The potential of x-ray virtual histology in the diagnosis of skin tumors.

BACKGROUND: Histopathological analysis represents the gold standard in clinical practice for diagnosing skin neoplasms. While the current diagnostic workflow has specialized in producing robust and accurate results, interpreting tissue architecture and malignant cellular morphology correctly remains one of the greatest challenges for pathologists. This paper aims to explore the prospect of applying x-ray virtual histology to human skin tumor excisions and correlating it with the histological validation. MATERIALS AND METHODS: Seven skin biopsies containing intriguing melanoma types and pigmented skin lesions were scanned using x-ray Computed micro-Tomography (µCT) and then sectioned for conventional histology assessment. RESULTS: The tissue microarchitecture reconstructed by µCT offers detailed insights into diagnosing the malignancy or benignity of the skin lesions. Three-dimensional reconstruction via x-ray virtual histology reveals infiltrative patterns in basal cell carcinoma and evaluated invasiveness in melanoma. The technology enables the identification of pagetoid distributions of neoplastic cells and the assessment of melanoma depth in three dimensions. CONCLUSION: Although the proposed approach is not intended to replace conventional histology, the non-destructive nature of the sample and the clarity provided by virtual inspection demonstrate the promising impact of µCT as a valid support method prior to conventional histological sectioning. Indeed, µCT images can suggest the optimal sectioning position before using a microtome, as is commonly performed in histological practice. Moreover, the three-dimensional nature of the proposed approach paves the way for a more accurate assessment of significant prognostic factors in melanoma, such as Breslow thickness, by considering the whole micro-volume rather than a two-dimensional observation.

Exploring deep learning models for 4D-STEM-DPC data processing.

For the study of magnetic materials at the nanoscale, differential phase contrast (DPC) imaging is a potent tool. With the advancements in direct detector technology, and consequent popularity gain for four-dimensional scanning transmission electron microscopy (4D-STEM), there has been an ongoing development of new and enhanced ways for STEM-DPC big data processing. Conventional algorithms are experimentally tailored, and so in this article we explore how supervised learning with convolutional neural networks (CNN) can be utilized for automated and consistent processing of STEM-DPC data. Two different approaches are investigated, one with direct tracking of the beam with regression analysis, and one where a modified U-net is used for direct beam segmentation as a pre-processing step. The CNNs are trained on experimentally obtained 4D-STEM data, enabling them to effectively handle data collected under similar instrument acquisition parameters. The model outputs are compared to conventional algorithms, particularly in how they process data in the presence of strong diffraction contrast, and how they affect domain wall profiles and width measurement.

An updated approach to the evaluation of the urinary sediment.

Examination of the urinary sediment (U-sed) is an important non-invasive, rapid, and inexpensive tool for the diagnosis and surveillance over time of renal diseases. In this Educational Review, we describe first how to collect, prepare, and examine urine samples in order to obtain reliable results. Then, we describe the U-sed findings in isolated microscopic hematuria, glomerular diseases, acute interstitial nephritis, acute kidney injury, reactivation of the BK virus in kidney transplant recipients, and crystalluric genetic diseases.

The influence of post-processing software on quantitative results in 4D flow cardiovascular magnetic resonance examinations.

