Synthetic MRI demonstrates prolonged regional relaxation times in the brain of preterm born neonates with severe postnatal morbidity

Background: To identify preterm infants at risk for neurodevelopment impairment that might benefit from early neurorehabilitation, early prognostic biomarkers of future outcomes are needed. Objective: To determine whether synthetic MRI is sensitive to age-related changes in regional tissue relaxation times in the brain of preterm born neonates when scanned at term equivalent age (TEA, 37–42 weeks), and to investigate whether severe postnatal morbidity results in prolonged regional tissue relaxation times. Materials and methods: This retrospective study included 70 very preterm born infants scanned with conventional and synthetic MRI between January 2017 and June 2019 at TEA. Infants with severe postnatal morbidity were allocated to a high-risk group (n = 22). All other neonates were allocated to a low-risk group (n = 48). Linear regression analysis was performed to determine the relationship between relaxation times and postmenstrual age (PMA) at scan. Analysis of covariance was used to evaluate the impact of severe postnatal morbidity in the high-risk group on T1 and T2 relaxation times. Receiver operating characteristic (ROC) curves were plotted and analysed with area under the ROC curve (AUC) to evaluate the accuracy of classifying high-risk patients based on regional relaxation times. Results: A linear age-related decrease of T1 and T2 relaxation times correlating with PMA at scan (between 37 and 42 weeks) was found in the deep gray matter, the cerebellum, the cortex, and the posterior limb of the internal capsule (PLIC) (p < .005 each), but not in the global, frontal, parietal, or central white matter. Analysis of covariance for both risk groups, adjusted for PMA, revealed significantly prolonged regional tissue relaxation times in neonates with severe postnatal morbidity, which was best illustrated in the central white matter of the centrum semiovale (T1 Δ = 11.5%, T2 Δ = 13.4%, p < .001) and in the PLIC (T1 Δ = 9.2%, T2 Δ = 6.9%, p < .001). The relaxation times in the PLIC and the central white matter predicted high-risk status with excellent accuracy (AUC range 0.82–0.86). Conclusion: Synthetic MRI-based relaxometry in the brain of preterm born neonates is sensitive to age-related maturational changes close to TEA. Severe postnatal morbidity correlated with a significant delay in tissue relaxation. Synthetic MRI may provide early prognostic biomarkers for neurodevelopment impairment

Expression of the chemokine receptor CCR5 in psoriasis and results of a randomized placebo controlled trial with a CCR5 inhibitor

Several reports have indicated that the chemokine receptor CCR5 and its ligands, especially CCL5 (formerly known as RANTES), may play a role in the pathogenesis of psoriasis. The purpose of this investigation was to examine the expression of CCR5 and its ligands in chronic plaque psoriasis and to evaluate the clinical and immunohistochemical effect of a CCR5 receptor inhibitor. Immunohistochemical analysis showed low but significant increased total numbers of CCR5 positive cells in epidermis and dermis of lesional skin in comparison to non-lesional skin. However, relative expression of CCR5 proportional to the cells observed revealed that the difference between lesional and non-lesional skin was only statistically significant in the epidermis for CD3 positive cells and in the dermis for CD68 positive cells. Quantification of mRNA by reverse transcriptase-polymerase chain reaction only showed an increased expression of CCL5 (RANTES) in lesional skin. A randomized placebo-controlled clinical trial in 32 psoriasis patients revealed no significant clinical effect and no changes at the immunohistochemical level comparing patients treated with placebo or a CCR5 inhibitor SCH351125. We conclude that although CCR5 expression is increased in psoriatic lesions, this receptor does not play a crucial role in the pathogenesis of psoriasis

Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI

Today, many MRI reconstruction techniques exist for undersampled MRI data. Regularization-based techniques inspired by compressed sensing allow for the reconstruction of undersampled data that would lead to an ill-posed reconstruction problem. Parallel imaging enables the reconstruction of MRI images from undersampled multi-coil data that leads to a well-posed reconstruction problem. Autocalibrating pMRI techniques encompass pMRI techniques where no explicit knowledge of the coil sensivities is required. A first purpose of this paper is to derive a novel autocalibration approach for pMRI that allows for the estimation and use of smooth, but high-bandwidth coil profiles instead of a compactly supported kernel. These high-bandwidth models adhere more accurately to the physics of an antenna system. The second purpose of this paper is to demonstrate the feasibility of a parameter-free reconstruction algorithm that combines autocalibrating pMRI and compressed sensing. Therefore, we present several techniques for automatic parameter estimation in MRI reconstruction. Experiments show that a higher reconstruction accuracy can be had using high-bandwidth coil models and that the automatic parameter choices yield an acceptable result

Automatic high-bandwidth calibration and reconstruction of arbitrarily sampled parallel MRI.

