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In this study, we propose a Convolutional Neural Network (CNN) with an assembly of non-linear fully connected layers for estimating body height and weight using a limited amount of data. This method can predict the parameters within acceptable clinical limits for most of the cases even when trained with limited data.

Objectives The ELANA® Heart Bypass creates a standardized sutureless anastomosis. Hereby, we investigate the influence of arteriotomy and graft size on coronary hemodynamics. Methods A computational fluid dynamics (CFD) model was developed. Arteriotomy size (standard 1.43 mm2; varied 0.94 – 3.6 mm2) and graft diameter (standard 2.5 mm; varied 1.5 – 5.0 mm) were independent parameters. Outcome parameters were coronary pressure and flow, and fractional flow reserve (FFR). Results The current size ELANA (arteriotomy 1.43 mm2) presented an estimated FFR 0.65 (39 mL/min). Enlarging arteriotomy increased FFR, coronary pressure, and flow. All reached a maximum once the arteriotomy (2.80 mm2) surpassed the coronary cross-sectional area (2.69 mm2, i.e. 1.85 mm diameter), presenting an estimated FFR 0.75 (46 mL/min). Increasing graft diameter was positively related to FFR, coronary pressure, and flow. Conclusion The ratio between the required minimal coronary diameter for application and the ELANA arteriotomy size effectuates a pressure drop that could be clinically relevant. Additional research and eventual lengthening of the anastomosis is advised. Graphical abstract

Accurate 3-D geometries of arteries and veins are important clinical data for diagnosis of arterial disease and intervention planning. Automatic segmentation of vessels in the transverse view suffers from the low lateral resolution and contrast. Convolutional neural networks are a promising tool for automatic segmentation of medical images, outperforming the traditional segmentation methods with high robustness. In this study, we aim to create a general, robust, and accurate method to segment the lumen–wall boundary of healthy central and peripheral vessels in large field-of-view freehand ultrasound (US) datasets. Data were acquired using the freehand US, in combination with a probe tracker. A total of ±36 000 cross-sectional images, acquired in the common, internal, and external carotid artery ( ${N} = 37$ ), in the radial, ulnar artery, and cephalic vein ( ${N} = 12$ ), and in the femoral artery ( ${N} = 5$ ) were included. To create masks (of the lumen) for training data, a conventional automatic segmentation method was used. The neural networks were trained on: 1) data of all vessels and 2) the carotid artery only. The performance was compared and tested using an open-access dataset. The recall, precision, DICE, and intersection over union (IoU) were calculated. Overall, segmentation was successful in the carotid and peripheral arteries. The Multires U-net architecture performs best overall with DICE = 0.93 when trained on the total dataset. Future studies will focus on the inclusion of vascular pathologies.

Survivors of myocardial infarction are at risk of life-threatening ventricular tachycardias (VTs) later in their lives. Current guidelines for implantable cardioverter defibrillators (ICDs) implantation to prevent VT-related sudden cardiac death is solely based on symptoms and left ventricular ejection fraction. Catheter ablation of scar-related VTs is performed following ICD therapy, reducing VTs, painful shocks, anxiety, depression and worsening heart failure. We postulate that better prediction of the occurrence and circuit of VT, will improve identification of patients at risk for VT and boost preventive ablation, reducing mortality and morbidity. For this purpose, multiple time-evolving aspects of the underlying pathophysiology, including the anatomical substrate, triggers and modulators, should be part of VT prediction models. We envision digital twins as a solution combining clinical expertise with three prediction approaches: evidence-based medicine (clinical practice), data-driven models (data science) and mechanistic models (biomedical engineering). This paper aims to create a mutual understanding between experts in the different fields by providing a comprehensive description of the clinical problem and the three approaches in an understandable manner, leveraging future collaborations and technological innovations for clinical decision support. Moreover, it defines open challenges and gains for digital twin solutions and discusses the potential of hybrid modelling.

Microfluidic designs are versatile examples of technology miniaturisation that find their applications in various cell biology research, especially to investigate the influence of environmental signals on cellular response dynamics. Multicellular systems operate in intricate cellular microenvironments where environmental signals govern well-orchestrated and robust responses, the understanding of which can be realized with integrated microfluidic systems. In this study, we present a fully automated and integrated microfluidic chip that can deliver input signals to single and isolated suspension or adherent cells in a precisely controlled manner. In respective analyses of different single cell types, we observe, in real-time, the temporal dynamics of caspase 3 activation during DMSO-induced apoptosis in single cancer cells (K562) and the translocation of STAT-1 triggered by interferon γ (IFNγ) in single fibroblasts (NIH3T3). Our investigations establish the employment of our versatile microfluidic system in probing temporal single cell signaling networks where alternations in outputs uncover signal processing mechanisms.

The central aortic pressure (CAP) provides insights into the prediction, prevention, diagnosis, and treatment of cardiovascular disease, but can't be directly measured non-invasively. Therefore, the development of a noninvasive CAP estimation method based on the non-invasively measured peripheral pressure waveform is critical for clinical decisions based on the CAP. Some existing widely applied methods, such as the generalized transfer function (GTF) method relating measured peripheral pressure to the CAP, do not or only partly account for inter-subject or intra-subject variability of the cardiovascular system. To overcome this pitfall, we propose a subject-specific central aortic pressure estimation method in this paper. The novel method presented can derive an accurate aortic pressure from the peripheral pressure based on an individualized pulse wave propagation model using a GTF method as a first guess. To develop a strategy to personalize a pulse wave propagation model one usually needs to optimize many input parameters. Therefore, we present a two-step approach with the screening method of Morris and the adaptive sparse generalized polynomial chaos expansion (agPCE) algorithm for the sensitivity analysis of the wave propagation model. First, for a-priori defined output of the model, a subset of important parameters is identified using the screening method of Morris. Next, a quantitative variance-based sensitivity analysis is performed using agPCE. This approach is applied to a 1D pulse wave propagation model to get the personalized parameters of the pulse wave propagation model for the estimation of a subject-specific central aortic pressure waveform and is validated with 26 patients. Compared with the GTF method, the proposed method showed better performance in estimating the central aortic pulse wave and predicting the parameters.

