Lansoprazole Increases Inorganic Pyrophosphate in Patients with Pseudoxanthoma Elasticum: A Double-Blind, Randomized, Placebo-Controlled Crossover Trial.

Pseudoxanthoma elasticum (PXE) is characterized by low levels of inorganic pyrophosphate (PPi) and a high activity of tissue-nonspecific alkaline phosphatase (TNAP). Lansoprazole is a partial inhibitor of TNAP. The aim was to investigate whether lansoprazole increases plasma PPi levels in subjects with PXE. We conducted a 2 × 2 randomized, double-blind, placebo-controlled crossover trial in patients with PXE. Patients were allocated 30 mg/day of lansoprazole or a placebo in two sequences of 8 weeks. The primary outcome was the differences in plasma PPi levels between the placebo and lansoprazole phases. 29 patients were included in the study. There were eight drop-outs due to the pandemic lockdown after the first visit and one due to gastric intolerance, so twenty patients completed the trial. A generalized linear mixed model was used to evaluate the effect of lansoprazole. Overall, lansoprazole increased plasma PPi levels from 0.34 ± 0.10 µM to 0.41 ± 0.16 µM (p = 0.0302), with no statistically significant changes in TNAP activity. There were no important adverse events. 30 mg/day of lansoprazole was able to significantly increase plasma PPi in patients with PXE; despite this, the study should be replicated with a large number of participants in a multicenter trial, with a clinical end point as the primary outcome.

Integrated experimental-computational analysis of a HepaRG liver-islet microphysiological system for human-centric diabetes research.

Microphysiological systems (MPS) are powerful tools for emulating human physiology and replicating disease progression in vitro. MPS could be better predictors of human outcome than current animal models, but mechanistic interpretation and in vivo extrapolation of the experimental results remain significant challenges. Here, we address these challenges using an integrated experimental-computational approach. This approach allows for in silico representation and predictions of glucose metabolism in a previously reported MPS with two organ compartments (liver and pancreas) connected in a closed loop with circulating medium. We developed a computational model describing glucose metabolism over 15 days of culture in the MPS. The model was calibrated on an experiment-specific basis using data from seven experiments, where HepaRG single-liver or liver-islet cultures were exposed to both normal and hyperglycemic conditions resembling high blood glucose levels in diabetes. The calibrated models reproduced the fast (i.e. hourly) variations in glucose and insulin observed in the MPS experiments, as well as the long-term (i.e. over weeks) decline in both glucose tolerance and insulin secretion. We also investigated the behaviour of the system under hypoglycemia by simulating this condition in silico, and the model could correctly predict the glucose and insulin responses measured in new MPS experiments. Last, we used the computational model to translate the experimental results to humans, showing good agreement with published data of the glucose response to a meal in healthy subjects. The integrated experimental-computational framework opens new avenues for future investigations toward disease mechanisms and the development of new therapies for metabolic disorders.

Cutaneous and Vascular Deposits of 18F-NaF by PET/CT in the Follow-Up of Patients with Pseudoxanthoma Elasticum.

Active microcalcification of elastic fibers is a hallmark of pseudoxanthoma elasticum and it can be measured with the assessment of deposition of 18F-NaF using a PET/CT scan at the skin and vascular levels. It is not known whether this deposition changes over time in absence of specific therapy. We repeated in two years a PET/CT scan using 18F-NaF as a radiopharmaceutical in patients with the disease and compared the deposition at skin and vessel. Furthermore, calcium score values at the vessel wall were also assessed. Main results indicate in the vessel walls that calcification progressed in each patient; by contrast, the active microcalcification, measured and target-to-background ratio showed reduced active deposition. By contrast, at skin levels (neck and axillae) the uptake of the pharmaceutical remains unchanged. In conclusion, because calcification in the arterial wall is not specific for pseudoxanthoma elasticum condition, the measurement of the deposition of 18F-NaF in the neck might be potentially used as a surrogate marker in future trials for the disease.

