Closed-loop baroreflex model with biophysically detailed afferent pathway.

In this work, we couple a lumped-parameter closed-loop model of the cardiovascular system with a physiologically-detailed mathematical description of the baroreflex afferent pathway. The model features a classical Hodgkin-Huxley current-type model for the baroreflex afferent limb (primary neuron) and for the second-order neuron in the central nervous system. The pulsatile arterial wall distension triggers a frequency-modulated sequence of action potentials at the afferent neuron.

Nasal septum-derived chondroprogenitor cells control mandibular condylar resorption consequent to orthognathic surgery: a clinical trial.

Condylar resorption is an aggressive and disability form of temporomandibular joint (TMJ) degenerative disease, usually non-respondent to conservative or minimally invasive therapies and often leading to surgical intervention and prostheses implantation. This condition is also one of the most dreaded postoperative complications of orthognathic surgery, with severe cartilage erosion and loss of subchondral bone volume and mineral density, associated with a painful or not inflammatory processes. Because regenerative medicine has emerged as an alternative for orthopedic cases with advanced degenerative joint disease, we conducted a phase I/IIa clinical trial (U1111-1194-6997) to evaluate the safety and efficacy of autologous nasal septal chondroprogenitor cells.

Data-driven models for the prediction of coronary atherosclerotic plaque progression/regression.

Coronary artery disease is defined by the existence of atherosclerotic plaque on the arterial wall, which can cause blood flow impairment, or plaque rupture, and ultimately lead to myocardial ischemia. Intravascular ultrasound (IVUS) imaging can provide a detailed characterization of lumen and vessel features, and so plaque burden, in coronary vessels. Prediction of the regions in a vascular segment where plaque burden can either increase (progression) or decrease (regression) following a certain therapy, has remained an elusive major milestone in cardiology.

Comparison of endothelial shear stress between ultrathin strut bioresorbable polymer drug-eluting stent vs durable-polymer drug-eluting stent post-stent implantation: An optical coherence tomography substudy from BIOFLOW II.

Background: Recent clinical data indicate a different performance of biodegradable polymer (BP)-drug eluting stent (DES) compared to durable polymer (DP)-DES. Whether this can be explained by a beneficial impact of BP-DES stent design on the local hemodynamic forces distribution remains unclear.

Objectives: To compare endothelial shear stress (ESS) distribution after implantation of ultrathin (us) BP-DES and DP-DES and examine the association between ESS and neointimal thickness (NIT) distribution in the two devices at 9 months follow up.

An anatomically detailed arterial-venous network model. Cerebral and coronary circulation.

In recent years, several works have addressed the problem of modeling blood flow phenomena in veins, as a response to increasing interest in modeling pathological conditions occurring in the venous network and their connection with the rest of the circulatory system. In this context, one-dimensional models have proven to be extremely efficient in delivering predictions in agreement with observations. Pursuing the increase of anatomical accuracy and its connection to physiological principles in haemodynamics simulations, the main aim of this work is to describe a novel closed-loop Anatomically-Detailed Arterial-Venous Network (ADAVN) model.

Modeling essential hypertension with a closed-loop mathematical model for the entire human circulation.

Arterial hypertension, defined as an increase in systemic arterial pressure, is a major risk factor for the development of diseases affecting the cardiovascular system. Every year, 9.4 million deaths worldwide are caused by complications arising from hypertension.

Effect of High-Intensity Statin Therapy on Atherosclerosis (IBIS-4): Manual Versus Automated Methods of IVUS Analysis.

Aims: Standard manual analysis of IVUS to study the impact of anti-atherosclerotic therapies on the coronary vessel wall is done by a core laboratory (CL), the ground truth (GT). Automatic segmentation of IVUS with a machine learning (ML) algorithm has the potential to replace manual readings with an unbiased and reproducible method. The aim is to determine if results from a CL can be replicated with ML methods.

Quantitative coronary three-dimensional geometry and its association with atherosclerotic disease burden and composition.

Background: Isolate features of the coronary anatomy have been associated with the pathophysiology of atherosclerotic disease. Computational methods have been described to allow precise quantification of the complex three-dimensional (3D) coronary geometry. The present study tested whether quantitative parameters that describe the spatial 3D coronary geometry is associated with the extension and composition of the underlying coronary artery disease (CAD).

From fetus to neonate: A review of cardiovascular modeling in early life.

Computational modeling has well-established utility in the study of cardiovascular hemodynamics, with applications in medical research and, increasingly, in clinical settings to improve the diagnosis and treatment of cardiovascular diseases. Most cardiovascular models developed to date have been of the adult circulatory system; however, the perinatal period is unique as cardiovascular physiology undergoes drastic changes from the fetal circulation, during the birth transition, and into neonatal life. There may also be further complications in this period: for example, preterm birth (defined as birth before completed weeks of gestation) carries risks of short-term cardiovascular instability and is associated with increased lifetime cardiovascular risk.

Pleiotropic antifibrotic actions of aspirin-triggered resolvin D1 in the lungs.

Introduction: Pulmonary fibrosis is a destructive, progressive disease that dramatically reduces life quality of patients, ultimately leading to death. Therapeutic regimens for pulmonary fibrosis have shown limited benefits, hence justifying the efforts to evaluate the outcome of alternative treatments.

Methods: Using a mouse model of bleomycin (BLM)-induced lung fibrosis, in the current work we asked whether treatment with pro-resolution molecules, such as pro-resolving lipid mediators (SPMs) could ameliorate pulmonary fibrosis.

A modular and reusable model of epithelial transport in the proximal convoluted tubule.