Vascular ultrasound imaging is inherently hampered by low lateral resolution and contrast. Steering of the ultrasound beams can be used to overcome these limitations in superficial artery imaging because the aperture-to-depth ratio is relatively high. However, in arteries located at larger depths, the steered beams do not overlap for larger steering angles. In this study, the ultrasound probe is physically translated over the abdomen to create large angles between acquisitions, while maintaining overlap on the abdominal aorta. In one phantom setup and 11 volunteers, 2-D cross-sectional multi-perspective ultrasound images of the abdominal aorta were acquired using seven angles between –45° and +45°. Automatic registration of the recorded images was performed by automatic feature detection of the aorta and spine. This automatic detection was successful in 62 out of 77 image sets. Compounded multi-perspective images showed an increase of contrast-to-noise ratios from 0.6 ± 0.1 to 1.2 ± 0.2 over the entire heart cycle in volunteers.

Purpose: Rupture of an arterosclerotic plaque in the carotid artery is a major cause of stroke. Biomechanical analysis of plaques is under development aiming to aid the clinician in the assessment of plaque vulnerability. Patient-specific three-dimensional (3D) geometry assessment of the carotid artery, including the bifurcation, is required as input for these biomechanical models. This requires a high-resolution, 3D, noninvasive imaging modality such as ultrasound (US). In this study, a high-resolution two-dimensional (2D) linear array in combination with a magnetic probe tracking device and automatic segmentation method was used to assess the geometry of the carotid artery. The advantages of using this system over a 3D ultrasound probe are its higher resolution (spatial and temporal) and its larger field of view. Methods: A slow sweep (v = ± 5 mm/s) was made over the subject’s neck so that the full geometry of the bifurcated geometry of the carotid artery is captured. An automated segmentation pipeline was developed. First, the Star-Kalman method was used to approximate the center and size of the vessels for every frame. Images were filtered with a Gaussian high-pass filter before conversion into the 2D monogenic signals, and multiscale asymmetry features were extracted from these data, enhancing low lateral wall-lumen contrast. These images, in combination with the initial ellipse contours, were used for an active deformable contour model to segment the vessel lumen. To segment the lumen–plaque boundary, Otsu’s automatic thresholding method was used. Distension of the wall due to the change in blood pressure was removed using a filter approach. Finally, the contours were converted into a 3D hexahedral mesh for a patient-specific solid mechanics model of the complete arterial wall. Results: The method was tested on 19 healthy volunteers and on 3 patients. The results were compared to manual segmentation performed by three experienced observers. Results showed an average Hausdorff distance of 0.86 mm and an average similarity index of 0.91 for the common carotid artery (CCA) and 0.88 for the internal and external carotid artery. For the total algorithm, the success rate was 89%, in 4 out of 38 datasets the ICA and ECA were not sufficient visible in the US images. Accurate 3D hexahedral meshes were successfully generated from the segmented images. Conclusions: With this method, a subject-specific biomechanical model can be constructed directly from a hand-held 2D US measurement, within 10 min, with a minimal user input. The performance of the proposed segmentation algorithm is comparable to or better than algorithms previously described in literature. Moreover, the algorithm is able to segment the CCA, ICA, and ECA including the carotid bifurcation in transverse B-mode images in both healthy and diseased arteries.

Significance: Intraplaque hemorrhage (IPH) is an important indicator of plaque vulnerability. Early detection could aid the prevention of stroke. Aim: We aim to detect IPH with single wavelength PA imaging in vivo and to improve image quality. Approach: We developed a singular value decomposition (SVD)-based filter to detect the nonstationary and stationary components in ultrasound data. A PA mask was created to detect stationary (IPH) sources. The method was tested ex vivo using phantoms and in vivo in patients. Results: The flow and IPH channels were successfully separated in the phantom data. We can also detect the PA signals from IPH and reject signals from the carotid lumen in vivo. Generalized contrast-to-noise ratio improved in both ex vivo and in vivo in US imaging. Conclusions: SVD-based filtering can successfully detect IPH using a single laser wavelength, opening up opportunities for more economical and cost-effective laser sources.

Aims Pressure loss versus transvalvular flow analysis challenges physiologic models of current aortic valve stenosis. New conceptual frameworks are needed to explain these real-world observations. Methods and results A patient-specific, 3D-printed, silicon model of a stenotic valve was placed inside an in-vitro haemodynamic model of the circulatory system. Instantaneous pressure and flow in the aorta and left ventricle were simulated according to measured patient specific parameters. Thereafter, a realistic transcatheter aortic valve was implanted (TAVI) in the model. Simulated post-TAVI mean pressure gradients resembled patient observations (3.7 ± 0.7 mmHg vs 6.7 ± 2.3 mmHg), but pre-TAVI measurements underestimated the pressure gradient (35.1 ± 0.6 mmHg vs 45.3 ± 1.5 mmHg). Conclusion Patient-specific 3D-printed stenotic aortic valve models could simulate baseline haemodynamics. A TAVI procedure was successfully performed on the 3D silicone rubber valve in a physiologic in-vitro model. Pre-TAVI haemodynamics in the model underestimated in-patient mean pressure gradient, whereas post TAVI pressure gradient was predicted correctly with the TAVI valve inside the 3D printed model. This study shows that these types of models could be used to study AS hemodynamics with the TAVI valve inside the 3D printed model. Improvements in the 3D-printed model, like addition of calcification and fine-tuning of the haemodynamic model, could further enhance accuracy of the simulation.

