive value of individual decline., Methods: One hundred five bvFTD patients were recruited from the German frontotemporal lobar degeneration (FTLD) consortium study. After defining two groups ("fast progressors" vs. "slow progressors"), we investigated the predictive value of MR brain volumes for disease progression rates performing exhaustive screenings with multivariate classification models., Results: We identified areas that predict disease progression rate within 1 year. Prediction measures revealed an overall accuracy of 80% across our 50 top classification models. Especially the pallidum, middle temporal gyrus, inferior frontal gyrus, cingulate gyrus, middle orbitofrontal gyrus, and insula occurred in these models., Discussion: Based on the revealed marker combinations an individual prognosis seems to be feasible. This might be used in clinical studies on an individualized progression model., Competing Interests: The authors declare no conflicts of interest., (© 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

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., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

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., (© 2021 International Parkinson and Movement Disorder Society.)

Objective: To determine the volume changes in gray and white matter during a long-term follow-up in patients suffering from pantothenate kinase-associated neurodegeneration (PKAN)., Methods: Magnetic resonance imaging was repeated in 13 patients and 14 age-matched controls after a mean interval of more than 7 years. T1-weighted sequences were evaluated by fully automated atlas-based volumetry, compared between groups and correlated with disease progression., Results: The patients did not show generalized cerebral atrophy but did show a significantly faster volume reduction in the globus pallidus during follow-up (between -0.96% and -1.02% per year, p < 0.05 adjusted for false discovery rate) than controls, which was significantly related to the progression in their dystonia scores (p = 0.032)., Conclusion: The volume loss in the globus pallidus over time-together with the accumulation of iron known as the "tiger's eye"-supports the pathophysiologic concept of this nucleus as a center of inhibition and its severe malfunction in PKAN.

Introduction: A volumetric MRI analysis of longitudinal regional cerebral atrophy in Huntington's disease (HD) was performed as a read-out of disease progression to calculate sample sizes for future clinical trials., Methods: This study was based on MRI data of 59 patients with HD and 40 controls recruited within the framework of the PADDINGTON study and investigated at baseline and follow-up after 6 and 15 months. Automatic atlas-based volumetry (ABV) of structural T1-weighted scans was used to calculate longitudinal volume changes of brain structures relevant in HD and to assess standardized effect sizes and sample sizes required for potential future studies., Results: Atrophy rates were largest in the caudate (-3.4%), putamen (-2.8%), nucleus accumbens (-1.6%), and the parietal lobes (-1.7%); the lateral ventricles showed an expansion by 6.0%. Corresponding effect sizes were -1.35 (caudate), -0.84 (putamen), -0.91 (nucleus accumbens), -1.05 (parietal lobe), and 0.92 (lateral ventricles) leading to N = 36 subjects per study group for detecting a 50% attenuation of atrophy for the best performing structure (caudate). A combined score of volume changes in non-overlapping compartments (striatum, parietal lobes, lateral ventricles) increased the effect size to -1.60 and substantially reduced the required sample sizes by 10 to N = 26 subjects per study group. This combined imaging score correlated significantly both with the CAP score and with the progression of the clinical phenotype., Conclusion: We propose ABV of the striatum together with parietal lobe and lateral ventricle volumes as a combined imaging read-out for progression studies including clinical trials in HD., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Objective: To determine the association of serum neurofilament light chain (NfL) with functional deterioration and brain atrophy during follow-up of patients with behavioral variant frontotemporal dementia (bvFTD)., Methods: Blood NfL levels from 74 patients with bvFTD, 26 with Alzheimer disease (AD), 17 with mild cognitive impairment (MCI), and 15 healthy controls (Con) at baseline and follow-up were determined and analyzed for the diagnostic potential in relation to functional assessment (Clinical Dementia Rating Scale Sum of Boxes [CDR-SOB], frontotemporal lobar degeneration-related CDR-SOB, Mini-Mental State Examination [MMSE]) and brain volumetry., Results: At baseline, serum NfL level correlated with CSF NfL (bvFTD r = 0.706, p < 0.0001; AD/MCI r = 0.666, p = 0.0003). Highest serum levels were observed in bvFTD ( p <0 0.0001 vs Con and MCI, p = 0.0078 vs AD, respectively). Discrimination of bvFTD from Con/MCI/AD was possible with 91%/74%/74% sensitivity and 79%/74%/58% specificity. At follow-up, serum NfL increased in bvFTD and AD ( p = 0.0039 and p = 0.0006, respectively). At baseline and follow-up, NfL correlated with functional scores of patients with bvFTD (e.g., CDR-SOB [baseline] r = 0.4157, p = 0.0006; [follow-up] r = 0.5629, p < 0.0001) and with atrophy in the gray and white matter of many brain regions including frontal and subcortical areas (e.g., frontal lobe: r = -0.5857, p < 0.0001; 95% confidence interval -0.7415 to -0.3701). For patients with AD/MCI, NfL correlated with the functional performance as well (e.g., CDR-SOB [baseline] r = 0.6624, p < 0.0001; [follow-up] r = 0.5659, p = 0.0003) but not with regional brain volumes., Conclusions: As serum NfL correlates with functional impairment and brain atrophy in bvFTD at different disease stages, we propose it as marker of disease severity, paving the way for its future use as outcome measure for clinical trials., Classification of Evidence: This study provides Class III evidence that for patients with cognitive problems, serum NfL concentration discriminates bvFTD from other forms of dementia., (© 2018 American Academy of Neurology.)

