15 research outputs found

    Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images

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    Polymeric endovascular implants are the next step in minimally invasive vascular interventions. As an alternative to traditional metallic drug-eluting stents, these often-erodible scaffolds present opportunities and challenges for patients and clinicians. Theoretically, as they resorb and are absorbed over time, they obviate the long-term complications of permanent implants, but in the short-term visualization and therefore positioning is problematic. Polymeric scaffolds can only be fully imaged using optical coherence tomography (OCT) imaging—they are relatively invisible via angiography—and segmentation of polymeric struts in OCT images is performed manually, a laborious and intractable procedure for large datasets. Traditional lumen detection methods using implant struts as boundary limits fail in images with polymeric implants. Therefore, it is necessary to develop an automated method to detect polymeric struts and luminal borders in OCT images; we present such a fully automated algorithm. Accuracy was validated using expert annotations on 1140 OCT images with a positive predictive value of 0.93 for strut detection and an R^2 correlation coefficient of 0.94 between detected and expert-annotated lumen areas. The proposed algorithm allows for rapid, accurate, and automated detection of polymeric struts and the luminal border in OCT images

    Demonstration of a Longitudinal Action Medical Mission (LAMM) Model to Teach Point-of-Care Ultrasound in Resource-Limited Settings

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    BACKGROUND: Short-term medical missions prevail as the most common form of international medical volunteerism, but they are ill-suited for medical education and training local providers in resource-limited settings. OBJECTIVE: The purpose of this study is to evaluate the effectiveness of a longitudinal educational program in training clinicians how to perform point-of-care ultrasound (POCUS) in resource-limited clinics. DESIGN: A retrospective study of such a four-month POCUS training program was conducted with clinicians from a rural hospital in Haiti. The model included one-on-one, in-person POCUS teaching sessions by volunteer instructors from the United States and Europe. The Haitian trainees were assessed at the start of the program and at its conclusion by a direct objective structured clinical examination (OSCE), administered by the visiting instructors, with similar pre- and post- program ultrasound competency assessments. RESULTS: Post-intervention, a significant improvement was observed (p < 0.0001), and each trainee showed significant overall improvement in POCUS competency independent of the initial competency pre-training (p < 0.005). There was a statistically significant improvement in POCUS application for five of the six medically relevant assessment categories tested. CONCLUSION: Our results provide a proof-of-concept for the longitudinal education-centered healthcare delivery framework in a resource-limited setting. Our longitudinal model provides local healthcare providers the skills to detect and diagnose significant pathologies, thereby reducing avoidable morbidity and mortality at little or no addition cost or risk to the patient. Furthermore, training local physicians obviates the need for frequent volunteering trips, saving costs in healthcare training and delivery

    Cell specific peripheral immune responses predict survival in critical COVID-19 patients

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    SARS-CoV-2 triggers a complex systemic immune response in circulating blood mononuclear cells. The relationship between immune cell activation of the peripheral compartment and survival in critical COVID-19 remains to be established. Here we use single-cell RNA sequencing and Cellular Indexing of Transcriptomes and Epitomes by sequence mapping to elucidate cell type specific transcriptional signatures that associate with and predict survival in critical COVID-19. Patients who survive infection display activation of antibody processing, early activation response, and cell cycle regulation pathways most prominent within B-, T-, and NK-cell subsets. We further leverage cell specific differential gene expression and machine learning to predict mortality using single cell transcriptomes. We identify interferon signaling and antigen presentation pathways within cDC2 cells, CD14 monocytes, and CD16 monocytes as predictors of mortality with 90% accuracy. Finally, we validate our findings in an independent transcriptomics dataset and provide a framework to elucidate mechanisms that promote survival in critically ill COVID-19 patients. Identifying prognostic indicators among critical COVID-19 patients holds tremendous value in risk stratification and clinical management

    Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images

    Get PDF
    Polymeric endovascular implants are the next step in minimally invasive vascular interventions. As an alternative to traditional metallic drug-eluting stents, these often-erodible scaffolds present opportunities and challenges for patients and clinicians. Theoretically, as they resorb and are absorbed over time, they obviate the long-term complications of permanent implants, but in the short-term visualization and therefore positioning is problematic. Polymeric scaffolds can only be fully imaged using optical coherence tomography (OCT) imaging—they are relatively invisible via angiography—and segmentation of polymeric struts in OCT images is performed manually, a laborious and intractable procedure for large datasets. Traditional lumen detection methods using implant struts as boundary limits fail in images with polymeric implants. Therefore, it is necessary to develop an automated method to detect polymeric struts and luminal borders in OCT images; we present such a fully automated algorithm. Accuracy was validated using expert annotations on 1140 OCT images with a positive predictive value of 0.93 for strut detection and an R^2 correlation coefficient of 0.94 between detected and expert-annotated lumen areas. The proposed algorithm allows for rapid, accurate, and automated detection of polymeric struts and the luminal border in OCT images

    Mixed Valvular Disease Following Transcatheter Aortic Valve Replacement: Quantification and Systematic Differentiation Using Clinical Measurements and Image-Based Patient‐Specific In Silico Modeling

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    Background: Mixed valvular disease (MVD), mitral regurgitation (MR) from pre‐existing disease in conjunction with paravalvular leak (PVL) following transcatheter aortic valve replacement (TAVR), is one of the most important stimuli for left ventricle (LV) dysfunction, associated with cardiac mortality. Despite the prevalence of MVD, the quantitative understanding of the interplay between pre‐existing MVD, PVL, LV, and post‐TAVR recovery is meager. Methods and Results: We quantified the effects of MVD on valvular‐ventricular hemodynamics using an image‐based patient‐specific computational framework in 72 MVD patients. Doppler pressure was reduced by TAVR (mean, 77%; N=72; P<0.05), but it was not always accompanied by improvements in LV workload. TAVR had no effect on LV workload in 22 patients, and LV workload post‐TAVR significantly rose in 32 other patients. TAVR reduced LV workload in only 18 patients (25%). PVL significantly alters LV flow and increases shear stress on transcatheter aortic valve leaflets. It interacts with mitral inflow and elevates shear stresses on mitral valve and is one of the main contributors in worsening of MR post‐TAVR. MR worsened in 32 patients post‐TAVR and did not improve in 18 other patients. Conclusions: PVL limits the benefit of TAVR by increasing LV load and worsening of MR and heart failure. Post‐TAVR, most MVD patients (75% of N=72; P<0.05) showed no improvements or even worsening of LV workload, whereas the majority of patients with PVL, but without that pre‐existing MR condition (60% of N=48; P<0.05), showed improvements in LV workload. MR and its exacerbation by PVL may hinder the success of TAVR

    Mixed Valvular Disease Following Transcatheter Aortic Valve Replacement: Quantification and Systematic Differentiation Using Clinical Measurements and Image-Based Patient‐Specific In Silico Modeling

    Get PDF
    Background: Mixed valvular disease (MVD), mitral regurgitation (MR) from pre‐existing disease in conjunction with paravalvular leak (PVL) following transcatheter aortic valve replacement (TAVR), is one of the most important stimuli for left ventricle (LV) dysfunction, associated with cardiac mortality. Despite the prevalence of MVD, the quantitative understanding of the interplay between pre‐existing MVD, PVL, LV, and post‐TAVR recovery is meager. Methods and Results: We quantified the effects of MVD on valvular‐ventricular hemodynamics using an image‐based patient‐specific computational framework in 72 MVD patients. Doppler pressure was reduced by TAVR (mean, 77%; N=72; P<0.05), but it was not always accompanied by improvements in LV workload. TAVR had no effect on LV workload in 22 patients, and LV workload post‐TAVR significantly rose in 32 other patients. TAVR reduced LV workload in only 18 patients (25%). PVL significantly alters LV flow and increases shear stress on transcatheter aortic valve leaflets. It interacts with mitral inflow and elevates shear stresses on mitral valve and is one of the main contributors in worsening of MR post‐TAVR. MR worsened in 32 patients post‐TAVR and did not improve in 18 other patients. Conclusions: PVL limits the benefit of TAVR by increasing LV load and worsening of MR and heart failure. Post‐TAVR, most MVD patients (75% of N=72; P<0.05) showed no improvements or even worsening of LV workload, whereas the majority of patients with PVL, but without that pre‐existing MR condition (60% of N=48; P<0.05), showed improvements in LV workload. MR and its exacerbation by PVL may hinder the success of TAVR

