Simulating rigid head motion artifacts on brain magnitude MRI data-Outcome on image quality and segmentation of the cerebral cortex.

Magnetic Resonance Imaging (MRI) datasets from epidemiological studies often show a lower prevalence of motion artifacts than what is encountered in clinical practice. These artifacts can be unevenly distributed between subject groups and studies which introduces a bias that needs addressing when augmenting data for machine learning purposes. Since unreconstructed multi-channel k-space data is typically not available for population-based MRI datasets, motion simulations must be performed using signal magnitude data. There is thus a need to systematically evaluate how realistic such magnitude-based simulations are. We performed magnitude-based motion simulations on a dataset (MR-ART) from 148 subjects in which real motion-corrupted reference data was also available. The similarity of real and simulated motion was assessed by using image quality metrics (IQMs) including Coefficient of Joint Variation (CJV), Signal-to-Noise-Ratio (SNR), and Contrast-to-Noise-Ratio (CNR). An additional comparison was made by investigating the decrease in the Dice-Sørensen Coefficient (DSC) of automated segmentations with increasing motion severity. Segmentation of the cerebral cortex was performed with 6 freely available tools: FreeSurfer, BrainSuite, ANTs, SAMSEG, FastSurfer, and SynthSeg+. To better mimic the real subject motion, the original motion simulation within an existing data augmentation framework (TorchIO), was modified. This allowed a non-random motion paradigm and phase encoding direction. The mean difference in CJV/SNR/CNR between the real motion-corrupted images and our modified simulations (0.004±0.054/-0.7±1.8/-0.09±0.55) was lower than that of the original simulations (0.015±0.061/0.2±2.0/-0.29±0.62). Further, the mean difference in the DSC between the real motion-corrupted images was lower for our modified simulations (0.03±0.06) compared to the original simulations (-0.15±0.09). SynthSeg+ showed the highest robustness towards all forms of motion, real and simulated. In conclusion, reasonably realistic synthetic motion artifacts can be induced on a large-scale when only magnitude MR images are available to obtain unbiased data sets for the training of machine learning based models.

In vivo monitoring of renal tubule volume fraction using dynamic parametric MRI.

PURPOSE: The increasing incidence of kidney diseases is a global concern, and current biomarkers and treatments are inadequate. Changes in renal tubule luminal volume fraction (TVF) serve as a rapid biomarker for kidney disease and improve understanding of renal (patho)physiology. This study uses the amplitude of the long T2 component as a surrogate for TVF in rats, by applying multiexponential analysis of the T2-driven signal decay to examine micromorphological changes in renal tissue. METHODS: Simulations were conducted to identify a low mean absolute error (MAE) protocol and an accelerated protocol customized for the in vivo study of T2 mapping of the rat kidney at 9.4 T. We then validated our bi-exponential approach in a phantom mimicking the relaxation properties of renal tissue. This was followed by a proof-of-principle demonstration using in vivo data obtained during a transient increase of renal pelvis and tubular pressure. RESULTS: Using the low MAE protocol, our approach achieved an accuracy of MAE < 1% on the mechanical phantom. The T2 mapping protocol customized for in vivo study achieved an accuracy of MAE < 3%. Transiently increasing pressure in the renal pelvis and tubules led to significant changes in TVF in renal compartments: ΔTVFcortex = 4.9%, ΔTVFouter_medulla = 4.5%, and ΔTVFinner_medulla = -14.6%. CONCLUSION: These results demonstrate that our approach is promising for research into quantitative assessment of renal TVF in in vivo applications. Ultimately, these investigations have the potential to help reveal mechanism in acute renal injury that may lead to chronic kidney disease, which will support research into renal disorders.

Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification.

Renal pathologies often manifest as alterations in kidney size, providing a valuable avenue for employing dynamic parametric MRI as a means to derive kidney size measurements for the diagnosis, treatment, and monitoring of renal disease. Furthermore, this approach holds significant potential in supporting MRI data-driven preclinical investigations into the intricate mechanisms underlying renal pathophysiology. The integration of deep learning algorithms is crucial in achieving rapid and precise segmentation of the kidney from temporally resolved parametric MRI, facilitating the use of kidney size as a meaningful (pre)clinical biomarker for renal disease. To explore this potential, we employed dynamic parametric T2 mapping of the kidney in rats in conjunction with a custom-tailored deep dilated U-Net (DDU-Net) architecture. The architecture was trained, validated, and tested on manually segmented ground truth kidney data, with benchmarking against an analytical segmentation model and a self-configuring no new U-Net. Subsequently, we applied our approach to in vivo longitudinal MRI data, incorporating interventions that emulate clinically relevant scenarios in rats. Our approach achieved high performance metrics, including a Dice coefficient of 0.98, coefficient of determination of 0.92, and a mean absolute percentage error of 1.1% compared with ground truth. The DDU-Net enabled automated and accurate quantification of acute changes in kidney size, such as aortic occlusion (-8% ± 1%), venous occlusion (5% ± 1%), furosemide administration (2% ± 1%), hypoxemia (-2% ± 1%), and contrast agent-induced acute kidney injury (11% ± 1%). This approach can potentially be instrumental for the development of dynamic parametric MRI-based tools for kidney disorders, offering unparalleled insights into renal pathophysiology.

