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BackgroundCentral blood pressure (cBP) is a better indicator of cardiovascular morbidity and mortality than peripheral BP (pBP). However, direct cBP measurement requires invasive techniques and indirect cBP measurement is based on rigid and empirical transfer functions applied to pBP. Thus, development of a personalized and well-validated method for non-invasive derivation of cBP from pBP is necessary to facilitate the clinical routine. The purpose of the present study was to develop a novel blind source separation tool to separate a single recording of pBP into their pressure waveforms composing its dynamics, to identify the compounds that lead to pressure waveform distortion at the periphery, and to estimate the cBP. The approach is patient-specific and extracts the underlying blind pressure waveforms in pBP without additional brachial cuff calibration or any a priori assumption on the arterial model.MethodsThe intra-arterial femoral BPfe and intra-aortic pressure BPao were anonymized digital recordings from previous routine cardiac catheterizations of eight patients at the German Heart Centre Berlin. The underlying pressure waveforms in BPfe were extracted by the single-channel independent component analysis (SCICA). The accuracy of the SCICA model to estimate the whole cBP waveform was evaluated by the mean absolute error (MAE), the root mean square error (RMSE), the relative RMSE (RRMSE), and the intraclass correlation coefficient (ICC). The agreement between the intra-aortic and estimated parameters including systolic (SBP), diastolic (DBP), mean arterial pressure (MAP), and pulse pressure (PP) was evaluated by the regression and Bland–Altman analyses.ResultsThe SCICA tool estimated the cBP waveform non-invasively from the intra-arterial BPfe with an MAE of 0.159 ± 1.629, an RMSE of 5.153 ± 0.957 mmHg, an RRMSE of 5.424 ± 1.304%, and an ICC of 0.94, as well as two waveforms contributing to morphological distortion at the femoral artery. The regression analysis showed a strong linear trend between the estimated and intra-aortic SBP, DBP, MAP, and PP with high coefficient of determination R2 of 0.98, 0.99, 0.99, and 0.97 respectively. The Bland–Altman plots demonstrated good agreement between estimated and intra-aortic parameters with a mean error and a standard deviation of difference of −0.54 ± 2.42 mmHg [95% confidence interval (CI): −5.28 to 4.20] for SBP, −1.97 ± 1.62 mmHg (95% CI: −5.14 to 1.20) for DBP, −1.49 ± 1.40 mmHg (95% CI: −4.25 to 1.26) for MAP, and 1.43 ± 2.79 mmHg (95% CI: −4.03 to 6.90) for PP.ConclusionsThe SCICA approach is a powerful tool that identifies sources contributing to morphological distortion at peripheral arteries and estimates cBP.

Recent progress in digital health data recording, advances in computing power, and methodological approaches that extract information from data as artificial intelligence are expected to have a disruptive impact on technology in medicine. One of the potential benefits is the ability to extract new and essential insights from the vast amount of data generated during health care delivery every day. Cardiovascular imaging is boosted by new intelligent automatic methods to manage, process, segment, and analyze petabytes of image data exceeding historical manual capacities. Algorithms that learn from data raise new challenges for regulatory bodies. Partially autonomous behavior and adaptive modifications and a lack of transparency in deriving evidence from complex data pose considerable problems. Controlling new technologies requires new controlling techniques and ongoing regulatory research. All stakeholders must participate in the quest to find a fair balance between innovation and regulation. The regulatory approach to artificial intelligence must be risk-based and resilient. A focus on unknown emerging risks demands continuous surveillance and clinical evaluation during the total product life cycle. Since learning algorithms are data-driven, high-quality data is fundamental for good machine learning practice. Mining, processing, validation, governance, and data control must account for bias, error, inappropriate use, drifts, and shifts, particularly in real-world data. Regulators worldwide are tackling twenty-first century challenges raised by “learning” medical devices. Ethical concerns and regulatory approaches are presented. The paper concludes with a discussion on the future of responsible artificial intelligence.

