Is it time for a retinoic acid-eluting stent or retinoic acid-coated balloon? Insights from experimental studies of systemic and local delivery of retinoids.

Although the incidence of restenosis and stent thrombosis has substantially declined during the last decades, they still constitute the two major causes of stent failure. These complications are partially attributed to the currently used cytostatic drugs, which can cause local inflammation, delay or prevent re-endothelialization and essentially cause arterial cell toxicity. Retinoic acid (RA), a vitamin A (retinol) derivative, is a naturally occurring substance used for the treatment of cell proliferation disorders. The agent has pleiotropic effects on vascular smooth muscle cells and macrophages: it influences the proliferation, migration, and transition of smooth muscle cells to other cell types and modulates macrophage activation. These observations are supported by accumulated evidence from in vitro and in vivo experiments. In addition, systemic and topical administration of RA can decrease the development of atherosclerotic plaques and reduce or inhibit restenosis after vascular injury (caused by embolectomy, balloon catheters, or ligation of arteries) in various experimental models. Recently, an RA-drug eluting stent (DES) has been tested in an animal model. In this review, we explore the effects of RA in atherosclerosis and the potential of the local delivery of RA through an RA-DES or RA-coated balloon for targeted therapeutic percutaneous vascular interventions. Despite promising published results, further experimental study is warranted to examine the safety and efficacy of RA-eluting devices in vascular artery disease.

Cleverballoon: An integrated approach for developing a drug-coated balloon with everolimus.

Coronary artery disease (CAD) is a chronic disease associated with high mortality and morbidity. Although treatment with drug-eluting stents is the most frequent interventional approach for coronary artery disease, drug-coated balloons (DCBs) constitute an innovative alternative, especially in the presence of certain anatomical conditions in the local coronary vasculature. DCBs allow the fast and homogenous transfer of drugs into the arterial wall, during the balloon inflation. Their use has been established for treating in-stent restenosis caused by stent implantation, while recent clinical trials have shown a satisfactory efficacy in de novo small-vessel disease. Several factors affect DCBs performance including the catheter design, the drug dose and formulation. Cleverballoon focuses on the design and development of an innovative DCB with everolimus. For the realization of the development of this new DCB, an integrated approach, including in- vivo, in-vitro studies and in-silico modelling towards the DCB optimization, is presented.Clinical Relevance-The proposed study introduces the integration of in- vivo, in-vitro and in silico approaches in the design and development process of a new DCB, following the principles of 3R's for the replacement, reduction, and refinement of animal and clinical studies.

Risk Stratification for Cardiotoxicity in Breast Cancer Patients: Predicting Early Decline of LVEF After Treatment.

This study introduces AI-based models in prediction and risk assessment of early cardiac dysfunction in older breast cancer patients, as a side-effect of their cancer treatment. Using only features extracted during the baseline evaluation of each patient the proposed methodology could predict a decline in LVEF values in 4 different follow-up intervals during the first year after treatment initiation (i.e. months 3-12), with a mean accuracy of 66.67% and up to 73.55%. Selected baseline predictive factors were ranked according to their prevalence in the evaluation experiments, replicating the importance of various cardiac disorders at baseline, LVEF value and a higher age, which are all previously reported, while introducing Diabetes as an important risk factor.Clinical Relevance- Healthcare providers can better assess cardiovascular health status and risk of cardiotoxicity in the cancer treatment continuum. This will enable timely intervention and close monitoring on high risk patients while saving resources for low risk patients.

Classification of Inflammation of Unknown Origin patients based on RNA-seq and SomaScan data.

A preliminary analysis was conducted on data acquired from RNA sequencing and SomaScan platforms, for the classification of patients with Inflammation of Unknown Origin. To this end, a multimodal data integration approach was designed, by combining the two platforms, in order to assess the potentiality of learning estimators, using the differentially expressed features from the independent profiling experiments of both platforms. The classification framing was the differentiation of Inflammation of Unknown Origin patients against a multitude of Systemic Autoinflammatory disease patients. Separate false discovery rate analyses were performed on each dataset to extract statistically significant features between the two designated sample groups. Genomic analysis managed higher overall classification metrics compared to proteomic analysis, averaging an ~19% increase overall metrics and classifiers, with a ~0.07% increase in standard error. The multimodal data integration approach achieved similar results to the individual platforms' analyses. More specifically, it managed the same classification accuracy, sensitivity, and specificity scores as the best individual analysis, with the simple Logistic Regression estimator.Clinical Relevance- This study highlights the advantage of exploiting RNA sequencing data to identify potential Inflammation of Unknown Origin disease specific biomarkers, even against other Systemic Autoinflammatory diseases. These findings are further emphasized given the non-apparent clinical discrepancy between Inflammation of Unknown Origin and other Systemic Autoinflammatory diseases.

