Ex vivo and in vivo Evaluation of [18F]PR04.MZ in Rodents: A Selective Dopamine Transporter Imaging Agent

N‐4‐Fluorobut‐2‐yn‐1‐yl‐2β‐carbomethoxy‐3β‐phenyltropane (PR04.MZ) has been developed as dopamine transporter (DAT) ligand for molecular imaging. It contains a terminally fluorinated, conformationally constrained nitrogen substituent that is well suited for the introduction of fluorine‐18. The present report describes the pharmacological characterisation of [¹⁸F]PR04.MZ. The ligand shows an IC₅₀ value of 2 nM against human DAT, whereas the IC₅₀ value against human serotonin transporter and human noradrenalin transporter are lower (110 nM and 22 nM , respectively). Furthermore, its ex vivo organ distribution, its binding profile in the rat brain and reversibility of binding were examined. A μPET study illuminates a fast kinetic profile and specific binding to rat DAT.     

Locally adaptive Bayesian P-splines with a Normal-Exponential-Gamma prior

An implementation of locally adaptive penalized spline smoothing using a class of heavy-tailed shrinkage priors for the estimation of functional forms with highly varying curvature or discontinuities is presented. These priors utilize scale mixtures of normals with locally varying exponential-gamma distributed variances for the differences of the P-spline coefficients. A fully Bayesian hierarchical structure is derived with inference about the posterior being based on Markov Chain Monte Carlo techniques. Three increasingly flexible and automatic approaches are introduced to estimate the spatially varying structure of the variances. An extensive simulation study for Gaussian, Poisson, and Binomial responses shows that the performance of this approach on a number of benchmark functions is competitive to that of previous approaches. Results from applications with Gaussian and Poisson responses support the simulation results.     

Reconstruction of graphs based on random walks

The analysis of complex networks is of major interest in various fields of science. In many applications we face the challenge that the exact topology of a network is unknown but we are instead given information about distances within this network. The theoretical approaches to this problem have so far been focusing on the reconstruction of graphs from shortest path distance matrices. Often, however, movements in networks do not follow shortest paths but occur in a random fashion. In these cases an appropriate distance measure can be defined as the mean length of a random walk between two nodes — a quantity known as the mean first hitting time.In this contribution we investigate whether a graph can be reconstructed from its mean first hitting time matrix and put forward an algorithm for solving this problem. A heuristic method to reduce the computational effort is described and analyzed. In the case of trees we can even give an algorithm for reconstructing graphs from incomplete random walk distance matrices.     

Diesel exhaust particles modulate the tight junction protein occludin in lung cells in vitro

Background  

Using an in vitro triple cell co-culture model consisting of human epithelial cells (16HBE14o-), monocyte-derived macrophages and dendritic cells, it was recently demonstrated that macrophages and dendritic cells create a transepithelial network between the epithelial cells to capture antigens without disrupting the epithelial tightness. The expression of the different tight junction proteins in macrophages and dendritic cells, and the formation of tight junction-like structures with epithelial cells has been demonstrated. Immunofluorescent methods combined with laser scanning microscopy and quantitative real-time polymerase chain reaction were used to investigate if exposure to diesel exhaust particles (DEP) (0.5, 5, 50, 125 μg/ml), for 24 h, can modulate the expression of the tight junction mRNA/protein of occludin, in all three cell types.     

Biomechanical assessment of new hand-powered pruning shears

The aim of the study was to assess the biomechanical strains on the hand-wrist system during grapevine pruning with newly designed pruning shears. Surface electromyography of the finger flexor muscle and wrist postures were analyzed in four vineyard workers during actual work with the new and reference hand-powered pruning shears. Due to the large inter-individual differences in biomechanical data observed with both pruning shears, no systematic effect of the new pruning shears on "extreme" flexion/extension (F/E) and ulnar/radial (U/R) wrist deviations was demonstrated. However, the use of the new pruning shears was associated with a higher frequency of "neutral and moderate" U/R deviations (U/R < 20%(max)) and, to a lesser extent, of "neutral and moderate" F/E deviations (F/E < 20%(max)). Due to the small sample of workers, this result must be confirmed in a larger population of vineyard workers.     

