A Blinded Evaluation of Brain Morphometry for Differential Diagnosis of Atypical Parkinsonism.

BACKGROUND: Advanced imaging techniques have been studied for differential diagnosis between PD, MSA, and PSP. OBJECTIVES: This study aims to validate the utility of individual voxel-based morphometry techniques for atypical parkinsonism in a blinded fashion. METHODS: Forty-eight healthy controls (HC) T1-WI were used to develop a referential dataset and fit a general linear model after segmentation into gray matter (GM) and white matter (WM) compartments. Segmented GM and WM with PD (n = 96), MSA (n = 18), and PSP (n = 20) were transformed into z-scores using the statistics of referential HC and individual voxel-based z-score maps were generated. An imaging diagnosis was assigned by two independent raters (trained and untrained) blinded to clinical information and final diagnosis. Furthermore, we developed an observer-independent index for ROI-based automated differentiation. RESULTS: The diagnostic performance using voxel-based z-score maps by rater 1 and rater 2 for MSA yielded sensitivities: 0.89, 0.94 (95% CI: 0.74-1.00, 0.84-1.00), specificities: 0.94, 0.80 (0.90-0.98, 0.73-0.87); for PSP, sensitivities: 0.85, 0.90 (0.69-1.00, 0.77-1.00), specificities: 0.98, 0.94 (0.96-1.00, 0.90-0.98). Interrater agreement was good for MSA (Cohen's kappa: 0.61), and excellent for PSP (0.84). Receiver operating characteristic analysis using the ROI-based new index showed an area under the curve (AUC): 0.89 (0.77-1.00) for MSA, and 0.99 (0.98-1.00) for PSP. CONCLUSIONS: These evaluations provide support for the utility of this imaging technique in the differential diagnosis of atypical parkinsonism demonstrating a remarkably high differentiation accuracy for PSP, suggesting potential use in clinical settings in the future.

Progressive Brain Atrophy in Multiple System Atrophy: A Longitudinal, Multicenter, Magnetic Resonance Imaging Study.

OBJECTIVE: To determine the rates of brain atrophy progression in vivo in patients with multiple system atrophy (MSA). BACKGROUND: Surrogate biomarkers of disease progression are a major unmet need in MSA. Small-scale longitudinal studies in patients with MSA using magnetic resonance imaging (MRI) to assess progression of brain atrophy have produced inconsistent results. In recent years, novel MRI post-processing methods have been developed enabling reliable quantification of brain atrophy in an automated fashion. METHODS: Serial 3D-T1-weighted MRI assessments (baseline and after 1 year of follow-up) of 43 patients with MSA were analyzed and compared to a cohort of early-stage Parkinson's disease (PD) patients and healthy controls (HC). FreeSurfer's longitudinal analysis stream was used to determine the brain atrophy rates in an observer-independent fashion. RESULTS: Mean ages at baseline were 64.4 ± 8.3, 60.0 ± 7.5, and 59.8 ± 9.2 years in MSA, PD patients and HC, respectively. A mean disease duration at baseline of 4.1 ± 2.5 years in MSA patients and 2.3 ± 1.4 years in PD patients was observed. Brain regions chiefly affected by MSA pathology showed progressive atrophy with annual rates of atrophy for the cerebellar cortex, cerebellar white matter, pons, and putamen of -4.24 ± 6.8%, -8.22 ± 8.8%, -4.67 ± 4.9%, and - 4.25 ± 4.9%, respectively. Similar to HC, atrophy rates in PD patients were minimal with values of -0.41% ± 1.8%, -1.47% ± 4.1%, -0.04% ± 1.8%, and -1.54% ± 2.2% for cerebellar cortex, cerebellar white matter, pons, and putamen, respectively. CONCLUSIONS: Patients with MSA show significant brain volume loss over 12 months, and cerebellar, pontine, and putaminal volumes were the most sensitive to change in mid-stage disease. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Somatostatin receptor subtype expression and radiomics from DWI-MRI represent SUV of [68Ga]Ga-DOTATOC PET in patients with meningioma.

