Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions.

Artificial intelligence, computational simulations, and extended reality, among other 21st century computational technologies, are changing the health care system. To collectively highlight the most recent advances and benefits of artificial intelligence, computational simulations, and extended reality in cardiovascular therapies, we coined the abbreviation AISER. The review particularly focuses on the following applications of AISER: 1) preprocedural planning and clinical decision making; 2) virtual clinical trials, and cardiovascular device research, development, and regulatory approval; and 3) education and training of interventional health care professionals and medical technology innovators. We also discuss the obstacles and constraints associated with the application of AISER technologies, as well as the proposed solutions. Interventional health care professionals, computer scientists, biomedical engineers, experts in bioinformatics and visualization, the device industry, ethics committees, and regulatory agencies are expected to streamline the use of AISER technologies in cardiovascular interventions and medicine in general.

First-in-Human Computational Preprocedural Planning of Left Main Interventions Using a New Everolimus-Eluting Stent.

Left main coronary artery stenting requires rigorous planning and optimal execution. This case series presents a new approach to left main stenting guided by preprocedural patient-specific computational simulations. Three patients with significant left main artery disease underwent simulation-guided intervention using a novel stent scaffold purpose-built for large coronary arteries. (Level of Difficulty: Advanced.).

Triggering receptor expressed on myeloid cells-1 (TREM-1) inhibition in atherosclerosis.

Triggering receptor expressed on myeloid cells-1 (TREM-1) is a transmembrane protein expressed on endothelial cells, white blood cells, smooth muscle cells and platelets. TREM-1 plays an important role in innate immunity. TREM-1 activation pathways are implicated both in sepsis and in non-infectious inflammatory conditions, including atherosclerosis. TREM-1 enhances the subendothelial lipid accumulation and expression of pro-inflammatory cytokines and matrix-degrading enzymes, thereby promoting inflammation and plaque destabilization. TREM-1 inhibitors attenuate the inflammatory process in the atherosclerotic plaque, leading to plaque stabilization. This review focuses on the role of TREM-1 in the pathophysiology of atherosclerosis and the effects of TREM-1 inhibition in the natural history of the disease.

Management of venous thromboembolism in pregnancy.

Venous thromboembolism (VTE) in pregnancy, consisting of deep venous thrombosis (DVT) and pulmonary embolism (PE), is a major factor of maternal mortality. Several patient-specific risk factors along with the physiologic changes of pregnancy promote a state of hypercoagulability in pregnant women. Detailed assessment of all pregnant women can establish a risk profile that would guide clinical decisions, and balance potential therapeutic benefits with side effects. Differentiating between physiologic changes of pregnancy and symptoms of VTE can be challenging and warrants meticulous clinical evaluation. Timely and accurate diagnosis of VTE with proper imaging is essential for its management, and systemic anticoagulation remains the cornerstone of VTE prevention and therapy. Furthermore, advanced invasive treatment options such as inferior vena cava filters and thrombectomy can be considered for complex cases. Importantly, the risk of systemic anticoagulation should be balanced against the risk of VTE-associated morbidity and mortality for mother and fetus, and an informed decision should be made. In this review, we present an up-to-date overview of VTE management in pregnancy and the postpartum period.

Patient-specific computational simulation of coronary artery bifurcation stenting.