LETHE: A Digital Intervention for Cognitive Decline.

Dementia is the main cause of disability in elderly populations. It has been shown that the risk factors of dementia are a mixture of pathological, lifestyle and heritable factors, with some of those being provably modifiable. Early diagnosis of dementia and approaches to slow down its evolution are currently the most prominent management methodologies due to lack of a cure. For that reason, a plethora of home-based assistive technologies for dementia management do exist, with most of them focusing on the improvement of memory and thinking. The main objective of LETHE is prevention in the whole spectrum of cognitive decline in the elderly population at risk reaching from asymptomatic to subjective or mild cognitive impairment to prodromal Dementia. LETHE will provide a Big Data collection platform and analysis system, that will allow prevention, personalized risk detection and intervention on cognitive decline. Through the subsequent 2-year clinical trial, the LETHE system, as well as the respective knowledge gained will be evaluated and validated. The scope of the current paper is to introduce the LETHE study and its respective novel platform as a holistic approach to multidomain lifestyle intervention trial studies. The present work depicts the architectural perspective and extends beyond state-of-the-art guidelines and approaches to health management systems and cloud platform development.Clinical Relevance - Patient Management Systems as well as lifestyle management platforms have significant clinical relevance as they allow for remote and continuous monitoring of patients' health status. LETHE aims to improve patient outcomes by providing predictive models for cognitive decline and patient adherence to the multimodal lifestyle intervention, enabling prompt and appropriate medical decisions.

Safety and Efficacy of an Innovative Everolimus-Coated Balloon in a Swine Coronary Artery Model.

BACKGROUND: Drug-coated balloons have been used as a non-stenting treatment in coronary and peripheral artery disease. Until recently, only sirolimus- and paclitaxel-coated balloons have been investigated in clinical trials. We evaluated the safety and efficacy of an innovative everolimus-coated balloon (ECB) in a swine coronary artery model. METHODS: thirty-two swine coronary arteries were prepared through dilatation with a non-coated angioplasty balloon in a closed-chest model. During a period of 90 days, the following four groups (four animals per group, two coronary arteries per animal) were compared for safety and efficacy: A, Rontis ECB with 2.5 µg/mm2 of drug per balloon surface; B, Rontis ECB with 7.5 µg/mm2; C, Rontis Europa Ultra bare balloon; and D, Magic Touch, Concept Medical, sirolimus-coated balloon with a drug load of 1.3 µg/mm2. RESULTS: Differences in local biological effects (arterial reaction scores) and surface of intimal area (mm2) were not statistically significant between the treatment groups. Numerically, group A showed the lowest intimal area and intimal mean thickness, while group B showed the lowest stenosis among all groups. CONCLUSIONS: ECB was safe and effective in a porcine coronary artery model. The dose of everolimus may play a role in the biocompatibility of the balloon.

Public Perspectives on Lifestyle-Related Behavior Change for Dementia Risk Reduction: An Exploratory Qualitative Study in The Netherlands.

BACKGROUND: There is accumulating evidence that addressing modifiable risk and protective factors has an impact on dementia rates. Insight into the public's perspectives on dementia risk reduction is needed to inform future individual-level interventions and public health approaches. OBJECTIVE: This study explores the publics' openness towards dementia risk reduction and willingness towards changing lifestyle behavior to reduce the future risk for dementia. METHODS: Using a screening questionnaire, participants were purposively selected based on lifestyle behaviors that are associated with dementia risk. One-on-one interviews were used to explore their openness towards dementia risk reduction and willingness towards behavior change. Independently, two researchers performed an inductive content analysis. RESULTS: Interviews were conducted with 23 participants aged from 40 to 79 years. Main themes that were identified from the data were: 1) abstractness of dementia risk reduction, 2) ambivalence towards changing behavior, 3) negative self-image and low behavioral control, and 4) all-or-nothing thinking about lifestyle change. CONCLUSIONS: The concept of dementia risk reduction seems difficult to translate to the personal context, particularly if individuals perceive that dementia would occur decades in the future. This is problematic because a large proportion of the public needs a healthier lifestyle to reduce the incidence of dementia. Translating healthy intentions into behavior is complex and involves overcoming a variety of barriers that complicate dementia risk reduction initiatives. Support is needed for individuals who experience additional obstacles that obstruct commencing to a healthier lifestyle (e.g., negative self-image, engaging in multiple unhealthy behaviors, unrealistic perceptions about lifestyle change).