OBJECTIVE: This retrospective study aimed to analyse the correlation between somatostatin receptor subtypes (SSTR 1-5) and maximum standardized uptake value (SUVmax) in meningioma patients using Gallium-68 DOTA-D-Phe1-Tyr3-octreotide Positron Emission Tomography ([68Ga]Ga-DOTATOC PET). Secondly, we developed a radiomic model based on apparent diffusion coefficient (ADC) maps derived from diffusion weighted magnetic resonance images (DWI MRI) to reproduce SUVmax. METHOD: The study included 51 patients who underwent MRI and [68Ga]Ga-DOTATOC PET before meningioma surgery. SUVmax values were quantified from PET images and tumour areas were segmented on post-contrast T1-weighted MRI and mapped to ADC maps. A total of 1940 radiomic features were extracted from the tumour area on each ADC map. A random forest regression model was trained to predict SUVmax and the model's performance was evaluated using repeated nested cross-validation. The expression of SSTR subtypes was quantified in 18 surgical specimens and compared to SUVmax values. RESULTS: The random forest regression model successfully predicted SUVmax values with a significant correlation observed in all 100 repeats (p < 0.05). The mean Pearson's r was 0.42 ± 0.07 SD, and the root mean square error (RMSE) was 28.46 ± 0.16. SSTR subtypes 2A, 2B, and 5 showed significant correlations with SUVmax values (p < 0.001, R2 = 0.669; p = 0.001, R2 = 0.393; and p = 0.012, R2 = 0.235, respectively). CONCLUSION: SSTR subtypes 2A, 2B, and 5 correlated significantly with SUVmax in meningioma patients. The developed radiomic model based on ADC maps effectively reproduces SUVmax using [68Ga]Ga-DOTATOC PET.

Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy.

Background: Multiple system atrophy (MSA) is a devastating disease characterized by a variable combination of motor and autonomic symptoms. Previous studies identified numerous clinical factors to be associated with shorter survival. Objective: To enable personalized patient counseling, we aimed at developing a risk model of survival based on baseline clinical symptoms. Methods: MSA patients referred to the Movement Disorders Unit in Innsbruck, Austria, between 1999 and 2016 were retrospectively analyzed. Kaplan-Meier curves and multivariate Cox regression analysis with least absolute shrinkage and selection operator penalty for variable selection were performed to identify prognostic factors. A nomogram was developed to estimate the 7 years overall survival probability. The performance of the predictive model was validated and calibrated internally using bootstrap resampling and externally using data from the prospective European MSA Study Group Natural History Study. Results: A total of 210 MSA patients were included in this analysis, of which 124 patients died. The median survival was 7 years. The following clinical variables were found to significantly affect overall survival and were included in the nomogram: age at symptom onset, falls within 3 years of onset, early autonomic failure including orthostatic hypotension and urogenital failure, and lacking levodopa response. The time-dependent area under curve for internal and external validation was >0.7 within the first 7 years of the disease course. The model was well calibrated showing good overlap between predicted and actual survival probability at 7 years. Conclusion: The nomogram is a simple tool to predict survival on an individual basis and may help to improve counseling and treatment of MSA patients.

Dorsolateral Nigral Hyperintensity on 1.5 T Versus 3 T Susceptibility-Weighted Magnetic Resonance Imaging in Neurodegenerative Parkinsonism.

Background: An absent dorsolateral nigral hyperintensity (DNH) is a common finding in patients with neurodegenerative parkinsonism at high or ultra-high field susceptibility-weighted magnetic resonance imaging (SWI). Objective: Despite increasing use of high field magnetic resonance imaging (MRI) in specialized centers, these scanners are still frequently unavailable in primary care or outpatient facilities and underdeveloped or emerging countries. Therefore, the aim of the present study was to evaluate the diagnostic utility of DNH assessment at 1.5 versus 3 T MRI to distinguish patients with neurodegenerative parkinsonism, including Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), from healthy controls (HC). Methods: Absence of DNH was assessed on visual inspection of anonymized 1.5 T and 3.0 T SWI scans in a case-control study including 86 patients with neurodegenerative parkinsonism and 33 healthy controls (HC). All study participants were consecutively recruited to undergo 1.5 and 3 T MRI. Results: Overall correct classification was 81.7% (95% CI, 72.6-88.4%) for 1.5 T and 95.7% (95% CI, 89.1-98.7%) for 3 T MRI in discriminating neurodegenerative parkinsonism from controls. However, while DNH was bilaterally present in all but one of the HC at 3 T MRI, it was rated as abnormal (at least unilateral absence) in 15 of 22 HC at 1.5 T MRI, resulting in a specificity of 31.8%. Conclusions: The results of the present study demonstrate an insufficient specificity of visual assessment of DNH at 1.5 T MRI for the diagnosis of neurodegenerative parkinsonism.

Brain microdialysate tau dynamics predict functional and neurocognitive recovery after poor-grade subarachnoid haemorrhage.