    SVEP1 is an endogenous ligand for the orphan receptor PEAR1

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    Sushi, von Willebrand factor type A, EGF and pentraxin domain containing 1 (SVEP1) is an extracellular matrix protein that causally promotes vascular disease and associates with platelet reactivity in humans. Here, using a human genomic and proteomic approach, we identify a high affinity, disease-relevant, and potentially targetable interaction between SVEP1 and the orphan receptor Platelet and Endothelial Aggregation Receptor 1 (PEAR1). This interaction promotes PEAR1 phosphorylation and disease associated AKT/mTOR signaling in vascular cells and platelets. Mice lacking SVEP1 have reduced platelet activation, and exogenous SVEP1 induces PEAR1-dependent activation of platelets. SVEP1 and PEAR1 causally and concordantly relate to platelet phenotypes and cardiovascular disease in humans, as determined by Mendelian Randomization. Targeting this receptor-ligand interaction may be a viable therapeutic strategy to treat or prevent cardiovascular and thrombotic disease

    Multilayer flow modulator enhances vital organ perfusion in patients with type B aortic dissection

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    Management of aortic dissections (AD) is still challenging, with no universally approved guideline among possible surgical, endovascular, or medical therapies. Approximately 25% of patients with AD suffer postintervention malperfusion syndrome or hemodynamic instability, with the risk of sudden death if left untreated. Part of the issue is that vascular implants may themselves induce flow disturbances that critically impact vital organs. A multilayer mesh construct might obviate the induced flow disturbances, and it is this concept we investigated. We used preintervention and post-multilayer flow modulator implantation (PM) geometries from clinical cases of type B AD. In-house semiautomatic segmentation routines were applied to computed tomography images to reconstruct the lumen. The device was numerically reconstructed and adapted to the PM geometry concentrically fit to the true lumen centerline. We also numerically designed a pseudohealthy case, where the geometry of the aorta was extracted interpolating geometric features of preintervention, postimplantation, and published representative healthy volunteers. Computational fluid dynamics methods were used to study the time-dependent flow patterns, shear stress metrics, and perfusion to vital organs. A three-element Windkessel lumped parameter module was coupled to a finite-volume solver to assign dynamic outlet boundary conditions. Multilayer flow modulator not only significantly reduced false lumen blood flow, eliminated local flow disturbances, and globally regulated wall shear stress distribution but also maintained physiological perfusion to peripheral vital organs. We propose further investigation to focus the management of AD on both modulation of blood flow and restoration of physiologic end-organ perfusion rather than mere restoration of vascular lamina morphology

    Multilayer flow modulator enhances vital organ perfusion in patients with type B aortic dissection

    No full text
    Management of aortic dissections (AD) is still challenging, with no universally approved guideline among possible surgical, endovascular, or medical therapies. Approximately 25% of patients with AD suffer postintervention malperfusion syndrome or hemodynamic instability, with the risk of sudden death if left untreated. Part of the issue is that vascular implants may themselves induce flow disturbances that critically impact vital organs. A multilayer mesh construct might obviate the induced flow disturbances, and it is this concept we investigated. We used preintervention and post-multilayer flow modulator implantation (PM) geometries from clinical cases of type B AD. In-house semiautomatic segmentation routines were applied to computed tomography images to reconstruct the lumen. The device was numerically reconstructed and adapted to the PM geometry concentrically fit to the true lumen centerline. We also numerically designed a pseudohealthy case, where the geometry of the aorta was extracted interpolating geometric features of preintervention, postimplantation, and published representative healthy volunteers. Computational fluid dynamics methods were used to study the time-dependent flow patterns, shear stress metrics, and perfusion to vital organs. A three-element Windkessel lumped parameter module was coupled to a finite-volume solver to assign dynamic outlet boundary conditions. Multilayer flow modulator not only significantly reduced false lumen blood flow, eliminated local flow disturbances, and globally regulated wall shear stress distribution but also maintained physiological perfusion to peripheral vital organs. We propose further investigation to focus the management of AD on both modulation of blood flow and restoration of physiologic end-organ perfusion rather than mere restoration of vascular lamina morphology
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