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Computational Fluid Dynamics (CFD) is used to assist in designing artificial valves and planning procedures, focusing on local flow features. However, assessing the impact on overall cardiovascular function or predicting longer-term outcomes may requires more comprehensive whole heart CFD models. Fitting such models to patient data requires numerous computationally expensive simulations, and depends on specific clinical measurements to constrain model parameters, hampering clinical adoption. Surrogate models can help to accelerate the fitting process while accounting for the added uncertainty. We create a validated patient-specific four-chamber heart CFD model based on the Navier-Stokes-Brinkman (NSB) equations and test Gaussian Process Emulators (GPEs) as a surrogate model for performing a variance-based global sensitivity analysis (GSA). GSA identified preload as the dominant driver of flow in both the right and left side of the heart, respectively. Left-right differences were seen in terms of vascular outflow resistances, with pulmonary artery resistance having a much larger impact on flow than aortic resistance. Our results suggest that GPEs can be used to identify parameters in personalized whole heart CFD models, and highlight the importance of accurate preload measurements. [ABSTRACT FROM AUTHOR]

Background: T-wave (TW) morphology indices based on time-warping ($d_{w}$) have shown significant cardiovascular risk stratification value. However, errors in the location of TW boundaries may impact their prognostic power. Our aim was to test the hypothesis that a weighted time-warping function (WF) would reduce the sensitivity of $d_{w}$ to these errors and improve their clinical significance. Methods: The WFs were proportional to (i) the reference TW ($\mathcal {T}$), and (ii) the absolute value of its derivative ($\mathcal {D}$). The index $d_{w}$ was recalculated using these WFs, and its performance was compared to the unweighted control case ($\mathcal {C}$) in four different scenarios: 1) robustness against simulated TW boundaries location errors; 2) ability to retain physiological information in an electrophysiological cardiac model; 3) ability to monitor blood potassium concentration changes ($\Delta [K^+]$) in 29 hemodialysis (HD) patients; 4) and the sudden cardiac death (SCD) risk stratification value of the TW morphology restitution (TMR) index, derived from $d_{w}$ , in 651 chronic heart failure (CHF) patients. Results and Discussion: The WFs led to a reduced sensitivity ($\mathcal {R}$) of $d_{w}$ to TW boundary location errors as compared to $\mathcal {C}$ (median $\mathcal {R}$ =0.19 and 0.22 and 0.35 for $\mathcal {T}$ , $\mathcal {D}$ and $\mathcal {C}$ , respectively). They also preserved the physiological relationship between $d_{w}$ and repolarization dispersion changes at ventricular level. No improvements in $\Delta [K^+]$ tracking were observed for the HD patients (Pearson’s median correlation [ $r$ ] between $\Delta [K^+]$ and $d_{w}$ was $0.86\leq r \leq 0.90$ for $\mathcal {T}$ , $\mathcal {D}$ and $\mathcal {C}$). In CHF patients, the SCD risk stratification value of TMR was improved by applying $\mathcal {T}$ (hazard ratio, HAR, of 2.80), followed by $\mathcal {D}$ (HAR=2.32) and $\mathcal {C}$ (HAR=2.23). Conclusions and Significance: The proposed WFs, with $\mathcal {T}$ showing the best performance, increased the robustness of time-warping based markers against TW location errors preserving their physiological information content and boosting their SCD risk stratification value. Results from this work support the use of $\mathcal {T}$ when deriving $d_{w}$ for future clinical applications. [ABSTRACT FROM AUTHOR]

Objective: The detection of metabolites such as choline in blood are important in clinical care for patients with cancer and cardiovascular disease. Choline is only present in human blood at low concentrations hence accurate measurement in an affordable point-of-care format is extremely challenging. Although complementary metal-oxide semiconductor (CMOS) and microfluidics are individually mature technologies, their integration has presented challenges that we overcome in a novel, cost-effective, single-step process. Methods: To demonstrate the process, we present the microfluidic integration of a metabolomics-on-CMOS point-of-care platform with four capillary microfluidic channels on top of a CMOS optical sensor array. Results: The fabricated device was characterised to verify the required structural profile, mechanical strength, optical spectra, and fluid flow. As a proof of concept, we used the device for the in-vitro quantification of choline in human blood plasma with a limit of detection of 3.2 μM and a resolution of 1.6 μM. Significance: Integration of microfluidics on to CMOS technology has the potential to enable advanced sensing technologies with extremely low limit of detection that are well suited to multiple clinical metabolite measurements. [ABSTRACT FROM AUTHOR]

Non-contact physiological measurement has the potential to provide low-cost, non-invasive health monitoring. However, machine vision approaches are often limited by the availability and diversity of annotated video datasets resulting in poor generalization to complex real-life conditions. To address these challenges, this work proposes the use of synthetic avatars that display facial blood flow changes and allow for systematic generation of samples under a wide variety of conditions. Our results show that training on both simulated and real video data can lead to performance gains under challenging conditions. We show strong performance on three large benchmark datasets and improved robustness to skin type and motion. These results highlight the promise of synthetic data for training camera-based pulse measurement; however, further research and validation is needed to establish whether synthetic data alone could be sufficient for training models. [ABSTRACT FROM AUTHOR]

Objective: In preclinical examinations, rotodynamic blood pumps (RBPs) are predominantly evaluated at design-point conditions. In clinical practice, however, they run at diversified modes of operation. This study aimed at extending current preclinical evaluation of hemolytic profiles in RBPs toward broader, clinically relevant ranges of operation. Methods: Two implantable RBPs – the HeartMate 3 (HM3) and the HeartWare Ventricular Assist Device (HVAD) – were analyzed at three pump speeds (HM3: 4300, 5600, 7000 rpm; HVAD: 1800, 2760, 3600 rpm) with three flow rates (1-9L/min) per speed setting. Hemolysis measurements were performed in heparinized bovine blood. The delta free hemoglobin (dfHb) and the normalized index of hemolysis (NIH) served as hemolytic measures. Statistical analysis was performed by multiple comparison of the 9 operating conditions. Moreover, computational fluid dynamics (CFD) was applied to provide mechanistic insights into the interrelation between hydraulics and hemolysis by correlating numerically computed hydraulic losses with in-vitro hemolytic measures. Results: In both devices, dfHb increased toward increasing speeds, particularly during low but also during high flow condition. By contrast, in both RBPs magnitudes of NIH were significantly elevated during low flow operation compared to high flow conditions (p<0.0036). Maps of hemolytic metrics revealed morphologically similar trends to in-silico hydraulic losses (r>0.793). Conclusions: While off-design operation is associated with increased hemolytic profiles, the setting of different operating conditions render a preclinical prediction of clinical impact with current hemolysis metrics difficult. Significance: The identified increase in hemolytic measures during episodes of off-design operation is highlighting the need to consider worst-case operation during preclinical examinations. [ABSTRACT FROM AUTHOR]

An ability to extract detailed spirometry-like breathing waveforms from wearable sensors promises to greatly improve respiratory health monitoring. Photoplethysmography (PPG) has been researched in depth for estimation of respiration rate, given that it varies with respiration through overall intensity, pulse amplitude and pulse interval. We compare and contrast the extraction of these three respiratory modes from both the ear canal and finger and show a marked improvement in the respiratory power for respiration induced intensity variations and pulse amplitude variations when recording from the ear canal. We next employ a data driven multi-scale method, noise assisted multivariate empirical mode decomposition (NA-MEMD), which allows for simultaneous analysis of all three respiratory modes to extract detailed respiratory waveforms from in-ear PPG. For rigour, we considered in-ear PPG recordings from healthy subjects, both older and young, patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) and healthy subjects with artificially obstructed breathing. Specific in-ear PPG waveform changes are observed for COPD, such as a decreased inspiratory duty cycle and an increased inspiratory magnitude, when compared with expiratory magnitude. These differences are used to classify COPD from healthy and IPF waveforms with a sensitivity of 87% and an overall accuracy of 92%. Our findings indicate the promise of in-ear PPG for COPD screening and unobtrusive respiratory monitoring in ambulatory scenarios and in consumer wearables. [ABSTRACT FROM AUTHOR]

