The purpose of this study was to evaluate temporal stability, multi‐center reproducibility and the influence of covariates on a multimodal MR protocol for quantitative muscle imaging and to ...facilitate its use as a standardized protocol for evaluation of pathology in skeletal muscle.
Quantitative T2, quantitative diffusion and four‐point Dixon acquisitions of the calf muscles of both legs were repeated within one hour. Sixty‐five healthy volunteers (31 females) were included in one of eight 3‐T MR systems. Five traveling subjects were examined in six MR scanners. Average values over all slices of water‐T2 relaxation time, proton density fat fraction (PDFF) and diffusion metrics were determined for seven muscles. Temporal stability was tested with repeated measured ANOVA and two‐way random intraclass correlation coefficient (ICC). Multi‐center reproducibility of traveling volunteers was assessed by a two‐way mixed ICC. The factors age, body mass index, gender and muscle were tested for covariance.
ICCs of temporal stability were between 0.963 and 0.999 for all parameters. Water‐T2 relaxation decreased significantly (P < 10−3) within one hour by ~ 1 ms. Multi‐center reproducibility showed ICCs within 0.879–0.917 with the lowest ICC for mean diffusivity. Different muscles showed the highest covariance, explaining 20–40% of variance for observed parameters.
Standardized acquisition and processing of quantitative muscle MRI data resulted in high comparability among centers. The imaging protocol exhibited high temporal stability over one hour except for water T2 relaxation times. These results show that data pooling is feasible and enables assembling data from patients with neuromuscular diseases, paving the way towards larger studies of rare muscle disorders.
Quantitative MR images from calf muscles were evaluated from eight different scanners and a traveling cohort. Standardized acquisition protocols and processing methods allow for highly reproducible quantitative (water‐T2, Dixon proton density fat fraction and DTI parameters) descriptions of muscle status. The temporal order of scans plays a key role when assessing T2 relaxation times. Data from different centers (but the same vendor with identical acquisition and processing) could be pooled in one database when the same scanning protocol is used.
The Transfer of Global and Local Processing Modes De Luca, Alberto; Verschoor, Stephan; Hommel, Bernhard
Journal of experimental psychology. Human perception and performance,
10/2022, Volume:
48, Issue:
10
Journal Article
Peer reviewed
Open access
Förster and Dannenberg's (2010) GLOMOsys theory claims that people process perceived events and internal information in a more global or more local processing mode and that adopted modes should ...transfer to other, unrelated tasks. If so, global/local processing modes would qualify as metacontrol states that are assumed to regulate processing dilemmas, like persistence/flexibility, exploitation/exploration, or speed/accuracy (Goschke, 2000). Given increasing rates of nonreplications of previously demonstrated far transfer from prime tasks that are likely to induce a particular global or local processing bias to logically and temporally unrelated probe tasks, we tested whether near and far transfer can be demonstrated under conditions that should be optimal for such transfer. We reduced the temporal distance between prime and probe trials by integrating them into a dual-task paradigm and used probe tasks that were either almost identical to the prime task or at least shared the relevant modality and attentional demands. We obtained significant transfer effects between almost identical visual global/local tasks, irrespective of the degree of cognitive conflict that these tasks generated, but did not find any evidence for somewhat farer transfer to other visual tasks, like a flanker task and an attentional blink task. That is, any substantial change in the probe task's characteristics compared with the prime task eliminated almost any signs of transfer. Altogether, we conclude that either global/local processing modes as envisioned by GLOMOsys do not exist or they normally do not transfer from global/local tasks to other, unrelated tasks.
Public Significance Statement
Our study tested whether focusing on global or local aspects of visual stimuli establishes a general information-processing mode that might also affect processing in other, unrelated tasks. We thus constructed experimental designs in which participants carried out two tasks in a row, with the first having them focus on either the global or the local aspects of visual stimuli. This affected information processing in the second task if this task was very similar to the first, but not if it differed. We conclude that either focusing on global or local aspects does not establish a general information-processing mode or this mode does not transfer to sufficiently dissimilar other tasks.
