Ultra-high-resolution 3D imaging of atherosclerosis in mice with synchrotron differential phase contrast: a proof of concept study.

The goal of this study was to investigate the performance of 3D synchrotron differential phase contrast (DPC) imaging for the visualization of both macroscopic and microscopic aspects of atherosclerosis in the mouse vasculature ex vivo. The hearts and aortas of 2 atherosclerotic and 2 wild-type control mice were scanned with DPC imaging with an isotropic resolution of 15 μm. The coronary artery vessel walls were segmented in the DPC datasets to assess their thickness, and histological staining was performed at the level of atherosclerotic plaques. The DPC imaging allowed for the visualization of complex structures such as the coronary arteries and their branches, the thin fibrous cap of atherosclerotic plaques as well as the chordae tendineae. The coronary vessel wall thickness ranged from 37.4 ± 5.6 μm in proximal coronary arteries to 13.6 ± 3.3 μm in distal branches. No consistent differences in coronary vessel wall thickness were detected between the wild-type and atherosclerotic hearts in this proof-of-concept study, although the standard deviation in the atherosclerotic mice was higher in most segments, consistent with the observation of occasional focal vessel wall thickening. Overall, DPC imaging of the cardiovascular system of the mice allowed for a simultaneous detailed 3D morphological assessment of both large structures and microscopic details.

Fluid dynamics simulation of right ventricular outflow tract oversizing.

OBJECTIVES: Repair of the right ventricular outflow tract (RVOT) in paediatric cardiac surgery remains challenging due to the high reoperation rate. Intimal hyperplasia and consequent arteriosclerosis is one of the most important limitation factors for graft durability. Since local shear stress and pressure are predictive elements for intimal hyperplasia and wall degeneration, we sought to determine in an oversized 12-mm RVOT model, with computed fluid dynamics simulation, the local haemodynamical factors that may explain intimal hyperplasia. This was done with the aim of identifying the optimal degree of oversizing for a 12-mm native RVOT. METHODS: Twenty domestic pigs, with a weight of 24.6 ± 0.89 kg and a native RVOT diameter of 12 ± 1.7 mm, had valve conduits of 12, 16, 18 and 20 mm implanted. Pressure and flow were measured at 75, 100 and 125% of normal flow at RVOT at the pulmonary artery, pulmonary artery bifurcation and at the left and right pulmonary arteries. Three-dimensional computed fluid dynamics (CFD) simulation in all four geometries in all flow modalities was performed. Local shear stress and pressure conditions were investigated. RESULTS: Corresponding to 75, 100 and 125% of steady-state flow, three inlet velocity profiles were obtained, 0.2, 0.29 and 0.36 m/s, respectively. At inflow velocity profiles, low shear stress areas, ranged from 0 to 2 Pa, combined with high-pressure areas ranging from 11.5 to 12.1 mmHg that were found at distal anastomosis, at bifurcation and at the ostia of the left and right pulmonary arteries in all geometries. CONCLUSIONS: In all three oversized geometries, the local reparation of shear stress and pressure in the 16-mm model showed a similar local profile as in the native 12 mm RVOT. According to these findings, we suggest oversizing the natural 12-mm RVOT by not more than 4 mm. The elements responsible for wall degeneration and intimal hyperplasia remain very similar to the conditions present in native RVOT.

Single centre experience of the application of self navigated 3D whole heart cardiovascular magnetic resonance for the assessment of cardiac anatomy in congenital heart disease.

BACKGROUND: For free-breathing cardiovascular magnetic resonance (CMR), the self-navigation technique recently emerged, which is expected to deliver high-quality data with a high success rate. The purpose of this study was to test the hypothesis that self-navigated 3D-CMR enables the reliable assessment of cardiovascular anatomy in patients with congenital heart disease (CHD) and to define factors that affect image quality. METHODS: CHD patients ≥2 years-old and referred for CMR for initial assessment or for a follow-up study were included to undergo a free-breathing self-navigated 3D CMR at 1.5T. Performance criteria were: correct description of cardiac segmental anatomy, overall image quality, coronary artery visibility, and reproducibility of great vessels diameter measurements. Factors associated with insufficient image quality were identified using multivariate logistic regression. RESULTS: Self-navigated CMR was performed in 105 patients (55% male, 23 ± 12y). Correct segmental description was achieved in 93% and 96% for observer 1 and 2, respectively. Diagnostic quality was obtained in 90% of examinations, and it increased to 94% if contrast-enhanced. Left anterior descending, circumflex, and right coronary arteries were visualized in 93%, 87% and 98%, respectively. Younger age, higher heart rate, lower ejection fraction, and lack of contrast medium were independently associated with reduced image quality. However, a similar rate of diagnostic image quality was obtained in children and adults. CONCLUSION: In patients with CHD, self-navigated free-breathing CMR provides high-resolution 3D visualization of the heart and great vessels with excellent robustness.