We review a collection of published renal epithelial transport models, from which we build a consistent and reusable mathematical model able to reproduce many observations and predictions from the literature. The flexible modular model we present here can be adapted to specific configurations of epithelial transport, and in this work we focus on transport in the proximal convoluted tubule of the renal nephron. Our mathematical model of the epithelial proximal convoluted tubule describes the cellular and subcellular mechanisms of the transporters, intracellular buffering, solute fluxes, and other processes.

A computational study of aortic insufficiency in patients supported with continuous flow left ventricular assist devices: Is it time for a paradigm shift in management?

Background: aortic insufficiency (AI) following continuous flow left ventricular assist device (CF-LVAD) implantation is a common complication. Traditional early management utilizes speed augmentation to overcome the regurgitant flow in an attempt to augment net forward flow, but this strategy increases the aortic transvalvular gradient which predisposes the patient to progressive aortic valve pathology and may have deleterious effects on aortic shear stress and right ventricular (RV) function.

Materials And Methods: We employed a closed-loop lumped-parameter mathematical model of the cardiovascular system including the four cardiac chambers with corresponding valves, pulmonary and systemic circulations, and the LVAD.

Human vs. machine vs. core lab for the assessment of coronary atherosclerosis with lumen and vessel contour segmentation with intravascular ultrasound.

A machine learning (ML) algorithm for automatic segmentation of intravascular ultrasound was previously validated. It has the potential to improve efficiency, accuracy and precision of coronary vessel segmentation compared to manual segmentation by interventional cardiology experts. The aim of this study is to compare the performance of human readers to the machine and against the readings from a Core Laboratory.

Sheltered in Stromal Tissue Cells, Orchestrates Inflammatory Neovascularization via Activation of the Mast Cell Chymase Pathway.

Microangiopathy may worsen the clinical outcome of Chagas disease. Given the obstacles to investigating the dynamics of inflammation and angiogenesis in heart tissues parasitized by , here we used intravital microscopy (IVM) to investigate microcirculatory alterations in the hamster cheek pouch (HCP) infected by green fluorescent protein-expressing (GFP-). IVM performed 3 days post-infection (3 dpi) consistently showed increased baseline levels of plasma extravasation.

Scaling laws and the left main coronary artery bifurcation. A combination of geometric and simulation analyses.

The geometry of coronary arteries is believed to play the role as an atherosclerotic risk factor on its own. The full characterization of the normal coronary network has been reported in the literature. Reports on the integration of geometry and functional data for normal coronary vessels started to proliferate more recently.

Fully automated lumen and vessel contour segmentation in intravascular ultrasound datasets.

Segmentation of lumen and vessel contours in intravascular ultrasound (IVUS) pullbacks is an arduous and time-consuming task, which demands adequately trained human resources. In the present study, we propose a machine learning approach to automatically extract lumen and vessel boundaries from IVUS datasets. The proposed approach relies on the concatenation of a deep neural network to deliver a preliminary segmentation, followed by a Gaussian process (GP) regressor to construct the final lumen and vessel contours.

Simultaneous assessment of coronary stenosis relevance with automated computed tomography angiography and intravascular ultrasound analyses and fractional flow reserve.

Objectives: To assess the diagnostic performance of computed tomography angiography (CTA) and intravascular ultrasound (IVUS) derived minimum lumen areas (MLA) from the same lesions that correspond to an FFR ≤0.80.

Methods And Results: A total of 24 patients (33 arteries) were collected retrospectively according to the following inclusion criteria: presence of a CTA diagnostic followed by an IVUS and FFR percutaneous coronary procedures.

A simple coronary blood flow model to study the collateral flow index.

In this work, we present a novel modeling framework to investigate the effects of collateral circulation into the coronary blood flow physiology. A prototypical model of the coronary tree, integrated with the concept of Collateral Flow Index (CFI), is employed to gain insight about the role of model parameters associated with the collateral circuitry, which results in physically-realizable solutions for specific CFI data. Then, we discuss the mathematical feasibility of pressure-derived CFI, anatomical implications and practical considerations involving the estimation of model parameters in collateral connections.

Adaptive constrained constructive optimisation for complex vascularisation processes.

Mimicking angiogenetic processes in vascular territories acquires importance in the analysis of the multi-scale circulatory cascade and the coupling between blood flow and cell function. The present work extends, in several aspects, the Constrained Constructive Optimisation (CCO) algorithm to tackle complex automatic vascularisation tasks. The main extensions are based on the integration of adaptive optimisation criteria and multi-staged space-filling strategies which enhance the modelling capabilities of CCO for specific vascular architectures.

Coronary arterial geometry: A comprehensive comparison of two imaging modalities.

The characterization of vascular geometry is a fundamental step towards the correct interpretation of coronary artery disease. In this work, we report a comprehensive comparison of the geometry featured by coronary vessels as obtained from coronary computed tomography angiography (CCTA) and the combination of intravascular ultrasound (IVUS) with bi-plane angiography (AX) modalities. We analyzed 34 vessels from 28 patients with coronary disease, which were deferred to CCTA and IVUS procedures.

Automated lumen segmentation using multi-frame convolutional neural networks in intravascular ultrasound datasets.

Aims: Assessment of minimum lumen areas in intravascular ultrasound (IVUS) pullbacks is time-consuming and demands adequately trained personnel. In this work, we introduce a novel and fully automated pipeline to segment the lumen boundary in IVUS datasets.

Methods And Results: First, an automated gating is applied to select end-diastolic frames and bypass saw-tooth artefacts.