Skin and Arterial Wall Deposits of 18F-NaF and Severity of Disease in Patients with Pseudoxanthoma Elasticum.

Pseudoxanthoma elasticum (PXE) is a genetic disease characterized by the calcification of elastin fibers. Our aim was to quantify vascular calcification in the arteries and the deposition of 18F-sodium-fluoride (18F-NaF) in the skin and vessel walls with positron emission tomography/computed tomography. This was an observational study including 18 patients with PXE. Vascular calcification was measured in Agatston units, and deposition in the skin and vessel walls was shown using target-to-background ratio (TBR). Severity of the disease was scored by Phenodex. We found higher vascular calcification in the popliteal, femoral, and aortic arch vessels compared to other vascular regions; however, the uptake of radiotracer was the highest in the aorta and femoral arteries. In the skin, the highest uptake was observed in the neck and the axillae. There was no significant association between 18F-NaF deposition in the arteries or skin and the global Phenodex score. In contrast, the Phenodex score was significantly associated in univariate analyses with the averaged vascular calcium score (p < 0.01). In the neck, patients with higher skin Phenodex scores exhibited higher radiotracer uptake. As a conclusion, because vascular calcification is physiological, our data suggested that the detection of cutaneous (neck) 18F-NaF deposits might serve to monitor the calcification process in the short-term for patients with PXE.

Publisher Correction: Bridging the gap between measurements and modelling: a cardiovascular functional avatar.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Plasma inorganic pyrophosphate and alkaline phosphatase in patients with pseudoxanthoma elasticum.

BACKGROUND: Inorganic pyrophosphate (PPi) plays a major role inhibiting dystrophic calcification. The aim was to analyze levels of PPi in patients having pseudoxanthoma elasticum (PXE), and controls as well as the enzymes who regulate the PPi plasma concentration. METHODS: We collected fasting blood samples from PXE patients and age- and sex-matched controls in ethylenediamine tetraacetic acid (EDTA) and citrate-theophylline-adenosine-dipyridamole (CTAD) containing tubes. We measured PPi, ENPP1 mass and activity, alkaline phosphatase (AP) and tissue non-specific alkaline phosphatase (TNAP), CD73 and Human Platelet Factor-4 (CXCL4). RESULTS: PPi in EDTA and CTAD samples were lower in PXE subjects than in controls (1.11±0.26 vs. 1.43±0.41 µM/L and 0.35±0.15 vs. 0.61±0.18 µM/L respectively, P<0.05). TNAP and liver TNAP activities were also higher in PXE than in controls (80.3±27.0 vs. 63.3±16.4 UI/L and 25.6±14.9 vs. 12.9±9.2 UI/L respectively, P<0.05). ENPP1 mass and activity as well as CD73 were almost identical. There was a weak but significant inverse correlation between TNAP activity and PPi levels (Pearson correlation -0.379, P<0.05) in both groups. CONCLUSIONS: High TNAP activity seems to contribute to low plasma levels of PPi in subjects with PXE, reinforcing the idea that pharmacological reduction of TNAP activity may help to reduce dystrophic calcification in PXE patients.

QModeling: a Multiplatform, Easy-to-Use and Open-Source Toolbox for PET Kinetic Analysis.

