Integrating molecular and clinical variables to predict myocardial recovery.

Mechanical unloading and circulatory support with left ventricular assist devices (LVADs) mediate significant myocardial improvement in a subset of advanced heart failure (HF) patients. The clinical and biological phenomena associated with cardiac recovery are under intensive investigation. Left ventricular (LV) apical tissue, alongside clinical data, were collected from HF patients at the time of LVAD implantation (n=208). RNA was isolated and mRNA transcripts were identified through RNA sequencing and confirmed with RT-qPCR. To our knowledge this is the first study to combine transcriptomic and clinical data to derive predictors of myocardial recovery. We used a bioinformatic approach to integrate 59 clinical variables and 22,373 mRNA transcripts at the time of LVAD implantation for the prediction of post-LVAD myocardial recovery defined as LV ejection fraction (LVEF) ≥40% and LV end-diastolic diameter (LVEDD) ≤5.9cm, as well as functional and structural LV improvement independently by using LVEF and LVEDD as continuous variables, respectively. To substantiate the predicted variables, we used a multi-model approach with logistic and linear regressions. Combining RNA and clinical data resulted in a gradient boosted model with 80 features achieving an AUC of 0.731±0.15 for predicting myocardial recovery. Variables associated with myocardial recovery from a clinical standpoint included HF duration, pre-LVAD LVEF, LVEDD, and HF pharmacologic therapy, and LRRN4CL (ligand binding and programmed cell death) from a biological standpoint. Our findings could have diagnostic, prognostic, and therapeutic implications for advanced HF patients, and inform the care of the broader HF population.

B cells mediate lung ischemia/reperfusion injury by recruiting classical monocytes via synergistic B cell receptor/TLR4 signaling.

Ischemia/reperfusion injury-mediated (IRI-mediated) primary graft dysfunction (PGD) adversely affects both short- and long-term outcomes after lung transplantation, a procedure that remains the only treatment option for patients suffering from end-stage respiratory failure. While B cells are known to regulate adaptive immune responses, their role in lung IRI is not well understood. Here, we demonstrated by intravital imaging that B cells are rapidly recruited to injured lungs, where they extravasate into the parenchyma. Using hilar clamping and transplant models, we observed that lung-infiltrating B cells produce the monocyte chemokine CCL7 in a TLR4-TRIF-dependent fashion, a critical step contributing to classical monocyte (CM) recruitment and subsequent neutrophil extravasation, resulting in worse lung function. We found that synergistic BCR-TLR4 activation on B cells is required for the recruitment of CMs to the injured lung. Finally, we corroborated our findings in reperfused human lungs, in which we observed a correlation between B cell infiltration and CM recruitment after transplantation. This study describes a role for B cells as critical orchestrators of lung IRI. As B cells can be depleted with currently available agents, our study provides a rationale for clinical trials investigating B cell-targeting therapies.

Defining cardiac functional recovery in end-stage heart failure at single-cell resolution.

Recovery of cardiac function is the holy grail of heart failure therapy yet is infrequently observed and remains poorly understood. In this study, we performed single-nucleus RNA sequencing from patients with heart failure who recovered left ventricular systolic function after left ventricular assist device implantation, patients who did not recover and non-diseased donors. We identified cell-specific transcriptional signatures of recovery, most prominently in macrophages and fibroblasts. Within these cell types, inflammatory signatures were negative predictors of recovery, and downregulation of RUNX1 was associated with recovery. In silico perturbation of RUNX1 in macrophages and fibroblasts recapitulated the transcriptional state of recovery. Cardiac recovery mediated by BET inhibition in mice led to decreased macrophage and fibroblast Runx1 expression and diminished chromatin accessibility within a Runx1 intronic peak and acquisition of human recovery signatures. These findings suggest that cardiac recovery is a unique biological state and identify RUNX1 as a possible therapeutic target to facilitate cardiac recovery.

