Cerebellar Volumetry in Ataxias: Relation to Ataxia Severity and Duration

Cerebellar atrophy is the neuropathological hallmark of most ataxias. Hence, quantifying the volume of the cerebellar grey and white matter is of great interest. In this study, we aim to identify volume differences in the cerebellum between spinocerebellar ataxia type 1 (SCA1), SCA3 and SCA6 as well as multiple system atrophy of cerebellar type (MSA-C). Our cross-sectional data set comprised mutation carriers of SCA1 (N=12), SCA3 (N=62), SCA6 (N=14), as well as MSA-C patients (N=16). Cerebellar volumes were obtained from T1-weighted magnetic resonance images. To compare the different atrophy patterns, we performed a z-transformation and plotted the intercept of each patient group's model at the mean of 7 years of ataxia duration as well as at the mean ataxia severity of 14 points in the SARA sum score. In addition, we plotted the extrapolation at ataxia duration of 0 years as well as 0 points in the SARA sum score. Patients with MSA-C demonstrated the most pronounced volume loss, particularly in the cerebellar white matter, at the late time intercept. Patients with SCA6 showed a pronounced volume loss in cerebellar grey matter with increasing ataxia severity compared to all other patient groups. MSA-C, SCA1 and SCA3 showed a prominent atrophy of the cerebellar white matter. Our results (i) confirmed SCA6 being considered as a pure cerebellar grey matter disease, (ii) emphasise the involvement of cerebellar white matter in the neuropathology of SCA1, SCA3 and MSA-C, and (iii) reflect the rapid clinical progression in MSA-C

Across‐vendor standardization of semi‐LASER for single‐voxel MRS at 3T

The semi‐adiabatic localization by adiabatic selective refocusing (sLASER) sequence provides single‐shot full intensity signal with clean localization and minimal chemical shift displacement error and was recommended by the international MRS Consensus Group as the preferred localization sequence at high‐ and ultra‐high fields. Across‐vendor standardization of the sLASER sequence at 3 tesla has been challenging due to the B1 requirements of the adiabatic inversion pulses and maximum B1 limitations on some platforms. The aims of this study were to design a short‐echo sLASER sequence that can be executed within a B1 limit of 15 μT by taking advantage of gradient‐modulated RF pulses, to implement it on three major platforms and to evaluate the between‐vendor reproducibility of its perfomance with phantoms and in vivo. In addition, voxel‐based first and second order B0 shimming and voxel‐based B1 adjustments of RF pulses were implemented on all platforms. Amongst the gradient‐modulated pulses considered (GOIA, FOCI and BASSI), GOIA‐WURST was identified as the optimal refocusing pulse that provides good voxel selection within a maximum B1 of 15 μT based on localization efficiency, contamination error and ripple artifacts of the inversion profile. An sLASER sequence (30 ms echo time) that incorporates VAPOR water suppression and 3D outer volume suppression was implemented with identical parameters (RF pulse type and duration, spoiler gradients and inter‐pulse delays) on GE, Philips and Siemens and generated identical spectra on the GE ‘Braino’ phantom between vendors. High‐quality spectra were consistently obtained in multiple regions (cerebellar white matter, hippocampus, pons, posterior cingulate cortex and putamen) in the human brain across vendors (5 subjects scanned per vendor per region; mean signal‐to‐noise ratio [less than] 33; mean water linewidth between 6.5 Hz to 11.4 Hz). The harmonized sLASER protocol is expected to produce high reproducibility of MRS across sites thereby allowing large multi‐site studies with clinical cohorts

Nonuniform Cardiac Denervation Observed by 11C-meta-Hydroxyephedrine PET in 6-OHDA-Treated Monkeys

Parkinson's disease presents nonmotor complications such as autonomic dysfunction that do not respond to traditional anti-parkinsonian therapies. The lack of established preclinical monkey models of Parkinson's disease with cardiac dysfunction hampers development and testing of new treatments to alleviate or prevent this feature. This study aimed to assess the feasibility of developing a model of cardiac dysautonomia in nonhuman primates and preclinical evaluations tools. Five rhesus monkeys received intravenous injections of 6-hydroxydopamine (total dose: 50 mg/kg). The animals were evaluated before and after with a battery of tests, including positron emission tomography with the norepinephrine analog 11C-meta-hydroxyephedrine. Imaging 1 week after neurotoxin treatment revealed nearly complete loss of specific radioligand uptake. Partial progressive recovery of cardiac uptake found between 1 and 10 weeks remained stable between 10 and 14 weeks. In all five animals, examination of the pattern of uptake (using Logan plot analysis to create distribution volume maps) revealed a persistent region-specific significant loss in the inferior wall of the left ventricle at 10 (P<0.001) and 14 weeks (P<0.01) relative to the anterior wall. Blood levels of dopamine, norepinephrine (P<0.05), epinephrine, and 3,4-dihydroxyphenylacetic acid (P<0.01) were notably decreased after 6-hydroxydopamine at all time points. These results demonstrate that systemic injection of 6-hydroxydopamine in nonhuman primates creates a nonuniform but reproducible pattern of cardiac denervation as well as a persistent loss of circulating catecholamines, supporting the use of this method to further develop a monkey model of cardiac dysautonomia

Image_1_Assessment of Cerebral and Cerebellar White Matter Microstructure in Spinocerebellar Ataxias 1, 2, 3, and 6 Using Diffusion MRI.JPEG