Patient-specific and lesion-specific computational simulation of bifurcation stenting is an attractive approach to achieve individualized pre-procedural planning that could improve outcomes. The objectives of this work were to describe and validate a novel platform for fully computational patient-specific coronary bifurcation stenting. Our computational stent simulation platform was trained using n = 4 patient-specific bench bifurcation models (n = 17 simulations), and n = 5 clinical bifurcation cases (training group, n = 23 simulations). The platform was blindly tested in n = 5 clinical bifurcation cases (testing group, n = 29 simulations). A variety of stent platforms and stent techniques with 1- or 2-stents was used. Post-stenting imaging with micro-computed tomography (µCT) for bench group and optical coherence tomography (OCT) for clinical groups were used as reference for the training and testing of computational coronary bifurcation stenting. There was a very high agreement for mean lumen diameter (MLD) between stent simulations and post-stenting µCT in bench cases yielding an overall bias of 0.03 (- 0.28 to 0.34) mm. Similarly, there was a high agreement for MLD between stent simulation and OCT in clinical training group [bias 0.08 (- 0.24 to 0.41) mm], and clinical testing group [bias 0.08 (- 0.29 to 0.46) mm]. Quantitatively and qualitatively stent size and shape in computational stenting was in high agreement with clinical cases, yielding an overall bias of < 0.15 mm. Patient-specific computational stenting of coronary bifurcations is a feasible and accurate approach. Future clinical studies are warranted to investigate the ability of computational stenting simulations to guide decision-making in the cardiac catheterization laboratory and improve clinical outcomes.

Three dimensional reconstruction of coronary artery stents from optical coherence tomography: experimental validation and clinical feasibility.

The structural morphology of coronary stents (e.g. stent expansion, lumen scaffolding, strut apposition, tissue protrusion, side branch jailing, strut fracture), and the local hemodynamic environment after stent deployment are key determinants of procedural success and subsequent clinical outcomes. High-resolution intracoronary imaging has the potential to enable the geometrically accurate three-dimensional (3D) reconstruction of coronary stents. The aim of this work was to present a novel algorithm for 3D stent reconstruction of coronary artery stents based on optical coherence tomography (OCT) and angiography, and test experimentally its accuracy, reproducibility, clinical feasibility, and ability to perform computational fluid dynamics (CFD) studies. Our method has the following steps: 3D lumen reconstruction based on OCT and angiography, stent strut segmentation in OCT images, packaging, rotation and straightening of the segmented struts, planar unrolling of the segmented struts, planar stent wireframe reconstruction, rolling back of the planar stent wireframe to the 3D reconstructed lumen, and final stent volume reconstruction. We tested the accuracy and reproducibility of our method in stented patient-specific silicone models using micro-computed tomography (µCT) and stereoscopy as references. The clinical feasibility and CFD studies were performed in clinically stented coronary bifurcations. The experimental and clinical studies showed that our algorithm (1) can reproduce the complex spatial stent configuration with high precision and reproducibility, (2) is feasible in 3D reconstructing stents deployed in bifurcations, and (3) enables CFD studies to assess the local hemodynamic environment within the stent. Notably, the high accuracy of our algorithm was consistent across different stent designs and diameters. Our method coupled with patient-specific CFD studies can lay the ground for optimization of stenting procedures, patient-specific computational stenting simulations, and research and development of new stent scaffolds and stenting techniques.

Computational and experimental mechanical performance of a new everolimus-eluting stent purpose-built for left main interventions.

Left main (LM) coronary artery bifurcation stenting is a challenging topic due to the distinct anatomy and wall structure of LM. In this work, we investigated computationally and experimentally the mechanical performance of a novel everolimus-eluting stent (SYNERGY MEGATRON) purpose-built for interventions to large proximal coronary segments, including LM. MEGATRON stent has been purposefully designed to sustain its structural integrity at higher expansion diameters and to provide optimal lumen coverage. Four patient-specific LM geometries were 3D reconstructed and stented computationally with finite element analysis in a well-validated computational stent simulation platform under different homogeneous and heterogeneous plaque conditions. Four different everolimus-eluting stent designs (9-peak prototype MEGATRON, 10-peak prototype MEGATRON, 12-peak MEGATRON, and SYNERGY) were deployed computationally in all bifurcation geometries at three different diameters (i.e., 3.5, 4.5, and 5.0 mm). The stent designs were also expanded experimentally from 3.5 to 5.0 mm (blind analysis). Stent morphometric and biomechanical indices were calculated in the computational and experimental studies. In the computational studies the 12-peak MEGATRON exhibited significantly greater expansion, better scaffolding, smaller vessel prolapse, and greater radial strength (expressed as normalized hoop force) than the 9-peak MEGATRON, 10-peak MEGATRON, or SYNERGY (p < 0.05). Larger stent expansion diameters had significantly better radial strength and worse scaffolding than smaller stent diameters (p < 0.001). Computational stenting showed comparable scaffolding and radial strength with experimental stenting. 12-peak MEGATRON exhibited better mechanical performance than the 9-peak MEGATRON, 10-peak MEGATRON, or SYNERGY. Patient-specific computational LM stenting simulations can accurately reproduce experimental stent testing, providing an attractive framework for cost- and time-effective stent research and development.