New Insights in the Era of Clinical Biomarkers as Potential Predictors of Systemic Therapy-Induced Cardiotoxicity in Women with Breast Cancer: A Systematic Review.

Cardiotoxicity induced by breast cancer therapies is a potentially serious complication associated with the use of various breast cancer therapies. Prediction and better management of cardiotoxicity in patients receiving chemotherapy is of critical importance. However, the management of cancer therapy-related cardiac dysfunction (CTRCD) lacks clinical evidence and is based on limited clinical studies. AIM: To provide an overview of existing and potentially novel biomarkers that possess a promising predictive value for the early and late onset of CTRCD in the clinical setting. METHODS: A systematic review of published studies searching for promising biomarkers for the prediction of CTRCD in patients with breast cancer was undertaken according to PRISMA guidelines. A search strategy was performed using PubMed, Google Scholar, and Scopus for the period 2013-2023. All subjects were >18 years old, diagnosed with breast cancer, and received breast cancer therapies. RESULTS: The most promising biomarkers that can be used for the development of an alternative risk cardiac stratification plan for the prediction and/or early detection of CTRCD in patients with breast cancer were identified. CONCLUSIONS: We highlighted the new insights associated with the use of currently available biomarkers as a standard of care for the management of CTRCD and identified potentially novel clinical biomarkers that could be further investigated as promising predictors of CTRCD.

An All-in-One Tool for 2D Atherosclerotic Disease Assessment and 3D Coronary Artery Reconstruction.

Diagnosis of coronary artery disease is mainly based on invasive imaging modalities such as X-ray angiography, intravascular ultrasound (IVUS) and optical coherence tomography (OCT). Computed tomography coronary angiography (CTCA) is also used as a non-invasive imaging alternative. In this work, we present a novel and unique tool for 3D coronary artery reconstruction and plaque characterization using the abovementioned imaging modalities or their combination. In particular, image processing and deep learning algorithms were employed and validated for the lumen and adventitia borders and plaque characterization at the IVUS and OCT frames. Strut detection is also achieved from the OCT images. Quantitative analysis of the X-ray angiography enables the 3D reconstruction of the lumen geometry and arterial centerline extraction. The fusion of the generated centerline with the results of the OCT or IVUS analysis enables hybrid coronary artery 3D reconstruction, including the plaques and the stent geometry. CTCA image processing using a 3D level set approach allows the reconstruction of the coronary arterial tree, the calcified and non-calcified plaques as well as the detection of the stent location. The modules of the tool were evaluated for efficiency with over 90% agreement of the 3D models with the manual annotations, while a usability assessment using external evaluators demonstrated high usability resulting in a mean System Usability Scale (SUS) score equal to 0.89, classifying the tool as "excellent".

Harmonization Strategies in Multicenter MRI-Based Radiomics.

Radiomics analysis is a powerful tool aiming to provide diagnostic and prognostic patient information directly from images that are decoded into handcrafted features, comprising descriptors of shape, size and textural patterns. Although radiomics is gaining momentum since it holds great promise for accelerating digital diagnostics, it is susceptible to bias and variation due to numerous inter-patient factors (e.g., patient age and gender) as well as inter-scanner ones (different protocol acquisition depending on the scanner center). A variety of image and feature based harmonization methods has been developed to compensate for these effects; however, to the best of our knowledge, none of these techniques has been established as the most effective in the analysis pipeline so far. To this end, this review provides an overview of the challenges in optimizing radiomics analysis, and a concise summary of the most relevant harmonization techniques, aiming to provide a thorough guide to the radiomics harmonization process.

A systematic review of miRNAs as biomarkers for chemotherapy-induced cardiotoxicity in breast cancer patients reveals potentially clinically informative panels as well as key challenges in miRNA research.

Breast cancer patients are at a particularly high risk of cardiotoxicity from chemotherapy having a detrimental effect on quality-of-life parameters and increasing the risk of mortality. Prognostic biomarkers would allow the management of therapies to mitigate the risks of cardiotoxicity in vulnerable patients and a key potential candidate for such biomarkers are microRNAs (miRNA). miRNAs are post-transcriptional regulators of gene expression which can also be released into the circulatory system and have been associated with the progression of many chronic diseases including many types of cancer. In this review, the evidence for the potential application of miRNAs as biomarkers for chemotherapy-induced cardiotoxicity (CIC) in breast cancer patientsis evaluated and a simple meta-analysis is performed to confirm the replication status of each reported miRNA. Further selection of miRNAs is performed by reviewing the reported associations of each miRNA with other cardiovascular conditions. Based on this research, the most representative panels targeting specific chemotherapy agents and treatment regimens are suggested, that contain several informative miRNAs, including both general markers of cardiac damage as well as those for the specific cancer treatments.