Background: Several commercially available software packages exist for the analysis of three-dimensional cine phase-contrast cardiovascular magnetic resonance (CMR) with three-directional velocity encoding (four-dimensional (4D) flow CMR). Only sparse data are available on the impact of these different software solutions on quantitative results. We compared two different commercially available and widely used software packages and their impact on the forward flow volume (FFV), peak velocity (PV), and maximum wall shear stress (WSS) per plane. Materials and methods: 4D flow CMR datasets acquired by 3 Tesla magnetic resonance imaging of 10 healthy volunteers, 13 aortic stenosis patients, and 7 aortic valve replacement patients were retrospectively analyzed for FFV, PV, and WSS using two software packages in six analysis planes along the thoracic aorta. Absolute (AD) and relative differences (RD), intraclass correlation coefficients (ICC), Bland-Altman analysis, and Spearman's correlation analysis were calculated. Results: For the FFV and PV in healthy volunteers, there was good to excellent agreement between both software packages [FFV: ICC = 0.93-0.97, AD: 0.1 ± 5.4 ml (-2.3 ± 2.4 ml), RD: -0.3 ± 8% (-5.7 ± 6.0%); PV: ICC = 0.81-0.99, AD: -0.02 ± 0.02 ml (-0.1 ± 0.1 ml), RD: -1.6 ± 2.1% (-9.3 ± 6.1%)]. In patients, the FFV showed good to excellent agreement [ICC: 0.75-0.91, AD: -1.8 ± 6.5 ml (-8.3 ± 9.9 ml), RD: -2.2 ± 9.2% (-13.8 ± 17.4%)]. In the ascending aorta, PV showed only poor to moderate agreement in patients (plane 2 ICC: 0.33, plane 3 ICC: 0.72), whereas the rest of the thoracic aorta revealed good to excellent agreement [ICC: 0.95-0.98, AD: -0.03 ± 0.07 (-0.1 ± 0.1 m/s), RD: -3.5 ± 7.9% (-7.8 ± 9.9%)]. WSS analysis showed no to poor agreement between both software packages. Global correlation analyses revealed good to very good correlation between FFV and PV and only poor correlation for WSS. Conclusions: There was good to very good agreement for the FFV and PV except for the ascending aorta in patients when comparing PV and no agreement for WSS. Standardization is therefore necessary.

Denoising of dual-VENC PC-MRI with large high/low VENC ratios.

PURPOSE: Dual velocity encoding PC-MRI can produce spurious artifacts when using high ratios of velocity encoding values (VENCs), limiting its ability to generate high-quality images across a wide range of encoding velocities. This study aims to propose and compare dual-VENC correction methods for such artifacts. THEORY AND METHODS: Two denoising approaches based on spatiotemporal regularization are proposed and compared with a state-of-the-art method based on sign correction. Accuracy is assessed using simulated data from an aorta and brain aneurysm, as well as 8 two-dimensional (2D) PC-MRI ascending aorta datasets. Two temporal resolutions (30,60) ms and noise levels (9,12) dB are considered, with noise added to the complex magnetization. The error is evaluated with respect to the noise-free measurement in the synthetic case and to the unwrapped image without additional noise in the volunteer datasets. RESULTS: In all studied cases, the proposed methods are more accurate than the Sign Correction technique. Using simulated 2D+T data from the aorta (60 ms, 9 dB), the Dual-VENC (DV) error 0 . 82 ± 0 . 07 $$ 0.82\pm 0.07 $$ is reduced to: 0 . 66 ± 0 . 04 $$ 0.66\pm 0.04 $$ (Sign Correction); 0 . 34 ± 0 . 04 $$ 0.34\pm 0.04 $$ and 0 . 32 ± 0 . 04 $$ 0.32\pm 0.04 $$ (proposed techniques). The methods are found to be significantly different (p-value < 0 . 05 $$ <0.05 $$ ). Importantly, brain aneurysm data revealed that the Sign Correction method is not suitable, as it increases error when the flow is not unidirectional. All three methods improve the accuracy of in vivo data. CONCLUSION: The newly proposed methods outperform the Sign Correction method in improving dual-VENC PC-MRI images. Among them, the approach based on temporal differences has shown the highest accuracy.

Intracranial aneurysm stiffness assessment using 4D Flow MRI.