Abstract Background Obesity is associated with cardiovascular complications, including pulmonary hypertension (PH). Reports suggest that peroxisome proliferator-activated receptor-γ (PPARγ) has direct action in preventing vascular remodelling in PH. Here we dissected the specific role of high-fat-diet (HFD)-induced obesity and vascular smooth muscle cell (VSMC)-PPARγ for remodelling of small pulmonary arteries. Methods Wild-type (WT) and VSMC-specific PPARγ-knockout (SmPparγ −/−) mice were fed a low-fat-diet (LFD, 10% kcal from fat) or HFD (60% kcal from fat) for 24 weeks. Mice were metabolically phenotyped (e.g. weight development, insulin/glucose tolerance) at the beginning, and after 12 and 24 weeks, respectively. At 24 weeks additionally pulmonary pressure, heart structure, pulmonary vascular muscularization together with gene and protein expression in heart and lung tissues were determined. Results HFD increased right ventricular systolic pressure (RVSP) to a similar extent in WT and SmPparγ −/− mice. HFD decreased glucose tolerance and insulin sensitivity in both WT and SmPparγ −/− mice. Importantly, the increase in RVSP correlated with the degree of insulin resistance. However, VSMC-PPARγ deficiency increased pulmonary vascular muscularization independently of the diet-induced rise in RVSP. This increase was associated with elevated expression of early growth response protein 1 in heart and osteopontin in lung tissue. Conclusions Here we demonstrate a correlation of insulin resistance and pulmonary pressure. Further, deficiency of PPARγ in VSMCs diet-independently leads to increased pulmonary vascular muscularization.

Background Animal studies demonstrated that serelaxin lessens fibrosis in heart failure. This study assessed its effect on myocardial deformation using cardiac magnetic resonance and elucidated its relationship to gene regulation and histology in a mouse heart failure model. Methods and Results C57BL/6J mice were subjected to SHAM (n=4) or transverse aortic constriction (TAC). At week 10, TAC mice were randomized to receive either serelaxin (0.5 mg/kg per day; n=11) or vehicle (n=13) for 4 weeks. Cardiac magnetic resonance imaging was performed at baseline and repeated at the end of the study (week 14). Cine images were used to calculate left ventricular (LV) global longitudinal, circumferential, and radial strain. Hearts were examined for histology and gene expression. Compared with SHAM, mice 10 weeks after TAC showed increased LV mass with significant decreases in LV deformation parameters, indicating subclinical deterioration of myocardial function. At week 14, TAC mice given serelaxin demonstrated significant improvements in all LV strain parameters and no decrease in LV stroke volume and ejection fraction compared with TAC mice given vehicle. A significant positive correlation between global circumferential strain and the extent of myocardial fibrosis was found, and global circumferential strain correlated significantly with the expression of heart failure genes in serelaxin‐treated mice. Conclusions Serelaxin improved cardiac magnetic resonance–derived myocardial deformation parameters as well as histomorphometric and gene expression findings in mice with heart failure. Cardiac magnetic resonance–derived myocardial mechanics correlate with histology and gene expression, stressing its utilization in myocardial remodeling.

Aims: Subclinical diastolic dysfuntion in patients with preclinical heart failure with preserved ejection fraction (HFpEF) has been demonstrated in patients with Marfan syndrome (MFS). We investigated the relationship between diastolic dysfunction and NT-proBNP levels in patients with MFS. Methods and results: NT-proBNP, C-reactive protein (CRP) and diastolic function were assessed in 217 patients with MFS (31 ± 16 y, 110 f. and in 339 patients referred for suspected MFS in whom the diagnosis was ruled out according to the Ghent nosology (30 ± 15 y, 154 f). Assessment of cardiovascular remodeling, diastolic function in echocardiography, and NT-proBNP was analyzed with univariate analysis and multi-parameter analysis of covariance (MANCOVA). NT-proBNP was 70.6 ± 74.8 pg/ml in patients with Marfan syndrome and 58.4 ± 100.3 pg/ml in controls (p = 0.002, Kolmogorov–Smirnov). There were significant intergroup differences regarding end-diastolic left ventricular volume (p