Recent studies have shown the efficacy of myocardial strain estimated using speckle tracking echocardiography (STE) in predicting response to cardiac resynchronisation therapy. This study focuses on circumferential strain patterns, comparing STE-acquired strains to tagged-magnetic resonance imaging (MRI-T). Second, the effect of regularisation was examined. Two-dimensional parasternal ultrasound (US) and MRI-T data were acquired in the left ventricular short-axis view of canines before (n = 8) and after (n = 9) left bunch branch block (LBBB) induction. US-based strain analysis was performed on Digital Imaging and Communications in Medicine data at the mid-level using three overall methods ("Commercial software," "Basic block-matching," "regularised block-matching"). Moreover, three regularisation approaches were implemented and compared. MRI-T analysis was performed using SinMod. Normalised regional circumferential strain curves, based on standard six or septal/lateral segments, were analysed and cross-correlated with MRI-T data. Systolic strain (SS) and septal rebound stretch (SRS) were calculated and compared. Overall agreement of normalised circumferential strain was good between all methods on a global and regional level. All STE methods showed a bias (>= 4% strain) toward higher SS estimates. Pre-LBBB, septal and lateral segment correlation was excellent between the Basic (mean rho = 0.96) and regularised (mean rho = 0.97) methods and MRI-T. The Commercial method showed a significant discrepancy between the two walls (septal rho = 0.94, lateral rho = 0.68). Correlation with MRI-T reduced between pre- and post-LBBB (Commercial rho = 0.79, Basic rho = 0.82, mean regularised rho = 0.86). Septal strain patterns and SRS varied with the STE software and type of regularisation, with all STE methods estimating nonzero SRS values pre-LBBB. Absolute values showed moderate agreement, with a bias for higher strain from STE. SRS varied with the type of software and extra regularisation applied. Open efforts are needed to understand the underlying causes of differences between STE methods before standardisation can be achieved. This is particularly important given the apparent clinical value of strain-based parameters such as SRS. (C) 2019 The Author(s). Published by Elsevier Inc. on behalf of World Federation for Ultrasound in Medicine & Biology.

Aims Using non-invasive 3D ultrasound, peak wall stress (PWS) and aortic stiffness can be evaluated, which may provide additional criteria in abdominal aortic aneurysm (AAA) risk assessment. In this study, these measures were determined in both young and age-matched individuals, and AAA patients while its relation to age, maximum diameter, and growth was assessed statistically. Methods and results Time-resolved 3D-US data were acquired for 30 volunteers and 65 AAA patients. The aortic geometry was segmented, and tracked over the cardiac cycle using 3D speckle tracking to characterize the wall motion. Wall stress analysis was performed using finite element analysis. Model parameters were optimized until the model output matched the measured 3D displacements. A significant increase in aortic stiffness was measured between the age-matched volunteers [median 0.58, interquartile range (IQR) 0.48-0.71 kPa ...m] and the small AAA patients (median 1.84, IQR 1.38-2.46 kPa ...m; P < 0.001). In addition, an increase in aortic stiffness was evaluated between the small (30-39 mm) and large (≥50 mm) AAAs (median 2.72, IQR 1.99-3.14 kPa ...m; P = 0.01). The 99th percentile wall stress showed a positive correlation with diameter (Ï = 0.73, P < 0.001), and significant differences between age-matched volunteers and AAA patients. Conclusion The AAA pathology causes an early and significant increase in aortic stiffness of the abdominal aorta, even after correcting for the expected effect of ageing and differences in arterial pressure. Moreover, some AAAs revealed relatively high PWS, although the maximum diameter was below the threshold for surgical repair. Using the current method, these measures become available during follow-up, which could improve AAA rupture risk assessment.

Current aortic stenosis severity grading is based mainly on the local properties of the stenotic valve, such as pressure gradient or jet velocity. Success rates of valve replacement therapy are still suboptimal, so alternative grading of AS should be investigated. We suggest the efficiency of power transfer from the left ventricle to the aorta, as it takes into account heart, valve and circulatory system. Left ventricular and circulatory power were estimated using a 0D model, which was optimised to patient data: left ventricular and aortic pressure, aortic flow and diastolic left ventricular volume. Optimisation was performed using a data assimilation method. These data were available in rest as well as chemically induced exercise for twelve patients. Using this limited data set, we showed that aortic valve efficiency is highly heterogeneous between patients, but also often dependent on the haemodynamic load. This indicates that power transfer efficiency is a highly interesting metric for further research in aortic stenosis.

Dynamic imaging of the skeletal muscles used to be strenuous and often impossible to perform manually. Accordingly, long-term dynamic musculoskeletal imaging has not been performed. The feasibility of long-term dynamic musculoskeletal functional analysis using hands-free ultrasound will be demonstrated in ten healthy endurance runners. After every kilometer, the vastus lateralis muscle was imaged whilst running using a fixated probe connected to a smart phone. The image quality was quantified by estimation of the probe-skin contact preservation and the field-of-view stability. Moreover, the pennation angles and muscle thicknesses were computed automatically. Long-term dynamic acquisition was successful in nine out of ten runners. Probe-skin contact loss ranged between 0 and 57% of the gait cycle. The biggest change in field-of-view occurred during the first kilometer with an average decline in complex-wavelet structural similarity index of 0.21, followed by an onward total decrease of 0.09, on average. The mean pennation angle and thickness were approximately constant, with the average fluctuation being 0.94 degrees and 0.11 cm, respectively. The feasibility of long-term musculoskeletal function analysis has been demonstrated, with probe-skin contact loss the main limiting factor. Dynamic, hands-free ultrasound might enable research for a more profound insight in the prevention and rehabilitation of musculoskeletal injuries.

Current decision-making for clinical intervention of abdominal aortic aneurysms (AAAs) is based on the maximum diameter of the aortic wall, but this does not provide patient-specific information on rupture risk. Ultrasound (US) imaging can assess both geometry and deformation of the aortic wall. However, low lateral contrast and resolution are currently limiting the precision of both geometry and local strain estimates. To tackle these drawbacks, a multiperspective scanning mode was developed on a dual transducer US system to perform strain imaging at high frame rates. Experimental imaging was performed on porcine aortas embedded in a phantom of the abdomen, pressurized in a mock circulation loop. US images were acquired with three acquisition schemes: Multiperspective ultrafast imaging, single perspective ultrafast imaging, and conventional line-by-line scanning. Image registration was performed by automatic detection of the transducer surfaces. Multiperspective images and axial displacements were compounded for improved segmentation and tracking of the aortic wall, respectively. Performance was compared in terms of image quality, motion tracking, and strain estimation. Multiperspective compound displacement estimation reduced the mean motion tracking error over one cardiac cycle by a factor 10 compared to conventional scanning. Resolution increased in radial and circumferential strain images, and circumferential signal-to-noise ratio (SNRe) increased by 10 dB. Radial SNRe is high in wall regions moving towards the transducer. In other regions, radial strain estimates remain cumbersome for the frequency used. In conclusion, multiperspective US imaging was demonstrated to improve motion tracking and circumferential strain estimation of porcine aortas in an experimental set-up.