Mortality and Severity in COVID-19 Patients on ACEIs and ARBs-A Systematic Review, Meta-Analysis, and Meta-Regression Analysis.

Purpose: The primary objective of this systematic review is to assess association of mortality in COVID-19 patients on Angiotensin-converting-enzyme inhibitors (ACEIs) and Angiotensin-II receptor blockers (ARBs). A secondary objective is to assess associations with higher severity of the disease in COVID-19 patients. Materials and Methods: We searched multiple COVID-19 databases (WHO, CDC, LIT-COVID) for longitudinal studies globally reporting mortality and severity published before January 18th, 2021. Meta-analyses were performed using 53 studies for mortality outcome and 43 for the severity outcome. Mantel-Haenszel odds ratios were generated to describe overall effect size using random effect models. To account for between study results variations, multivariate meta-regression was performed with preselected covariates using maximum likelihood method for both the mortality and severity models. Result: Our findings showed that the use of ACEIs/ARBs did not significantly influence either mortality (OR = 1.16 95% CI 0.94-1.44, p = 0.15, I 2 = 93.2%) or severity (OR = 1.18, 95% CI 0.94-1.48, p = 0.15, I 2 = 91.1%) in comparison to not being on ACEIs/ARBs in COVID-19 positive patients. Multivariate meta-regression for the mortality model demonstrated that 36% of between study variations could be explained by differences in age, gender, and proportion of heart diseases in the study samples. Multivariate meta-regression for the severity model demonstrated that 8% of between study variations could be explained by differences in age, proportion of diabetes, heart disease and study country in the study samples. Conclusion: We found no association of mortality or severity in COVID-19 patients taking ACEIs/ARBs.

Mortality Benefit of Remdesivir in COVID-19: A Systematic Review and Meta-Analysis.

Importance/Background: During current public health emergency of COVID-19 pandemic, repurposing of existing antiviral drugs may be an efficient strategy since there is no proven effective treatment. Published literature shows Remdesivir has broad-spectrum antiviral activity against numerous RNA viruses and has been recently recognized as a promising therapy against SARS-CoV-2. Methods: A systematic search was conducted for full length manuscripts published between inception and July 19th, 2020 focussing on efficacy and safety of Remdesivir in COVID-19. The primary outcomes were defined as mortality rate and median days to recovery based on the available pooled data. The secondary outcome was adverse events rate and drug discontinuation rate. Statistical Analysis: All outcomes were performed using Comprehensive Meta-Analysis software package (Bio stat, Englewood, NJ, USA). Results: A total of 1,895 patients from 9 studies were included in this qualitative synthesis. In patients treated with Remdesivir, the mean recovery time was 15.84 days (95% CI 11.68-20, SE 2.12; I 2 = 97.24) and the pooled mortality rate was 11.3% (95% CI 7.9-16%; I 2 = 74.85). However, treatment with Remdesivir was associated with adverse effects (55.3%, 95% CI 31.5-76.9%; I 2 = 97.66) eventually warranting the discontinuation of the drug (17.8%, 95% CI 8.6-33.1%; I 2 = 95.64). The meta-analysis of three clinical trials indicated that administration of Remdesivir significantly reduces the mortality compared to the placebo (OR 0.70, 95% CI 0.58-0.84, p ≤ 0.001; I 2 = 16.6). Conclusions and Relevance: The result of contemporary meta-analysis suggests mortality benefit with Remdesivir in COVID-19 and median recovery time was over 2 weeks. The pooled mortality with Remdesivir was found to be very low, and this analysis can shed light on this potential treatment for COVID-19 patients.