Studies in Zebrafish and Rat Models Support Dual Blockade of EP2 and EP4 (Prostaglandin E2 Receptors Type 2 and 4) for Renoprotection in Glomerular Hyperfiltration and Albuminuria.

BACKGROUND: Glomerular hyperfiltration (GH) is an important mechanism in the development of albuminuria in hypertension. Upregulation of COX2 (cyclooxygenase 2) and prostaglandin E2 (PGE2) was linked to podocyte damage in GH. We explored the potential renoprotective effects of either separate or combined pharmacological blockade of EP2 (PGE2 receptor type 2) and EP4 (PGE2 receptor type 4) in GH. METHODS: We conducted in vivo studies in a transgenic zebrafish model (Tg[fabp10a:gc-EGFP]) suitable for analysis of glomerular filtration barrier function and a genetic rat model with GH, albuminuria, and upregulation of PGE2. Similar pharmacological interventions and primary outcome analysis on albuminuria phenotype development were conducted in both model systems. RESULTS: Stimulation of zebrafish embryos with PGE2 induced an albuminuria-like phenotype, thus mimicking the suggested PGE2 effects on glomerular filtration barrier dysfunction. Both separate and combined blockade of EP2 and EP4 reduced albuminuria phenotypes in zebrafish and rat models. A significant correlation between albuminuria and podocyte damage in electron microscopy imaging was identified in the rat model. Dual blockade of both receptors showed a pronounced synergistic suppression of albuminuria. Importantly, this occurred without changes in arterial blood pressure, glomerular filtration rate, or tissue oxygenation in magnetic resonance imaging, while RNA sequencing analysis implicated a potential role of circadian clock genes. CONCLUSIONS: Our findings confirm a role of PGE2 in the development of albuminuria in GH and support the renoprotective potential of combined pharmacological blockade of EP2 and EP4 receptors. These data support further translational research to explore this therapeutic option and a possible role of circadian clock genes.

Monitoring kidney size to interpret MRI-based assessment of renal oxygenation in acute pathophysiological scenarios.

AIM: Tissue hypoxia is an early key feature of acute kidney injury. Assessment of renal oxygenation using magnetic resonance imaging (MRI) markers T2 and T2 * enables insights into renal pathophysiology. This assessment can be confounded by changes in the blood and tubular volume fractions, occurring upon pathological insults. These changes are mirrored by changes in kidney size (KS). Here, we used dynamic MRI to monitor KS for physiological interpretation of T2 * and T2 changes in acute pathophysiological scenarios. METHODS: KS was determined from T2 *, T2 mapping in rats. Six interventions that acutely alter renal tissue oxygenation were performed directly within the scanner, including interventions that change the blood and/or tubular volume. A biophysical model was used to estimate changes in O2 saturation of hemoglobin from changes in T2 * and KS. RESULTS: Upon aortic occlusion KS decreased; this correlated with a decrease in T2 *, T2 . Upon renal vein occlusion KS increased; this negatively correlated with a decrease in T2 *, T2 . Upon simultaneous occlusion of both vessels KS remained unchanged; there was no correlation with decreased T2 *, T2 . Hypoxemia induced mild reductions in KS and T2 *, T2 . Administration of an X-ray contrast medium induced sustained KS increase, with an initial increase in T2 *, T2 followed by a decrease. Furosemide caused T2 *, T2 elevation and a minor increase in KS. Model calculations yielded physiologically plausible calibration ratios for T2 *. CONCLUSION: Monitoring KS allows physiological interpretation of acute renal oxygenation changes obtained by T2 *, T2 . KS monitoring should accompany MRI-oximetry, for new insights into renal pathophysiology and swift translation into human studies.

Multi-laboratory performance assessment of diffuse optics instruments: the BitMap exercise.

