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Characterization of blood flow rheology in hematological disorders is critical for understanding disease pathophysiology. Existing methods to measure blood rheological parameters are limited in their physiological relevance, and there is a need for new tools that focus on the microcirculation and extract properties at finer resolution than overall flow resistance. Herein, we present a method that combines microfluidic systems and powerful object-tracking computational technologies with mathematical modeling to separate the red blood cell flow profile into a bulk component and a wall component. We use this framework to evaluate differential contributions of effective viscosity and wall friction to the overall resistance in blood from patients with sickle cell disease (SCD) under a range of oxygen tensions. Our results demonstrate that blood from patients with SCD exhibits elevated frictional and viscous resistances at all physiologic oxygen tensions. Additionally, the viscous resistance increases more rapidly than the frictional resistance as oxygen tension decreases, which may confound analyses that extract only flow velocities or overall flow resistances. Furthermore, we evaluate the impact of transfusion treatments on the components of the resistance, revealing patient variability in blood properties that may improve our understanding of the heterogeneity of clinical responses to such treatments. Overall, our system provides a new method to analyze patient-specific blood properties and can be applied to a wide range of hematological and vascular disorders.

Four-dimensional flow magnetic resonance imaging (i.e., 4D flow MRI) has become a valuable tool for the in vivo assessment of blood flow within large vessels and cardiac chambers. As wall shear stress (WSS) has been correlated with the development and progression of cardiovascular disease, focus has been directed at developing techniques to quantify WSS directly from 4D flow MRI data. The goal of this study was to compare the accuracy of two such techniques - termed the velocity and flow-based methods - in the setting of simplified and complex flow scenarios. Synthetic MR data were created from exact solutions to the Navier-Stokes equations for the steady and pulsatile flow of an incompressible, Newtonian fluid through a rigid cylinder. In addition, synthetic MR data were created from the predicted velocity fields derived from a fluid-structure interaction (FSI) model of pulsatile flow through a thick-walled, multi-layered model of the carotid bifurcation. Compared to the analytical solutions for steady and pulsatile flow, the flow-based method demonstrated greater accuracy than the velocity-based method in calculating WSS across all changes in fluid velocity/flow rate, tube radius, and image signal-to-noise (p 0.001). Furthermore, the velocity-based method was more sensitive to boundary segmentation than the flow-based method. When compared to results from the FSI model, the flow-based method demonstrated greater accuracy than the velocity-based method with average differences in time-averaged WSS of 0.31 ± 1.03 Pa and 0.45 ± 1.03 Pa, respectively (p 0.005). These results have implications on the utility, accuracy, and clinical translational of methods to determine WSS from 4D flow MRI.

During the COVID-19 pandemic, the development of point-of-care (POC) diagnostic testing accelerated in an unparalleled fashion. As a result, there has been an increased need for accurate, robust, and easy-to-use POC testing in a variety of non-traditional settings (i.e., pharmacies, drive-thru sites, schools). While stakeholders often express the desire for POC technologies that are "as simple as digital pregnancy tests," there is little discussion of what this means in regards to device design, development, and assessment. The design of POC technologies and systems should take into account the capabilities and limitations of the users and their environments. Such "human factors" are important tenets that can help technology developers create POC technologies that are effective for end-users in a multitude of settings. Here, we review the core principles of human factors and discuss lessons learned during the evaluation process of SARS-CoV-2 POC testing.

Wall shear stress (WSS) is an important mediator of cardiovascular pathologies and there is a need for its reliable evaluation as a potential prognostic indicator. The purpose of this work was to develop a method that quantifies WSS from two-dimensional (2D) phase contrast magnetic resonance (PCMR) imaging derived flow waveforms, apply this method to PCMR data acquired in the abdominal aorta of healthy volunteers, and to compare PCMR-derived WSS values to values predicted from a computational fluid dynamics (CFD) simulation. The method uses PCMR-derived flow versus time waveforms constrained by the Womersley solution for pulsatile flow in a cylindrical tube. The method was evaluated for sensitivity to input parameters, intrastudy repeatability and was compared with results from a patient-specific CFD simulation. 2D-PCMR data were acquired in the aortas of healthy men (n = 12) and women (n = 15) and time-averaged WSS (TAWSS) was compared. Agreement was observed when comparing TAWSS between CFD and the PCMR flow-based method with a correlation coefficient of 0.88 (CFD: 15.0 ± 1.9 versus MRI: 13.5 ± 2.4 dyn/cm2) though comparison of WSS values between the PCMR-based method and CFD predictions indicate that the PCMR method underestimated instantaneous WSS by 3.7 ± 7.6 dyn/cm2. We found no significant difference in TAWSS magnitude between the sexes; 8.19 ± 2.25 versus 8.07 ± 1.71 dyn/cm2, p = 0.16 for men and women, respectively.