Kinetic modeling is at the basis of most quantification methods for dynamic PET data. Specific software is required for it, and a free and easy-to-use kinetic analysis toolbox can facilitate routine work for clinical research. The relevance of kinetic modeling for neuroimaging encourages its incorporation into image processing pipelines like those of SPM, also providing preprocessing flexibility to match the needs of users. The aim of this work was to develop such a toolbox: QModeling. It implements four widely-used reference-region models: Simplified Reference Tissue Model (SRTM), Simplified Reference Tissue Model 2 (SRTM2), Patlak Reference and Logan Reference. A preliminary validation was also performed: The obtained parameters were compared with the gold standard provided by PMOD, the most commonly-used software in this field. Execution speed was also compared, for time-activity curve (TAC) estimation, model fitting and image generation. QModeling has a simple interface, which guides the user through the analysis: Loading data, obtaining TACs, preprocessing the model for pre-evaluation, generating parametric images and visualizing them. Relative differences between QModeling and PMOD in the parameter values are almost always below 10-8. The SRTM2 algorithm yields relative differences from 10-3 to 10-5 when [Formula: see text] is not fixed, since different, validated methods are used to fit this parameter. The new toolbox works efficiently, with execution times of the same order as those of PMOD. Therefore, QModeling allows applying reference-region models with reliable results in efficient computation times. It is free, flexible, multiplatform, easy-to-use and open-source, and it can be easily expanded with new models.

Non-invasive Assessment of Systolic and Diastolic Cardiac Function During Rest and Stress Conditions Using an Integrated Image-Modeling Approach.

Background: The possibility of non-invasively assessing load-independent parameters characterizing cardiac function is of high clinical value. Typically, these parameters are assessed during resting conditions. However, for diagnostic purposes, the parameter behavior across a physiologically relevant range of heart rate and loads is more relevant than the isolated measurements performed at rest. This study sought to evaluate changes in non-invasive estimations of load-independent parameters of left-ventricular contraction and relaxation patterns at rest and during dobutamine stress. Methods: We applied a previously developed approach that combines non-invasive measurements with a physiologically-based, reduced-order model of the cardiovascular system to provide subject-specific estimates of parameters characterizing left ventricular function. In this model, the contractile state of the heart at each time point along the cardiac cycle is modeled using a time-varying elastance curve. Non-invasive data, including four-dimensional magnetic resonance imaging (4D Flow MRI) measurements, were acquired in nine subjects without a known heart disease at rest and during dobutamine stress. For each of the study subjects, we constructed two personalized models corresponding to the resting and the stress state. Results: Applying the modeling framework, we identified significant increases in the left ventricular contraction rate constant [from 1.5 ± 0.3 to 2 ± 0.5 (p = 0.038)] and relaxation constant [from 37.2 ± 6.9 to 46.1 ± 12 (p = 0.028)]. In addition, we found a significant decrease in the elastance diastolic time constant from 0.4 ± 0.04 s to 0.3 ± 0.03 s (p = 0.008). Conclusions: The integrated image-modeling approach allows the assessment of cardiovascular function given as model-based parameters. The agreement between the estimated parameter values and previously reported effects of dobutamine demonstrates the potential of the approach to assess advanced metrics of pathophysiology that are otherwise difficult to obtain non-invasively in clinical practice.

Bridging the gap between measurements and modelling: a cardiovascular functional avatar.

Lumped parameter models of the cardiovascular system have the potential to assist researchers and clinicians to better understand cardiovascular function. The value of such models increases when they are subject specific. However, most approaches to personalize lumped parameter models have thus far required invasive measurements or fall short of being subject specific due to a lack of the necessary clinical data. Here, we propose an approach to personalize parameters in a model of the heart and the systemic circulation using exclusively non-invasive measurements. The personalized model is created using flow data from four-dimensional magnetic resonance imaging and cuff pressure measurements in the brachial artery. We term this personalized model the cardiovascular avatar. In our proof-of-concept study, we evaluated the capability of the avatar to reproduce pressures and flows in a group of eight healthy subjects. Both quantitatively and qualitatively, the model-based results agreed well with the pressure and flow measurements obtained in vivo for each subject. This non-invasive and personalized approach can synthesize medical data into clinically relevant indicators of cardiovascular function, and estimate hemodynamic variables that cannot be assessed directly from clinical measurements.

Estimating the irreversible pressure drop across a stenosis by quantifying turbulence production using 4D Flow MRI.