SIGNIFICANCE: Multi-laboratory initiatives are essential in performance assessment and standardization-crucial for bringing biophotonics to mature clinical use-to establish protocols and develop reference tissue phantoms that all will allow universal instrument comparison. AIM: The largest multi-laboratory comparison of performance assessment in near-infrared diffuse optics is presented, involving 28 instruments and 12 institutions on a total of eight experiments based on three consolidated protocols (BIP, MEDPHOT, and NEUROPT) as implemented on three kits of tissue phantoms. A total of 20 synthetic indicators were extracted from the dataset, some of them defined here anew. APPROACH: The exercise stems from the Innovative Training Network BitMap funded by the European Commission and expanded to include other European laboratories. A large variety of diffuse optics instruments were considered, based on different approaches (time domain/frequency domain/continuous wave), at various stages of maturity and designed for different applications (e.g., oximetry, spectroscopy, and imaging). RESULTS: This study highlights a substantial difference in hardware performances (e.g., nine decades in responsivity, four decades in dark count rate, and one decade in temporal resolution). Agreement in the estimates of homogeneous optical properties was within 12% of the median value for half of the systems, with a temporal stability of <5 % over 1 h, and day-to-day reproducibility of <3 % . Other tests encompassed linearity, crosstalk, uncertainty, and detection of optical inhomogeneities. CONCLUSIONS: This extensive multi-laboratory exercise provides a detailed assessment of near-infrared Diffuse optical instruments and can be used for reference grading. The dataset-available soon in an open data repository-can be evaluated in multiple ways, for instance, to compare different analysis tools or study the impact of hardware implementations.

3D-printed tissue-simulating phantoms for near-infrared fluorescence imaging of rheumatoid diseases.

SIGNIFICANCE: Fluorescence imaging of rheumatoid diseases with indocyanine green (ICG) is an emerging technique with unique potential for diagnosis and therapy. Device characterization, monitoring of the performance, and further developments of the technique require tissue-equivalent fluorescent phantoms of high stability with appropriate anatomical shapes. AIM: Our investigations aim at the development of a three-dimensional (3D) printing technique to fabricate hand and finger models with appropriate optical properties in the near-infrared spectral range. These phantoms should have fluorescence properties similar to ICG, and excellent photostability and durability over years. APPROACH: We modified a 3D printing methacrylate photopolymer by adding the fluorescent dye Lumogen IR 765 to the raw material. Reduced scattering and absorption coefficients were adjusted to values representative of the human hand by incorporating titanium dioxide powder and black ink. The properties of printed phantoms of various compositions were characterized using UV/Vis and fluorescence spectroscopy, and time-resolved measurements. Photostability and bleaching were investigated with a hand imager. For comparison, several phantoms with ICG as fluorescent dye were printed and characterized as well. RESULTS: The spectral properties of Lumogen IR 765 are very similar to those of ICG. By optimizing the concentrations of Lumogen, titanium dioxide, and ink, anatomically shaped hand and vessel models with properties equivalent to in vivo investigations with a fluorescence hand imager could be printed. Phantoms with Lumogen IR 765 had an excellent photostability over up to 4 years. In contrast, phantoms printed with ICG showed significant bleaching and degradation of fluorescence over time. CONCLUSIONS: 3D printing of phantoms with Lumogen IR 765 is a promising method for fabricating anatomically shaped fluorescent tissue models of excellent stability with spectral properties similar to ICG. The phantoms are well-suited to monitor the performance of hand imagers. Concepts can easily be transferred to other fluorescence imaging applications of ICG.

Continuous diffusion spectrum computation for diffusion-weighted magnetic resonance imaging of the kidney tubule system.

BACKGROUND: The use of rigid multi-exponential models (with a priori predefined numbers of components) is common practice for diffusion-weighted MRI (DWI) analysis of the kidney. This approach may not accurately reflect renal microstructure, as the data are forced to conform to the a priori assumptions of simplified models. This work examines the feasibility of less constrained, data-driven non-negative least squares (NNLS) continuum modelling for DWI of the kidney tubule system in simulations that include emulations of pathophysiological conditions. METHODS: Non-linear least squares (LS) fitting was used as reference for the simulations. For performance assessment, a threshold of 5% or 10% for the mean absolute percentage error (MAPE) of NNLS and LS results was used. As ground truth, a tri-exponential model using defined volume fractions and diffusion coefficients for each renal compartment (tubule system: Dtubules , ftubules ; renal tissue: Dtissue , ftissue ; renal blood: Dblood , fblood ;) was applied. The impact of: (I) signal-to-noise ratio (SNR) =40-1,000, (II) number of b-values (n=10-50), (III) diffusion weighting (b-rangesmall =0-800 up to b-rangelarge =0-2,180 s/mm2), and (IV) fixation of the diffusion coefficients Dtissue and Dblood was examined. NNLS was evaluated for baseline and pathophysiological conditions, namely increased tubular volume fraction (ITV) and renal fibrosis (10%: grade I, mild) and 30% (grade II, moderate). RESULTS: NNLS showed the same high degree of reliability as the non-linear LS. MAPE of the tubular volume fraction (ftubules ) decreased with increasing SNR. Increasing the number of b-values was beneficial for ftubules precision. Using the b-rangelarge led to a decrease in MAPE ftubules compared to b-rangesmall. The use of a medium b-value range of b=0-1,380 s/mm2 improved ftubules precision, and further bmax increases beyond this range yielded diminishing improvements. Fixing Dblood and Dtissue significantly reduced MAPE ftubules and provided near perfect distinction between baseline and ITV conditions. Without constraining the number of renal compartments in advance, NNLS was able to detect the (fourth) fibrotic compartment, to differentiate it from the other three diffusion components, and to distinguish between 10% vs. 30% fibrosis. CONCLUSIONS: This work demonstrates the feasibility of NNLS modelling for DWI of the kidney tubule system and shows its potential for examining diffusion compartments associated with renal pathophysiology including ITV fraction and different degrees of fibrosis.