BACKGROUND: Although arterial stiffness is known as a biomarker for cardiovascular events and stroke, there is limited information in the literature regarding the stiffness of intracranial aneurysms. In this study, we aim to assess the stiffness of intracranial aneurysms using 4D Flow MRI. METHODS: A total of 27 aneurysms in 25 patients with internal carotid artery aneurysms were included in this study. Using 4D Flow MRI, we measured the arterial pulse wave form during a cardiac cycle at planes proximal and distal to the target aneurysm. The damping of these waveforms through the aneurysm was defined as the aneurysm damping index (ADI) and compared to the contralateral side. We also investigated the clinical factors related to the ADI. RESULTS: ADI assessment was successful in all cases. The average ADI was 1.18±0.28, which was significantly larger than 1.0 (P = 0.0027 [t-test]). The ADI on the aneurysm side was larger than on the contralateral side (1.19±0.30 vs 1.05±0.17, P = 0.029 [t-test]). On multivariate analysis, the use of beta-blockers (ß=0.46, P = 0.015) and smoking history (ß=-0.22, P = 0.024) showed a significant correlation with ADI. CONCLUSION: We have proposed a novel method to observe arterial pulse wave dumping through intracranial aneurysm using 4D Flow MRI. The damping can be quantitatively observed, and the ADI has correlations with clinical factors such as antihypertensive drugs and smoking. Further studies should focus more on evaluating aneurysm stiffness and its clinical applications.

Quantitative microbiology with widefield microscopy: navigating optical artefacts for accurate interpretations.

Time-resolved live-cell imaging using widefield microscopy is instrumental in quantitative microbiology research. It allows researchers to track and measure the size, shape, and content of individual microbial cells over time. However, the small size of microbial cells poses a significant challenge in interpreting image data, as their dimensions approache that of the microscope's depth of field, and they begin to experience significant diffraction effects. As a result, 2D widefield images of microbial cells contain projected 3D information, blurred by the 3D point spread function. In this study, we employed simulations and targeted experiments to investigate the impact of diffraction and projection on our ability to quantify the size and content of microbial cells from 2D microscopic images. This study points to some new and often unconsidered artefacts resulting from the interplay of projection and diffraction effects, within the context of quantitative microbiology. These artefacts introduce substantial errors and biases in size, fluorescence quantification, and even single-molecule counting, making the elimination of these errors a complex task. Awareness of these artefacts is crucial for designing strategies to accurately interpret micrographs of microbes. To address this, we present new experimental designs and machine learning-based analysis methods that account for these effects, resulting in accurate quantification of microbiological processes.

Ortho-positronium lifetime for soft-tissue classification.

The objective of this work is to showcase the ortho-positronium lifetime as a probe for soft-tissue characterization. We employed positron annihilation lifetime spectroscopy to experimentally measure the three components of the positron annihilation lifetime-para-positronium (p-Ps), positron, and ortho-positronium (o-Ps)-for three types of porcine, non-fixated soft tissues ex vivo: adipose, hepatic, and muscle. Then, we benchmarked our measurements with X-ray phase-contrast imaging, which is the current state-of-the-art for soft-tissue analysis. We found that the o-Ps lifetime in adipose tissues (2.54 ± 0.12 ns) was approximately 20% longer than in hepatic (2.04 ± 0.09 ns) and muscle (2.03 ± 0.12 ns) tissues. In addition, the separation between the measurements for adipose tissue and the other tissues was better from o-Ps lifetime measurement than from X-ray phase-contrast imaging. This experimental study proved that the o-Ps lifetime is a viable non-invasive probe for characterizing and classifying the different soft tissues. Specifically, o-Ps lifetime as a soft-tissue characterization probe had a strong sensitivity to the lipid content that can be potentially implemented in commercial positron emission tomography scanners that feature list-mode data acquisition.

A hybrid simulation method towards the gamma ray phase contrast imaging for metallic material.

A high efficiency simulation method for propagation-based phase-contrast imaging, called directional macro-wavefront (DMWF), is developed with the aim of simulating high-energy phase-contrast imaging. This method takes both Monte Carlo and wave optical propagation into consideration. Traditional wave-optics-based simulation methods for phase-contrast imaging encounter unacceptable computational complexity when high-energy radiation is used. In contrast, this method effectively addresses this issue by using macro-wavefront integration. Several simulation examples using typical parameters of inverse Compton scattering sources are presented to illustrate the excellent energy adaptability and efficiency of the DMWF method. This method provides a more efficient approach for phase-contrast imaging simulations, which will drive the advancement of high-energy phase-contrast imaging.

Computational modeling of left ventricular flow using PC-CMR-derived four-dimensional wall motion.