The diagnosis and management of diabetes require frequent monitoring of blood sugar levels. Prolonged exposure of most of the monosaccharides in the bloodstream results in the glycation of hemoglobin. This glycated hemoglobin (HbA1c) based test plays an important role to avoid diabetic complications. However, noninvasive estimation of HbA1c is a very new, promising, and challenging topic in modern bioengineering scopes. The purpose of this study is to develop and verify mathematical models in order to quantify the glycated hemoglobin in-vivo percentage non-invasively. This research utilized photon diffusion theory to develop the finger models and genetic symbolic regression methods to solve the models to estimate the level of glycated hemoglobin in the blood. The validation of these models with human participants indicated a high degree of correlation (0.887 and 0.907 Pearson's r value), and high precision (2.56% and 2.96% coefficient of variation (%CV)) for transmission and reflection type noninvasive digital volume pulse-based signals. This research will be a breakthrough for the application of noninvasive HbA1c estimation. [ABSTRACT FROM AUTHOR]

Objective: Needle-free jet injection is a drug delivery technique that uses the momentum of the fluid drug to break through the skin. This technique has recently also been applied to blood release, aiming to collect samples from capillaries in the skin without needing a lancet prick. This work provides new information about the wound geometry and tissue disruption caused by shallow jet injection with circular-shaped and slot-shaped jets. Methods: We use histological analysis to compare the disruption of tissue, including blood vessels, caused by lancet-pricking and jet injection with a circular-shaped jet and a lancet-inspired slot-shaped jet. Results: Intradermal injection into porcine skin using a slot-shaped jet disrupted more vascular endothelium in the tissue than a circular-shaped jet and did so at a smaller penetration depth with smaller wound volume. Our results suggest that shallow jet injections may have the potential to release more capillary blood than a lancet prick. Conclusion: These findings demonstrate that a reversible jet injector might be used in diabetes management as a device to release and collect blood samples, in addition to being used to deliver insulin. Significance: Tissue disruption is crucial to consider when using jet injection to deliver drugs and release capillary blood. [ABSTRACT FROM AUTHOR]

Objective: The design of an Artificial Pancreas (AP) to regulate blood glucose levels requires reliable control methods. Model Predictive Control has emerged as a promising approach for glycemia control. However, model–based control methods require computationally simple and identifiable mathematical models that represent glucose dynamics accurately, which is challenging due to the complexity of glucose homeostasis. Methods: In this work, a simple model is deduced to estimate blood glucose concentration in subjects with Type 1 Diabetes Mellitus (T1DM). Novel features in the model are power–law kinetics for intraperitoneal insulin absorption and a separate glucagon sensitivity state. Profile likelihood and a method based on singular value decomposition of the sensitivity matrix are carried out to assess parameter identifiability and guide a model reduction for improving the identification of parameters. Results: A reduced model with 10 parameters is obtained and calibrated, showing good fit to experimental data from pigs where insulin and glucagon boluses were delivered in the intraperitoneal cavity. Conclusion: A simple model with power–law kinetics can accurately represent glucose dynamics submitted to intraperitoneal insulin and glucagon injections. The reduced model was found to exhibit local practical as well as structural identifiability. Importance: The proposed model facilitates intraperitoneal bi-hormonal model-based closed-loop control in animal trials. [ABSTRACT FROM AUTHOR]

The introduction of ultrafast ultrasound and spatiotemporal filtering has significantly improved the sensitivity of Doppler ultrasound imaging. This work describes the development of a 3D power Doppler imaging technique which uses a 1D-array ultrasound probe that mechanically translates at a constant speed. The continuous translation allows for a fast scan of a large 3D volume without requiring complex hardware. The technique was realized in a prototype and its feasibility illustrated using phantom and in vivo kidney and breast lesion experiments. Although this 3D Doppler imaging technique is limited in some aspects, it enables power Doppler imaging of a large volume in a short acquisition time with less computational costs. [ABSTRACT FROM AUTHOR]

As a biomarker for liver disease, bilirubin has been utilized in prognostic scoring systems for cirrhosis. While laboratory-based methods are used to determine bilirubin levels in clinical settings, they do not readily lend themselves to applications outside of hospitals. Consequently, bilirubin monitoring for cirrhotic patients is often performed only intermittently; thus, episodes requiring clinical interventions could be missed. This work investigates the feasibility of measuring bilirubin concentration in whole porcine blood samples using dual-wavelength transmission measurement. A compact and low-cost dual-wavelength transmission measurement setup is developed and optimized to measure whole blood bilirubin concentrations. Using small volumes of whole porcine blood (72 µL), we measured the bilirubin concentration within a range corresponding to healthy individuals and cirrhotic patients (1.2–30 mg/dL). We demonstrate that bilirubin levels can be estimated with a positive correlation (R-square > 0.95) and an accuracy of ±1.7 mg/dL, with higher reliability in cirrhotic bilirubin concentrations (> 4 mg/dL) – critical for high-risk patients. The optical and electronic components utilized are economical and can be readily integrated into a miniature, low-cost, and user-friendly system. This could provide a pathway for point-of-care monitoring of blood bilirubin outside of medical facilities (e.g., patient's home). [ABSTRACT FROM AUTHOR]

According to the World Health Organization, about 422 million people worldwide have type 1 or type 2 diabetes (T1D, T2D), with the latter accounting for 90–95% of cases. Safe and effective treatment of patients with diabetes requires accurate and frequent monitoring of their blood sugar levels. Continuous glucose monitoring (CGM) is a monitoring technology developed to address this need, and its use among U.S. T1D patients has increased from 6% in 2011 to 38% in 2018 and continues to increase worldwide in both T1D and T2D. This paper presents a data-driven approach to determine $\Omega$ , a finite set of representative daily profiles (motifs) such that almost any daily CGM profile generated by a patient can be matched to one of the motifs in $\Omega$. The training data set (9741 profiles) was used to identify 8 candidate sets of motifs, while the validation data set (14 175 profiles) was used to select the final set $\Omega$. The robustness of $\Omega$ was established by using it to successfully classify (match against a representative daily profile in $\Omega$) 99.0% of 42 595 daily CGM profiles in the testing data set. All data sets contained daily CGM profiles from six studies involving T1D and T2D patients using a variety of treatment modes, including daily insulin injections, insulin pumps, or artificial pancreas (AP). The classified profiles can be used in predictive modeling, decision support, and automated control systems (e.g., AP). [ABSTRACT FROM AUTHOR]

Objective: To enable a real-time surgical guidance system that simultaneously monitors blood vessel perfusion, oxygen saturation, thrombosis, and tissue recovery by combining multiple optical imaging techniques into a single system: visible imaging, mosaic filter-based snapshot hyperspectral imaging (HSI), and laser speckle contrast imaging (LSCI). Methods: The multimodal optical imaging system was demonstrated by clamping blood vessels in the small intestines of rats to create areas of restricted blood flow. Subsequent tissue damage and regeneration were monitored during procedures. Using LSCI, vessel perfusion was measured, revealing the biological activity and survival of organ tissues. Blood oxygen saturation was monitored using HSI in the near-infrared region. Principal component analysis was used over the spectral dimension to identify an HSI wavelength combination optimized for hemodynamic biomarker visualization. HSI and LSCI were complimentary, identifying thrombus generation and tissue recovery, which was not possible in either modalityalone. Results and Conclusion: By analyzing multimodal tissue information from visible imaging, LSCI perfusion imaging, and HSI, a recovery prognosis could be determined based on the blood supply to the organ. The unique combination of the complementary imaging techniques into a single surgical microscope holds promise for improving the real-time determination of blood supply and tissue prognosis during surgery. Significance: Precise real-time monitoring for vascular anomalies promises to reduce the risk of organ damage in precise surgical operations such as tissue resection and transplantation. In addition, the convergence of label-free imaging technologies removes delays associated with the injection and diffusion of vascular monitoring dyes. [ABSTRACT FROM AUTHOR]

