Model-based super-resolution reconstruction for pseudo-continuous Arterial Spin Labeling.

Arterial spin labeling (ASL) is a promising, non-invasive perfusion magnetic resonance imaging technique for quantifying cerebral blood flow (CBF). Unfortunately, ASL suffers from an inherently low signal-to-noise ratio (SNR) and spatial resolution, undermining its potential. Increasing spatial resolution without significantly sacrificing SNR or scan time represents a critical challenge towards routine clinical use. In this work, we propose a model-based super-resolution reconstruction (SRR) method with joint motion estimation that breaks the traditional SNR/resolution/scan-time trade-off. From a set of differently oriented 2D multi-slice pseudo-continuous ASL images with a low through-plane resolution, 3D-isotropic, high resolution, quantitative CBF maps are estimated using a Bayesian approach. Experiments on both synthetic whole brain phantom data, and on in vivo brain data, show that the proposed SRR Bayesian estimation framework outperforms state-of-the-art ASL quantification.

Super-Resolution Reconstruction of Multi-Slice T2-W FLAIR MRI Improves Multiple Sclerosis Lesion Segmentation.

Due to acquisition time constraints, T2-w FLAIR MRI of Multiple Sclerosis (MS) patients is often acquired with multi-slice 2D protocols with a low through-plane resolution rather than with high-resolution 3D protocols. Automated lesion segmentation on such low-resolution (LR) images, however, performs poorly and leads to inaccurate lesion volume estimates. Super-resolution reconstruction (SRR) methods can then be used to obtain a high-resolution (HR) image from multiple LR images to serve as input for lesion segmentation. In this work, we evaluate the effect on MS lesion segmentation of three SRR approaches: one based on interpolation, a state-of-the-art self-supervised CNN-based strategy, and a recently proposed model-based SRR method. These SRR strategies were applied to LR acquisitions simulated from 3D T2-w FLAIR MRI of MS patients. Each SRR method was evaluated in terms of image reconstruction quality and subsequent lesion segmentation performance. When compared to segmentation on LR images, the three considered SRR strategies demonstrate improved lesion segmentation. Furthermore, in some scenarios, SRR achieves a similar segmentation performance compared to segmentation of HR images.Clinical relevance- This study demonstrates the positive impact of super-resolution reconstruction from T2-w FLAIR multi-slice MRI acquisitions on segmentation performance of MS lesions.

The effect of pH and nitrite on the haem pocket of GLB-33, a globin-coupled neuronal transmembrane receptor of Caenorhabditis elegans.

Out of the 34 globins in Caenorhabditis elegans, GLB-33 is a putative globin-coupled transmembrane receptor with a yet unknown function. The globin domain (GD) contains a particularly hydrophobic haem pocket, that rapidly oxidizes to a low-spin hydroxide-ligated haem state at physiological pH. Moreover, the GD has one of the fastest nitrite reductase activity ever reported for globins. Here, we use a combination of electronic circular dichroism, resonance Raman and electron paramagnetic resonance (EPR) spectroscopy with mass spectrometry to study the pH dependence of the ferric form of the recombinantly over-expressed GD in the presence and absence of nitrite. The competitive binding of nitrite and hydroxide is examined as well as nitrite-induced haem modifications at acidic pH. Comparison of the spectroscopic results with data from other haem proteins allows to deduce the important effect of Arg at position E10 in stabilization of exogenous ligands. Furthermore, continuous-wave and pulsed EPR indicate that ligation of nitrite occurs in a nitrito mode at pH 5.0 and above. At pH 4.0, an additional formation of a nitro-bound haem form is observed along with fast formation of a nitri-globin.

To shift or to rotate? Comparison of acquisition strategies for multi-slice super-resolution magnetic resonance imaging.

Multi-slice (MS) super-resolution reconstruction (SRR) methods have been proposed to improve the trade-off between resolution, signal-to-noise ratio and scan time in magnetic resonance imaging. MS-SRR consists in the estimation of an isotropic high-resolution image from a series of anisotropic MS images with a low through-plane resolution, where the anisotropic low-resolution images can be acquired according to different acquisition schemes. However, it is yet unclear how these schemes compare in terms of statistical performance criteria, especially for regularized MS-SRR. In this work, the estimation performance of two commonly adopted MS-SRR acquisition schemes based on shifted and rotated MS images respectively are evaluated in a Bayesian framework. The maximum a posteriori estimator, which introduces regularization by incorporating prior knowledge in a statistically well-defined way, is put forward as the estimator of choice and its accuracy, precision, and Bayesian mean squared error (BMSE) are used as performance criteria. Analytic calculations as well as Monte Carlo simulation experiments show that the rotated scheme outperforms the shifted scheme in terms of precision, accuracy, and BMSE. Furthermore, the superior performance of the rotated scheme is confirmed in real data experiments and in retrospective simulation experiments with and without inter-image motion. Results show that the rotated scheme allows regularized MS-SRR with a higher accuracy and precision than the shifted scheme, besides being more resilient to motion.

Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping.

Quantitative Magnetic Resonance (MR) imaging provides reproducible measurements of biophysical parameters, and has become an essential tool in clinical MR studies. Unfortunately, 3D isotropic high resolution (HR) parameter mapping is hardly feasible in clinical practice due to prohibitively long acquisition times. Moreover, accurate and precise estimation of quantitative parameters is complicated by inevitable subject motion, the risk of which increases with scanning time. In this paper, we present a model-based super-resolution reconstruction (SRR) method that jointly estimates HR quantitative parameter maps and inter-image motion parameters from a set of 2D multi-slice contrast-weighted images with a low through-plane resolution. The method uses a Bayesian approach, which allows to optimally exploit prior knowledge of the tissue and noise statistics. To demonstrate its potential, the proposed SRR method is evaluated for a T1 and T2 quantitative mapping protocol. Furthermore, the method's performance in terms of precision, accuracy, and spatial resolution is evaluated using simulated as well as real brain imaging experiments. Results show that our proposed fully flexible, quantitative SRR framework with integrated motion estimation outperforms state-of-the-art SRR methods for quantitative MRI.

EPR and DFT analysis of biologically relevant chromium(V) complexes with d-glucitol and d-glucose.

1,2-diolato ligands, such as carbohydrates and glycoproteins, tend to stabilize chromium(V), thus forming important intermediates that have been implicated in the genotoxicity of Cr(VI). Since many years, room-temperature continuous-wave electron paramagnetic resonance (EPR) at X-band microwave frequencies has been used as a standard characterization tool to study chromium(V) intermediates formed during the reduction of Cr(VI) in the presence of biomolecules. In this work, the added value is tested of using a combination of pulsed and high-field EPR techniques with density functional theory computations to unravel the nature of Cr(V) complexes with biologically relevant chelators, such as carbohydrates. The study focuses on the oxidochromium(V) complexes formed during reduction of potassium dichromate with glutathione in the presence of the monosaccharide d-glucose or the polyalcohol d-glucitol. It is shown that although the presence of a multitude of Cr(V) intermediates may hamper a complete structural determination, the combined EPR and DFT approach reveals unambiguously the effect of freezing on the location of the counterions, the gradual replacement of water ligands by the diols, and the preference of Cr(V) to bind certain conformers.