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., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

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., (© 2017 International Parkinson and Movement Disorder Society.)

Objective: To assess the utility of serum neurofilament for diagnosis and monitoring of primary progressive aphasia (PPA) variants., Methods: We investigated neurofilament light chain (NF-L) levels in blood of 99 patients with PPA (40 with nonfluent variant PPA [nfvPPA], 38 with semantic variant PPA [svPPA], 21 with logopenic variant PPA [lvPPA]) and compared diagnostic performance with that reached by CSF NF-L, phosphorylated neurofilament heavy chain (pNF-H), β-amyloid (Aβ 1-42 ), tau, and phosphorylated tau. The longitudinal change of blood NF-L levels was measured and analyzed for correlation with functional decline and brain atrophy., Results: Serum NF-L is increased in PPA compared to controls and discriminates between nfvPPA/svPPA and lvPPA with 81% sensitivity and 67% specificity (cutoff 31 pg/mL). CSF NF-L, pNF-H, tau, phosphorylated tau, and Aβ 1-42 achieved similar performance, and pNF-H was the only marker for discrimination of nfvPPA from svPPA/lvPPA. In most patients with nfvPPA and svPPA, but not lvPPA, serum NF-L increased within follow-up. The increase correlated with functional decline and progression of atrophy of the left frontal lobe of all patients with PPAs and the right middle frontal gyrus of patients with nfvPPA and svPPA., Conclusions: Blood level of NF-L can aid the differential diagnosis of PPA variants, especially in combination with CSF pNF-H. Because serum NF-L correlates with functional decline and atrophy in the disease course, it qualifies as an objective disease status marker. Extended follow-up studies with cases of known neuropathology are imperative., Classification of Evidence: This study provides Class I evidence that in patients with PPA, blood levels of NF-L can distinguish the logopenic variant from the nonfluent/agrammatic and semantic variants., (© 2017 American Academy of Neurology.)

For rapid visualization of subdural electrodes with respect to cortical and subcortical structures, we describe a novel and fully automated method based on coregistration, normalization, optional cerebellum masking, and volume rendering of 3D MR imaging data taken before and after implantation. The key step employs the skull-stripped preimplantation image as a mask to also remove the skull in the postimplantation image. The extracted brain is presented in 3D with the electrodes directly visible by their susceptibility artifacts. Compared with alternative methods, ours is based on freely available software and does not require manual intervention.