SVEP1 is an endogenous ligand for the orphan receptor PEAR1.

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.

Targeting Immune-Fibroblast Crosstalk in Myocardial Infarction and Cardiac Fibrosis.

Inflammation and tissue fibrosis co-exist and are causally linked to organ dysfunction. However, the molecular mechanisms driving immune-fibroblast crosstalk in human cardiac disease remains unexplored and there are currently no therapeutics to target fibrosis. Here, we performed multi-omic single-cell gene expression, epitope mapping, and chromatin accessibility profiling in 38 donors, acutely infarcted, and chronically failing human hearts. We identified a disease-associated fibroblast trajectory marked by cell surface expression of fibroblast activator protein (FAP), which diverged into distinct myofibroblasts and pro-fibrotic fibroblast populations, the latter resembling matrifibrocytes. Pro-fibrotic fibroblasts were transcriptionally similar to cancer associated fibroblasts and expressed high levels of collagens and periostin (POSTN), thymocyte differentiation antigen 1 (THY-1), and endothelin receptor A (EDNRA) predicted to be driven by a RUNX1 gene regulatory network. We assessed the applicability of experimental systems to model tissue fibrosis and demonstrated that 3 different in vivo mouse models of cardiac injury were superior compared to cultured human heart and dermal fibroblasts in recapitulating the human disease phenotype. Ligand-receptor analysis and spatial transcriptomics predicted that interactions between C-C chemokine receptor type 2 (CCR2) macrophages and fibroblasts mediated by interleukin 1 beta (IL-1ß) signaling drove the emergence of pro-fibrotic fibroblasts within spatially defined niches. This concept was validated through in silico transcription factor perturbation and in vivo inhibition of IL-1ß signaling in fibroblasts where we observed reduced pro-fibrotic fibroblasts, preferential differentiation of fibroblasts towards myofibroblasts, and reduced cardiac fibrosis. Herein, we show a subset of macrophages signal to fibroblasts via IL-1ß and rewire their gene regulatory network and differentiation trajectory towards a pro-fibrotic fibroblast phenotype. These findings highlight the broader therapeutic potential of targeting inflammation to treat tissue fibrosis and restore organ function.

Peripheral blood mononuclear cell tissue factor (F3 gene) transcript levels and circulating extracellular vesicles are elevated in severe coronavirus 2019 (COVID-19) disease.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with excessive coagulation, thrombosis, and mortality. OBJECTIVE: To provide insight into mechanisms that contribute to excessive coagulation in coronavirus 2019 (COVID-19) disease. PATIENTS/METHODS: Blood from COVID-19 patients was investigated for coagulation-related gene expression and functional activities. RESULTS: Single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells from severe COVID-19 patients revealed a 5.2-fold increase in tissue factor (TF [F3 gene]) transcript expression levels (P < .05), the trigger of extrinsic coagulation; a 7.7-fold increase in C1-inhibitor (SERPING1 gene; P < .01) transcript expression levels, an inhibitor of intrinsic coagulation; and a 4.4-fold increase in anticoagulant thrombomodulin (TM [THBD gene]) transcript expression levels (P < .001). Bulk RNA-seq analysis of sorted CD14+ monocytes on an independent cohort of COVID-19 patients confirmed these findings (P < .05). Indicative of excessive coagulation, 41% of COVID-19 patients' plasma samples contained high D-dimer levels (P < .0001); of these, 19% demonstrated extracellular vesicle TF activity (P = .109). COVID-19 patients' ex vivo plasma-based thrombin generation correlated positively with D-dimer levels (P < .01). Plasma procoagulant extracellular vesicles were elevated ∼9-fold in COVID-19 patients (P < .01). Public scRNA-seq data sets from bronchoalveolar lung fluid and our peripheral blood mononuclear cell scRNA-seq data show CD14+ monocytes/macrophages TF transcript expression levels are elevated in severe but not mild or moderate COVID-19 patients. CONCLUSIONS: Beyond local lung injury, SARS-CoV-2 infection increases systemic TF (F3) transcript levels and elevates circulating extracellular vesicles that likely contribute to disease-associated coagulation, thrombosis, and related mortality.

