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 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

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

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 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

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

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 pre-process 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

Antithrombotic treatment during coronary angioplasty after failed thrombolysis: strategies and prognostic implications. Results of the RESPIRE registry

Abstract Background Thrombolysis is still used when primary angioplasty is delayed for a long time, but 25%–30% of patients require rescue angioplasty (RA). There are no established recommendations for antithrombotic management in RA. This registry analyzes regimens for antithrombotic management. Methods A retrospective, multicenter, observational registry of consecutive patients treated with RA at 8 hospitals. All variables were collected and follow-up took place at 6 months. Results The study included 417 patients. Antithrombotic therapy in RA was: no additional drugs 22.3%, unfractionated heparin (UFH) 36.6%, abciximab 15.5%, abciximab plus UFH 10.5%, bivalirudin 5.7%, enoxaparin 4.3%, and others 4.7%. Outcomes at 6 months were: mortality 9.1%, infarction 3.3%, definite or probable stent thrombosis 4.3%, revascularization 1.9%, and stroke 0.5%. Mortality was related to cardiogenic shock, age > 75 years, and anterior location. The stent thrombosis rate was highest with bivalirudin (12.5% at 6 months). The incidence of bleeding at admission was high (14.8%), but most cases were not severe (82% BARC ≤2). Variables independently associated with bleeding were: femoral access (OR 3.30; 95% CI 1.3–8.3: p = 0.004) and post-RA abciximab infusion (OR 2.26; 95% CI 1.02–5: p = 0.04). Conclusions Antithrombotic treatment regimens in RA vary greatly, predominant strategies consisting of no additional drugs or UFH 70 U/kg. No regimen proved predictive of mortality, but bivalirudin was related to more stent thrombosis. There was a high incidence of bleeding, associated with post-RA abciximab infusion and femoral access

Validation study to determine the accuracy of central blood pressure measurement using the SphygmoCor XCEL cuff device in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

Abstract Central aortic blood pressure could be helpful in the evaluation of patients with aortic stenosis (AS). The SphygmoCor XCEL device estimates central blood pressure (BP) measurement with its easy‐to‐use, operator‐independent procedure. However, this device has not been properly validated against invasive measurement in patients with severe AS. We evaluated the relationship between cuff‐brachial BP, transfer function‐estimated and invasively measured central aortic pressure in patients with severe AS before and after transcatheter aortic valve replacement (TAVR). Agreement between techniques was analyzed and, according to the ARTERY Society recommendations, the minimum acceptable error was a mean difference ± SD ≤5 ± ≤8 mm Hg. A total of 94 patients with AS undergoing TAVR had simultaneous non‐invasive and invasive measurements of central BP before and after the procedure. Before TAVR central systolic BP was in average slightly underestimated, though with wide variability, when using the default calibration of brachial‐cuff SBP (mean difference ± SD, −3 ± 15 mm Hg), and after TAVR the degree of underestimation increased (mean difference ± SD, −9 ± 13 mm Hg). The agreement tended to improve for those patients with low aortic gradient stenosis compared to those with high gradient at baseline (mean difference ± SD, −2 ± 11 mm Hg vs. −4 ± 17, respectively, p = .3). The cuff‐brachial systolic BP yielded numerically lower degree of agreement and weaker correlation with invasive measurements than SphygmoCor XCEL. In patients with severe AS the SphygmoCor XCEL cuff device, despite showing strong correlation, does not meet the ARTERY Society accuracy criteria for non‐invasive measurement of central SBP

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