In cancer treatment, laser ablation is a promising technique used to induce localized thermal damage. Different variables influence the temperature distribution in the tissue and the resulting therapy efficacy; thus, the optimal therapy settings are required for obtaining the desired clinical outcome. In this work, thermomechanical modeling of contactless laser ablation was implemented to analyze the sensitivity of independent variables on the optimal treatment conditions. The Finite Element Method was utilized to solve the governing equations, i.e., the bioheat, mechanical deformation, and the Navier-Stokes equations. Validation of the model was performed by comparing experimental and simulated temperatures, which indicated high accuracy for estimating temperature. In particular, the results showed that the model can estimate temperature with a good correlation factor (R = 0.98) and low Mean Absolute Error (3.9 °C). A sensitivity analysis based on laser irradiation time, power, beam distribution, and the blood vessel depth on temperature distribution and fraction of necrotic tissue was performed. An optimization process was performed based on the most significant variables, i.e., laser irradiation time and power. This resulted in an indication of the optimal therapy settings for achieving maximum procedure efficiency i.e., the required fraction of necrotic tissue within the target volume, constituted by tumor and safety margins around it. [ABSTRACT FROM AUTHOR]

Objective: Wearable systems that enable continuous non-invasive monitoring of hemodynamic parameters can aid in cardiac health evaluation in non-hospital settings. The seismocardiogram (SCG) is a non-invasively acquired cardiovascular biosignal for which timings of fiducial points, like aortic valve opening (AO) and aortic valve closing (AC), can enable estimation of key hemodynamic parameters. However, SCG is susceptible to motion artifacts, making accurate estimation of these points difficult when corrupted by high-g or in-band vibration artifacts. In this paper, a novel denoising pipeline is proposed that removes vehicle-vibration artifacts from corrupted SCG beats for accurate fiducial point detection. Methods: The noisy SCG signal is decomposed with ensemble empirical mode decomposition (EEMD). Corrupted segments of the decomposed signal are then identified and removed using the quasi-periodicity of the SCG. Signal quality assessment of the reconstructed SCG beats then removes unreliable beats before feature extraction. The overall approach is validated on simulated vehicle-corrupted SCG generated by adding real subway collected vibration signals onto clean SCG. Results: SNR increased by 8.1dB in the AO complex and 11.5dB in the AC complex of the SCG signal. Hemodynamic timing estimation errors reduced by 16.5% for pre-ejection period (PEP), 67.2% for left ventricular ejection time (LVET), and 57.7% for PEP/LVET—a feature previously determined in prior work to be of great importance for assessing blood volume status during hemorrhage. Conclusion: These findings suggest that usable SCG signals can be recovered from vehicle-corrupted SCG signals using the presented denoising framework, allowing for accurate hemodynamic timing estimation. Significance: Reliable hemodynamic estimates from vehicle-corrupted SCG signals will enable the adoption of the SCG in outside-of-hospital settings. [ABSTRACT FROM AUTHOR]

It is well known that non-invasive blood pressure measurements significantly underestimate true systolic blood pressure (SBP), and overestimate diastolic blood pressure (DBP). The aetiology for these errors has not yet been fully established. This study aimed to investigate the accuracy of Korotkoff sounds for detection of SBP and DBP points as used in brachial cuff sphygmomanometry. Brachial cuff pressure and Korotkoff sounds were obtained in 11 patients (6 males: 69.0 ± 6.2 years, 5 females: 71.8 ± 5.5 years) undergoing diagnostic coronary angiography. K2 Korotkoff sounds were obtained by high-pass filtering (>20 Hz) the microphone-recorded signal to eliminate low frequency components. Analysis of the timing of K2 Korotkoff sounds relative to cuff pressure and intra-arterial pressure shows that the onset of K2 Korotkoff sounds reliably detect the start of blood flow under the brachial cuff and their termination, marks the cuff pressure closely coincident with DBP. We have made the critical observation that blood flow under the cuff does not begin when cuff pressure falls just below SBP as is conventionally assumed, and that the delay in the opening of the artery following occlusion, and the consequent delay in the generation of K2 Korotkoff sounds, may lead to significant errors in the determination of SBP of up to 24 mmHg. Our data suggest a potential role of arterial stiffness as a major component of the errors recorded, with underestimation of SBP much more significant for subjects with stiff arteries than for subjects with more compliant arteries. [ABSTRACT FROM AUTHOR]

Objective: Bioresorbable materials represent a promising technology for the treatment of coronary disease. Among the different materials employed, magnesium stents display favourable mechanical properties. One of the main uncertainties regarding use is their behaviour when deployed on coronary bifurcations, especially when their retardant coating has been damaged during the implantation process. This paper analyses the temporal evolution of the degradation of a damaged magnesium stent inserted into a coronary bifurcation. Methods: The rate of erosion-corrosion and the effect of the flow configuration on the mass transfer coefficient were estimated on the basis of previous experimental studies and numerical simulations. This coefficient has been employed to reproduce the conditions that can appear in real stent configurations, and computational fluid dynamics simulations were performed. Results: The diffusion coefficient for this particular case has been calculated from the mass transfer coefficient and the Sherwood number. The results of the simulation show how the presence of the inner artery wall has a positive effect, preventing a premature degradation of the stent, and how the distal strut is protected by the presence of the proximal struts. Conclusions: This study demonstrates the usefulness of the proposed methodology to evaluate the temporal evolution of the degradation of struts made of magnesium alloys. In addition, this methodology can be applied to a study of different materials and geometric configurations. Significance: The proposed technique can contribute to expanding existing knowledge concerning bioresorbable stent flow-corrosion, thus improving their design and implantation. [ABSTRACT FROM AUTHOR]

Objective: To extend closed-loop modeling of the heart-rate reflex (HRR) by including the dynamic effects of concurrent changes in blood CO2 tension. This extended dynamic model can be used to generate physio-markers of “baroreflex gain” (BRG) and “chemoreflex gain” (CRG) that allow quantitative assessment of the possible impact of pathologies upon HRR. Mild Cognitive Impairment (MCI) is used as an example. Methods: The proposed data-based closed-loop modeling methodology estimates the forward and reverse dynamic components of the model via Laguerre kernel expansions of two open-loop models using spontaneous time-series data collected in 45 MCI patients and 15 controls. The BRG and CRG physio-markers are subsequently computed for each subject via simulation of the obtained closed-loop model for unit-step change of arterial pressure or blood CO2 tension, respectively. Results: Both open-loop and closed-loop HRR modeling revealed that MCI patients exhibit significantly smaller CRG relative to controls (p<0.001), but not significantly different BRG. Furthermore, the closed-loop model captured the dynamic effect of sympathetic activity as resonant peak around 0.1 Hz (Mayer wave) in the chemoreflex and baroreflex transfer functions (not captured via open-loop modeling). This may prove valuable in advancing our understanding of how sympathetic activity impacts HRR in various pathologies. Conclusion: The extended HRR model, incorporating the dynamic effects of concurrent changes of blood CO2 tension, revealed significantly reduced chemoreflex gain (but not baroreflex gain) in MCI patients. Furthermore, the closed-loop model captured the sympathetic influence around 0.1 Hz. Significance: Multivariate closed-loop dynamic modeling is valuable for understanding physiological autoregulation. [ABSTRACT FROM AUTHOR]

Objective: To improve insulin treatment in type 2 diabetes (T2D) using model-based control techniques, the underlying model needs to be individualized to each patient. Due to the impact of unknown meals, exercise and other factors on the blood glucose, it is difficult to utilize available data from continuous glucose monitors (CGMs) for model fitting and parameter estimation purposes. Methods: To overcome this problem, we propose a novel method for modeling the glycemic disturbances as a stochastic process. To differentiate meals from other glycemic disturbances, we model the meal intake as a separate stochastic process while encompassing all other disturbances in another stochastic process. Using particle filtering, we validate the model on simulations as well as on clinical data. Results: Based on simulated CGM data, the residuals generated by the particle filter are white, indicating a good model fit. For the clinical data, we use parameter values estimated based on fasting glucose data. The residuals obtained from clinical CGM data contain correlations up to lag 5. Conclusion: The proposed model is shown to adequately describe the meal-induced glucose fluctuations in simulated CGM data while validations on clinical CGM data show promising results as well. Significance: The proposed model may lay the grounds for new ways of utilizing available CGM data, including CGM-based parameter estimation and stochastic optimal control. [ABSTRACT FROM AUTHOR]