Investigation of crimping effects on the stent deployment through in silico modeling.

Atherosclerosis is one of the most mortal diseases that affects the arterial vessels, due to accumulation of plaque, altering the hemodynamic environment of the artery by preventing the sufficient delivery of blood to other organs. Stents are expandable tubular wires, used as a treatment option. In silico studies have been extensively exploited towards examining the performance of such devices by employing Finite Element Modeling. This study models the crimping stage during stent implantation to examine the effect of inclusion of pre-stress state of the stent. The results show that modeling of the crimping stress state of the stent prior to the deployment results in under-expansion of the stent, due to the indirect inclusion of strain-induced hardening effects. As a result, it is evident that the compressive stent stress configuration is important to be considered in the computational modeling approaches of stent deployment.

A proof-of-concept study for the simulation of blood flow in a post arterial segment for different blood rheology models.

Cardiovascular disease (CVD) and especially atherosclerosis are chronic inflammatory diseases which cause the atherosclerotic plaque growth in the arterial vessels and the blood flow reduction. Stents have revolutionized the treatment of this disease to a great extent by restoring the blood flow in the vessel. The present study investigates the performance of the blood flow after stent implantation in patient-specific coronary artery and demonstrates the effect of using Newtonian vs. non-Newtonian blood fluid models in the distribution of endothelial shear stress. In particular, the Navier-Stokes and continuity equations were employed, and three non-Newtonian fluid models were investigated (Carreau, Carreau-Yasuda and the Casson model). Computational finite elements models were used for the simulation of blood flow. The comparison of the results demonstrates that the Newtonian fluid model underestimates the calculation of Endothelial Shear Stress, while the three non-Newtonian fluids present similar distribution of shear stress. Keywords: Blood flow dynamics, stented artery, non-Newtonian fluid. Clinical Relevance- This work demonstrates that when blood flow modeling is performed at stented arteries and predictive models are developed, the non-Newtonian nature of blood must be considered.

An in silico trials platform for the evaluation of stent design effect in post-implantation outcomes.

Bioresorbable Vascular Scaffolds (BVS), developed to allow drug deliver and mechanical support, followed by complete resorption, have revolutionized atherosclerosis treatment. InSilc is a Cloud platform for in silico clinical trials (ISCT) used in the design, development and evaluation pipeline of stents. The platform integrates beyond the state-of-the-art multi-disciplinary and multiscale models, which predict the scaffold's performance in the short/acute and medium/long term. In this study, a use case scenario of two Bioabsorbable Vascular Stents (BVSs) implanted in the same arterial anatomy is presented, allowing the whole InSilc in silico pipeline to be applied and predict how the different aspects of this intervention affect the success of stenting process.

Histopathological evaluation of a retinoic acid eluting stent in a rabbit iliac artery model.

This study aimed to evaluate the safety and efficacy of innovative retinoic acid (RA) eluting stents with bioabsorbable polymer. Sixty stents divided in ten groups were implanted in the iliac arteries of 30 rabbits. Two polymers ("A", poly (lactic-co-glycolic acid) and "B", polylactic acid), and three doses ("Low", "Medium" and "High") of RA (groups: AL, AM, AH, BL, BM, BH) were used on cobalt chromium stents (Rontis Corporation), one group of bare stent (C), one group (D) of Everolimus eluting stent (Xience-Pro, Abbot Vascular), and two groups of Rontis Everolimus eluting stents coated with polymer A (EA) and B (EB). Treated arteries were explanted after 4 weeks, processed by methyl methacrylate resin and evaluated by histopathology. None of the implanted stents was related with thrombus formation or extensive inflammation. Image analysis showed limited differences between groups regarding area stenosis (BH, D and EB groups had the lower values). Group BH had lower intimal mean thickness than AH (105.1 vs 75.3 µm, p = 0.024). Stents eluting RA, a non-cytotoxic drug, were not related with thrombus formation and had an acceptable degree of stenosis 4 weeks post implantation. RA dose and type of polymer may play role in the biocompatibility of the stents.

Investigation of the drug release time from the biodegrading coating of an everolimus eluting stent.