OBJECTIVE: Osteoarthritis (OA) is a chronic joint disease characterized by progressive degradation of cartilage. It affects more than 10% of the people aged over 60 years-old worldwide with a rising prevalence due to the increasingly aging population. OA is a major source of pain, disability, and socioeconomic cost. Currently, the lack of effective diagnosis and affordable imaging options for early detection and monitoring of OA presents the clinic with many challenges. Spectroscopic Photoacoustic (sPA) imaging has the potential to reveal changes in cartilage composition with different degrees of damage, based on optical absorption contrast.DESIGN: In this study, the capabilities of sPA imaging and its potential to characterize cartilage damage were explored. To this end, 15 pieces of cartilage samples from patients undergoing a total joint replacement were collected and were imaged ex vivo with sPA imaging at a wide optical spectral range (between 500 nm and 1300 nm) to investigate the photoacoustic properties of cartilage tissue. All the PA spectra of the cartilage samples were analyzed and compared to the corresponding histological results.RESULTS: The collagen related PA spectral changes were clearly visible in our imaging data and were related to different degrees of cartilage damage. The results are in good agreement with histology and the current gold standard, i.e., the Mankin score.CONCLUSIONS: This study demonstrates the potential and possible clinical application of sPA imaging in OA.

Patient outcome in trans‐aortic valve implantation (TAVI) therapy partly relies on a patient's haemodynamic properties that cannot be determined from current diagnostic methods alone. In this study, we predict changes in haemodynamic parameters (as a part of patient outcome) after valve replacement treatment in aortic stenosis patients. A framework to incorporate uncertainty in patient‐specific model predictions for decision support is presented. A 0D lumped parameter model including the left ventricle, a stenotic valve and systemic circulatory system has been developed, based on models published earlier. The unscented Kalman filter (UKF) is used to optimize model input parameters to fit measured data pre‐intervention. After optimization, the valve treatment is simulated by significantly reducing valve resistance. Uncertain model parameters are then propagated using a polynomial chaos expansion approach. To test the proposed framework, three in silico test cases are developed with clinically feasible measurements. Quality and availability of simulated measured patient data are decreased in each case. The UKF approach is compared to a Monte Carlo Markov Chain (MCMC) approach, a well‐known approach in modelling predictions with uncertainty. Both methods show increased confidence intervals as measurement quality decreases. By considering three in silico test‐cases we were able to show that the proposed framework is able to incorporate optimization uncertainty in model predictions and is faster and the MCMC approach, although it is more sensitive to noise in flow measurements. To conclude, this work shows that the proposed framework is ready to be applied to real patient data., In this study, we aim to provide a framework to predict changes in haemodynamic parameters (as a part of patient outcome) after valve replacement treatment in aortic stenosis. The framework involves uncertain input parameter optimization using an unscented Kalman filter approach. Valve replacement treatment is then simulated, and uncertainties are propagated via polynomial chaos expansions. The framework is able to capture measurement quality in prediction confidence intervals and is ready to be applied to patient data. Novelty Statement We developed a lumped parameter model to predict changes in haemodynamic parameters after valve replacement therapy in aortic stenosisWe showed a data assimilation approach (Unscented Kalman Filter) is suitable for parameter optimization for this model based on available clinical data, with estimated optimization uncertaintyWe expanded parameter optimization via Unscented Kalman Filtering via sensitivity‐based weightingWe coupled uncertain parameter optimization with a polynomial chaos expansion approach to propagate uncertain parameters in treatment prediction

Left ventricular assist devices (LVAD) provide cardiac support to patients with advanced heart failure. Methods that can directly measure remaining LV function following device implantation do not currently exist. Previous studies have shown that a combination of loading (LV pressure) and deformation (strain) measurements enables quantitation of myocardial work. We investigated the use of ultrasound (US) strain imaging and pressure–strain loop analysis in LVAD-supported hearts under different hemodynamic and pump unloading conditions, with the aim of determining LV function with and without LVAD support. Ex vivo porcine hearts (n = 4) were implanted with LVADs and attached to a mock circulatory loop. Measurements were performed at hemodynamically defined “heart conditions” as the hearts deteriorated from baseline. Hemodynamic (including LV pressure) and radio-frequency US data were acquired during a pump-ramp protocol at speeds from 0 (with no pump outflow) to 10 000 revolutions per minute (rpm). Regional circumferential (εcirc) and radial (εrad) strains were estimated over each heart cycle. Regional ventricular dyssynchrony was quantitated through time-to-peak strain. Mean change in LV pulse pressure and εcirc between 0 and 10 krpm were −21.8 mm Hg and −7.24% in the first condition; in the final condition −46.8 mm Hg and −19.2%, respectively. εrad was not indicative of changes in pump speed or heart condition. Pressure–strain loops showed a degradation in the LV function and an increased influence of LV unloading: loop area reduced by 90% between 0 krpm in the first heart condition and 10 krpm in the last condition. High pump speeds and degraded condition led to increased dyssynchrony between the septal and lateral LV walls. Functional measurement of the LV while undergoing LVAD support is possible by using US strain imaging and pressure–strain loops. This can provide important information about remaining pump function. Use of novel LV pressure estimation or measurement techniques would be required for any future use in LVAD patients.

Background Exercise stress echocardiography is clinically used to assess cardiovascular diseases. For accurate cardiac evaluation, a stable field-of-view is required. However, transducer orientation and position are difficult to preserve. Hands-free acquisitions might provide more consistent and reproducible results. In this study, the field-of-view stability and variability of hands-free acquisitions are objectively quantified in a comparison with manually obtained images, based on image structural and feature similarities. In addition, the feasibility and consistency of hands-free strain imaging is assessed. Methods In twelve healthy males, apical and parasternal images were acquired hands-free, using a fixation device, and manually, during semi-supine exercise sessions. In the final ten seconds of every exercise period, the image structural similarity and cardiac feature consistency were computed using a steerable pyramid employing complex, oriented wavelets. An algorithm discarding images displaying lung artifacts was created. Hands-free strain consistency was analyzed. Results Hands-free acquisitions were possible in 9 of the 12 subjects, whereas manually 10 out of 12 could be imaged. The image structural similarity was significantly improved in the hands-free apical window acquisitions (0.91 versus 0.82), and at least equally good in the parasternal window (0.90 versus 0.82). The change in curvature and orientation of the interventricular septum also appeared to be lower in the hands-free acquisitions. The variability in field-of-view was similar in both acquisitions. Longitudinal, septal strain was shown to be at least as consistent when obtained hands-free compared to manual acquisitions. Conclusions The field-of-view was shown to be more or equally stable and consistent in the hands-free data in comparison to manually obtained images. The variability was similar, thus respiration- and exercise-induced motions were comparable for manual and hands-free acquisitions. Additionally, the feasibility of hands-free strain has been demonstrated. Furthermore, the results suggest the hands-free measurements to be more reproducible, though further analysis is required.