Background: Peri-device leak (PDL) following left atrial appendage occlusion (LAAO) may lead to an increased risk of thrombosis. However, current modalities for PDL detection, such as trans-esophageal echo (TEE) and cardiac CT do not provide quantitative measures of PDL. Objective: to use dielectric imaging (DI) to measure PDL from a Watchman (WM) LAAO device. Methods: A conductivity contrast agent is injected into the left atrium (LA) through the WM delivery system, while making DI measurements. Recordings are analyzed with a two-compartment model and the flow from the left atrial appendage (LAA) characterized by a “% clearance / beat” (CPB) parameter. With ethics approval, four dogs (26 ± 1.8  kg) were anesthetized and ventilated. Body-surface electrodes were placed and impedance data continuously acquired. WM devices (0–35% oversized) were introduced and placed into the LAA. During the study, the WM was either fully or partial deployed. At each deployment level, 10 mL of conductivity contrast was injected through the WM delivery sheath. At twenty-two deployment conditions, Doppler-flow TEE measurements were made, and compared to the DI-based value. Results: In all cases, CPB values correctly predicted the TEE-based assessment of PDL (100% sensitivity/specificity). The TEE leak size also corresponded to CPB values with a correlation of r = 0.914 (p < 0.001). Conclusion: Using DI signals, the leak flow from the WM LAAO can be measured and yields comparative results to TEE for detection of PDL. The DI method requires no other imaging modality or ionizing radiation and iodine contrast agent injection. [ABSTRACT FROM AUTHOR]

Point-of-care devices can analyze or characterize a sample in a short time. New technologies in medical science seek integrations of different measurement techniques for a complete analysis. This study describes the fabrication method, tests, and results of microtechnology as an approach for an integrated rheometer. The portable device measured the average flow velocity to calculate its viscosity. The whole system encompasses a microdevice integrated to a data acquisition system powered by USB and controlled by full custom software. As a result, we obtained an easy-to-handle and fabricate hand-held microrheometer. The device was tested using Newtonian fluids such as Mili-Q water, an aqueous solution of Ethylene-glycol at 40% and 25% and Non-Newtonian blood samples. The whole device can provide the non-linear viscosity of a 0.08 ml blood sample in less than 30 seconds, in a wide range of shear rate with an accuracy of 93%. More importantly, due to its detection method and simplicity, it can be enclosed within almost any fluidic microsystem, including biomedical applications. [ABSTRACT FROM AUTHOR]

Objective: Local oscillation of the chest wall in response to events during the cardiac cycle may be captured using a sensing modality called seismocardiography (SCG), which is commonly used to infer cardiac time intervals (CTIs) such as the pre-ejection period (PEP). An important factor impeding the ubiquitous application of SCG for cardiac monitoring is that morphological variability of the signals makes consistent inference of CTIs a difficult task in the time-domain. The goal of this work is therefore to enable SCG-based physiological monitoring during trauma-induced hemorrhage using signal dynamics rather than morphological features. Methods: We introduce and explore the observation that SCG signals follow a consistent low-dimensional manifold structure during periods of changing PEP induced in a porcine model of trauma injury. Furthermore, we show that the distance traveled along this manifold correlates strongly to changes in PEP (Δ PEP). Results: Δ PEP estimation during hemorrhage was achieved with a median R2 of 92.5% using a rapid manifold approximation method, comparable to an ISOMAP reference standard, which achieved an R2 of 95.3%. Conclusion: Rapidly approximating the manifold structure of SCG signals allows for physiological inference abstracted from the time-domain, laying the groundwork for robust, morphology-independent processing methods. Significance: Ultimately, this work represents an important advancement in SCG processing, enabling future clinical tools for trauma injury management. [ABSTRACT FROM AUTHOR]

Objective: This paper presents a comparative study of computational fluid dynamics (CFD) simulations and in vitro hemolysis examinations of a bearingless centrifugal blood pump. The outcomes of the in vitro study are analyzed with the help of CFD hemolysis models. Methods: Several pump prototypes were manufactured and tested. Each model was implemented in a CFD framework and simulated with different Eulerian hemolysis models. The outcomes are compared to experimental data. The model achieving the highest correlation is used to explain the in vitro outcomes in detail. Results: It is shown that a double-stage model achieves the best correlation. The sensitivity of the simulation is considerably lower than that of in vitro tests. The CFD model reveals that most of the cell destruction is caused in the radial gap of the pump. Further critical regions are the bottom volume and the shroud clearance gap. Only 0.5% of the priming volume is subject to overcritical shear stress. Conclusion: Cell compatibility can be improved by increasing the radial gap, lowering the shroud and hub clearance gaps, and increasing the fillet radius of the inlet nozzle. CFD models can be used to examine the cell damage effects and help to further improve the pump design. Significance: This paper compares different Eulerian CFD hemolysis models, parameter sets, and equivalent shear stresses to several in vitro hemolysis tests. The sensitivity of the models is compared to that of in vitro studies. It is shown that CFD simulations have their limitations but can help with interpreting the outcomes of in vitro studies. [ABSTRACT FROM AUTHOR]

Objective: With the growing demand for livers in the field of transplantation, interest in normothermic ex situ machine perfusion (NMP) has increased in recent years. This may open the door for novel therapeutic interventions such as repair of suboptimal grafts. For successful long-term NMP of livers, blood glucose (BG) levels need to be maintained in a close to physiological range. Methods: We present an “automated insulin delivery” (AID) system integrated into an NMP system, which automatically adjusts insulin infusion rates based on continuous BG measurements in a closed loop manner during ex situ pig and human liver perfusion. An online glucose sensor for continuous glucose monitoring was integrated and evaluated in blood. A model based and a proportional controller were implemented and compared in their ability to maintain BG within the physiological range. Results: The continuous glucose sensor is capable of measuring BG directly in human and pig blood for multiple days with an average error of 0.6 mmol/L. There was no significant difference in the performance of the two controllers in terms of their ability to keep BG in the physiological range. With the integrated AID, BG was controlled within the physiological range on average in 80% and 76% of the perfusion time for human and pig livers, respectively. Conclusion: The presented work offers a method and shows the feasibility to maintain BG in the physiological range for multiple (up to ten) days during ex situ liver perfusion with the help of an automated AID. Significance: Maintaining BG within the physiological range is required to enable long-term ex situ liver perfusion. [ABSTRACT FROM AUTHOR]