Gradient nonlinearities in magnetic resonance imaging (MRI) cause spatially varying mismatches between the imposed and the effective gradients and can cause significant biases in rotationally ...invariant diffusion MRI measures derived from, for example, diffusion tensor imaging. The estimation of the orientational organization of fibrous tissue, which is nowadays frequently performed with spherical deconvolution techniques ideally using higher diffusion weightings, can likewise be biased by gradient nonlinearities. We explore the sensitivity of two established spherical deconvolution approaches to gradient nonlinearities, namely constrained spherical deconvolution (CSD) and damped Richardson‐Lucy (dRL). Additionally, we propose an extension of dRL to take into account gradient imperfections, without the need of data interpolation. Simulations show that using the effective b‐matrix can improve dRL fiber orientation estimation and reduces angular deviations, while CSD can be more robust to gradient nonlinearity depending on the implementation. Angular errors depend on a complex interplay of many factors, including the direction and magnitude of gradient deviations, underlying microstructure, SNR, anisotropy of the effective response function, and diffusion weighting. Notably, angular deviations can also be observed at lower b‐values in contrast to the perhaps common assumption that only high b‐value data are affected. In in vivo Human Connectome Project data and acquisitions from an ultrastrong gradient (300 mT/m) scanner, angular differences are observed between applying and not applying the effective gradients in dRL estimation. As even small angular differences can lead to error propagation during tractography and as such impact connectivity analyses, incorporating gradient deviations into the estimation of fiber orientations should make such analyses more reliable.
Gradient nonlinearities cause spatially varying mismatches between the imposed and the effective gradients in diffusion magnetic resonance imaging. We explore the sensitivity of spherical deconvolution approaches, including constrained spherical deconvolution and damped Richardson‐Lucy (dRL), to gradient nonlinearity artifacts. Additionally, we propose an extension of the dRL method to take into account gradient imperfections without the need of data interpolation. As even small angular differences can lead to error propagation during fiber tractography, incorporating gradient deviations into the estimation of the fiber orientation distributions should make such analyses more reliable.
•We introduce a novel framework to perform spherical deconvolution with multiple anisotropic response functions (mFOD).•We show that the proposed framework can be used to improve the FOD estimation ...in the cortical gray matter.•Fiber tractography performed with mFOD reaches the cortical GM with more coverage and contiguity than with previous methods.•The proposed framework is a first step towards GM to GM fiber tractography.
In diffusion MRI, spherical deconvolution approaches can estimate local white matter (WM) fiber orientation distributions (FOD) which can be used to produce fiber tractography reconstructions. The applicability of spherical deconvolution to gray matter (GM), however, is still limited, despite its critical role as start/endpoint of WM fiber pathways. The advent of multi-shell diffusion MRI data offers additional contrast to model the GM signal but, to date, only isotropic models have been applied to GM. Evidence from both histology and high-resolution diffusion MRI studies suggests a marked anisotropic character of the diffusion process in GM, which could be exploited to improve the description of the cortical organization. In this study, we investigated whether performing spherical deconvolution with tissue specific models of both WM and GM can improve the characterization of the latter while retaining state-of-the-art performances in WM. To this end, we developed a framework able to simultaneously accommodate multiple anisotropic response functions to estimate multiple, tissue-specific, fiber orientation distributions (mFODs). As proof of principle, we used the diffusion kurtosis imaging model to represent the WM signal, and the neurite orientation dispersion and density imaging (NODDI) model to represent the GM signal. The feasibility of the proposed approach is shown with numerical simulations and with data from the Human Connectome Project (HCP). The performance of our method is compared to the current state of the art, multi-shell constrained spherical deconvolution (MSCSD). The simulations show that with our new method we can accurately estimate a mixture of two FODs at SNR≥50. With HCP data, the proposed method was able to reconstruct both tangentially and radially oriented FODs in GM, and performed comparably well to MSCSD in computing FODs in WM. When performing fiber tractography, the trajectories reconstructed with mFODs reached the cortex with more spatial continuity and for a longer distance as compared to MSCSD and allowed to reconstruct short trajectories tangential to the cortical folding. In conclusion, we demonstrated that our proposed method allows to perform spherical deconvolution of multiple anisotropic response functions, specifically improving the performances of spherical deconvolution in GM tissue.
