Combined CG-HDG Method for Elliptic Problems: Performance Model

We combine continuous and discontinuous Galerkin methods in the setting of a model diffusion problem. Starting from a hybrid discontinuous formulation, we replace element interiors by more general subsets of the computational domain - groups of elements that support a piecewise-polynomial continuous expansion. This step allows us to identify a~new weak formulation of Dirichlet boundary condition in the continuous framework. We examine the expected performance of a Galerkin solver that would use continuous Galerkin method with weak Dirichlet boundary conditions in each mesh partition and connect partitions weakly using trace variable as in HDG method

On weak Dirichlet boundary conditions for elliptic problems in the continuous Galerkin method

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.We combine continuous and discontinuous Galerkin methods in the setting of a model diffusion problem. Starting from a hybrid discontinuous formulation, we replace element interiors by more general subsets of the computational domain – groups of elements that support a piecewisepolynomial continuous expansion. This step allows us to identify a new weak formulation of Dirichlet boundary condition in the continuous framework. We show that the boundary condition leads to a stable discretization with a single parameter insensitive to mesh size and polynomial order of the expansion. The robustness of the approach is demonstrated on several numerical examples.European Union Horizon 2020US National Science Foundatio

Modulatory effects of levodopa on cerebellar connectivity in Parkinson’s disease

Levodopa has been the mainstay of symptomatic therapy for Parkinson’s disease (PD) for the last five decades. However, it is associated with the development of motor fluctuations and dyskinesia, in particular after several years of treatment. The aim of this study was to shed light on the acute brain functional reorganization in response to a single levodopa dose. Functional magnetic resonance imaging (fMRI) was performed after an overnight withdrawal of dopaminergic treatment and 1 h after a single dose of 250 mg levodopa in a group of 24 PD patients. Eigenvector centrality was calculated in both treatment states using resting-state fMRI. This offers a new data-driven and parameter-free approach, similar to Google’s PageRank algorithm, revealing brain connectivity alterations due to the effect of levodopa treatment. In all PD patients, levodopa treatment led to an improvement of clinical symptoms as measured with the Unified Parkinson’s Disease Rating Scale motor score (UPDRS-III). This therapeutic effect was accompanied with a major connectivity increase between cerebellar brain regions and subcortical areas of the motor system such as the thalamus, putamen, globus pallidus, and brainstem. The degree of interconnectedness of cerebellar regions correlated with the improvement of clinical symptoms due to the administration of levodopa. We observed significant functional cerebellar connectivity reorganization immediately after a single levodopa dose in PD patients. Enhanced general connectivity (eigenvector centrality) was associated with better motor performance as assessed by UPDRS-III score. This underlines the importance of considering cerebellar networks as therapeutic targets in PD

Different brain areas require different analysis models: fMRI observations in Parkinson’s disease

Foreseeing how specific brain areas respond in time to a stimulus can be a prerequisite for a successfully conceived fMRI experiment. We demonstrate that in medicated Parkinson’s disease patients, putamen's activation peaks around the onset of tapping but does not persist throughout the tapping block, whereas sustained activation is observed in the motor cortex. Consequently, in the widely used tapping paradigm “On vs. Off L-DOPA”, the drug effect remains undetected if statistical analysis apply a block design instead of an event-related one. Ignoring this information can lead to fallacious conclusions which suggests using different models to investigate different brain regions

Improving brain imaging in Parkinson's disease by accounting for simultaneous motor output

Parkinson's disease leads to a variety of movement impairments. While studying the disease with fMRI, the main motivation for the research becomes one of its major obstacles: the motor output is unpredictable. Therefore it is troublesome to access, inside the scanner, performances of motor tasks and reliably relate them to brain measurements. We proposed to overcome this by expanding the patients’ number and restricting statistical criteria from a previous study which used a glove with non-magnetic sensors during scanning. Our results revealed basal ganglia not observed in the previous study confirming the usefulness of the device in fMRI studies

Does higher gadolinium concentration play a role in the morphologic assessment of brain tumors? Results of a multicenter intraindividual crossover comparison of gadobutrol versus gadobenate dimeglumine (the MERIT Study).

BACKGROUND AND PURPOSE: Gadobenate dimeglumine has proved advantageous compared with other gadolinium-based contrast agents for contrast-enhanced brain MR imaging. Gadobutrol is a more highly concentrated agent (1.0 mol/L). This study intraindividually compared 0.1-mmol/kg doses of these agents for qualitative and quantitative evaluation of brain tumors. MATERIALS AND METHODS: Adult patients with suspected or known brain tumors underwent 2 identical MR imaging examinations at 1.5T, 1 with gadobenate dimeglumine and the other with gadobutrol, both at a dose of 0.1-mmol/kg body weight. The agents were injected in randomized order separated by 3–14 days. Imaging sequences and acquisition timing were identical for the 2 examinations. Three blinded readers evaluated images qualitatively for diagnostic information (lesion extent, delineation, morphology, enhancement, global preference) and quantitatively for CNR and LBR. RESULTS: One hundred fourteen of 123 enrolled patients successfully underwent both examinations. Final diagnoses were intra-axial tumors, metastases, extra-axial tumors, "other" tumors, and "nontumor" (49, 46, 8, 7, and 4 subjects, respectively). Readers 1, 2, and 3 demonstrated preference for gadobenate dimeglumine in 46 (40.7%), 54 (47.4%), and 49 (43.0%) patients, respectively, compared with 6, 7, and 7 patients for gadobutrol ( P < .0001, all readers). Highly significant ( P < .0001, all readers) preference for gadobenate dimeglumine was demonstrated for all other qualitative end points. Inter-reader agreement was good for all evaluations (κ = 0.414–0.629). Significantly superior CNR and LBR were determined for gadobenate dimeglumine ( P < .019, all readers). CONCLUSIONS: Significantly greater morphologic information and lesion enhancement are achieved on brain MR imaging with 0.1-mmol/kg gadobenate dimeglumine compared with gadobutrol at an equivalent dose. CNR : contrast-to-noise ratio GBCA : gadolinium-based contrast agent GRE : gradient-recalled echo LBR : lesion-to-background ratio NSF : nephrogenic systemic fibrosis SE : spin-echo SI : signal intensit

Improving fMRI in Parkinson's disease by accounting for realistic motor output

In Parkinson's disease (PD), the motor loop functioning and the patients’ motor output are unpredictable, due to brain compensatory mechanisms initiated up to decades before diagnosis. Consequently, the accuracy of motor tasks during fMRI is impeded, and deviations of the movement performance affect results. Kinematic modeling based on simultaneous measurements with MR-compatible gloves has been previously proposed as means to address this problem and outperform conventional boxcar modeling (Standard). Here, we adopted this approach in a larger cohort along with conservative statistics employing family-wise error (FWE) correction at the voxel level (p< 0.05) to be less prone to produce false positives