Objective: Multiple daily injections (MDI) therapy is the most common treatment for type 1 diabetes (T1D) including basal insulin doses to keep glucose levels constant during fasting conditions and bolus insulin doses with meals. Optimal insulin dosing is critical to achieving satisfactory glycemia but is challenging due to inter- and intra-individual variability. Here, we present a novel model-based iterative algorithm that optimizes insulin doses using previous-day glucose, insulin, and meal data. Methods: Our algorithm employs a maximum-a-posteriori method to estimate parameters of a model describing the effects of changes in basal-bolus insulin doses. Then, parameter estimates, their confidence intervals, and the goodness of fit, are combined to generate new recommendations. We assessed our algorithm in three ways. First, a clinical data set of 150 days (15 participants) were used to evaluate the proposed model and the estimation method. Second, 60-day simulations were performed to demonstrate the efficacy of the algorithm. Third, a sample 6-day clinical experiment is presented and discussed. Results: The model fitted the clinical data well with a root-mean-square-error of 1.75 mmol/L. Simulation results showed an improvement in the time in target (3.9–10 mmol/L) from 64% to 77% and a decrease in the time in hypoglycemia (< 3.9 mmol/L) from 8.1% to 3.8%. The clinical experiment demonstrated the feasibility of the algorithm. Conclusion: Our algorithm has the potential to improve glycemic control in people with T1D using MDI. Significance: This work is a step forward towards a decision support system that improves their quality of life. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study is to design a physical model of a magnetic filtration system which can separate magnetic nanoparticle (MNP)-tagged cytokines from fluid at physiologically relevant flow rates employed during cardiopulmonary bypass (CPB) procedures. Methods: The Navier-Stokes equations for the pressure driven flow in the chamber and the quasistatic stray magnetic field produced by an array of permanent magnets were solved using finite element analysis in COMSOL Multiphysics for 2D and 3D representations of the flow chamber. Parameters affecting the drag and magnetic forces including flow chamber dimensions, high gradient magnet array configurations, and particle properties, were changed and evaluated for their effect on MNP capture. Results: Flow chamber dimensions which achieve appropriate flow conditions for CPB were identified, and magnetic force within the chamber decreased with increased chamber height. A magnetic “block” array produced the highest magnetic force within the chamber. Polymeric microparticles loaded with MNPs were shown to have increased particle capture with increased hydrodynamic diameter. Conclusion: The model achieved a predicted efficiency up to 100% capture in a single-pass of fluid flowing at 1.75 L/min. Significance: This work is an important step in designing a magnetic flow chamber that can remove the magnetically tagged cytokines under high flow employed during CPB. Cytokines have been shown to stimulate the systemic inflammatory response (SIR) associated with CPB and are an established therapeutic target to mitigate the SIR. In the long term, this work aims to guide researchers in the more accurate design of magnetic separation systems. [ABSTRACT FROM AUTHOR]

Objective: In this work, we design iterative algorithms for the delivery of long-acting (basal) and rapid-acting (bolus) insulin, respectively, for people with type 1 diabetes (T1D) on multiple-daily-injections (MDIs) therapy using feedback from self-monitoring of blood glucose (SMBG) measurements. Methods: Iterative learning control (ILC) updates basal therapy consisting of one long-acting insulin injection per day, while run-to-run (R2R) adapts meal bolus therapy via the update of the mealtime-specific insulin-to-carbohydrate ratio (CR). Updates are due weekly and are based upon sparse SMBG measurements. Results: Upon termination of the 20 weeks long in-silico trial, in a scenario characterized by meal carbohydrate (CHO) normally distributed with mean $\mu$ = [50, 75, 75] grams and standard deviation $\sigma$ = [5, 7, 7] grams, our strategy produced statistically significant improvements in time in range (70--180) [mg/dl], from 66.9(33.1) $\%$ to 93.6(6.7) $\%$ , $p$ = 0.02. Conclusions: Iterative learning shows potential to improve glycemic regulation over time by driving blood glucose closer to the recommended glycemic targets. Significance: Decision support systems (DSSs) and automated therapy advisors such as the one proposed here are expected to improve glycemic outcomes reducing the burden on patients on MDI therapy. [ABSTRACT FROM AUTHOR]

Acute ischemic stroke is a major health problem with a high mortality rate and a high risk for permanent disabilities. Selective brain hypothermia has the neuroprotective potential to possibly lower cerebral harm. A recently developed catheter system enables to combine endovascular blood cooling and thrombectomy using the same endovascular access. By using the penumbral perfusion via leptomeningeal collaterals, the catheter aims at enabling a cold reperfusion, which mitigates the risk of a reperfusion injury. However, cerebral circulation is highly patient-specific and can vary greatly. Since direct measurement of remaining perfusion and temperature decrease induced by the catheter is not possible without additional harm to the patient, computational modeling provides an alternative to gain knowledge about resulting cerebral temperature decrease. In this work, we present a brain temperature model with a realistic division into gray and white matter and consideration of spatially resolved perfusion. Furthermore, it includes detailed anatomy of cerebral circulation with possibility of personalizing on base of real patient anatomy. For evaluation of catheter performance in terms of cold reperfusion and to analyze its general performance, we calculated the decrease in brain temperature in case of a large vessel occlusion in the middle cerebral artery (MCA) for different scenarios of cerebral arterial anatomy. Congenital arterial variations in the circle of Willis had a distinct influence on the cooling effect and the resulting spatial temperature distribution before vessel recanalization. Independent of the branching configurations, the model predicted a cold reperfusion due to a strong temperature decrease after recanalization (1.4–2.2  $^{\circ }$ C after 25 min of cooling, recanalization after 20 min of cooling). Our model illustrates the effectiveness of endovascular cooling in combination with mechanical thrombectomy and its results serve as an adequate substitute for temperature measurement in a clinical setting in the absence of direct intraparenchymal temperature probes. [ABSTRACT FROM AUTHOR]

Optical properties of human blood during coagulation were studied using optical coherence tomography (OCT) and the parameter of clotting time derived from the 1/e light penetration depth (d(1/e)) versus time was developed in our previous work. In this study, in order to know if a new OCT test can characterize the blood-coagulation process under different treatments in vitro, the effects of two different activators (calcium ions and thrombin) and anticoagulants, i.e., acetylsalicylic acid (ASA, a well-known drug aspirin) and melagatran (a direct thrombin inhibitor), at various concentrations are evaluated. A swept-source OCT system with a 1300 nm center wavelength is used for detecting the blood-coagulation process in vitro under a static condition. A dynamic study of d1/e reveals a typical behavior due to coagulation induced by both calcium ions and thrombin, and the clotting time is concentration-dependent. Dose-dependent ASA and melagatran prolong the clotting times. ASA and melagatran have different effects on blood coagulation. As expected, melagatran is much more effective than ASA in anticoagulation by the OCT measurements. The OCT assay appears to be a simple method for the measurement of blood coagulation to assess the effects of activators and anticoagulants, which can be used for activator and anticoagulant screening.

Infection by the parasite of malaria is a serious healthcare problem for populations residing primarily in tropical and subtropical countries. Early detection of the disease is essential to reduce both the mortality rate and spreading of the disease in the infected areas. Current methods for malaria diagnosis still rely on microscopic analysis of blood smears, which is a time-consuming and expensive process, in addition of requiring trained examiners to perform the analysis. In this paper, we introduce a novel fast screening tool for malaria based on a portable blood impedance analyzer. The simultaneous multi-tone injection of current and voltage detection of the device allow reducing the screening time (order of seconds) while enhancing the differences in impedance signal registered among frequencies to increase parasitemia level discrimination. We went further to demonstrate the possibility of directly applying the device on blood samples collected from volunteers to distinguish between infected and non-infected samples. Minimum parasitemia level discriminated was 0.0078% (or, equivalently 390 parasites/μl), which closely approaches the international standard set to 200 parasites/μl. Finally, we also show the frequency dependency of ring-synchronized and unsynchronized blood samples, which can constitute the basis for development of a point-of-care and laboratory-free method to distinguish different stages of malaria infection in economic stagnated communities. [ABSTRACT FROM AUTHOR]

Objective: Neutropenia is an adverse event commonly arising during intensive chemotherapy of acute myeloid leukemia (AML). It is often associated with infectious complications. Mathematical modeling, simulation, and optimization of the treatment process would be a valuable tool to support clinical decision making, potentially resulting in less severe side effects and deeper remissions. However, until now, there has been no validated mathematical model available to simulate the effect of chemotherapy treatment on white blood cell (WBC) counts and leukemic cells simultaneously. Methods: We developed a population pharmacokinetic/pharmacodynamic (PK/PD) model combining a myelosuppression model considering endogenous granulocyte-colony stimulating factor (G-CSF), a PK model for cytarabine (Ara-C), a subcutaneous absorption model for exogenous G-CSF, and a two-compartment model for leukemic blasts. This model was fitted to data of 44 AML patients during consolidation therapy with a novel Ara-C plus G-CSF schedule from a phase II controlled clinical trial. Additionally, we were able to optimize treatment schedules with respect to disease progression, WBC nadirs, and the amount of Ara-C and G-CSF. Results: The developed PK/PD model provided good prediction accuracies and an interpretation of the interaction between WBCs, G-CSF, and blasts. For 14 patients (those with available bone marrow blast counts), we achieved a median 4.2-fold higher WBC count at nadir, which is the most critical time during consolidation therapy. The simulation results showed that relative bone marrow blast counts remained below the clinically important threshold of 5%, with a median of 60% reduction in Ara-C. Conclusion: These in silico findings demonstrate the benefits of optimized treatment schedules for AML patients. Significance: Until 2017, no new drug had been approved for the treatment of AML, fostering the optimal use of currently available drugs. [ABSTRACT FROM AUTHOR]