Subarachnoid haemorrhage is a devastating disease that results in neurocognitive deficits and a poor functional outcome in a considerable proportion of patients. In this study, we investigated the prognostic value of microtubule-associated tau protein measured in the cerebral microdialysate for long-term functional and neuropsychological outcomes in poor-grade subarachnoid haemorrhage patients. We recruited 55 consecutive non-traumatic subarachnoid haemorrhage patients who underwent multimodal neuromonitoring, including cerebral microdialysis. Mitochondrial dysfunction was defined as lactate-to-pyruvate ratio >30 together with pyruvate >70 mmol/L and metabolic distress as lactate-to-pyruvate ratio >40. The multidimensional 12-month outcome was assessed by means of the modified Rankin scale (poor outcome: modified Rankin scale ≥4) and a standardized neuropsychological test battery. We used multivariable generalized estimating equation models to assess associations between total microdialysate-tau levels of the first 10 days after admission and hospital complications and outcomes. Patients were 56 ± 12 years old and presented with a median Hunt & Hess score of 5 (interquartile range: 3-5). Overall mean total microdialysate-tau concentrations were highest within the first 24 h (5585 ± 6291 pg/mL), decreased to a minimum of 2347 ± 4175 pg/mL on Day 4 (P < 0.001) and remained stable thereafter (P = 0.613). Higher total microdialysate-tau levels were associated with the occurrence of delayed cerebral ischaemia (P = 0.001), episodes of metabolic distress (P = 0.002) and mitochondrial dysfunction (P = 0.034). Patients with higher tau levels had higher odds for a poor 12-month functional outcome (adjusted odds ratio: 2.61; 95% confidence interval: 1.32-5.17; P = 0.006) and impaired results in the trail making test-B (adjusted odds ratio: 3.35; 95% confidence interval: 1.16-9.68; P = 0.026) indicative of cognitive flexibility. Total microdialysate-tau levels significantly decreased over the first 10 days (P < 0.05) in patients without delayed cerebral ischaemia or good functional outcomes and remained high in those with delayed cerebral ischaemia and poor 12-month outcomes, respectively. Dynamic changes of total tau in the cerebral microdialysate may be a useful biomarker for axonal damage associated with functional and neurocognitive recovery in poor-grade subarachnoid haemorrhage patients. In contrast, ongoing axonal damage beyond Day 3 after bleeding indicates a higher risk for delayed cerebral ischaemia as well as a poor functional outcome.

Trial of Deferiprone in Parkinson's Disease.

BACKGROUND: Iron content is increased in the substantia nigra of persons with Parkinson's disease and may contribute to the pathophysiology of the disorder. Early research suggests that the iron chelator deferiprone can reduce nigrostriatal iron content in persons with Parkinson's disease, but its effects on disease progression are unclear. METHODS: We conducted a multicenter, phase 2, randomized, double-blind trial involving participants with newly diagnosed Parkinson's disease who had never received levodopa. Participants were assigned (in a 1:1 ratio) to receive oral deferiprone at a dose of 15 mg per kilogram of body weight twice daily or matched placebo for 36 weeks. Dopaminergic therapy was withheld unless deemed necessary for symptom control. The primary outcome was the change in the total score on the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS; range, 0 to 260, with higher scores indicating more severe impairment) at 36 weeks. Secondary and exploratory clinical outcomes at up to 40 weeks included measures of motor and nonmotor disability. Brain iron content measured with the use of magnetic resonance imaging was also an exploratory outcome. RESULTS: A total of 372 participants were enrolled; 186 were assigned to receive deferiprone and 186 to receive placebo. Progression of symptoms led to the initiation of dopaminergic therapy in 22.0% of the participants in the deferiprone group and 2.7% of those in the placebo group. The mean MDS-UPDRS total score at baseline was 34.3 in the deferiprone group and 33.2 in the placebo group and increased (worsened) by 15.6 points and 6.3 points, respectively (difference, 9.3 points; 95% confidence interval, 6.3 to 12.2; P<0.001). Nigrostriatal iron content decreased more in the deferiprone group than in the placebo group. The main serious adverse events with deferiprone were agranulocytosis in 2 participants and neutropenia in 3 participants. CONCLUSIONS: In participants with early Parkinson's disease who had never received levodopa and in whom treatment with dopaminergic medications was not planned, deferiprone was associated with worse scores in measures of parkinsonism than those with placebo over a period of 36 weeks. (Funded by the European Union Horizon 2020 program; FAIRPARK-II ClinicalTrials.gov number, NCT02655315.).

Characterization and diagnostic potential of R2* in early-stage progressive supranuclear palsy variants.