Today, many MRI reconstruction techniques exist for undersampled MRI data. Regularization-based techniques inspired by compressed sensing allow for the reconstruction of undersampled data that would lead to an ill-posed reconstruction problem. Parallel imaging enables the reconstruction of MRI images from undersampled multi-coil data that leads to a well-posed reconstruction problem. Autocalibrating pMRI techniques encompass pMRI techniques where no explicit knowledge of the coil sensivities is required. A first purpose of this paper is to derive a novel autocalibration approach for pMRI that allows for the estimation and use of smooth, but high-bandwidth coil profiles instead of a compactly supported kernel. These high-bandwidth models adhere more accurately to the physics of an antenna system. The second purpose of this paper is to demonstrate the feasibility of a parameter-free reconstruction algorithm that combines autocalibrating pMRI and compressed sensing. Therefore, we present several techniques for automatic parameter estimation in MRI reconstruction. Experiments show that a higher reconstruction accuracy can be had using high-bandwidth coil models and that the automatic parameter choices yield an acceptable result

Optimization of compressed sensing/RARE combining acquisition schemes

C

Accelerating in vivo fast spin echo high angular resolution diffusion imaging with an isotropic resolution in mice through compressed sensing

Purpose Echo planar imaging (EPI) is commonly used to acquire the many volumes needed for high angular resolution diffusion Imaging (HARDI), posing a higher risk for artifacts, such as distortion and deformation. An alternative to EPI is fast spin echo (FSE) imaging, which has fewer artifacts but is inherently slower. The aim is to accelerate FSE such that a HARDI data set can be acquired in a time comparable to EPI using compressed sensing. Methods Compressed sensing was applied in either q-space or simultaneously in k-space and q-space, by undersampling the k-space in the phase-encoding direction or retrospectively eliminating diffusion directions for different degrees of undersampling. To test the replicability of the acquisition and reconstruction, brain data were acquired from six mice, and a numerical phantom experiment was performed. All HARDI data were analyzed individually using constrained spherical deconvolution, and the apparent fiber density and complexity metric were evaluated, together with whole-brain tractography. Results The apparent fiber density and complexity metric showed relatively minor differences when only q-space undersampling was used, but deteriorate when k-space undersampling was applied. Likewise, the tract density weighted image showed good results when only q-space undersampling was applied using 15 directions or more, but information was lost when fewer volumes or k-space undersampling were used. Conclusion It was found that acquiring 15 to 20 diffusion directions with a full k-space and reconstructed using compressed sensing could suffice for a replicable measurement of quantitative measures in mice, where areas near the sinuses and ear cavities are untainted by signal loss

Magnetization transfer contrast imaging detects early white matter changes in the APP/PS1 amyloidosis mouse model

While no definitive cure for Alzheimer's disease exists yet, currently available treatments would benefit greatly from an earlier diagnosis. It has previously been shown that Magnetization transfer contrast (MTC) imaging is able to detect amyloid β plaques in old APP/PS1 mice. In the current study we investigated if MTC is also able to visualize early amyloid β (Aβ) induced pathological changes. In a cross-sectional study, a comparison was made between the MT ratio of wild type (WT) and APP/PS1 mice at 2, 4, 6, 8 and 24 months of age. We observed an increased MT-ratio in the cortex of 24 month old APP/PS1 mice as compared to WT mice. However, when comparing the MT-ratio of the cortex of WT mice with the MT-ratio of the APP/PS1 mice at 2, 4, 6 or 8 months of age, no significant changes could be observed. In contrast to the cortex, we consistently observed a decreased MT-ratio in the splenium of 4, 6 and 8 month old APP/PS1 mice as compared to age-matched WT mice. Lastly, the decreased MT-ratio in the splenium of APP/PS1 mice correlated to the Aβ plaque deposition, astrogliosis and microgliosis. This MT-ratio decrease did however not correlate to the myelin content. Combined, our results suggest that MTC is able to visualize early Aβ-induced changes in the splenium but not the cortex of APP/PS1 mice