The effect of learning on the evolution of new courtship behavior: a simulation model

The fact that individuals learn can change the relationship between genotype and phenotype in the population, and thus affect the evolutionary response to selection. Here we ask how male ability to learn from female response affects the evolution of a novel male behavioral courtship trait under pre-existing female preference (sensory drive). We assume a courtship trait which has both a genetic and a learned component, and a two-level female response to males. With individual-based simulations we show that, under this scenario, learning generally increases the strength of selection on the genetic component of the courtship trait, at least when the population genetic mean is still low. As a consequence, learning not only accelerates the evolution of the courtship trait, but also enables it when the trait is costly, which in the absence of learning results in an adaptive valley. Furthermore, learning can enable the evolution of the novel trait in the face of gene flow mediated by immigration of males that show superior attractiveness to females based on another, non-heritable trait. However, rather than increasing monotonically with the speed of learning, the effect of learning on evolution is maximized at intermediate learning rates. This model shows that, at least under some scenarios, the ability to learn can drive the evolution of mating behaviors through a process equivalent to Waddington's genetic assimilation.

Uncertainty associated with Monte Carlo radiation transport in radionuclide metrology

In radionuclide metrology, Monte Carlo (MC) simulation is widely used to compute parameters associated with primary measurements or calibration factors. Although MC methods are used to estimate uncertainties, the uncertainty associated with radiation transport in MC calculations is usually difficult to estimate. Counting statistics is the most obvious component of MC uncertainty and has to be checked carefully, particularly when variance reduction is used. However, in most cases fluctuations associated with counting statistics can be reduced using sufficient computing power. Cross-section data have intrinsic uncertainties that induce correlations when apparently independent codes are compared. Their effect on the uncertainty of the estimated parameter is difficult to determine and varies widely from case to case. Finally, the most significant uncertainty component for radionuclide applications is usually that associated with the detector geometry. Recent 2D and 3D x-ray imaging tools may be utilized, but comparison with experimental data as well as adjustments of parameters are usually inevitable.

An Advocacy for the Use of 3D Stem Cell Culture Systems for the Development of Regenerative Medicine: An Emphasis on Photoreceptor Generation

The availability of stem cells is of great promise to study early developmental stages and to generate adequate cells for cell transfer therapies. Although many researchers using stem cells were successful in dissecting intrinsic and extrinsic mechanisms and in generating specific cell phenotypes, few of the stem cells or the differentiated cells show the capacity to repair a tissue. Advances in cell and stem cell cultivation during the last years made tremendous progress in the generation of bona fide differentiated cells able to integrate into a tissue after transplantation, opening new perspectives for developmental biology studies and for regenerative medicine. In this review, we focus on the main works attempting to create in vitro conditions mimicking the natural environment of CNS structures such as the neural tube and its development in different brain region areas including the optic cup. The use of protocols growing cells in 3D organoids is a key strategy to produce cells resembling endogenous ones. An emphasis on the generation of retina tissue and photoreceptor cells is provided to highlight the promising developments in this field. Other examples are presented and discussed, such as the formation of cortical tissue, the epithelial gut or the kidney organoids. The generation of differentiated tissues and well-defined cell phenotypes from embryonic stem (ES) cells or induced pluripotent cells (iPSCs) opens several new strategies in the field of biology and regenerative medicine. A 3D organ/tissue development in vitro derived from human cells brings a unique tool to study human cell biology and pathophysiology of an organ or a specific cell population. The perspective of tissue repair is discussed as well as the necessity of cell banking to accelerate the progress of this promising field.

Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

Connectivity analysis on diffusion MRI data of the whole- brain suffers from distortions caused by the standard echo- planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a âeurooetheoretically correctâeuro and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.

How to report multiple outcome metrics in virtual reality simulation

Background Virtual reality (VR) simulation is increasingly used in surgical disciplines. Since VR simulators measure multiple outcomes, standardized reporting is needed. Methods We present an algorithm for combining multiple VR outcomes into dimension summary measures, which are then integrated into a meaningful total score. We reanalyzed the data of two VR studies applying the algorithm. Results The proposed algorithm was successfully applied to both VR studies. Conclusions The algorithm contributes to standardized and transparent reporting in VR-related research.