Optimized in-phase and opposed-phase MR imaging for accurate detection of small fat or water fractions: theoretical considerations and experimental application in emulsions

Object  

To optimize strategies and measurement parameters for quantification of small fat and water fractions (<10%) in mixtures of both components by 4-point in-phase and opposed-phase gradient-echo imaging and to compare theoretical results with in-vitro experiments using emulsions.     

Automated reference-free detection of motion artifacts in magnetic resonance images

Objectives

Our objectives were to provide an automated method for spatially resolved detection and quantification of motion artifacts in MR images of the head and abdomen as well as a quality control of the trained architecture.

Materials and methods

T1-weighted MR images of the head and the upper abdomen were acquired in 16 healthy volunteers under rest and under motion. Images were divided into overlapping patches of different sizes achieving spatial separation. Using these patches as input data, a convolutional neural network (CNN) was trained to derive probability maps for the presence of motion artifacts. A deep visualization offers a human-interpretable quality control of the trained CNN. Results were visually assessed on probability maps and as classification accuracy on a per-patch, per-slice and per-volunteer basis.

Results

On visual assessment, a clear difference of probability maps was observed between data sets with and without motion. The overall accuracy of motion detection on a per-patch/per-volunteer basis reached 97%/100% in the head and 75%/100% in the abdomen, respectively.

Conclusion

Automated detection of motion artifacts in MRI is feasible with good accuracy in the head and abdomen. The proposed method provides quantification and localization of artifacts as well as a visualization of the learned content. It may be extended to other anatomic areas and used for quality assurance of MR images.

     

Comparison of T1-weighted 2D TSE, 3D SPGR,and two-point 3D Dixon MRI for automated segmentation of visceral adipose tissue at 3 Tesla

Objectives

To evaluate and compare conventional T1-weighted 2D turbo spin echo (TSE), T1-weighted 3D volumetric interpolated breath-hold examination (VIBE), and two-point 3D Dixon-VIBE sequences for automatic segmentation of visceral adipose tissue (VAT) volume at 3 Tesla by measuring and compensating for errors arising from intensity nonuniformity (INU) and partial volume effects (PVE).

Materials and methods

The body trunks of 28 volunteers with body mass index values ranging from 18 to 41.2 kg/m² (30.02 ± 6.63 kg/m²) were scanned at 3 Tesla using three imaging techniques. Automatic methods were applied to reduce INU and PVE and to segment VAT. The automatically segmented VAT volumes obtained from all acquisitions were then statistically and objectively evaluated against the manually segmented (reference) VAT volumes.

Results

Comparing the reference volumes with the VAT volumes automatically segmented over the uncorrected images showed that INU led to an average relative volume difference of ?59.22 ± 11.59, 2.21 ± 47.04, and ?43.05 ± 5.01 % for the TSE, VIBE, and Dixon images, respectively, while PVE led to average differences of ?34.85 ± 19.85, ?15.13 ± 11.04, and ?33.79 ± 20.38 %. After signal correction, differences of ?2.72 ± 6.60, 34.02 ± 36.99, and ?2.23 ± 7.58 % were obtained between the reference and the automatically segmented volumes. A paired-sample two-tailed t test revealed no significant difference between the reference and automatically segmented VAT volumes of the corrected TSE (p = 0.614) and Dixon (p = 0.969) images, but showed a significant VAT overestimation using the corrected VIBE images.

Conclusion

Under similar imaging conditions and spatial resolution, automatically segmented VAT volumes obtained from the corrected TSE and Dixon images agreed with each other and with the reference volumes. These results demonstrate the efficacy of the signal correction methods and the similar accuracy of TSE and Dixon imaging for automatic volumetry of VAT at 3 Tesla.