Background Current clinical guidelines for surgical repair of abdominal aortic aneurysms (AAAs) are primarily based on maximum diameter assessment. From a biomechanical point of view, not only the diameter but also peak wall stresses will play an important role in rupture risk assessment. These methods require patient specific geometry which typically uses computed tomography (CT) or magnetic resonance imaging. Recently, wall stress analysis based on 3D ultrasound (US) has been proposed, and shows promising results. However, the major limitations in these studies were the use of manual segmentation and the limiting field of view of US. Therefore in this study, the AAA is imaged with multiperspective 3D ultrasound, merged to obtain a large field of view, and afterwards automatically segmented. Geometry and wall stress results were validated using CT imaging. Methods Three dimensional US and CT data were available for 40 AAA patients (maximum diameter 34–61 mm). The full US based AAA geometry was determined using automatic segmentation, and when the aneurysm exceeded a single 3D volume, automatic fusion of multiple 3D US volumes was used. Wall stress analysis was performed for all AAA patients and percentile wall stresses were derived. The accuracy of the US based geometry and wall stress prediction was measured by comparison with CT data. Results Estimated geometries derived from 3D US and CT data showed good similarity, with an overall median similarity index (SI) of 0.89 and interquartile range of 0.87–0.92, whereas the median Hausdorff distances (HD), a measure for the maximum local mismatch, was 4.6 (4.0–5.9) mm for all AAA geometries. Thereby, the wall stress results based on merged multiperspective 3D US data revealed a greater similarity to CT than single 3D US data. Conclusion This study showed that large volume geometry assessment of AAAs using multiperspective 3D ultrasound, segmentation and fusion, and wall stress analysis is feasible in a robust and labour efficient manner.

Photoacoustic imaging (PAI) is a promising imaging modality due to its high optical specificity. However, the low signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of in vivo PA images are major challenges that prevent PAI from finding its place in clinics. This paper investigates the merit of spatial compounding of PA images in arterial phantoms and the achievable improvements of SNR, when in vivo conditions are mimicked. The analysis of the compounding technique was performed on a polyvinyl alcohol vessel phantom with black threads embedded in its wall. The in vivo conditions were mimicked by limiting the rotation range in ±30°, adding turbid surrounding medium, and filling the lumen with porcine blood. Finally, the performance of the technique was evaluated in ex vivo human carotid plaque samples. Results showed that spatial compounding elevates the SNR by 5–10 dB and CNR by 1–5 dB, depending on the location of the absorbers. This paper elucidates prospective in vivo PA characterization of carotid plaques by proposing a method to enhance PA image quality.

The potential impact of hemodynamic and vascular wall models on the diagnosis, treatment, and wellbeing of thousands of patients suffering from cardiovascular diseases, is tremendous. Despite the potential impact, it is not straightforward to use these models for individualized diagnosis and intervention planning (model predictive decision support). Major challenges are the adaptation of the models to patient-specific conditions and the necessary uncertainty assessment of the simulated outcome measures. In this manuscript, we will present our view on what is needed to make cardiovascular models suitable for clinical decision support. Hereto, we will first describe how an engineer might support clinical decisions. Secondly, we will give a description of the challenges faced by the engineers. Finally we will introduce an innovative approach in which model personalization is guided by sensitivity analysis, and in which the effect of input uncertainties and model assumptions (acknowledged model errors) on model predictions are considered during model corroboration. The approach is illustrated by two different vascular cases. Hopefully our view will be useful in bringing models from the pre-clinical phase to the clinical phase where they will actually be used for model predictive decision support. (C) 2017 Published by Elsevier B.V.

Aims: Videodensitometric assessment of aortography provides a periprocedural quantitation of prosthetic valve regurgitation (PVR) after transcatheter aortic valve implantation. We sought to compare the videodensitometric parameters of PVR severity to the regurgitation fraction (RF) in a controlled in vitro setting. Methods and results: In a mock circulation system, a transcatheter balloon-expandable valve inserted at the aortic valve position was gradually deformed to induce different grades of paravalvular leakage and the RF was measured with a transonic flow probe. Contrast aortography was performed and the following videodensitometric parameters were generated: left ventricle aortic regurgitation (LV-AR), LV outflow tract AR (LVOT-AR), quantitative regurgitation assessment (qRA) index, relative maximum density (relative max), and maximum upslope of the LV time-density curve. The correlation was substantial between videodensitometric parameters (LV-AR, LVOT-AR, qRA index, relative max, and maximum upslope) and RF (r 2=0.96, 0.96, 0.93, 0.87, and 0.93; p2=0.99) with a mean difference of 1.92% (95% limits of agreement: ±2.83). The correlations of LV-AR and LVOT-AR with RF were stronger when more than one cardiac cycle was included in the analysis (one cycle: r 2=0.85 and r 2=0.83; four cycles: r 2=0.96 and r 2=0.96, for LV-AR and LVOT-AR, respectively). Including more cycles beyond four did not improve accuracy. Conclusions: Quantitative assessment of PVR by videodensitometry of aortograms strongly correlates with the actual RF in a controlled in vitro setting. Accuracy is improved by including more than one cardiac cycle in the analysis.

In the above article [1], one error, (1), was found which has an impact on the results and interpretation of the image quality that was described in four sentences, (2)-(5). This correction does not mitigate the overall conclusion of this work, but does positively support improvements of the proposed method (multi-perspective ultrafast imaging) in comparison with the standard method (focused line-by-line imaging).