Intracardiac hemodynamics plays a crucial role in the onset and development of cardiac and valvular diseases. Simulations of blood flow in the left ventricle (LV) have provided valuable insight into assessing LV hemodynamics. While fully coupled fluid-solid modelings of the LV remain challenging due to the complex passive-active behavior of the LV wall myocardium, the integration of imaging-driven quantification of structural motion with computational fluid dynamics (CFD) modeling in the LV holds the promise of feasible and clinically translatable characterization of patient-specific LV hemodynamics. In this study, we propose to integrate two magnetic resonance imaging (MRI) modalities with the moving-boundary CFD method to characterize intracardiac LV hemodynamics. Our method uses the standard cine cardiac magnetic resonance (CMR) images to estimate four-dimensional myocardial motion, eliminating the need for involved myocardial material modeling to capture LV wall behavior. In conjunction with CMR, phase contrast-MRI (PC-MRI) was used to measure temporal blood inflow rates at the mitral orifice, serving as an additional boundary condition. Flow patterns, including velocity streamlines, vortex rings, and kinetic energy, were characterized and compared to the available data. Moreover, relationships between LV wall kinematic markers and flow characteristics were determined without myocardial material modeling and using a non-rigid image registration (NRIR) method. The fidelity of the simulation was quantitatively evaluated by validating the flow rate at the aortic outflow tract against respective PC-MRI measures. The proposed methodology offers a novel and feasible toolset that works with standard PC-CMR protocols to improve the clinical assessment of LV characteristics in prognostic studies and surgical planning.

bSSFP Phase Contrast (PC-SSFP) at 0.55T Applied to Aortic Flow.

BACKGROUND: There is a growing interest in the development and application of mid-field (0.55T) for cardiac MR, including flow imaging. However, aortic flow imaging at 0.55T has limited SNR, especially in diastolic phases where there is reduced inflow-driven contrast for spoiled gradient echo (GRE) sequences. The low SNR can limit the accuracy of flow and regurgitant fraction measurements. METHODS: In this work, we developed a 2D phase contrast (PC) acquisition with balanced steady state free precession (bSSFP), termed PC-SSFP, for flow imaging and quantification at 0.55T. This PC-SSFP approach precisely nulls the 0th and 1st gradient moments at both the TE and TR, except for the flow-encoded acquisition, for which the 1st gradient moment at the TE is determined by the VENC. Our proposed sequence was tested in both phantoms and in healthy volunteers (n=11), to measure aortic flow. In volunteers, both a breath-hold and a free-breathing protocol, with averaging to increase SNR, were obtained. Total flow, peak flow, cardiac output and SNR were compared for PC-SSFP and PC-GRE. Stroke volumes were also measured and compared to planimetry method. RESULTS: In a phantom, SNR was significantly higher using PC-SSFP compared to PC-GRE (25.5±9.6 vs 8.2±2.9), and the velocity measurements agreed well (R = 1.00). In healthy subjects, for both breath-hold (bh) and free-breathing (fb) protocols, PC-SSFP measured accurate peak flow (fb: R = 0.99, bh: R = 0.96) and cardiac output (fb: R = 0.98, bh: R = 0.88), compared to PC-GRE, accurate stroke volume (fb: R = 0.94, bh: R = 0.97), compared to planimetry measurement, and offered constant high SNR (fb: 28±9 vs 18±6, bh: 24±7 vs 11±3) over the cardiac cycle in 11 subjects. CONCLUSION: PC-SSFP is a more reliable evaluation tool for aortic flow quantification, when compared to the conventional PC-GRE method at 0.55T, providing higher SNR, and thus potentially more accurate flows.

Assessment of neurofluid dynamics in relation to clinical improvement after tap-test: pilot study.