Background Knowledge of tissue properties of the abdominal aorta can improve understanding of vascular disease and guide interventional approaches. Existing MRI methods to quantify aortic wall displacement and strain are unable to discern circumferential heterogeneity. Purpose To assess regional variation in abdominal aortic wall displacement and strain as a function of circumferential position using spiral cine displacement encoding with stimulated echoes (DENSE). Study type Prospective. Population Cardiovascular disease-free men (n = 8) and women (n = 9) ages 30-42. Sequences Prospective electrocardiogram (ECG)-gated and navigator echo-gated spiral, cine 2D DENSE and retrospective ECG-gated phase contrast MR (PCMR) sequences at 3T. Assessment In-plane displacement values of the aortic wall acquired with DENSE were used to determine radial and circumferential aortic wall motion. A quadrilateral-based 2D strain calculation method was implemented to determine strain from the displacement field. Peak displacement and its radial and circumferential contributions as well as peak circumferential strain were compared among eight circumferential wall segments. Distensibility was calculated using PCMR and compared with homogenized circumferential strain. Statistical tests To account for repeated measurements in volunteers, linear mixed models for mean sector values were created for displacement magnitude, circumferential displacement, radial displacement, and circumferential strain. Comparisons were made between sectors. Calculated distensibility and homogenized circumferential strain were compared using Bland-Altman analysis. Statistical significance was defined as P Results Displacement was highest in the anterior wall (1.5 ± 0.7 mm) and was primarily in the radial as compared with circumferential direction (1.04 ± 0.05 mm vs. 0.81 ± 0.42 mm). Circumferential strain was highest in the lateral walls (left 0.16 ± 0.05 and right 0.21 ± 0.12) with homogenized circumferential strain of 0.14 ± 0.05. Data conclusion DENSE imaging in the abdominal aortic wall demonstrated that the anterior aortic wall exhibits the greatest displacement, while the lateral wall experiences the largest circumferential strain. Level of evidence 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:731-743.

Background Stanford type B dissection of the descending aorta is a potentially fatal condition that is poorly understood. Limited scientific understanding of the role of current interventional techniques, as well as heterogeneity in the condition, contributes to lack of consensus as to the most effective treatment strategy. This study introduces an anatomically accurate model for investigating aortic dissection in a laboratory setting. Materials and methods A silicone model was fabricated and filled with fluid to mimic human blood. Flow was established, and the model was scanned using a four-dimensional flow magnetic resonance imaging protocol. On analysis, luminal flow rates were quantified by multiplying local velocity by included area. Results The upstream total flow was compared with the sum of the flow in the true and false lumens. The two values were within the margin of error. Furthermore, flow rates matched with the relative areas of each compartment. Conclusions These results validate our model as a novel and unique system that mimics a type B aortic dissection and will allow for more sophisticated analysis of dissection physiology in future studies.

Knowledge of tissue properties of the abdominal aorta can improve understanding of vascular disease and guide interventional approaches. Existing MRI methods to quantify aortic wall displacement and strain are unable to discern circumferential heterogeneity.To assess regional variation in abdominal aortic wall displacement and strain as a function of circumferential position using spiral cine displacement encoding with stimulated echoes (DENSE).Prospective.Cardiovascular disease-free men (n = 8) and women (n = 9) ages 30-42.Prospective electrocardiogram (ECG)-gated and navigator echo-gated spiral, cine 2D DENSE and retrospective ECG-gated phase contrast MR (PCMR) sequences at 3T.In-plane displacement values of the aortic wall acquired with DENSE were used to determine radial and circumferential aortic wall motion. A quadrilateral-based 2D strain calculation method was implemented to determine strain from the displacement field. Peak displacement and its radial and circumferential contributions as well as peak circumferential strain were compared among eight circumferential wall segments. Distensibility was calculated using PCMR and compared with homogenized circumferential strain.To account for repeated measurements in volunteers, linear mixed models for mean sector values were created for displacement magnitude, circumferential displacement, radial displacement, and circumferential strain. Comparisons were made between sectors. Calculated distensibility and homogenized circumferential strain were compared using Bland-Altman analysis. Statistical significance was defined as P 0.05.Displacement was highest in the anterior wall (1.5 ± 0.7 mm) and was primarily in the radial as compared with circumferential direction (1.04 ± 0.05 mm vs. 0.81 ± 0.42 mm). Circumferential strain was highest in the lateral walls (left 0.16 ± 0.05 and right 0.21 ± 0.12) with homogenized circumferential strain of 0.14 ± 0.05.DENSE imaging in the abdominal aortic wall demonstrated that the anterior aortic wall exhibits the greatest displacement, while the lateral wall experiences the largest circumferential strain.3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:731-743.

The prevalence of abdominal aortic aneurysms differs greatly between men and women across the spectrum of ages. The reason for this discrepancy is not clear and likely involves several factors including the impact of sex hormones. We hypothesize that the unique spatial localization of abdominal aortic aneurysms is dictated in part by local hemodynamic forces on the vascular wall. Specifically, we propose that oscillatory shear stress is a specific signal to the endothelium that initiates the events ultimately leading to abdominal aortic aneurysm formation. We are proposing that sex-dependent differences in oscillatory shear stress in the infra-renal aorta may explain the observed differences between men and women. Initial observations suggest that, indeed, men and women have different degrees of oscillatory blood flow in the infra-renal abdominal aorta. The challenge is to extend these observations to show a causal relationship between oscillatory flow and aneurysm formation.