Reliable kidney size determination by magnetic resonance imaging in pathophysiological settings.

AIM: Kidney diseases constitute a major health challenge, which requires noninvasive imaging to complement conventional approaches to diagnosis and monitoring. Several renal pathologies are associated with changes in kidney size, offering an opportunity for magnetic resonance imaging (MRI) biomarkers of disease. This work uses dynamic MRI and an automated bean-shaped model (ABSM) for longitudinal quantification of pathophysiologically relevant changes in kidney size. METHODS: A geometry-based ABSM was developed for kidney size measurements in rats using parametric MRI (T2 , T2 * mapping). The ABSM approach was applied to longitudinal renal size quantification using occlusion of the (a) suprarenal aorta or (b) the renal vein, (c) increase in renal pelvis and intratubular pressure and (d) injection of an X-ray contrast medium into the thoracic aorta to induce pathophysiologically relevant changes in kidney size. RESULTS: The ABSM yielded renal size measurements with accuracy and precision equivalent to the manual segmentation, with >70-fold time savings. The automated method could detect a ~7% reduction (aortic occlusion) and a ~5%, a ~2% and a ~6% increase in kidney size (venous occlusion, pelvis and intratubular pressure increase and injection of X-ray contrast medium, respectively). These measurements were not affected by reduced image quality following administration of ferumoxytol. CONCLUSION: Dynamic MRI in conjunction with renal segmentation using an ABSM supports longitudinal quantification of changes in kidney size in pathophysiologically relevant experimental setups mimicking realistic clinical scenarios. This can potentially be instrumental for developing MRI-based diagnostic tools for various kidney disorders and for gaining new insight into mechanisms of renal pathophysiology.

Quantitative Assessment of Renal Perfusion and Oxygenation by Invasive Probes: Basic Concepts.

Renal tissue hypoperfusion and hypoxia are early key elements in the pathophysiology of acute kidney injury of various origins, and may also promote progression from acute injury to chronic kidney disease. Here we describe basic principles of methodology to quantify renal hemodynamics and tissue oxygenation by means of invasive probes in experimental animals. Advantages and disadvantages of the various methods are discussed in the context of the heterogeneity of renal tissue perfusion and oxygenation.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by a separate chapter describing the experimental procedure and data analysis.

Space-enhanced time-domain diffuse optics for determination of tissue optical properties in two-layered structures.

A novel methodology for solving the inverse problem of diffuse optics for two-layered structures is proposed to retrieve the absolute quantities of optical absorption and reduced scattering coefficients of the layers simultaneously. A liquid phantom with various optical absorption properties in the deep layer is prepared and experimentally investigated using the space-enhanced time-domain method. Monte-Carlo simulations are applied to analyze the different measurements in time domain, space domain, and by the new methodology. The deviations of retrieved values from nominal values of both layers' optical properties are simultaneously reduced to a very low extent compared to the single-domain methods. The reliability and uncertainty of the retrieval performance are also considerably improved by the new methodology. It is observed in time-domain analyses that for the deep layer the retrieval of absorption coefficient is almost not affected by the scattering properties and this kind of "deep scattering neutrality" is investigated and overcome as well.

Diffusion-weighted Renal MRI at 9.4 Tesla Using RARE to Improve Anatomical Integrity.