PURPOSE: Idiopathic Normal pressure hydrocephalus (iNPH) is an under-diagnosed in elderly patients but none of the diagnostic tests are currently sufficiently sensitive or specific. The objective of this study was to analyze the dynamics of neurofluids by PC-MRI in relation to clinical evolution as measured using the iNPH grading scale after tap-test. METHOD: We prospectively included patients with suspected iNPH. All these patients underwent PCMRI to assess craniospinal hemohydrodynamics with analysis of the stroke volume of the cephalospinal fluid (CSF) within the Sylvius' aqueduct, within the high cervical subarachnoid spaces and the arteriovenous stroke volume. By this means, we calculated a compliance index. Morphological analysis was carried out using the DESH score. The infusion test was measuring the resistance to CSF flow. We analysed all these parameters according to the clinical improvement of the patients. RESULTS: 23 patients were included. Compliance index assessed by PC-MRI was significantly higher in the group of patients with improvement > 10% (p = 0.015). CONCLUSIONS: Our study highlights the importance of investigating arteriovenous and CSF interactions in iNPH. This involves understanding the physiological and pathophysiological mechanisms related to the circulation of neurofluids. The analysis of the interactions of these neurofluids allows for a comprehensive understanding of the system.

4D flow MRI velocity uncertainty quantification.

PURPOSE: An automatic method is presented for estimating 4D flow MRI velocity measurement uncertainty in each voxel. The velocity distance (VD) metric, a statistical distance between the measured velocity and local error distribution, is introduced as a novel measure of 4D flow MRI velocity measurement quality. METHODS: The method uses mass conservation to assess the local velocity error variance and the standardized difference of means (SDM) velocity to estimate the velocity error correlations. VD is evaluated as the Mahalanobis distance between the local velocity measurement and the local error distribution. The uncertainty model is validated synthetically and tested in vitro under different flow resolutions and noise levels. The VD's application is demonstrated on two in vivo thoracic vasculature 4D flow datasets. RESULTS: Synthetic results show the proposed uncertainty quantification method is sensitive to aliased regions across various velocity-to-noise ratios and assesses velocity error correlations in four- and six-point acquisitions with correlation errors at or under 3.2%. In vitro results demonstrate the method's sensitivity to spatial resolution, venc settings, partial volume effects, and phase wrapping error sources. Applying VD to assess in vivo 4D flow MRI in the aorta demonstrates the expected increase in measured velocity quality with contrast administration and systolic flow. CONCLUSION: The proposed 4D flow MRI uncertainty quantification method assesses velocity measurement error owing to sources including noise, intravoxel phase dispersion, and velocity aliasing. This method enables rigorous comparison of 4D flow MRI datasets obtained in longitudinal studies, across patient populations, and with different MRI systems.

An Eulerian formulation for the computational modeling of phase-contrast MRI.

PURPOSE: Computational simulation of phase-contrast MRI (PC-MRI) is an attractive way to physically interpret properties and errors in MRI-reconstructed flow velocity fields. Recent studies have developed PC-MRI simulators that solve the Bloch equation, with the magnetization transport being modeled using a Lagrangian approach. Because this method expresses the magnetization as spatial distribution of particles, influences of particle densities and their spatial uniformities on numerical accuracy are well known. This study developed an alternative method for PC-MRI modeling using an Eulerian approach in which the magnetization is expressed as a spatially smooth continuous function. METHODS: The magnetization motion was described using the Bloch equation with an advection term and computed on a fixed grid using a finite difference method, and k-space sampling was implemented using the spoiled gradient echo sequence. PC-MRI scans of a fully developed flow in straight and stenosed cylinders were acquired to provide numerical examples. RESULTS: Reconstructed flow in a straight cylinder showed excellent agreement with input velocity profiles and mean errors were less than 0.5% of the maximum velocity. Numerical cases of flow in a stenosed cylinder successfully demonstrated the velocity profiles, with displacement artifacts being dependent on scan parameters and intravoxel dephasing due to flow disturbances. These results were in good agreement with those obtained using the Lagrangian approach with a sufficient particle density. CONCLUSION: The feasibility of the Eulerian approach to PC-MRI modeling was successfully demonstrated.

Ultra-fast Digital DPC Yielding High Spatio-temporal Resolution for Low-Dose Phase Characterization.