Aims: In the minimalist transcatheter aortic valve implantation (TAVI) era, the usage of transoesophageal echocardiography has become restricted. Conversely, aortography has gained clinical ground in quantifying prosthetic valve regurgitation (PVR) during the procedure. In a mock circulation system, we sought to compare the contrast volume required and the accuracy of aortographic videodensitometric PVR assessment using a synchronised diastolic and standard (non-synchronised) injection aortography. Methods and results: Synchronised diastolic injection triggered by the signal stemming from the mock circulation was compared with standard non-synchronised injection. A transcatheter heart valve was implanted and was deformed step by step by advancing a screw perpendicularly to the cage of the valve in order to create increasing PVR. Quantitative measurement of PVR was derived from time-density curves of both a reference area (aortic root) and a region of interest (left ventricle) developed by a videodensitometric software. The volume of contrast required for the synchronised diastolic injection was significantly less than in the non-synchronised injection (8.1 [7.9-8.5] ml vs. 19.4 [19.2-19.9] ml, p

Fibrin is a plasma protein with a central role in blood clotting and wound repair.Upon vascular injury, fibrin forms resilient fibrillar networks (clots) via a multi-step self assembly process, from monomers, to double-stranded protofibrils, to a branched network of thick fibers. In vitro, fibrin self-assembly is sensitive to physicochemical conditions like the solution pH and ionic strength, which tune the strength of the non-covalent driving forces. Here we report a surprising finding that the buffer—which is necessary to control the pH and is typically considered to be inert—also significantly influences fibrin self-assembly. We show by confocal microscopy and quantitative light-scattering that various common buffering agents have no effect on the initial assembly of fibrin monomers into protofibrils but strongly hamper the subsequent lateral association of protofibrils into thicker fibers. At 3 mg/ml fibrin, the averagenumber of protofibrils per fiber drops nearly 10-fold, from 180 in the presence of 20 mM HEPES to only 20 in the presence of 200 mM HEPES. By using different enzymes to initiate fibrin self assembly, we reveal that the mechanism of buffer-induced changes in fibrin assembly involves weakening of the interactions between the so-called αC-region, which are long flexible appendages on fibrin that couple adjacent protofibrils. We further find that the structural changes are independent of the molecular structure of the buffering agents and even occur in fibrin networks formed from platelet-poor plasma, suggesting that buffers act by changing the hydrogen bonding network structure of the hydration layer surrounding fibrin. This buffer mediated decrease in protofibril bundling results in a marked reduction in the permeability of fibrin networks. Yet, the buffers only weakly influence the elastic modulus of fibrin networksbecause the effect of higher fiber density is cancelled out by the effect of the smaller stiffness of thinner fibers. Buffers can therefore be used as a tuning parameter to independently control the elastic properties and the permeability of fibrin networks, which is useful in studies of cell adhesion and migration. Our work raises the possibility that fibrin assembly in vivo may be regulated by variations in the acute-phase levels of bicarbonate and phosphate, which act as physiological buffering agents of blood pH. Moreover, our findings add a striking new example of buffer-induced effects on biomolecular self-assembly to recent findings for a range of proteins and lipids.

Assessment of microvasculature and tissue perfusion can provide diagnostic information on local or systemic diseases. Photoacoustic (PA) imaging has strong clinical potential because of its sensitivity to hemoglobin. We used a hand-held PA probe with integrated diode lasers and examined its feasibility and validity in the detection of increasing blood volume and (sub) dermal vascularization. Blood volume detection was tested in custom-made perfusion phantoms. Results showed that an increase of blood volume in a physiological range of 1.3% to 5.4% could be detected. The results were validated with power Doppler sonography. Using a motorized scanning setup, areas of the skin were imaged at relatively short scanning times (

In the clinic, the cardiotocogram (CTG), the combined registration of fetal heart rate (FHR) and uterine contractions, is used to predict fetal well-being. Amongst others, fetal heart rate variability (FHRV) is an important indicator of fetal distress. In this study we add FHRV to our previously developed CTG simulation model, in order to improve its use as a research and educational tool.We implemented three sources of variability by applying either 1/f or white noise to the peripheral vascular resistance, baroreceptor output, or efferent vagal signal. Simulated FHR tracings were evaluated by visual inspection and spectral analysis.All power spectra showed a 1/f character, irrespective of noise type and source. The clinically observed peak near 0.1 Hz was only obtained by applying white noise to the different sources of variability. Similar power spectra were found when peripheral vascular resistance or baroreceptor output was used as source of variability. Sympathetic control predominantly influenced the low frequency power, while vagal control influenced both low and high frequency power. In contrast to clinical data, model results did not show an increase of FHRV during FHR decelerations. Still, addition of FHRV improves the applicability of the model as an educational and research tool.(C) 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Variations in systemic properties of the arterial tree, such as aging-induced vessel stiffness, can alter the shape of pressure and flow waveforms. As a consequence, the hemodynamics around a cerebral aneurysm change, and therefore, also the corresponding in- and outlet boundary conditions (BCs) used for three-dimensional (3D) calculations of hemodynamic indices. In this study, we investigate the effects of variations in systemic properties on wall shear stress (WSS) indices of a cerebral aneurysm. We created a virtual patient database by varying systemic properties within physiological ranges. BCs for 3D-CFD simulations were derived using a pulse wave propagation model for each realization of the virtual database. WSS indices were derived from the 3D simulations and their variabilities quantified. Variations in BCs, caused by changes in systemic properties, yielded variabilities in the WSS indices that were of the same order of magnitude as differences in these WSS indices between ruptured and unruptured aneurysms. Sensitivity analysis showed that the systemic properties impacted both in- and outlet BCs simultaneously and altered the WSS indices. We conclude that the influence of variations in patient-specific systemic properties on WSS indices should be evaluated when using WSS indices in multidisciplinary rupture prediction models.

The aim of this position paper is to provide a brief overview of the current status of cardiovascular modelling and of the processes required and some of the challenges to be addressed to see wider exploitation in both personal health management and clinical practice. In most branches of engineering the concept of the digital twin, informed by extensive and continuous monitoring and coupled with robust data assimilation and simulation techniques, is gaining traction: the Gartner Group listed it as one of the top ten digital trends in 2018. The cardiovascular modelling community is starting to develop a much more systematic approach to the combination of physics, mathematics, control theory, artificial intelligence, machine learning, computer science and advanced engineering methodology, as well as working more closely with the clinical community to better understand and exploit physiological measurements, and indeed to develop jointly better measurement protocols informed by model-based understanding. Developments in physiological modelling, model personalisation, model outcome uncertainty, and the role of models in clinical decision support are addressed and ‘where-next’ steps and challenges discussed. © 2019. This is the authors' manuscript to the article.