INTRODUCTION: Iron accumulation in subcortical brain nuclei has been shown to be differentially increased in atypical parkinsonian disorders. It is unclear whether the patterns of iron accumulation are consistent between variants of progressive supranuclear palsy (PSP) and their diagnostic utility in early to moderately advanced stages of the diseases. METHODS: Brain iron content (R2*) was quantified using magnetic resonance imaging in patients clinically diagnosed as PSP - parkinsonism (PSP-P, n = 15), PSP - Richardson's syndrome (PSP-RS, n = 14), Parkinson's disease (PD, n = 15), or the parkinsonian variant of multiple system atrophy (MSA-P, n = 14) using established criteria, and healthy controls (HC). Disease duration was less than 5 years in all patients. The quantification of regional R2* was performed using a semi-automatized approach. RESULTS: Significant group differences in R2*, primarily within the red nucleus and the substantia nigra, were identified between PSP, PD, MSA-P, and HC, but not between PSP-P and PSP-RS. However, distinct R2* correlation patterns across brain regions were observed for the different groups. Good classification performances (sensitivity and specificity >80%) were only obtained for PSP vs. HC. For all other comparisons, sensitivity and/or specificity was below <70%. CONCLUSION: Iron accumulation in subcortical brain nuclei has distinct correlated patterns in PSP-P and PSP-RS, which could be reflecting different pathophysiological mechanisms. Increased iron content in these nuclei appears to be a predictor for atypical parkinsonian disorders such as PSP and MSA. Further studies are required to reproduce this finding and elucidate the evolution of these patterns over the course of the disease.

Revisiting brain iron deficiency in restless legs syndrome using magnetic resonance imaging.

STUDY OBJECTIVES: Studies on brain iron content in restless legs syndrome (RLS) using magnetic resonance imaging (MRI) are heterogeneous. In this study, we sought to leverage the availability of a large dataset including a range of iron-sensitive MRI techniques to reassess the association between brain iron content and RLS with added statistical power and to compare these results to previous studies. METHODS: The relaxation rates R2, R2', and R2* and quantitative susceptibility are MRI parameters strongly correlated to iron content. In general, these parameters are sensitive to magnetic field variations caused by iron particles. These parameters were quantified within iron-rich brain regions using a fully automatized approach in a cohort of 72 RLS patients and individually age and gender-matched healthy controls identified from an existing dataset acquired at the Sleep Laboratory of the Department of Neurology, Medical University of Innsbruck. 3 T-MRI measures were corrected for age and volume of the segmented brain nuclei and results were compared with previous findings in a meta-analysis. RESULTS: In our cohort, RLS patients had increased R2* signal in the caudate and increased quantitative susceptibility signal in the putamen and the red nucleus compared to controls, suggesting increased iron content in these areas. The meta-analysis revealed no significant pooled effect across all brain regions. Furthermore, potential publication bias was identified for the substantia nigra. CONCLUSIONS: Normal and increased iron content of subcortical brain areas detected in this study is not in line with the hypothesis of reduced brain iron storage, but favors CSF investigations and post mortem studies indicating alteration of brain iron mobilization and homeostasis in RLS.

HFP-QSMGAN: QSM from homodyne-filtered phase images.

PURPOSE: Homodyne filtering is a standard preprocessing step in the estimation of SWI. Unfortunately, SWI is not quantitative, and QSM cannot be accurately estimated from filtered phase images. Compared with gradient-echo sequences suitable for computing QSM, SWI is more readily available and is often the only susceptibility-sensitive sequence acquired in the clinical setting. In this project, we aimed to quantify susceptibility from the homodyne-filtered phase (HFP), acquired for computing susceptibility-weighted images, using convolutional neural networks to solve the compounded problem of (1) computing the solution to the inverse dipole problem, and (2) compensating for the effects of the homodyne filtering. METHODS: Two convolutional neural networks, the U-Net and a modified QSMGAN architecture (HFP-QSMGAN), were trained to predict QSM maps at different TEs from HFP images. The QSM maps were quantified from a gradient-echo sequence acquired in the same individuals using total generalized variation (TGV)-QSM. The QSM maps estimated directly from the HFP were also included for comparison. Voxel-wise predictions and, importantly, regional predictions of susceptibility with adjustment to a reference region, were compared. RESULTS: Our results indicate that the U-Net model provides more accurate voxel-wise predictions of susceptibility compared with HFP-QSMGAN and HFP-QSM. However, regional estimates of susceptibility predicted by HFP-QSMGAN are more strongly correlated with the values from TGV-QSM compared with those of U-Net and HFP-QSM. CONCLUSION: Accurate prediction of susceptibility can be achieved from filtered SWI phase using convolutional neural networks.