In the scanning transmission electron microscope, both phase imaging of beam-sensitive materials and characterization of a material's functional properties using in situ experiments are becoming more widely available. As the practicable scan speed of 4D-STEM detectors improves, so too does the temporal resolution achievable for both differential phase contrast (DPC) and ptychography. However, the read-out burden of pixelated detectors, and the size of the gigabyte to terabyte sized data sets, remain a challenge for both temporal resolution and their practical adoption. In this work, we combine ultra-fast scan coils and detector signal digitization to show that a high-fidelity DPC phase reconstruction can be achieved from an annular segmented detector. Unlike conventional analog data phase reconstructions from digitized DPC-segment images yield reliable data, even at the fastest scan speeds. Finally, dose fractionation by fast scanning and multi-framing allows for postprocess binning of frame streams to balance signal-to-noise ratio and temporal resolution for low-dose phase imaging for in situ experiments.

Micro to macro scale anatomical analysis of the human hippocampal arteries with synchrotron hierarchical phase-contrast tomography.

PURPOSE: To date, no non-invasive imaging modality has been employed to profile the structural intricacies of the hippocampal arterial microvasculature in humans. We hypothesised that synchrotron-based imaging of the human hippocampus would enable precise characterisation of the arterial microvasculature. METHODS: Two preserved human brains from, a 69-year-old female and a 63-year-old male body donors were imaged using hierarchical phase-contrast tomography (HiP-CT) with synchrotron radiation at multiple voxel resolutions from 25.08 µm down to 2.45 µm. Subsequent manual and semi-automatic artery segmentation were performed followed by morphometric analyses. These data were compared to published data from alternative methodologies. RESULTS: HiP-CT made it possible to segment in context the arterial architecture of the human hippocampus. Our analysis identified anterior, medial and posterior hippocampal arteries arising from the P2 segment of the posterior cerebral artery on the image slices. We mapped arterial branches with external diameters greater than 50 µm in the hippocampal region. We visualised vascular asymmetry and quantified arterial structures with diameters as small as 7 µm. CONCLUSIONS: Through the application of HiP-CT, we have provided the first imaging visualisation and quantification of the arterial system of the human hippocampus at high resolution in the context of whole brain imaging. Our results bridge the gap between anatomical and histological scales.

Volumetric changes of the enteric nervous system under physiological and pathological conditions measured using x-ray phase-contrast tomography.

Background and Aim: Full-thickness biopsies of the intestinal wall may be used to study and assess damage to the neurons of the enteric nervous system (ENS), that is, enteric neuropathy. The ENS is difficult to examine due to its localization deep in the intestinal wall and its organization with several connections in diverging directions. Histological sections used in clinical practice only visualize the sample in a two-dimensional way. X-ray phase-contrast micro-computed tomography (PC-µCT) has shown potential to assess the cross-sectional thickness and volume of the ENS in three dimensions (3D). The aim of this study was to explore the potential of PC-µCT to evaluate its use to determine the size of the ENS. Methods: Full-thickness biopsies of ileum obtained during surgery from five controls and six patients clinically diagnosed with enteric neuropathy and dysmotility were included. Punch biopsies of 1 mm in diameter and 1 cm in length, from an area containing myenteric plexus, were extracted from paraffin blocks, and scanned with synchrotron-based PC-µCT without any staining. Results: The microscopic volumetric structure of the neural tissue (consisting of both ganglia and fascicles) could be determined in all samples. The ratio of neural tissue volume/total tissue volume was higher in controls than in patients with enteric neuropathy (P = 0.013). The patient with the longest disease duration had the lowest ratio. Conclusion: The assessment of neural tissue can be performed in an objective, standardized way, to ensure reproducibility and comparison under physiological and pathological conditions. Further evaluation is needed to examine the role of this method in the diagnosis of enteric neuropathy.

The 4D Camera: An 87 kHz Direct Electron Detector for Scanning/Transmission Electron Microscopy.