Vascular smooth muscle- and myeloid cell-derived integrin α9ß1 does not directly mediate the development of atherosclerosis in mice.

BACKGROUND AND AIMS: Sushi, von Willebrand factor type A, EGF pentraxin domain-containing 1 (SVEP1), an extracellular matrix protein, is a human coronary artery disease locus that promotes atherosclerosis. We previously demonstrated that SVEP1 induces vascular smooth muscle cell (VSMC) proliferation and an inflammatory phenotype in the arterial wall to enhance the development of atherosclerotic plaque. The only receptor known to interact with SVEP1 is integrin α9ß1, a cell surface receptor that is expressed by VSMCs and myeloid lineage-derived monocytes and macrophages. Our previous in vitro studies suggested that integrin α9ß1 was necessary for SVEP1-induced VSMC proliferation and inflammation; however, the underlying mechanisms mediated by integrin α9ß1 in these cell types during the development of atherosclerosis remain poorly understood. METHODS AND RESULTS: Here, using cell-specific gene targeting, we investigated the effects of the integrin α9ß1 receptor on VSMCs and myeloid cells in mouse models of atherosclerosis. Interestingly, we found that depleting integrin α9ß1 in either VSMCs or myeloid cells did not affect the formation or complexity of atherosclerotic plaque in vessels after either 8 or 16 weeks of high fat diet feeding. CONCLUSIONS: Our results indicate that integrin α9ß1 in these two cell types does not mediate the in vivo effect of SVEP1 in the development of atherosclerosis. Instead, our results suggest either the presence of other potential receptor(s) or alternative integrin α9ß1-expressing cell types responsible for SVEP1 induced signaling in the development of atherosclerosis.

Donor Macrophages Modulate Rejection After Heart Transplantation.

BACKGROUND: Cellular rejection after heart transplantation imparts significant morbidity and mortality. Current immunosuppressive strategies are imperfect, target recipient T cells, and have adverse effects. The innate immune response plays an essential role in the recruitment and activation of T cells. Targeting the donor innate immune response would represent the earliest interventional opportunity within the immune response cascade. There is limited knowledge about donor immune cell types and functions in the setting of cardiac transplantation, and no current therapeutics exist for targeting these cell populations. METHODS: Using genetic lineage tracing, cell ablation, and conditional gene deletion, we examined donor mononuclear phagocyte diversity and macrophage function during acute cellular rejection of transplanted hearts in mice. We performed single-cell RNA sequencing on donor and recipient macrophages and monocytes at multiple time points after transplantation. On the basis of our imaging and single-cell RNA sequencing data, we evaluated the functional relevance of donor CCR2+ (C-C chemokine receptor 2) and CCR2- macrophages using selective cell ablation strategies in donor grafts before transplant. Last, we performed functional validation that donor macrophages signal through MYD88 (myeloid differentiation primary response protein 88) to facilitate cellular rejection. RESULTS: Donor macrophages persisted in the rejecting transplanted heart and coexisted with recipient monocyte-derived macrophages. Single-cell RNA sequencing identified donor CCR2+ and CCR2- macrophage populations and revealed remarkable diversity among recipient monocytes, macrophages, and dendritic cells. Temporal analysis demonstrated that donor CCR2+ and CCR2- macrophages were transcriptionally distinct, underwent significant morphologic changes, and displayed unique activation signatures after transplantation. Although selective depletion of donor CCR2- macrophages reduced allograft survival, depletion of donor CCR2+ macrophages prolonged allograft survival. Pathway analysis revealed that donor CCR2+ macrophages are activated through MYD88/nuclear factor kappa light chain enhancer of activated B cells signaling. Deletion of MYD88 in donor macrophages resulted in reduced antigen-presenting cell recruitment, reduced ability of antigen-presenting cells to present antigen to T cells, decreased emergence of allograft-reactive T cells, and extended allograft survival. CONCLUSIONS: Distinct populations of donor and recipient macrophages coexist within the transplanted heart. Donor CCR2+ macrophages are key mediators of allograft rejection, and deletion of MYD88 signaling in donor macrophages is sufficient to suppress rejection and extend allograft survival. This highlights the therapeutic potential of donor heart-based interventions.