This case-study examines the release time of the everolimus drug from an experimental biodegrading coating of a Rontis corp. drug eluting stent (DES). The controlled drug release is achieved by the degradation of the coating, which consists of a mixture of polylactic co-glycolic acid (PLGA) and everolimus (55:45). In our analysis, we used the outcome of another study, which contains the geometry of an in-silico deployed Rontis corp. stent in a 3D reconstructed coney arterial segment. Using this geometry as input, the everolimus release was simulated using a computational model that includes: i) modeling of the blood flow dynamics, ii) modeling of PLGA degradation, and iii) modeling of the everolimus advection and diffusion towards both the lumen and the arterial wall. The results show the rapid release of everolimus. This is justified due to the high porosity of the coating, which is caused by the initial high concentration of everolimus in the coating.Clinical Relevance - The methodology presented in this work is an additional step towards predicting accurately drug release from DES. Also, the results of our work prove that high drug concentration in the coating causes its rapid release, which could be used as input in the design of new DES.

Error Propagation in the Simulation of Atherosclerotic Plaque Growth and the Prediction of Atherosclerotic Disease Progression.

Assessments of coronary artery disease can be achieved using non-invasive computed tomography coronary angiography (CTCA). CTCA can be further used for the 3D reconstruction of the coronary arteries and the development of computational models. However, image acquisition and arterial reconstruction introduce an error which can be propagated, affecting the computational results and the accuracy of diagnostic and prognostic models. In this work, we investigate the effect of an imaging error, propagated to a diagnostic index calculated using computational modelling of blood flow and then to prognostic models based on plaque growth modelling or binary logistic predictive modelling. The analysis was performed utilizing data from 20 patients collected at two time points with interscan period of six years. The collected data includes clinical and risk factors, biological and biohumoral data, and CTCA imaging. The results demonstrated that the error propagated and may have significantly affected some of the final outcomes. The calculated propagated error seemed to be minor for shear stress, but was major for some variables of the plaque growth model. In parallel, in the current analysis SmartFFR was not considerably affected, with the limitation of only one case located into the gray zone.

An in silico trials platform for the evaluation of effect of the arterial anatomy configuration on stent implantation.

The introduction of Bioresorbable Vascular Scaffolds (BVS) has revolutionized the treatment of atherosclerosis. InSilc is an in silico clinical trial (ISCT) platform in a Cloud-based environment used for the design, development and evaluation of BVS. Advanced multi-disciplinary and multiscale models are integrated in the platform towards predicting the short/acute and medium/long term scaffold performance. In this study, InSilc platform is employed in a use case scenario and demonstrates how the whole in silico pipeline allows the interpretation of the effect of the arterial anatomy configuration on stent implantation.

A proof-of-concept study for the prediction of the de-novo atherosclerotic plaque development using finite elements.

The type of the atherosclerotic plaque has significant clinical meaning since plaque vulnerability depends on its type. In this work, we present a computational approach which predicts the development of new plaques in coronary arteries. More specifically, we employ a multi-level model which simulates the blood fluid dynamics, the lipoprotein transport and their accumulation in the arterial wall and the triggering of inflammation using convection-diffusion-reaction equations and in the final level, we estimate the plaque volume which causes the arterial wall thickening. The novelty of this work relies on the conceptual approach that using the information from 94 patients with computed tomography coronary angiography (CTCA) imaging at two time points we identify the correlation of the computational results with the real plaque components detected in CTCA. In the next step, we use these correlations to generate two types of de-novo plaques: calcified and non-calcified. Evaluation of the model's performance is achieved using eleven patients, who present de-novo plaques at the follow-up imaging. The results demonstrate that the computationally generated plaques are associated significantly with the real plaques indicating that the proposed approach could be used for the prediction of specific plaque type formation.

Investigation of Drug Eluting Stents performance in human atherosclerotic artery through in silico modeling.

Atherosclerosis is a chronic inflammatory disease associated with heart attack and stroke. It causes the growth of atherosclerotic plaques inside the arterial vessels, which in turn results to the reduction of the blood flow to the different organs. Drug-Eluting Stents (DES) are mesh-like wires, carrying pharmaceutical coating, designed to dilate and support the arterial vessel, restore blood flow and through the controlled local drug delivery inhibit neo-intimal thickening. In silico modeling is an efficient method of accurately predicting and assessing the performance of the stenting procedure. The present in silico study investigates the performance of two different stents (Bare Metal Stent, Drug-Eluting Stent) in a patient-specific coronary artery and assesses the effect of stent coating, considering that the same procedural approach is followed by the interventional cardiologist. The results demonstrate that even if small differences are obtained in the two models, the incorporation of the stent coatings (in DES) does not significantly affect the outcomes of the stent deployment, the stresses and strains in the scaffold and the arterial tissue. Nevertheless, it is suggested that regarding the DES expansion, higher pressure should be applied at the inner surface of the stent.