We describe the development, operation, and application of the 4D Camera-a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at ∼480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implemented to process the resulting 10-700 Gigabyte-sized raw datasets. The back illuminated detector provides the ability to detect single electron events at accelerating voltages from 30 to 300 kV. Through electron counting, the resulting sparse data sets are reduced in size by 10--300× compared to the raw data, and open-source sparsity-based processing algorithms offer rapid data analysis. The high frame rate allows for large and complex scanning diffraction experiments to be accomplished with typical scanning transmission electron microscopy scanning parameters.

Respiratory-resolved five-dimensional flow cardiovascular magnetic resonance : In-vivo validation and respiratory-dependent flow changes in healthy volunteers and patients with congenital heart disease.

BACKGROUND: This study aimed to validate respiratory-resolved five-dimensional (5D) flow cardiovascular magnetic resonance (CMR) against real-time two-dimensional (2D) phase-contrast MRI, assess the impact of number of respiratory states, and measure the impact of respiration on hemodynamics in congenital heart disease (CHD) patients. METHODS: Respiratory-resolved 5D flow MRI-derived net and peak flow measurements were compared to real-time 2D phase-contrast MRI-derived measurements in 10 healthy volunteers. Pulmonary-to-systemic flow ratios (Qp:Qs) were measured in 19 CHD patients and aortopulmonary collateral burden was measured in 5 Fontan patients. Additionally, the impact of number of respiratory states on measured respiratory-driven net flow changes was investigated in 10 healthy volunteers and 19 CHD patients (shunt physiology, n = 11, single ventricle disease [SVD], n = 8). RESULTS: There was good agreement between 5D flow MRI and real-time 2D phase-contrast-derived net and peak flow. Respiratory-driven changes had a good correlation (rho = 0.64, p < 0.001). In healthy volunteers, fewer than four respiratory states reduced measured respiratory-driven flow changes in veins (5.2 mL/cycle, p < 0.001) and arteries (1.7 mL/cycle, p = 0.05). Respiration drove substantial venous net flow changes in SVD (64% change) and shunt patients (57% change). Respiration had significantly greater impact in SVD patients compared to shunt patients in the right and left pulmonary arteries (46% vs 15%, p = 0.003 and 59% vs 20%, p = 0.002). Qp:Qs varied by 37 ± 24% over respiration in SVD patients and 12 ± 20% in shunt patients. Aortopulmonary collateral burden varied by 118 ± 84% over respiration in Fontan patients. The smallest collateral burden was measured during active inspiration in all patients and the greatest burden was during active expiration in four of five patients. Reduced respiratory resolution blunted measured flow changes in the caval veins of shunt and SVD patients (p < 0.005). CONCLUSIONS: Respiratory-resolved 5D flow MRI measurements agree with real-time 2D phase contrast. Venous measurements are sensitive to number of respiratory states, whereas arterial measurements are more robust. Respiration has a substantial impact on caval vein flow, Qp:Qs, and collateral burden in CHD patients.

Differential phase contrast from electrons that cause inner shell ionization.

Differential Phase Contrast (DPC) imaging, in which deviations in the bright field beam are in proportion to the electric field, has been extensively studied in the context of pure elastic scattering. Here we discuss differential phase contrast formed from core-loss scattered electrons, i.e. those that have caused inner shell ionization of atoms in the specimen, using a transition potential approach for which we study the number of final states needed for a converged calculation. In the phase object approximation, we show formally that differential phase contrast formed from core-loss scattered electrons is mainly a result of preservation of elastic contrast. Through simulation we demonstrate that whether the inelastic DPC images show element selective contrast depends on the spatial range of the ionization interaction, and specifically that when the energy loss is low the delocalisation can lead to contributions to the contrast from atoms other than that ionized. We further show that inelastic DPC images remain robustly interpretable to larger thicknesses than is the case for elastic DPC images, owing to the incoherence of the inelastic wavefields, though subtleties due to channelling remain. Lastly, we show that while a very high dose will be needed for sufficient counting statistics to discern differential phase contrast from core-loss scattered electrons, there is some enhancement of the signal-to-noise ratio with thickness that makes inelastic DPC imaging more achievable for thicker samples.