ADC textural features in patients with single brain metastases improve clinical risk models.

AIMS: In this retrospective study we performed a quantitative textural analysis of apparant diffusion coefficient (ADC) images derived from diffusion weighted MRI (DW-MRI) of single brain metastases (BM) patients from different primary tumors and tested whether these imaging parameters may improve established clinical risk models. METHODS: We identified 87 patients with single BM who had a DW-MRI at initial diagnosis. Applying image segmentation, volumes of contrast-enhanced lesions in T1 sequences, hyperintense T2 lesions (peritumoral border zone (T2PZ)) and tumor-free gray and white matter compartment (GMWMC) were generated and registered to corresponding ADC maps. ADC textural parameters were generated and a linear backward regression model was applied selecting imaging features in association with survival. A cox proportional hazard model with backward regression was fitted for the clinical prognostic models (diagnosis-specific graded prognostic assessment score (DS-GPA) and the recursive partitioning analysis (RPA)) including these imaging features. RESULTS: Thirty ADC textural parameters were generated and linear backward regression identified eight independent imaging parameters which in combination predicted survival. Five ADC texture features derived from T2PZ, the volume of the T2PZ, the normalized mean ADC of the GMWMC as well as the mean ADC slope of T2PZ. A cox backward regression including the DS-GPA, RPA and these eight parameters identified two MRI features which improved the two risk scores (HR = 1.14 [1.05;1.24] for normalized mean ADC GMWMC and HR = 0.87 [0.77;0.97]) for ADC 3D kurtosis of the T2PZ.) CONCLUSIONS: Textural analysis of ADC maps in patients with single brain metastases improved established clinical risk models. These findings may aid to better understand the pathogenesis of BM and may allow selection of patients for new treatment options.

Serum NfL in Alzheimer Dementia: Results of the Prospective Dementia Registry Austria.

Background and Objectives: The neurofilament light chain (NfL) is a biomarker for neuro-axonal injury in various acute and chronic neurological disorders, including Alzheimer's disease (AD). We here investigated the cross-sectional and longitudinal associations between baseline serum NfL (sNfL) levels and cognitive, behavioural as well as MR volumetric findings in the Prospective Dementia Registry Austria (PRODEM-Austria). Materials and Methods: All participants were clinically diagnosed with AD according to NINCDS-ADRDA criteria and underwent a detailed clinical assessment, cognitive testing (including the Mini Mental State Examination (MMSE) and the Consortium to Establish a Registry for Alzheimer's Disease (CERAD)), the neuropsychiatric inventory (NPI) and laboratory evaluation. A total of 237 patients were included in the study. Follow-up examinations were done at 6 months, 1 year and 2 years with 93.3% of patients undergoing at least one follow-up. We quantified sNfL by a single molecule array (Simoa). In a subgroup of 125 subjects, brain imaging data (1.5 or 3T MRI, with 1 mm isotropic resolution) were available. Brain volumetry was assessed using the FreeSurfer image analysis suite (v6.0). Results: Higher sNfL concentrations were associated with worse performance in cognitive tests at baseline, including CERAD (B = −10.084, SE = 2.999, p < 0.001) and MMSE (B = −3.014, SE = 1.293, p = 0.021). The sNfL levels also correlated with the presence of neuropsychiatric symptoms (NPI total score: r = 0.138, p = 0.041) and with smaller volumes of the temporal lobe (B = −0.012, SE = 0.003, p = 0.001), the hippocampus (B = −0.001, SE = 0.000201, p = 0.013), the entorhinal (B = −0.000308, SE = 0.000124, p = 0.014), and the parahippocampal cortex (B = −0.000316, SE = 0.000113, p = 0.006). The sNfL values predicted more pronounced cognitive decline over the mean follow-up period of 22 months, but there were no significant associations with respect to change in neuropsychiatric symptoms and brain volumetric measures. Conclusions: the sNfL levels relate to cognitive, behavioural, and imaging hallmarks of AD and predicts short term cognitive decline.

Qualitative and Quantitative Comparison of Hippocampal Volumetric Software Applications: Do All Roads Lead to Rome?