Objective: Insulin resistance can be triggered by enhanced dephosphorylation of the insulin receptor or downstream components in the insulin signaling cascade through protein tyrosine phosphatases (PTPs). Downregulating density-enhanced phosphatase-1 (DEP-1) resulted in an improved metabolic status in previous analyses. This phenotype was primarily caused by hepatic DEP-1 reduction. Methods: Here we further elucidated the role of DEP-1 in glucose homeostasis by employing a conventional knockout model to explore the specific contribution of DEP-1 in metabolic tissues. Ptprj−/− (DEP-1 deficient) and wild-type C57BL/6 mice were fed a low-fat or high-fat diet. Metabolic phenotyping was combined with analyses of phosphorylation patterns of insulin signaling components. Additionally, experiments with skeletal muscle cells and muscle tissue were performed to assess the role of DEP-1 for glucose uptake. Results: High-fat diet fed-Ptprj−/− mice displayed enhanced insulin sensitivity and improved glucose tolerance. Furthermore, leptin levels and blood pressure were reduced in Ptprj−/− mice. DEP-1 deficiency resulted in increased phosphorylation of components of the insulin signaling cascade in liver, skeletal muscle and adipose tissue after insulin challenge. The beneficial effect on glucose homeostasis in vivo was corroborated by increased glucose uptake in skeletal muscle cells in which DEP-1 was downregulated, and in skeletal muscle of Ptprj−/− mice. Conclusion: Together, these data establish DEP-1 as novel negative regulator of insulin signaling.

AimTo study the effects of RD on renal artery wall function non-invasively using magnetic resonance.Methods and results32 patients undergoing RD were included. A 3.0 Tesla magnetic resonance of the renal arteries was performed before RD and after 6-month. We quantified the vessel sharpness of both renal arteries using a quantitative analysis tool (Soap-Bubble®). In 17 patients we assessed the maximal and minimal cross-sectional area of both arteries, peak velocity, mean flow, and renal artery distensibility. In a subset of patients wall shear stress was assessed with computational flow dynamics. Neither renal artery sharpness nor renal artery distensibility differed significantly. A significant increase in minimal and maximal areas (by 25.3%, p = 0.008, and 24.6%, p = 0.007, respectively), peak velocity (by 16.9%, p = 0.021), and mean flow (by 22.4%, p = 0.007) was observed after RD. Wall shear stress significantly decreased (by 25%, p = 0.029). These effects were observed in blood pressure responders and non-responders.ConclusionsRD is not associated with adverse effects at renal artery level, and leads to an increase in cross-sectional areas, velocity and flow and a decrease in wall shear stress.

We sought to evaluate the impact of ischemic burden for the prediction of hard cardiac events (cardiac death or nonfatal myocardial infarction) in patients with known or suspected CAD who undergo dobutamine stress cardiac magnetic resonance imaging (DCMR).We included 3166 patients (pts.), mean age 63 ± 12 years, 27% female, who underwent DCMR in 3 tertiary cardiac centres (University Hospital Heildelberg, German Heart Institute and Kings College London). Pts. were separated in groups based on the number of ischemic segments by wall motion abnormalities (WMA) as follows: 1. no ischemic segment, 2. one ischemic segment, 3. two ischemic segments and 4. ≥ three ischemic segments. Cardiac death and nonfatal myocardial infarction were registered as hard cardiac events. Pts. with an "early" revascularization procedure (in the first three months after DCMR) were not included in the final survival analysis.Pts. were followed for a median of 3.1 years (iqr 2-4.5 years). 187 (5.9%) pts. experienced hard cardiac events. 2349 (74.2%) had no inducible ischemia, 189 (6%) had ischemia in 1 segment, 292 (9.2%) in 2 segments and 336 (10.6%) ≥ 3 segments. Patients with only 1 ischemic segment showed a high rate of hard cardiac events of ∼ 6% annually, which was 10-fold higher compared to those without ischemia (0.6% annually, p < 0.001) but similar to those with 2 and ≥ 3 ischemic segments (∼ 5.5% and ∼ 7%, p = NS).The presence of inducible ischemia even in a single 'culprit' myocardial segment during DCMR is enough to predict hard cardiac events in patients with known or suspected CAD.