Development of imaging biomarkers for rare neurodegenerative diseases such as spinocerebellar ataxia (SCA) is important to non-invasively track progression of disease pathology and monitor response to interventions. Diffusion MRI (dMRI) has been shown to identify cross-sectional degeneration of white matter (WM) microstructure and connectivity between healthy controls and patients with SCAs, using various analysis methods. In this paper, we present dMRI data in SCAs type 1, 2, 3, and 6 and matched controls, including longitudinal acquisitions at 12–24-month intervals in a subset of the cohort, with up to 5 visits. The SCA1 cohort also contained 3 premanifest patients at baseline, with 2 showing ataxia symptoms at the time of the follow-up scans. We focused on two aspects: first, multimodal evaluation of the dMRI data in a cross-sectional approach, and second, longitudinal trends in dMRI data in SCAs. Three different pipelines were used to perform cross-sectional analyses in WM: region of interest (ROI), tract-based spatial statistics (TBSS), and fixel-based analysis (FBA). We further analyzed longitudinal changes in dMRI metrics throughout the brain using ROI-based analysis. Both ROI and TBSS analyses identified higher mean (MD), axial (AD), and radial (RD) diffusivity and lower fractional anisotropy (FA) in the cerebellum for all SCAs compared to controls, as well as some cerebral alterations in SCA1, 2, and 3. FBA showed lower fiber density (FD) and fiber crossing (FC) regions similar to those identified by ROI and TBSS analyses. FBA also highlighted corticospinal tract (CST) abnormalities, which was not detected by the other two pipelines. Longitudinal ROI-based analysis showed significant increase in AD in the middle cerebellar peduncle (MCP) for patients with SCA1, suggesting that the MCP may be a good candidate region to monitor disease progression. The patient who remained symptom-free throughout the study displayed no microstructural abnormalities. On the other hand, the two patients who were at the premanifest stage at baseline, and showed ataxia symptoms in their follow-up visits, displayed AD values in the MCP that were already in the range of symptomatic patients with SCA1 at their baseline visit, demonstrating that microstructural abnormalities are detectable prior to the onset of ataxia.</p

Table_1_Assessment of Cerebral and Cerebellar White Matter Microstructure in Spinocerebellar Ataxias 1, 2, 3, and 6 Using Diffusion MRI.XLSX

Development of imaging biomarkers for rare neurodegenerative diseases such as spinocerebellar ataxia (SCA) is important to non-invasively track progression of disease pathology and monitor response to interventions. Diffusion MRI (dMRI) has been shown to identify cross-sectional degeneration of white matter (WM) microstructure and connectivity between healthy controls and patients with SCAs, using various analysis methods. In this paper, we present dMRI data in SCAs type 1, 2, 3, and 6 and matched controls, including longitudinal acquisitions at 12–24-month intervals in a subset of the cohort, with up to 5 visits. The SCA1 cohort also contained 3 premanifest patients at baseline, with 2 showing ataxia symptoms at the time of the follow-up scans. We focused on two aspects: first, multimodal evaluation of the dMRI data in a cross-sectional approach, and second, longitudinal trends in dMRI data in SCAs. Three different pipelines were used to perform cross-sectional analyses in WM: region of interest (ROI), tract-based spatial statistics (TBSS), and fixel-based analysis (FBA). We further analyzed longitudinal changes in dMRI metrics throughout the brain using ROI-based analysis. Both ROI and TBSS analyses identified higher mean (MD), axial (AD), and radial (RD) diffusivity and lower fractional anisotropy (FA) in the cerebellum for all SCAs compared to controls, as well as some cerebral alterations in SCA1, 2, and 3. FBA showed lower fiber density (FD) and fiber crossing (FC) regions similar to those identified by ROI and TBSS analyses. FBA also highlighted corticospinal tract (CST) abnormalities, which was not detected by the other two pipelines. Longitudinal ROI-based analysis showed significant increase in AD in the middle cerebellar peduncle (MCP) for patients with SCA1, suggesting that the MCP may be a good candidate region to monitor disease progression. The patient who remained symptom-free throughout the study displayed no microstructural abnormalities. On the other hand, the two patients who were at the premanifest stage at baseline, and showed ataxia symptoms in their follow-up visits, displayed AD values in the MCP that were already in the range of symptomatic patients with SCA1 at their baseline visit, demonstrating that microstructural abnormalities are detectable prior to the onset of ataxia.</p

CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation

Quantifying the volume of the cerebellum and its lobes is of profound interest in various neurodegenerative and acquired diseases. Especially for the most common spinocerebellar ataxias (SCA), for which the first antisense oligonculeotide-base gene silencing trial has recently started, there is an urgent need for quantitative, sensitive imaging markers at pre-symptomatic stages for stratification and treatment assessment. This work introduces CerebNet, a fully automated, extensively validated, deep learning method for the lobular segmentation of the cerebellum, including the separation of gray and white matter. For training, validation, and testing, T1-weighted images from 30 participants were manually annotated into cerebellar lobules and vermal sub-segments, as well as cerebellar white matter. CerebNet combines FastSurferCNN, a UNet-based 2.5D segmentation network, with extensive data augmentation, e.g. realistic non-linear deformations to increase the anatomical variety, eliminating additional preprocessing steps, such as spatial normalization or bias field correction. CerebNet demonstrates a high accuracy (on average 0.87 Dice and 1.742mm Robust Hausdorff Distance across all structures) outperforming state-of-the-art approaches. Furthermore, it shows high test-retest reliability (average ICC >0.97 on OASIS and Kirby) as well as high sensitivity to disease effects, including the pre-ataxic stage of spinocerebellar ataxia type 3 (SCA3). CerebNet is compatible with FreeSurfer and FastSurfer and can analyze a 3D volume within seconds on a consumer GPU in an end-to-end fashion, thus providing an efficient and validated solution for assessing cerebellum sub-structure volumes. We make CerebNet available as source-code (https://github.com/Deep-MI/FastSurfer)