Derivation of extra-embryonic and intra-embryonic macrophage lineages from human pluripotent stem cells.

Tissue-resident macrophages are increasingly recognized as important determinants of organ homeostasis, tissue repair, remodeling and regeneration. Although the ontogeny and function of tissue-resident macrophages has been identified as distinct from postnatal hematopoiesis, the inability to specify, in vitro, similar populations that recapitulate these developmental waves has limited our ability to study their function and potential for regenerative applications. We took advantage of the concept that tissue-resident macrophages and monocyte-derived macrophages originate from distinct extra-embryonic and definitive hematopoietic lineages to devise a system to generate pure cultures of macrophages that resemble tissue-resident or monocyte-derived subsets. We demonstrate that human pluripotent stem cell-derived extra-embryonic-like and intra-embryonic-like hematopoietic progenitors differentiate into morphologically, transcriptionally and functionally distinct macrophage populations. Single-cell RNA sequencing of developing and mature cultures uncovered distinct developmental trajectories and gene expression programs of macrophages derived from extra-embryonic-like and intra-embryonic-like hematopoietic progenitors. These findings establish a resource for the generation of human tissue resident-like macrophages to study their specification and function under defined conditions and to explore their potential use in tissue engineering and regenerative medicine applications.

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

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.

E-wave asymmetry elucidates diastolic ventricular stiffness-relaxation coupling: model-based prediction with in vivo validation.

Load, chamber stiffness, and relaxation are the three established determinants of global diastolic function (DF). Coupling of systolic stiffness and isovolumic relaxation has been hypothesized; however, diastolic stiffness-relaxation coupling (DSRC) remains unknown. The parametrized diastolic filling (PDF) formalism, a validated DF model incorporates DSRC. PDF model-predicted DSRC was validated by analysis of 159 Doppler E-waves from a published data set (22 healthy volunteers undergoing bicycle exercise). E-waves at varying (46-120 bpm) heart rates (HR) demonstrated variation in acceleration time (AT), deceleration time (DT), and E-wave peak velocity. AT, DT, and Epeak were converted into PDF parameters: stiffness ([Formula: see text]), relaxation ([Formula: see text]), and load (xo) using published numerical methods. Univariate linear regression showed that over a twofold increase in HR, AT, and DT decrease ([Formula: see text] = -0.44; P < 0.001 and r = -0.42; P < 0.001, respectively), while, DT/AT remains constant (r = -0.04; P = 0.67). Similarly, [Formula: see text] increases with HR (r = 0.55; P < 0.001), while [Formula: see text] has no significant correlation with HR (r = 0.08; P = 0.32). However, the dimensionless DSRC parameter ψ = c2/4k shows no significant correlation with HR (r = -0.03; P = 0.7). Furthermore, ψ is uniquely determined by DT/AT rather than AT or DT independently. Constancy of ψ in spite of a twofold increase in HR establishes that stiffness (k) and relaxation (c) are coupled and manifest via a HR-invariant parameter of E-wave asymmetry and should not be considered independent of each other. The manifestation of DSRC through E-wave asymmetry via ψ underscores the value of DT/AT as a physiological, mechanism-derived index of DF.NEW & NOTEWORTHY: Although diastolic stiffness and relaxation are considered independent chamber properties, the cardio-hemic inertial oscillation that generates E-waves obeys Newton's law. E-waves vary with heart rate requiring simultaneous change in stiffness and relaxation. By retrospective analysis of human heart-rate varying transmitral Doppler-data, we show that diastolic stiffness and relaxation are coupled and that the coupling manifests through E-wave asymmetry, quantified through a parametrized diastolic filling model-derived dimensionless parameter, which only depends on deceleration time and acceleration time, readily obtainable via standard echocardiography.