Objective: This paper aims to compare the performance of several commonly known machine-learning (ML) models versus a classic Autoregression with Exogenous inputs (ARX) model in the prediction of blood glucose (BG) levels using time-series data of patients with Type 1 diabetes (T1D). Methods: The ML algorithms include ML-based regression models and deep learning models such as a vanilla Long-Short-Term-Memory (LSTM) Network and a Temporal Convolution Network (TCN). Evaluations have been conducted with respect to different input features, regression model orders, as well as using the recursive method or direct method for multi-step prediction of BG levels. Prediction performance metrics include the average Root Mean Square Error (RMSE), temporal gain (TG) for early prediction, and the normalized energy of the second-order differences (ESOD) of the predicted time series to reflect risk of false alerts on hypo/hyper glycemia events. Results: The ARX model achieved the lowest average RMSE for both recursive and direct methods, the second highest average TG under the direct method, but with a higher average normalized ESOD than some other models. Conclusion: There was no significant advantage observed from the ML models compared to the classic ARX model in predicting BG levels for T1D, except that TCN's performance was more robust with respect to BG trajectories with spurious oscillations, for which ARX tended to over-predict peak BG values and under-predict valley BG values. Significance: Insight learned from this study could help researchers and clinical practitioners to select appropriate models for BG prediction. [ABSTRACT FROM AUTHOR]

Conventional long-term ventricular assist devices continue to be extremely problematic due to infections caused by percutaneous drivelines and thrombotic events associated with the use of blood-contacting surfaces. Here we describe a muscle-powered cardiac assist device that avoids both these problems by using an internal muscle energy converter to drive a non-blood-contacting extra-aortic balloon pump. The technology was developed previously in this lab and operates by converting the contractile energy of the latissimus dorsi muscle into hydraulic power that can be used, in principle, to drive any blood pump amenable to pulsatile actuation. The two main advantages of this implantable power source are that it 1) significantly reduces infection risk by avoiding a constant skin wound, and 2) improves patient quality-of-life by eliminating all external hardware components. The counterpulsatile balloon pumps, which compress the external surface of the ascending aorta during the diastolic phase of the cardiac cycle, offer another critical advantage in the setting of long-term circulatory support in that they increase cardiac output and improve coronary perfusion without touching the blood. The goal of this work is to combine these two technologies into a single circulatory support system that eliminates driveline complications and avoids surface-mediated thromboembolic events, thereby providing a safe, tether-free means to support the failing heart over extended – or even indefinite – periods of time. [ABSTRACT FROM AUTHOR]

The analyses presented in Part 1 are expanded to three-phase composite materials. The theory developed in Part 1 is used for analytical and numerical calculations of dielectric spectra. In this study, three-phase systems with single-shelled particles were considered. The disordered particle distribution, aligned orientation of particles, and particles placed in different lattice structures are studied. It is shown that both two-phase and three-phase composites exhibit β-dispersion, while three-phase composites additionally exhibit δ-dispersion. This is the fundamental difference in the spectra for two- and three-phase materials. In the case of aligned orientation, the effective permittivity in the direction perpendicular to the spheroid plane exhibits a maximum at a volume fraction of approximately 0.5. Both two- and three-phase materials display this behavior. This may be of interest for the development of new metamaterials. The dielectric properties of composite materials with random distribution and periodic arrangement of particles differ significantly. The dielectric spectrum of erythrocyte suspension in plasma was measured by means of electrochemical impedance spectroscopy. The measurement system consisted of a small chamber with two planar electrodes placed at the bottom and an impedance analyzer. The dielectric properties of erythrocyte cytoplasm and membrane were numerically determined based on experimental data. The measurement of the dielectric properties of whole blood and blood components is very promising for various medical applications. [ABSTRACT FROM AUTHOR]

Electrochemical impedance spectra of composite materials contain information on the topological arrangement, volume fraction, and shape of particles, as well as the dielectric properties of the matrix and particles. The objective of this study is to investigate how these parameters affect the dielectric spectrum and what reliable information can be extracted from experimental data. The main attention was focused on systems with dielectric behavior similar to that of human blood. Mostly plasma and erythrocytes determine the dielectric properties of whole blood. Erythrocytes suspended in plasma can be considered as three-phase systems with single-shelled particles. A theoretical approach based on the effective medium theory is developed for calculating the effective permittivity and conductivity of three-phase composites at a wide frequency range (from 0 to 1 GHz). A finite-difference method is applied to model three-dimensional periodic structures. A special case of two-phase materials is used to demonstrate the influence of the shape and arrangement of particles on dielectric properties. Theoretical and numerical approaches are applied to two-phase composites with spherical, spheroidal and biconcave particles and are compared with each other and with published data. It is shown that two-phase composites exhibit only β-dispersion. In contrast to the quasi-static limit, the wide-bandwidth impedance spectroscopy makes it possible to distinguish between disordered and regular arrangements of spheroidal and biconcave particles. The results can be used to analyze the dielectric properties of blood, which is very promising for various medical applications. This study of two-phase composites can be further extended to three-phase composites. [ABSTRACT FROM AUTHOR]

Objective: Spectral analysis of laser Doppler flowmetry (LDF) signals has been widely used in studies of physiological vascular function regulation. An alternative to LDF is the laser speckle contrast imaging method (LSCI), which is based on the same physical principle. In contrast to LDF, LSCI provides non-scanning full-field imaging of a relatively wide skin area and offers high spatial and temporal resolutions, which allows visualization of microvascular structure. This circumstance, together with a large number of works which had shown the effectiveness of temporal LSCI analysis, gave impetus to experimental studies of the relation between LDF and LSCI used to monitor the temporal dynamics of blood flow. Methods: Continuous wavelet transform was applied to construct a time-frequency representation of a signal. Results: Analysis of 10 minute LDF and LSCI output signals recorded simultaneously revealed rather high correlation between oscillating components. It was demonstrated for the first time that the spectral energy of oscillations in the 0.01–2 Hz frequency range of temporal LSCI recordings carries the same information as the conventional LDF recordings and hence it reflects the same physiological vascular tone regulation mechanisms. Conclusion: The approach proposed can be used to investigate speckle pattern dynamics by LSCI in both normal and pathological conditions. Significance: The results of research on the influence of spatial binning and averaging on the spectral characteristics of perfusion monitored by LSCI are of considerable interest for the development of LSCI systems optimized to evaluate temporal dynamics. [ABSTRACT FROM AUTHOR]

Objective: Cerebrovascular diseases are one of the main global causes of death and disability in the adult population. The preferred imaging modality for the diagnostic routine is digital subtraction angiography, an invasive modality. Time-resolved three-dimensional arterial spin labeling magnetic resonance angiography (4D ASL MRA) is an alternative non-invasive modality, which captures morphological and blood flow data of the cerebrovascular system, with high spatial and temporal resolution. This work proposes advanced medical image processing methods that extract the anatomical and hemodynamic information contained in 4D ASL MRA datasets. Methods: A previously published segmentation method, which uses blood flow data to improve its accuracy, is extended to estimate blood flow parameters by fitting a mathematical model to the measured vascular signal. The estimated values are then refined using regression techniques within the cerebrovascular segmentation. The proposed method was evaluated using fifteen 4D ASL MRA phantoms, with ground-truth morphological and hemodynamic data, fifteen 4D ASL MRA datasets acquired from healthy volunteers, and two 4D ASL MRA datasets from patients with a stenosis. Results: The proposed method reached an average Dice similarity coefficient of 0.957 and 0.938 in the phantom and real dataset segmentation evaluations, respectively. The estimated blood flow parameter values are more similar to the ground-truth values after the refinement step, when using phantoms. A qualitative analysis showed that the refined blood flow estimation is more realistic compared to the raw hemodynamic parameters. Conclusion: The proposed method can provide accurate segmentations and blood flow parameter estimations in the cerebrovascular system using 4D ASL MRA datasets. Significance: The information obtained with the proposed method can help clinicians and researchers to study the cerebrovascular system non-invasively. [ABSTRACT FROM AUTHOR]