Brain volumetric software is increasingly suggested for clinical routine. The present study quantifies the agreement across different software applications. Ten cases with and ten gender- and age-adjusted healthy controls without hippocampal atrophy (median age: 70; 25-75% range: 64-77 years and 74; 66-78 years) were retrospectively selected from a previously published cohort of Alzheimer's dementia patients and normal ageing controls. Hippocampal volumes were computed based on 3 Tesla T1-MPRAGE-sequences with FreeSurfer (FS), Statistical-Parametric-Mapping (SPM; Neuromorphometrics and Hammers atlases), Geodesic-Information-Flows (GIF), Similarity-and-Truth-Estimation-for-Propagated-Segmentations (STEPS), and Quantib™. MTA (medial temporal lobe atrophy) scores were manually rated. Volumetric measures of each individual were compared against the mean of all applications with intraclass correlation coefficients (ICC) and Bland-Altman plots. Comparing against the mean of all methods, moderate to low agreement was present considering categorization of hippocampal volumes into quartiles. ICCs ranged noticeably between applications (left hippocampus (LH): from 0.42 (STEPS) to 0.88 (FS); right hippocampus (RH): from 0.36 (Quantib™) to 0.86 (FS). Mean differences between individual methods and the mean of all methods [mm3] were considerable (LH: FS -209, SPM-Neuromorphometrics -820; SPM-Hammers -1474; Quantib™ -680; GIF 891; STEPS 2218; RH: FS -232, SPM-Neuromorphometrics -745; SPM-Hammers -1547; Quantib™ -723; GIF 982; STEPS 2188). In this clinically relevant sample size with large spread in data ranging from normal aging to severe atrophy, hippocampal volumes derived by well-accepted applications were quantitatively different. Thus, interchangeable use is not recommended.

Cardiac sympathetic innervation in Parkinson's disease versus multiple system atrophy.

PURPOSE: The aims of this study were to evaluate the diagnostic accuracy of the dual imaging method combining cardiac iodine-123-metaiodobenzylguanidine single-photon emission computed tomography combined with low-dose chest computed tomography compared to routine cardiac scintigraphy, and assess regional differences in tracer distribution and the relationships between imaging and autonomic function in Parkinson's disease and multiple system atrophy. METHODS: A prospective study including 19 Parkinson's disease and 12 multiple system atrophy patients was performed. Patients underwent clinical evaluation, iodine-123-metaiodobenzylguanidine single-photon emission computed tomography combined with chest computed tomography, planar scintigraphy, and cardiovascular autonomic function tests. RESULTS: Co-registration of single-photon emission computed tomography and chest computed tomography resulted in three groups with distinct patterns of tracer uptake: homogeneous, non-homogeneously reduced and absent. There was a significant difference in group allocation among patients with multiple system atrophy and Parkinson's disease (p = 0.001). Most multiple system atrophy patients showed homogeneous uptake, and the majority of Parkinson's disease patients showed absent cardiac tracer uptake. We identified a pattern of heterogeneous cardiac tracer uptake in both diseases with reductions in the apex and the lateral myocardial wall. Sympathetic dysfunction reflected by a missing blood pressure overshoot during Valsalva manoeuvre correlated with cardiac tracer distribution in Parkinson's disease patients (p < 0.001). CONCLUSIONS: The diagnostic accuracy of the dual imaging method and routine cardiac scintigraphy were similar. Anatomical tracer allocation provided by the dual imaging method of cardiac iodine-123-metaiodobenzylguanidine single-photon emission computed tomography and chest computed tomography identified a heterogeneous subgroup of Parkinson's disease and multiple system atrophy patients with reduced cardiac tracer uptake in the apex and the lateral wall. Sympathetic dysfunction correlated with cardiac imaging in Parkinson's disease patients.

Factors associated with impaired quality of life three months after being diagnosed with COVID-19.

PURPOSE: To assess patient characteristics associated with health-related quality of life (HR-QoL) and its mental and physical subcategories 3 months after diagnosis with COVID-19. METHODS: In this prospective multicentre cohort study, HR-QoL was assessed in 90 patients using the SF-36 questionnaire (36-item Short Form Health Survey), which consists of 8 health domains that can be divided into a mental and physical health component. Mental health symptoms including anxiety, depression, and post-traumatic stress disorders were evaluated using the Hospital Anxiety and Depression Scale (HADS) and Post-traumatic Stress Disorder Checklist-5 (PCL-5) 3 months after COVID-19. Using descriptive statistics and multivariable regression analysis, we identified factors associated with impaired HR-QoL 3 months after COVID-19 diagnosis. RESULTS: Patients were 55 years of age (IQR, 49-63; 39% women) and were classified as severe (23%), moderate (57%), or mild (20%) according to acute disease severity. HR-QoL was impaired in 28/90 patients (31%). Younger age [per year, adjOR (95%CI) 0.94 (0.88-1.00), p = 0.049], longer hospitalization [per day, adjOR (95%CI) 1.07 (1.01-1.13), p = 0.015], impaired sleep [adjOR (95%CI) 5.54 (1.2-25.61), p = 0.028], and anxiety [adjOR (95%CI) 15.67 (3.03-80.99), p = 0.001) were independently associated with impaired HR-QoL. Twenty-nine percent (n = 26) scored below the normal range on the mental health component of the SF-36 and independent associations emerged for anxiety, depression, and self-reported numbness. Impairments in the physical health component of the SF-36 were reported by 12 (13%) patients and linked to hypogeusia and fatigue. CONCLUSION: Every third patient reported a reduction in HR-QoL 3 months after COVID-19 diagnosis and impairments were more prominent in mental than physical well-being.