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

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.

CellTagging: combinatorial indexing to simultaneously map lineage and identity at single-cell resolution.

Single-cell technologies are offering unparalleled insight into complex biology, revealing the behavior of rare cell populations that are masked in bulk population analyses. One current limitation of single-cell approaches is that lineage relationships are typically lost as a result of cell processing. We recently established a method, CellTagging, permitting the parallel capture of lineage information and cell identity via a combinatorial cell indexing approach. CellTagging integrates with high-throughput single-cell RNA sequencing, where sequential rounds of cell labeling enable the construction of multi-level lineage trees. Here, we provide a detailed protocol to (i) generate complex plasmid and lentivirus CellTag libraries for labeling of cells; (ii) sequentially CellTag cells over the course of a biological process; (iii) profile single-cell transcriptomes via high-throughput droplet-based platforms; and (iv) generate a CellTag expression matrix, followed by clone calling and lineage reconstruction. This lentiviral-labeling approach can be deployed in any organism or in vitro culture system that is amenable to viral transduction to simultaneously profile lineage and identity at single-cell resolution.

Demonstration of a Longitudinal Medical Education Model (LMEM) Model to Teach Point-of-Care Ultrasound in Resource-Limited Settings.

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 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 in POCUS competency was observed across six different fundamental areas of ultrasound (p < 0.0001). According to our objective structured clinical examination (OSCE), the mean assessment score increased from 0.47 to 1.68 out of a maximum score of 2 points, 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.

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

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. NEW & NOTEWORTHY The majority of aortic dissection modeling efforts have focused on the maintenance of physiological flow using minimally invasive placed grafts. The multilayer flow modulator is a complex mesh construct of wires, designed to eliminate flow disruptions in the lumen, regulate the physiological wall stresses, and enhance endothelial function and offering the promise of improved perfusion of vital organs. This has never been fully proved or modeled, and these issues we confirmed using a dynamic framework of time-varying arterial waveforms.

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

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 R2 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.

Automated Segmentation of Bioresorbable Vascular Scaffold Struts in Intracoronary Optical Coherence Tomography Images.

Bioresorbable vascular scaffolds (BVS), the next step in the continuum of minimally invasive vascular interventions present new opportunities for patients and clinicians but challenges as well. As they are comprised of polymeric materials standard imaging is challenging. This is especially problematic as modalities like optical coherence tomography (OCT) become more prevalent in cardiology. OCT, a light-based intracoronary imaging technique, provides cross-sectional images of plaque and luminal morphology. Until recently segmentation of OCT images for BVS struts was performed manually by experts. However, this process is time consuming and not tractable for large amounts of patient data. Several automated methods exist to segment metallic stents, which do not apply to the newer BVS. Given this current limitation coupled with the emerging popularity of the BVS technology, it is crucial to develop an automated methodology to segment BVS struts in OCT images. The objective of this paper is to develop a novel BVS strut detection method in intracoronary OCT images. First, we preprocess the image to remove imaging artifacts. Then, we use a K-means clustering algorithm to automatically segment the image. Finally, we isolate the stent struts from the rest of the image. The accuracy of the proposed method was evaluated using expert estimations on 658 annotated images acquired from 7 patients at the time of coronary arterial interventions. Our proposed methodology has a positive predictive value of 0.93, a Pearson Correlation coefficient of 0.94, and a F1 score of 0.92. The proposed methodology allows for rapid, accurate, and fully automated segmentation of BVS struts in OCT images.