Matrix metalloproteinase (MMP)-dependent extracellular matrix (ECM) remodeling is a key feature in cardiometabolic syndrome-associated adipogenesis and atherosclerosis. Activation of membrane-tethered (MT) 1-MMP depends on furin (PCSK3). However, the regulation and function of the natural furin-inhibitor serpinB8 and thus furin/MT1-MMP-activity in obesity-related tissue inflammation/remodeling is unknown. Here we aimed to determine the role of serpinB8/furin in obesity-associated chronic inflammation.Monocyte → macrophage transformation was characterized by decreases in serpinB8 and increases in furin/MT1-MMP. Rescue of serpinB8 by protein overexpression inhibited furin-dependent pro-MT1-MMP activation in macrophages, supporting its role as a furin-inhibitor. Obese white adipose tissue-facilitated macrophage migration was inhibited by furin- and MMP-inhibition, stressing the importance of the furin-MMP axis in fat tissue inflammation/remodeling. Monocytes from obese patients (body mass index (BMI) >30kg/m(2)) had higher furin, MT1-MMP, and resistin gene expression compared to normal weight individuals (BMI

Abstract  Computational fluid dynamics (CFD) methods based on three-dimensional (3D) vessel reconstructions have recently been shown to provide prognostically relevant hemodynamic data. However, the geometry reconstruction and the assessment of clinically relevant hemodynamic parameters may depend on the used imaging modality. In this study, the silicon model of the left coronary artery (LCA) was acquired with a biplane angiography. The geometry reconstruction was done using commercial CAAS 5.2 QCA 3D software and compared with an original geometry. The original model is an optically digitized post-mortem vessel cast. The biplane angiography reconstruction achieved a Hausdorff surface distance of 0.236 mm to the original geometry that is comparable with results obtained in our earlier study for computed tomography (CT) and magnetic resonance imaging (MRI) reconstructions. Steady flow simulations were performed with a commercial CFD program FLUENT. A comparison of the calculated wall shear stress (WSS) shows good correlation for histograms (r = 0.97) and good agreement among the four modalities with a mean WSS of 0.65 Pa in the original model, of 0.68 Pa in the CT-based model, of 0.67 Pa in the MRI based model, and of 0.69 Pa in the biplane angiography-based model. We can conclude that the biplane angiography-based reconstructions can be used for the WSS profiling of the coronary arteries. [ABSTRACT FROM AUTHOR]

Abstract  Computational fluid dynamics (CFD) methods based on in vivo three-dimensional vessel reconstructions have recently been shown to provide prognostically relevant hemodynamic data. However, the geometry reconstruction and the assessment of clinically relevant hemodynamic parameters may depend on the used imaging modality. This study compares geometric reconstruction and calculated wall shear stress (WSS) values based on magnetic resonance imaging (MRI) and computed tomography (CT). Both imaging methods were applied to a same 2.5-fold upscale silicon model of the left coronary artery (LCA) main bifurcation. The original model is an optically digitized post mortem vessel cast. This digitized geometry is considered as a “gold standard” or original geometry for the MRI versus CT comparative study. The use of the upscale model allowed generating a high resolution CT raw data set with voxel size of 0.156 × 0.156 × 0.36 mm3 and a high resolution MRI data set with an equivalent voxel size of 0.196 × 0.196 × 0.196 mm3 for corresponding in vivo conditions. MRI based reconstruction achieved a mean Hausdorff surface distance of 0.1 mm to the original geometry. This is 2.5 times better than CT based reconstruction with mean Hausdorff surface distance of 0.252 mm. A comparison of the calculated mean WSS shows good correlation (r = 0.97) and good agreement among the three modalities with a WSS of 0.65 Pa in the original model, of 0.68 Pa in the CT based model and of 0.67 Pa in the MRI based model. [ABSTRACT FROM AUTHOR]