Cerebral Amyloid Angiopathy (CAA) is characterized by cerebrovascular amyloid-β accumulation leading to hallmark cortical MRI markers, such as vascular reactivity, but white matter is also affected. ...By studying the relationship in different disease stages of Dutch-type CAA (D-CAA), we tested the relation between vascular reactivity and microstructural white matter integrity loss. In a cross-sectional study in D-CAA, 3 T MRI was performed with Blood-Oxygen-Level-Dependent (BOLD) fMRI upon visual activation to assess vascular reactivity and diffusion tensor imaging to assess microstructural white matter integrity through Peak Width of Skeletonized Mean Diffusivity (PSMD). We assessed the relationship between BOLD parameters – amplitude, time-to-peak (TTP), and time-to-baseline (TTB) – and PSMD, with linear and quadratic regression modeling. In total, 25 participants were included (15/10 pre-symptomatic/symptomatic; mean age 36/59 y). A lowered BOLD amplitude (unstandardized β = 0.64, 95%CI 0.10, 1.18, p = 0.02, Adjusted R2 = 0.48), was quadratically associated with increased PSMD levels. A delayed BOLD response, with prolonged TTP (β = 8.34 × 10−6, 95%CI 1.84 × 10−6, 1.48 × 10−5, p = 0.02, Adj. R2 = 0.25) and TTB (β = 6.57 × 10−6, 95%CI 1.92 × 10−6, 1.12 × 10−5, p = 0.008, Adj. R2 = 0.29), was linearly associated with increased PSMD. In D-CAA subjects, predominantly in the symptomatic stage, impaired cerebrovascular reactivity is related to microstructural white matter integrity loss. Future longitudinal studies are needed to investigate whether this relation is causal.
Background
The immunological pathophysiologies of chronic inflammatory demyelinating polyneuropathy (CIDP) and multifocal motor neuropathy (MMN) differ considerably, but neither has been elucidated ...completely. Quantitative magnetic resonance imaging (MRI) techniques such as diffusion tensor imaging, T2 mapping, and fat fraction analysis may indicate in vivo pathophysiological changes in nerve architecture. Our study aimed to systematically study nerve architecture of the brachial plexus in patients with CIDP, MMN, motor neuron disease (MND) and healthy controls using these quantitative MRI techniques.
Methods
We enrolled patients with CIDP (n = 47), MMN (n = 29), MND (n = 40) and healthy controls (n = 10). All patients underwent MRI of the brachial plexus and we obtained diffusion parameters, T2 relaxation times and fat fraction using an automated processing pipeline. We compared these parameters between groups using a univariate general linear model.
Results
Fractional anisotropy was lower in patients with CIDP compared to healthy controls (p < 0.001), patients with MND (p = 0.010) and MMN (p < 0.001). Radial diffusivity was higher in patients with CIDP compared to healthy controls (p = 0.015) and patients with MND (p = 0.001) and MMN (p < 0.001). T2 relaxation time was elevated in patients with CIDP compared to patients with MND (p = 0.023). Fat fraction was lower in patients with CIDP and MMN compared to patients with MND (both p < 0.001).
Conclusion
Our results show that quantitative MRI parameters differ between CIDP, MMN and MND, which may reflect differences in underlying pathophysiological mechanisms.
With this study, we show that quantitative MRI techniques reveal differences in the brachial plexus between patients with CIDP, MMN, MND and healthy controls. CIDP is characterized by lower FA and higher RD than MMN, MND and healthy controls, whilst MMN is characterized by higher FA values than CIDP and MND. These differences between CIDP and MMN are the most remarkable and important finding as they emphasize important differences in the underlying pathophysiologies.
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