The cardiotocogram (CTG) is commonly used to monitor fetal well-being during labor and delivery. It shows the input (uterine contractions) and output (fetal heart rate, FHR) of a complex chain of events including hemodynamics, oxygenation and regulation. Previously we developed a mathematical model to obtain better understanding of the relation between CTG signals and vital, but clinically unavailable signals such as fetal blood pressure and oxygenation. The aim of this study is to improve this model by reducing complexity of submodels where parameter estimation is complicated (e.g. regulation) or where less detailed model output is sufficient (e.g. cardiac function), and by using a more realistic physical basis for the description of other submodels (e.g. vessel compression).Evaluation of the new model is performed by simulating the effect of uterine contractions on FHR as initiated by reduction of uterine blood flow, mediated by changes in oxygen and blood pressure, and effected by the chemoreflex and baroreflex. Furthermore the ability of the model to simulate uterine artery occlusion experiments in sheep is investigated.With the new model a more realistic FHR decrease is obtained during contraction-induced reduction of uterine blood flow, while the reduced complexity and improved physical basis facilitate interpretation of model results and thereby make the model more suitable for use as a research and educational tool.

Continuous-flow left ventricular assist devices (CF-LVADs) generally operate at a constant speed, which reduces pulsatility in the arteries and may lead to complications such as functional changes in the vascular system, gastrointestinal bleeding, or both. The purpose of this study is to increase the arterial pulse pressure and pulsatility by controlling the CF-LVAD flow rate. A MicroMed DeBakey pump was used as the CF-LVAD. A model simulating the flow rate through the aortic valve was used as a reference model to drive the pump. A mock circulation containing two synchronized servomotor-operated piston pumps acting as left and right ventricles was used as a circulatory system. Proportional-integral control was used as the control method. First, the CF-LVAD was operated at a constant speed. With pulsatile-speed CF-LVAD assistance, the pump was driven such that the same mean pump output was generated. Continuous and pulsatile-speed CF-LVAD assistance provided the same mean arterial pressure and flow rate, while the index of pulsatility increased significantly for both arterial pressure and pump flow rate signals under pulsatile speed pump support. This study shows the possibility of improving the pulsatility of CF-LVAD support by regulating pump speed over a cardiac cycle without reducing the overall level of support.

Recent approaches to the in vitro experimental study of cardiac fluid mechanics involve the use of whole biological structures to investigate in the lab novel therapeutic approaches for the treatment of heart pathologies. To enhance reliability and repeatability, the influence of the actuation strategy of the experimental apparatuses on the biomechanics of biological structures needs to be assessed. Using echography and intracardiac high-speed imaging, we compared the mitral valve (MV) anatomo-functional features (coaptation areas/lengths, papillary muscles-valvular plane distances) in two passive-beating-heart mock loops with internal (IPML) or external (EPML) pressurization of the ventricular chamber. Both apparatuses showed fluid dynamic conditions that closely resembled the physiology. The MVs analyzed in the EPML presented coaptation areas and lengths that were systematically higher, and exhibited greater variability from early-to peak-systole, as compared to those in the IPML. Moreover, in the EPML, the MV leaflets exhibited a convexity with high curvature toward the atrium. With the IPML, MV coaptation lengths ranged similar to available clinical data and the papillary muscles-valve plane distances were more stable throughout systole. In conclusion, both the apparatuses allow for reproducing in vitro the left heart hemodynamics, in terms of flow rates and pressures, with proper mitral valve continence. Results suggest that the IPML is more suitable for replicating the physiological MV functioning, while the EPML may have more potential as a model for the study of MV pathologies. IPEM.

OBJECTIVE: Quantifying the absolute coronary blood flow can be done using continuous infusion thermodilution requiring a dedicated infusion catheter. Up to now, there has been little insight into the effect of small variabilities in the physical parameters on the temperature gradient along this catheter. The key goal of this study is to develop and validate a computer model that predicts the temperature of the infusion fluid at the infusion site of the infusion catheter. A secondary goal is to gain insight into the influence of physical variations for the individual patient on the calculated blood flow rate. APPROACH: A numerical model of the temperature in the catheter was built using the convection-diffusion equation and validated using an in vitro setup. A sensitivity analysis was performed to investigate the influence of the catheter path inside the body and the temperature of the infusion fluid at different infusion rates. These results were compared to in vivo measurements of 94 patients. Finally, the variation in the computed blood flow rate is estimated considering an average patient, using small variations in the physical parameters. MAIN RESULTS: The computed temperature corresponded well with the in vitro measurements, since a maximal difference of 1.5% was observed. The length of the catheter path inside the body had the most influence on the temperature of the infusion fluid at the infusion site. Moreover, temperatures from the numerical model were similar to the results from in vivo measurements. By varying the length of the catheters with 0.04 m, the largest deviation in the calculated blood flow was 33.3 ml/min. SIGNIFICANCE: Insight is gained into the influence of physical variations on the temperature of the infusion fluid at the infusion site of the catheter using thermodilution. The developed numerical model can possibly be used to reduce time in estimating the blood flow rate.

Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI) images is an essential step for calculation of clinical indices such as stroke volume, ejection fraction. In this paper, a new automatic LV segmentation method combines a Hierarchical Extreme Learning Machine (H-ELM) and a new location method is developed. An H-ELM can achieve more compact and meaningful feature representations and learn the segmentation task from the ground truth. A new automatic LV location method is integrated to improve the accuracy of classification and reduce the cost of segmentation. Experimental results (including 30 cases, 10 cases for training, 20 cases for testing) show that the mean absolute deviation of images segmented by our proposed method is about 67.9, 81.3 and 98.7% of those images segmented by the level set, the SVM and Hu’s method, respectively. The mean maximum absolute deviation of images segmented by our proposed method is about 63.5, 77.3 and 98.0% of those images segmented by the level set, the SVM and Hu’s method, respectively. The mean dice similarity coefficient of images segmented by our proposed method is about 13.7, 9.3 and 0.5% higher than that of those images segmented by the level set, the SVM and Hu’s method, respectively. The mean speed of our proposed method is about 38.3, 6.7 and 23.8 times faster than that of the level set, the SVM and Hu’s method, respectively. The standard deviation of our proposed method is the lowest among four methods. The results validate that our proposed method is efficient and satisfactory for the LV segmentation.