Objective: A noninvasive intracranial pressure (ICP) estimation method is proposed that incorporates a model-based approach within a probabilistic framework to mitigate the effects of data and modeling uncertainties. Methods: A first-order model of the cerebral vasculature relates measured arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) to ICP. The model is driven by the ABP waveform and is solved for a range of mean ICP values to predict the CBFV waveform. The resulting errors between measured and predicted CBFV are transformed into likelihoods for each candidate ICP in two steps. First, a baseline ICP estimate is established over five data windows of 20 beats by combining the likelihoods with a prior distribution of the ICP to yield an a posteriori distribution whose median is taken as the baseline ICP estimate. A single-state model of cerebral autoregulatory dynamics is then employed in subsequent data windows to track changes in the baseline by combining ICP estimates obtained with a uniform prior belief and model-predicted ICP. For each data window, the estimated model parameters are also used to determine the ICP pulse pressure. Results: On a dataset of thirteen pediatric patients with a variety of pathological conditions requiring invasive ICP monitoring, the method yielded for mean ICP estimation a bias (mean error) of 0.6 mmHg and a root-mean-squared error of 3.7 mmHg. Conclusion: These performance characteristics are well within the acceptable range for clinical decision making. Significance: The method proposed here constitutes a significant step towards robust, continuous, patient-specific noninvasive ICP determination. [ABSTRACT FROM AUTHOR]

Near-infrared (NIR) remote photoplethysmography (PPG) promises attractive applications in darkness, as it involves unobtrusive, invisible light. However, since the PPG strength (AC/DC) is much lower in the NIR spectrum than in the RGB spectrum, robust vital signs monitoring is more challenging. In this paper, we propose a new PPG-extraction method, DIScriminative signature based extraction (DIS), to significantly improve the pulse-rate measurement in NIR. Our core idea is to use both the color signals containing blood absorption variations and additional disturbance signals as input for PPG extraction. By defining a discriminative signature, we use one-step least-squares regression (joint optimization) to retrieve the pulsatile component from color signals and suppress disturbance signals simultaneously. A large-scale lab experiment, recorded in NIR with heavy body motions, shows the significant improvement of DIS over the state-of-the-art method, whereas its principle is simple and generally applicable. [ABSTRACT FROM AUTHOR]

Objective: Hemolysis is one of the main reasons for blood sample rejection in clinical laboratories. The scope of this study is to develop a simple, sensitive, and cost-effective method for hemolysis detection in presence of interferants like bilirubin, and lipids in sub-microliter volumes of blood plasma. Methods: Experimental samples were prepared in plasma extracted from whole blood. These samples were typically mixtures of hemoglobin, bilirubin, and lipids of varying concentrations. A multispectral optical setup was devised to probe these samples without any optical filters or moving parts. Results: The hemoglobin content in the samples were measured within the range of 0 mg/dL to 400 mg/dL concentration using <1 μL of detection volume. Detection sensitivity of >90% accuracy and ∼10% coefficient of variation across 27 unknown samples. The optical attenuation path length used was merely ∼150 micrometers. The spectral interference due to overlapping absorption spectrum of bilirubin and scattering spectrum of lipids are resolved using linear matrix algebra algorithms. Conclusion: Hemolysis can lead to spurious measurements of key clinical parameters such as Potassium, Lactate Dehydrogenase, Aspartic Acid Transferase, and other diagnostic biomarkers. Commonly used visual inspection of blood plasma coloration is prone to variability. Description of the sample preparation, calibration and verification of the experimental setup and linear matrix algebra algorithm for analyte interference determination is reported here. Significance: Owing to the sub-microliter detection volume and high sensitivity, the system has realistic potential to be implemented in point of care medical devices that demands such low volumes of clinical specimen. [ABSTRACT FROM AUTHOR]

Objective: Vascular permeability (VP) is a mechanical parameter which plays an important role in cancer initiation, metastasis, and progression. To date, there are only a few non-invasive methods that can be used to image VP in solid tumors. Most of these methods require the use of contrast agents and are expensive, limiting widespread use. Methods: In this paper, we propose a new method to image VP in tumors, which is based on the use of ultrasound poroelastography. Estimation of VP by poroelastography requires knowledge of the Young's modulus (YM), Poisson's ratio (PR), and strain time constant (TC) in the tumors. In our method, we find the ellipse which best fits the tumor (regardless of its shape) using an eigen-system-based fitting technique and estimate the YM and PR using Eshelby's elliptic inclusion formulation. A Fourier method is used to estimate the axial strain TC, which does not require any initial guess and is highly robust to noise. Results: It is demonstrated that the proposed method can estimate VP in irregularly shaped tumors with an accuracy of above $\text{80}\%$ using ultrasound simulation data with signal-to-noise ratio of 20 dB or higher. In vivo feasibility of the proposed technique is demonstrated in an orthotopic mouse model of breast cancer. Conclusion: The proposed imaging method can provide accurate and localized estimation of VP in cancers non-invasively and cost-effectively. Significance: Accurate and non-invasive assessment of VP can have a significant impact on diagnosis, prognosis, and treatment of cancers. [ABSTRACT FROM AUTHOR]

Objective: The hepatic arterial buffer response is a well-known phenomenon in hepatic circulation, describing the response of hepatic arterial resistance to changes in portal vein flow. Several vasoactive metabolites underlying its mechanism have been proposed, however, there is currently no clear consensus. The aim of this study is to investigate the hepatic arterial buffer response of porcine livers preserved in a controlled ex vivo perfusion machine. Methods: Porcine livers are perfused on an ex vivo perfusion machine and hemodynamic experiments investigating the hepatic arterial resistance response to portal vein flow and vena cava pressure variations are conducted. A simple hemodynamic model is developed to support the interpretation of the received measurements. Further, a mechanism is proposed that explains hepatic arterial resistance changes in response to vena cava pressure as myogenic and in response to portal vein flow as a combined washout and myogenic effect. Results: A clear correlation between hepatic sinusoidal pressure levels and hepatic arterial resistance is observed where an increase of approximately 4 mmHg of hepatic sinusoidal pressure level results in doubling of the hepatic arterial resistance. This relation is considered during the analysis of the portal vein flow variations resulting in a reduced isolated effect of adenosine washout on hepatic arterial resistance. With an average buffer capacity of 27% during our experiments, the hepatic arterial buffer response shows to be unimpaired in the ex vivo scenario. Conclusion: First, washout and myogenic effects both influence the hepatic arterial buffer response; and second, hepatic sinusoidal pressure levels strongly influence the hepatic arterial resistance. Significance: These results present new findings in hemodynamics of the liver, which are fundamental for successful ex vivo liver perfusion. [ABSTRACT FROM AUTHOR]

Objective: We take the release of stress hormone cortisol as a part of an intermittent control feedback system in contrast to the existing continuous models. By modeling cortisol secretion as an impulsive system, we design an impulsive controller as opposed to a continuous controller for adjusting cortisol levels while maintaining the blood cortisol levels within bounds that satisfy circadian demand and cost constraints. Methods: We develop an analytical approach along with an algorithm for identifying both the timing and amplitude of the control. Results: The model and the algorithm are tested by two examples to illustrate that the proposed approach achieves impulsive control and that the obtained blood cortisol levels render the circadian rhythm and the ultradian rhythm consistent with the known physiology of cortisol secretion. Conclusions: The approach successfully achieves the desired circadian impulsive control, which has great potential to be used in personalizing the medications in order to control the cortisol levels optimally. Significance: This type of bioinspired intermittent controllers can be employed for designing noncontinuous controllers in treating Addisonian disease, which is caused by the adrenal deficiency. [ABSTRACT FROM AUTHOR]