Diffusion-weighted magnetic resonance imaging (DWI) is a non-invasive imaging technique sensitive to tissue water movement. By enabling a discrimination between tissue properties without the need of contrast agent administration, DWI is invaluable for probing tissue microstructure in kidney diseases. DWI studies commonly make use of single-shot Echo-Planar Imaging (ss-EPI) techniques that are prone to suffering from geometric distortion. The goal of the present study was to develop a robust DWI technique tailored for preclinical magnetic resonance imaging (MRI) studies that is free of distortion and sensitive to detect microstructural changes. Since fast spin-echo imaging techniques are less susceptible to B0 inhomogeneity related image distortions, we introduced a diffusion sensitization to a split-echo Rapid Acquisition with Relaxation Enhancement (RARE) technique for high field preclinical DWI at 9.4 T. Validation studies in standard liquids provided diffusion coefficients consistent with reported values from the literature. Split-echo RARE outperformed conventional ss-EPI, with ss-EPI showing a 3.5-times larger border displacement (2.60 vs. 0.75) and a 60% higher intra-subject variability (cortex = 74%, outer medulla = 62% and inner medulla = 44%). The anatomical integrity provided by the split-echo RARE DWI technique is an essential component of parametric imaging on the way towards robust renal tissue characterization, especially during kidney disease.

Spatially-enhanced time-domain NIRS for accurate determination of tissue optical properties.

A multivariate method integrating time and space resolved techniques of near-infrared spectroscopy is proposed for simultaneously retrieving the absolute quantities of optical absorption and scattering properties in tissues. The time-domain feature of photon migration is advantageously constrained and regularized by its spatially-resolved amplitude patterns in the inverse procedure. Measurements of tissue-mimicking phantoms with various optical properties are analyzed with Monte-Carlo simulations to validate the method performance. The uniqueness, stability, and uncertainty of the method are discussed.

Experimental MRI Monitoring of Renal Blood Volume Fraction Variations En Route to Renal Magnetic Resonance Oximetry.

Diagnosis of early-stage acute kidney injury (AKI) will benefit from a timely identification of local tissue hypoxia. Renal tissue hypoxia is an early feature in AKI pathophysiology, and renal oxygenation is increasingly being assessed through T2*-weighted magnetic resonance imaging (MRI). However, changes in renal blood volume fraction (BVf) confound renal T2*. The aim of this study was to assess the feasibility of intravascular contrast-enhanced MRI for monitoring renal BVf during physiological interventions that are concomitant with variations in BVf and to explore the possibility of correcting renal T2* for BVf variations. A dose-dependent study of the contrast agent ferumoxytol was performed in rats. BVf was monitored throughout short-term occlusion of the renal vein, which is known to markedly change renal blood partial pressure of O2 and BVf. BVf calculated from MRI measurements was used to estimate oxygen saturation of hemoglobin (SO2). BVf and SO2 were benchmarked against cortical data derived from near-infrared spectroscopy. As estimated from magnetic resonance parametric maps of T2 and T2*, BVf was shown to increase, whereas SO2 was shown to decline during venous occlusion (VO). This observation could be quantitatively reproduced in test-retest scenarios. Changes in BVf and SO2 were in good agreement with data obtained from near-infrared spectroscopy. Our findings provide motivation to advance multiparametric MRI for studying AKIs, with the ultimate goal of translating MRI-based renal BVf mapping into clinical practice en route noninvasive renal magnetic resonance oximetry as a method of assessing AKI and progression to chronic damage.

Expansion dynamics of supercritical water probed by picosecond time-resolved photoelectron spectroscopy.

Vibrational excitation of liquid water with femtosecond laser pulses can create extreme states of water. Yet, the dynamics directly after initial sub-picosecond delocalization of molecular vibrations remain largely unclear. We study the ultrafast expansion dynamics of an accordingly prepared supercritical water phase with a picosecond time resolution. Our experimental setup combines vacuum-compatible liquid micro-jet technology and a table top High Harmonic light source driven by a femtosecond laser system. An ultrashort laser pulse centered at a wavelength of 2900 nm excites the OH-stretch vibration of water molecules in the liquid. The deposited energy corresponds to a supercritical phase with a temperature of about 1000 K and a pressure of more than 1 GPa. We use a time-delayed extreme ultraviolet pulse centered at 38.6 eV, and obtained via High Harmonic generation (HHG), to record valence band photoelectron spectra of the expanding water sample. The series of photoelectron spectra is analyzed with noise-corrected target transform fitting (cTTF), a specifically developed multivariate method. Together with a simple fluid dynamics simulation, the following picture emerges: when a supercritical phase of water expands into vacuum, temperature and density of the first few nanometers of the expanding phase drop below the critical values within a few picoseconds. This results in a supersaturated phase, in which condensation seeds form and grow from small clusters to large clusters on a 100 picosecond timescale.