A benchmark study by Boileau et al tested 6 commonly used numerical schemes for 1D wave propagation, for their ability to capture the main features of pressure, flow, and area waveforms in large arteries. While all numerical schemes showed good agreement in pressure and flow waveforms for smaller arterial networks, the simplified trapezium rule method proposed by Kroon et al showed an overestimation for the systolic pressure of 1% in proximal regions and an underestimation of 3% in distal regions in comparison with the 5 other schemes when using a larger arterial network, published as the ADAN56 model. The authors attributed this difference to the neglection of the dynamic part of the pressure at vessel junctions. Carson et al resolved these differences by proposing 2 methods to implement the dynamic part of the pressure in the simplified trapezium rule method scheme. In the present study, an alternative method is introduced extending the work by Kroon et al. This alternative method consists of a new 0D element, which is placed at vessel junctions. The strength of this new element is the ease of implementation and its flexible coupling with other elements, without introducing additional degrees of freedom or the need of a penalty function. This new approach is compared with 5 other numerical schemes, which already have the dynamic part of the pressure incorporated. The new method shows excellent agreement with these schemes for the ADAN56 model.

Hypothermia, if provided before coronary reperfusion, reduces infarct size in animal models of acute myocardial infarction (AMI). Translation to humans has failed so far, because the target temperature is not reached in time within the endangered myocardium using systemic hypothermia method. Hence, a clinically applicable method has been developed to provide intracoronary hypothermia using cold saline, selectively infused locally into the infarct area. In this study, a lumped parameter model has been designed to support the clinical method and to describe this myocardial cooling process mathematically. This model is able to predict the myocardial temperature changes over time, which cannot be measured, based on the temperature and flow of the intracoronary injected cold saline and coronary arterial blood. It was validated using data from an isolated beating porcine heart model and applied on data from patients with AMI undergoing intracoronary hypothermia. In prospect, the computational model may be used as an assistive tool to calculate the patient specific flow rate and temperature of saline required for reliable achievement of the target myocardial temperature in the hypothermia enhanced clinical treatment of AMI.

Photoacoustic imaging (PAI) is a promising imaging modality due to its high optical specificity. However, the low signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of in vivo PA images are major challenges that prevent PAI from finding its place in clinics. This paper investigates the merit of spatial compounding of PA images in arterial phantoms and the achievable improvements of SNR, when in vivo conditions are mimicked. The analysis of the compounding technique was performed on a polyvinyl alcohol vessel phantom with black threads embedded in its wall. The in vivo conditions were mimicked by limiting the rotation range in ±30°, adding turbid surrounding medium, and filling the lumen with porcine blood. Finally, the performance of the technique was evaluated in ex vivo human carotid plaque samples. Results showed that spatial compounding elevates the SNR by 5-10 dB and CNR by 1-5 dB, depending on the location of the absorbers. This paper elucidates prospective in vivo PA characterization of carotid plaques by proposing a method to enhance PA image quality.

OBJECTIVES This study sought to compare a new quantitative angiographic technique to cardiac magnetic resonance-derived regurgitation fraction (CMR-RF) for the quantification of prosthetic valve regurgitation (PVR) after transcatheter aortic valve replacement (TAVR). BACKGROUND PVR after TAVR is challenging to quantify, especially during the procedure. METHODS Post-replacement aortograms in 135 TAVR recipients were analyzed offline by videodensitometry to measure the ratio of the time-resolved contrast density in the left ventricular outflow tract to that in the aortic root (videodensitometric aortic regurgitation [VD-AR]). CMR was performed within an interval of = 10% corresponded to > mild PVR as defined by CMR-RF (area under the curve: 0.94; p = 25% corresponded to moderate-to-severe PVR (area under the curve: 0.99; p = 0.004; sensitivity 100%, specificity 98%). Intraobserver reproducibility was excellent for both techniques (for CMR-RF, intraclass correlation coefficient: 0.91, p

Background Exercise is accepted as an important contribution to the rehabilitation of patients with cardiovascular disease (CVD). This study aims to better understand the possible causes for lack of consensus and reviews the effects of three exercise modalities (aerobic, resistance and combined exercise) on central hemodynamics, arterial stiffness and cardiac function for better rehabilitation strategies in CVD. Methods The electronic data sources, Cochrane Library, MEDLINE, Web of Science, EBSCO (CINAHL), and ScienceDirect from inception to July 2017 were searched for randomized controlled trials (RCTs) investigating the effect of exercise modalities in adult patients with CVD. The effect size was estimated as mean differences (MD) with 95% confidence intervals (CI). Subgroup analysis and meta-regression were used to study potential moderating factors. Results Thirty-eight articles describing RCTs with a total of 2089 patients with CVD were included. The pooling revealed that aerobic exercise [MD(95%CI) = -5.87 (-8.85, -2.88), P = 0.0001] and resistance exercise [MD(95%CI) = -7.62 (-10.69, -4.54), P

Background Currently, the decision to treat iliac artery stenoses is mainly based on visual inspection of digital subtraction angiographies. Intra‐arterial pressure measurements can provide clinicians with accurate hemodynamic information. However, pressure measurements are rarely performed because of their invasiveness and the time required. Therefore, the aim of the study was to test the feasibility of a computational model that can predict translesional pressure gradients across iliac artery stenoses on the basis of imaging data only. Methods and Results Patients (N=21) with symptomatic peripheral arterial disease and a peak systolic velocity ratio between 2.5 and 5.0 were included in the study. Patients underwent per‐procedural 3‐dimensional rotational angiography and hyperemic intra‐arterial translesional pressure measurements. Vascular anatomical features were reconstructed from the 3‐dimensional rotational angiography data into an axisymmetrical 2‐dimensional computational mesh, and flow was estimated on the basis of the stenosis geometry. Computational fluid dynamics were performed to predict the pressure gradient and were compared with the measured pressure gradients. A good agreement by overlapping error bars of the predicted and measured pressure gradients was found in 21 of 25 lesions. Stratification of the stenosis on the basis of the predicted pressure gradient into hemodynamic not significant ( Conclusions The feasibility of the patient‐specific computational model to predict the hyperemic translesional pressure gradient over iliac artery stenosis was successfully tested. Presented results suggest that, with further optimization and corroboration, the model can become a valuable aid to the diagnosis of equivocal iliac artery stenosis. Clinical Trial Registration URL : http://www.trialregister.nl . Unique identifier: NTR 5085.