Objective: This paper focuses on a novel and portable device prototype with optical detectors to quickly and efficiently detect hemozoin (Hz) in blood, aiming at malaria diagnostics. Methods: Taking advantage of the particular features of malaria parasite in infected blood, particularly the Hz formation, the main innovation described is a portable device for the optical quantification of parasitic Hz in blood, through optical absorbance spectrophotometry. This device comprises detection chambers for fluidic samples, an optical emission and detection system, and a power supply system to provide autonomy. The working principle is based on colorimetric detection, by absorbance, at six specific wavelengths. A detection algorithm relates the absorbance values at all wavelengths to quantify the Hz concentration, thus working as a biomarker of malaria presence and stage. Results: Under the tested conditions, e.g., in fluidic samples containing synthetic Hz, hemoglobin, and diluted whole blood, the device detected Hz above 1 μg/mL concentrations with 100% sensitivity and 96.3% specificity. Conclusion: This paper features an autonomous, portable, 1-min analysis time, and low-cost per test device, without the need for samples, centrifugation, allowing the use of whole blood. Significance: The presented device is a step ahead for meeting the growing clinical demands for reliable, rapid, portable, and quantitative malaria diagnosis. [ABSTRACT FROM AUTHOR]

Objective: Diabetes patients are increasingly using a continuous glucose sensor to monitor blood glucose and an insulin pump connected to an infusion cannula to administer insulin. Applying these devices requires two separate insertion sites, one for the sensor and one for the cannula. Integrating sensor with cannula to perform glucose sensing and insulin infusion through a single insertion site would significantly simplify and improve diabetes treatment by reducing the overall system size and the number of necessary needle pricks. Presently, several research groups are pursuing the development of combined glucose sensing and insulin infusion devices, termed single-port devices, by integrating sensing and infusion technologies created from scratch. Methods: Instead of creating the device from scratch, we utilized already existing technologies and introduced three design concepts of integrating commercial glucose sensors and infusion cannulas. We prototyped and evaluated each concept according to design simplicity, ease of insertion, and sensing accuracy. Results: We found that the best single-port device is the one in which a Dexcom sensor is housed inside a Medtronic cannula so that its glucose sensitive part protrudes from the cannula tip. The low degree of component modification required to arrive at this configuration allowed us to test the efficiency and safety of the device in humans. Conclusion: Results from these studies indicate the feasibility of combining commercial glucose sensing and insulin delivery technologies to realize a functional single-port device. Significance: Our development approach may be generally useful to provide patients with innovative medical devices faster and at reduced costs. [ABSTRACT FROM AUTHOR]

Fontan patients often develop circulatory failure and are in desperate need of a therapeutic solution. A blood pump surgically placed in the cavopulmonary pathway can substitute the function of the absent sub-pulmonary ventricle by generating a mild pressure boost. However, there is currently no commercially available device designed for the cavopulmonary application; and the risks and benefits of implanting a ventricular assist device (VAD), originally designed for the left ventricular application, on the right circulation of failing Fontan patients is not yet clear. Moreover, further research is needed to compare the hemodynamics between the two clinically-considered surgical configurations for cavopulmonary assist, with Full and inferior vena cava (IVC) support corresponding to the entire venous return or only the inferior venous return, respectively, being routed through the VAD. In this study, we used a numerical model of the failing Fontan physiology to evaluate the Fontan hemodynamic response to a left VAD during the IVC and Full support scenarios. We observed that during Full support, the VAD improved the cardiac output while maintaining blood pressures within safe ranges, and lowered the IVC pressure to <15 mmHg; however, we found a potential risk of lung damage at higher pump speeds due to the excessive pulmonary pressure elevation. IVC support, on the other hand, did not benefit the hemodynamics in the patient cases simulated, resulting in the superior vena cava pressure increasing to an unsafe level of >20 mmHg. The findings in this study may be helpful to surgeons for recognizing the risks of a cavopulmonary VAD and developing coherent clinical strategies for the implementation of cavopulmonary support. [ABSTRACT FROM AUTHOR]

Objective: Non-invasive sensing and reliable estimation of physiological parameters are important features of hemodialysis machines, especially for therapy customization (biofeedback). In this paper, we present a new method for joint estimation of two important hemodialysis-related physiological parameters—relative blood volume and plasma sodium concentration. Methods: Our method makes use of a non-invasive sensor setup and a mathematical estimator. The estimator, based on the Kalman filter, allows merging data from multiple sensors, newly designed as well as onboard, with modeling knowledge about the hemodialysis process. The system was validated on in vitro hemodialysis sessions using bovine blood. Results: The estimation error we obtained (0.97 ± 0.73% on relative blood volume and 0.47 ± 0.19 mM on plasmatic sodium) proved to be comparable with that of the reference data for both parameters—the system is sufficiently accurate to be relevant in a clinical context. Conclusion: Our system has the potential to provide accurate and important information on the state of a patient undergoing hemodialysis, while only low-cost modifications to the existing onboard sensors are required. Significance: Through improved knowledge of blood parameters during hemodialysis, our method will allow better patient monitoring and therapy customization in hemodialysis. [ABSTRACT FROM AUTHOR]

Objective: Septic shock (SS) patients often show elevated heart rate (HR) despite resuscitation, and this condition is considered an early manifestation of myocardial dysfunction due to an impairment of autonomic nervous system (ANS). We aimed at proposing a mathematical model to assess the autonomic control of ventricular contractility (VC) and HR to track changes in heart functionality during an experimental animal model of SS and resuscitation. Methods: SS was induced in six adult swine by polymicrobial peritonitis. We analyzed the beat-to-beat variability of the maximum positive time derivative of left ventricular pressure (dP/dt max), heart period (HP), and aortic blood pressure (ABP). We identified the transfer functions relating fluctuations in ABP and HP to dP/dt max to characterize the static and dynamic properties of the arterial baroreflex and the force-frequency relation mechanisms, respectively. Standard indices of autonomic dysfunction have also been considered as HR variability (HRV) and baroreflex sensitivity (BRS). Results: During baseline, the baroreflex is predominant in controlling VC with a gain value of −5.8 (−7.5,−3) s−1, compared to −1.2 (−1.9,−0.5) mmHg/s ms−1 of the force–frequency autoregulation. During shock, both mechanisms increase their extent in VC control (higher gains and slightly faster dynamics for the baroreflex). After resuscitation, the physiological control of VC is not restored and all the animals still exhibit high HR and reduced HRV and BRS. Conclusion: A condition of cardiovascular inefficiency is persistent after resuscitation and this could be due to autonomic dysfunction. Significance: The ANS in SS is crucial to restore homeostasis. Our model could be used to evaluate the efficacy of treatments on VC and related control mechanisms. [ABSTRACT FROM AUTHOR]

Objective: To develop quantitative methods for the clinical interpretation of the ballistocardiogram (BCG). Methods: A closed-loop mathematical model of the cardiovascular system is proposed to theoretically simulate the mechanisms generating the BCG signal, which is then compared with the signal acquired via accelerometry on a suspended bed. Results: Simulated arterial pressure waveforms and ventricular functions are in good qualitative and quantitative agreement with those reported in the clinical literature. Simulated BCG signals exhibit the typical I, J, K, L, M, and N peaks and show good qualitative and quantitative agreement with experimental measurements. Simulated BCG signals associated with reduced contractility and increased stiffness of the left ventricle exhibit different changes that are characteristic of the specific pathological condition. Conclusion: The proposed closed-loop model captures the predominant features of BCG signals and can predict pathological changes on the basis of fundamental mechanisms in cardiovascular physiology. Significance: This paper provides a quantitative framework for the clinical interpretation of BCG signals and the optimization of BCG sensing devices. The present paper considers an average human body and can potentially be extended to include variability among individuals. [ABSTRACT FROM AUTHOR]