Intracerebral Iron Accumulation may be Associated with Secondary Brain Injury in Patients with Poor Grade Subarachnoid Hemorrhage.

BACKGROUND: The amount of intracranial blood is a strong predictor of poor outcome after subarachnoid hemorrhage (SAH). Here, we aimed to measure iron concentrations in the cerebral white matter, using the cerebral microdialysis (CMD) technique, and to associate iron levels with the local metabolic profile, complications, and functional outcome. METHODS: For the observational cohort study, 36 patients with consecutive poor grade SAH (Hunt & Hess grade of 4 or 5, Glasgow Coma Scale Score ≤ 8) undergoing multimodal neuromonitoring were analyzed for brain metabolic changes, including CMD iron levels quantified by graphite furnace atomic absorption spectrometry. The study time encompassed 14 days after admission. Statistical analysis was performed using generalized estimating equations. RESULTS: Patients were admitted in a poor clinical grade (n = 26, 72%) or deteriorated within 24 h (n = 10, 28%). The median blood volume in the subarachnoid space was high (SAH sum score = 26, interquartile range 20-28). Initial CMD iron was 44 µg/L (25-65 µg/L), which significantly decreased to a level of 25 µg/L (14-30 µg/L) at day 4 and then constantly increased over the remaining neuromonitoring days (p < 0.01). A higher intraventricular hemorrhage sum score (≥ 5) was associated with higher CMD iron levels (Wald-statistic = 4.1, df = 1, p = 0.04) but not with the hemorrhage load in the subarachnoid space (p = 0.8). In patients developing vasospasm, the CMD iron load was higher, compared with patients without vasospasm (Wald-statistic = 4.1, degree of freedom = 1, p = 0.04), which was not true for delayed cerebral infarction (p = 0.4). Higher iron concentrations in the brain extracellular fluid (34 µg/L, 36-56 µg/L vs. 23 µg/L, 15-37 µg/L) were associated with mitochondrial dysfunction (CMD lactate to pyruvate ratio > 30 and CMD-pyruvate > 70 µM/L, p < 0.001). Brain extracellular iron load was not associated with functional outcome after 3 months (p > 0.5). CONCLUSIONS: This study suggests that iron accumulates in the cerebral white matter in patients with poor grade SAH. These findings may support trials aiming to scavenger brain extracellular iron based on the hypothesis that iron-mediated neurotoxicity may contribute to acute and secondary brain injury following SAH.

Anatomically Standardized Detection of MRI Atrophy Patterns in Early-Stage Alzheimer's Disease.

MRI studies have consistently identified atrophy patterns in Alzheimer's disease (AD) through a whole-brain voxel-based analysis, but efforts to investigate morphometric profiles using anatomically standardized and automated whole-brain ROI analyses, performed at the individual subject space, are still lacking. In this study we aimed (i) to utilize atlas-derived measurements of cortical thickness and subcortical volumes, including of the hippocampal subfields, to identify atrophy patterns in early-stage AD, and (ii) to compare cognitive profiles at baseline and during a one-year follow-up of those previously identified morphometric AD subtypes to predict disease progression. Through a prospectively recruited multi-center study, conducted at four Austrian sites, 120 patients were included with probable AD, a disease onset beyond 60 years and a clinical dementia rating of ≤1. Morphometric measures of T1-weighted images were obtained using FreeSurfer. A principal component and subsequent cluster analysis identified four morphometric subtypes, including (i) hippocampal predominant (30.8%), (ii) hippocampal-temporo-parietal (29.2%), (iii) parieto-temporal (hippocampal sparing, 20.8%) and (iv) hippocampal-temporal (19.2%) atrophy patterns that were associated with phenotypes differing predominately in the presentation and progression of verbal memory and visuospatial impairments. These morphologically distinct subtypes are based on standardized brain regions, which are anatomically defined and freely accessible so as to validate its diagnostic accuracy and enhance the prediction of disease progression.