The pressure drop across a stenotic vessel is an important parameter in medicine, providing a commonly used and intuitive metric for evaluating the severity of the stenosis. However, non-invasive estimation of the pressure drop under pathological conditions has remained difficult. This study demonstrates a novel method to quantify the irreversible pressure drop across a stenosis using 4D Flow MRI by calculating the total turbulence production of the flow. Simulation MRI acquisitions showed that the energy lost to turbulence production can be accurately quantified with 4D Flow MRI within a range of practical spatial resolutions (1-3 mm; regression slope = 0.91, R2 = 0.96). The quantification of the turbulence production was not substantially influenced by the signal-to-noise ratio (SNR), resulting in less than 2% mean bias at SNR > 10. Pressure drop estimation based on turbulence production robustly predicted the irreversible pressure drop, regardless of the stenosis severity and post-stenosis dilatation (regression slope = 0.956, R2 = 0.96). In vitro validation of the technique in a 75% stenosis channel confirmed that pressure drop prediction based on the turbulence production agreed with the measured pressure drop (regression slope = 1.15, R2 = 0.999, Bland-Altman agreement = 0.75 ± 3.93 mmHg).

Assessment of turbulent viscous stress using ICOSA 4D Flow MRI for prediction of hemodynamic blood damage.

Flow-induced blood damage plays an important role in determining the hemodynamic impact of abnormal blood flow, but quantifying of these effects, which are dominated by shear stresses in highly fluctuating turbulent flow, has not been feasible. This study evaluated the novel application of turbulence tensor measurements using simulated 4D Flow MRI data with six-directional velocity encoding for assessing hemodynamic stresses and corresponding blood damage index (BDI) in stenotic turbulent blood flow. The results showed that 4D Flow MRI underestimates the maximum principal shear stress of laminar viscous stress (PLVS), and overestimates the maximum principal shear stress of Reynolds stress (PRSS) with increasing voxel size. PLVS and PRSS were also overestimated by about 1.2 and 4.6 times at medium signal to noise ratio (SNR) = 20. In contrast, the square sum of the turbulent viscous shear stress (TVSS), which is used for blood damage index (BDI) estimation, was not severely affected by SNR and voxel size. The square sum of TVSS and the BDI at SNR >20 were underestimated by less than 1% and 10%, respectively. In conclusion, this study demonstrated the feasibility of 4D Flow MRI based quantification of TVSS and BDI which are closely linked to blood damage.

4D Flow MRI-based pressure loss estimation in stenotic flows: Evaluation using numerical simulations.

PURPOSE: To assess how 4D flow MRI-based pressure and energy loss estimates correspond to net transstenotic pressure gradients (TPGnet) and their dependence on spatial resolution. METHODS: Numerical velocity data of stenotic flow were obtained from computational fluid dynamics (CFD) simulations in geometries with varying stenosis degrees, poststenotic diameters and flow rates. MRI measurements were simulated at different spatial resolutions. The simplified and extended Bernoulli equations, Pressure-Poisson equation (PPE), and integration of turbulent kinetic energy (TKE) and viscous dissipation were compared against the true TPGnet . RESULTS: The simplified Bernoulli equation overestimated the true TPGnet (8.74 ± 0.67 versus 6.76 ± 0.54 mmHg). The extended Bernoulli equation performed better (6.57 ± 0.53 mmHg), although errors remained at low TPGnet . TPGnet estimations using the PPE were always close to zero. Total TKE and viscous dissipation correlated strongly with TPGnet for each geometry (r(2) > 0.93) and moderately considering all geometries (r(2) = 0.756 and r(2) = 0.776, respectively). TKE estimates were accurate and minorly impacted by resolution. Viscous dissipation was overall underestimated and resolution dependent. CONCLUSION: Several parameters overestimate or are not linearly related to TPGnet and/or depend on spatial resolution. Considering idealized axisymmetric geometries and in absence of noise, TPGnet was best estimated using the extended Bernoulli equation. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.