Brain Structure and Degeneration Staging in Friedreich Ataxia: Magnetic Resonance Imaging Volumetrics from the ENIGMA-Ataxia Working Group.

OBJECTIVE: Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA. METHODS: A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole-brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls. RESULTS: The brainstem, dentate nucleus region, and superior and inferior cerebellar peduncles showed the greatest reductions in volume relative to controls (Cohen d = 1.5-2.6). Cerebellar gray matter alterations were most pronounced in lobules I-VI (d = 0.8), whereas cerebral differences occurred most prominently in precentral gyri (d = 0.6) and corticospinal tracts (d = 1.4). Earlier onset age predicted less volume in the motor cerebellum (rmax  = 0.35) and peduncles (rmax  = 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles (rmax  = -0.49); subgrouping showed these to be robust and early features of FRDA, and strong candidates for further biomarker validation. Cerebral white matter abnormalities, particularly in corticospinal pathways, emerge as intermediate disease features. Cerebellar and cerebral gray matter loss, principally targeting motor and sensory systems, preferentially manifests later in the disease course. INTERPRETATION: FRDA is defined by an evolving spatial profile of neuroanatomical changes beyond primary pathology in the cerebellum and spinal cord, in line with its progressive clinical course. The design, interpretation, and generalization of research studies and clinical trials must consider neuroanatomical staging and associated interindividual variability in brain measures. ANN NEUROL 2021;90:570-583.

Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging.

The advent of susceptibility-sensitive MRI techniques, such as susceptibility weighted imaging (SWI), has enabled accurate in vivo visualization and quantification of iron deposition within the human brain. Although previous approaches have been introduced to segment iron-rich brain regions, such as the substantia nigra, subthalamic nucleus, red nucleus, and dentate nucleus, these methods are largely unavailable and manual annotation remains the most used approach to label these regions. Furthermore, given their recent success in outperforming other segmentation approaches, convolutional neural networks (CNN) promise better performances. The aim of this study was thus to evaluate state-of-the-art CNN architectures for the labeling of deep brain nuclei from SW images. We implemented five CNN architectures and considered ensembles of these models. Furthermore, a multi-atlas segmentation model was included to provide a comparison not based on CNN. We evaluated two prediction strategies: individual prediction, where a model is trained independently for each region, and combined prediction, which simultaneously predicts multiple closely located regions. In the training dataset, all models performed with high accuracy with Dice coefficients ranging from 0.80 to 0.95. The regional SWI intensities and volumes from the models' labels were strongly correlated with those obtained from manual labels. Performances were reduced on the external dataset, but were higher or comparable to the intrarater reliability and most models achieved significantly better results compared to multi-atlas segmentation. CNNs can accurately capture the individual variability of deep brain nuclei and represent a highly useful tool for their segmentation from SW images.

Epileptic aphasia - A critical appraisal.

INTRODUCTION: Aphasic and other language disturbances occur in patients with epilepsy during and after epileptic seizures. Moreover, the interictal language profile in these patients is heterogeneous, varying from normal language profile to impairment in different language functions. The aim of this paper was to critically review the terms and concepts of ictal language alterations. MATERIAL AND METHOD: For this review we performed an extensive literature search on the term "epileptic aphasia" and analyzed the semiology and terminology indicating language-associated seizure symptoms. In addition, we give an overview on EEG, etiology, and brain imaging findings and ictal language disorders. RESULTS: In the literature, a plethora of terms indicates language-associated seizure symptoms. Simultaneous Video-EEG monitoring represents the gold standard to correctly classify ictal versus postictal language disturbances and to differentiate aphasic symptoms from speech automatisms. Different rhythmic and periodic EEG patterns associated with ictal language disturbances are recognized. Cerebral magnetic resonance imaging (cMRI) is essential in the diagnosis of seizures and epilepsy. Brain tumors and acute or remote cerebrovascular lesions are the most frequently reported structural etiologies underlying ictal language alterations. However, it has to be recognized that brain imaging may show alterations being the consequence of seizures itself rather than its cause. Functional brain imaging might be informative in patients with inconclusive EEG and MRI findings. Overall, seizure-associated aphasia is reported to have good lateralizing significance. CONCLUSION: Various language disturbances are caused by different types of seizures, epilepsies and underlying etiologies. In the clinical context, simultaneous Video-EEG monitoring facilitates precise classification of ictal versus postictal language alterations and differentiation of aphasic symptoms from speech automatisms.