ReviewBiophysics reviews2023
Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease.
Review in Biophysics reviews, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 63 citations in OpenAlex.
- From barrier to guide: Exploiting disease-specific hemodynamics for enhanced nanodrug targeting in cardiovascular diseases.Pharmaceutical science advances · 2026Review
- HeartSimSage: Attention-Enhanced Graph Neural Networks for Accelerating Cardiac Mechanics Modeling.Journal of computational physics · 2026Article
- Influence of wall distensibility on local hemodynamics at the normal carotid bifurcation: a fluid-structure interaction study.Biomechanics and modeling in mechanobiology · 2026Article
- Postnatal pulmonary artery development from transcript to tissue.Journal of the Royal Society, Interface · 2026Article
- A patient-specific CTA-CFD framework deciphers hemodynamic heterogeneity after fenestrated TEVAR: a pilot study.Frontiers in bioengineering and biotechnology · 2026Article
- Coupling CFD and Machine Learning to Assess Flow Properties in Porous Scaffolds for Tissue Engineering.Micromachines · 2025Article
- Article
- Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care.Biomedicines · 2025Review
- Hybrid physics-based and data-driven modeling of vascular bifurcation pressure differences.Computers in biology and medicine · 2025Article
- FSGe: A fast and strongly-coupled 3D fluid-solid-growth interaction method.Computer methods in applied mechanics and engineering · 2024Article
- Rapid estimation of left ventricular contractility with a physics-informed neural network inverse modeling approach.Artificial intelligence in medicine · 2024Article
- Non-invasive fractional flow reserve estimation in coronary arteries using angiographic images.Scientific reports · 2024Article
- Article
- Virtual Shape-Editing of Patient-Specific Vascular Models Using Regularized Kelvinlets.IEEE transactions on bio-medical engineering · 2024Article
- Hemodynamics and Wall Mechanics of Vascular Graft Failure.Arteriosclerosis, thrombosis, and vascular biology · 2024Review
- Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations.NPJ digital medicine · 2024Article
- Assessment of aortic hemodynamics in patients with thoracoabdominal aortic aneurysm using four-dimensional magnetic resonance imaging: a cross-sectional study.Quantitative imaging in medicine and surgery · 2024Article
- A Modular Framework for Implicit 3D-0D Coupling in Cardiac Mechanics.Computer methods in applied mechanics and engineering · 2024Article
- Learning reduced-order models for cardiovascular simulations with graph neural networks.Computers in biology and medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Physics-based computational models of the cardiovascular system are increasingly used to simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and diseased states. While predictive models using computational fluid dynamics (CFD) originated primarily for use in surgical planning, their application now extends well beyond this purpose. In this review, we describe an increasingly wide range of modeling applications aimed at uncovering fundamental mechanisms of disease progression and development, performing model-guided design, and generating testable hypotheses to drive targeted experiments. Increasingly, models are incorporating multiple physical processes spanning a wide range of time and length scales in the heart and vasculature. With these expanded capabilities, clinical adoption of patient-specific modeling in congenital and acquired cardiovascular disease is also increasing, impacting clinical care and treatment decisions in complex congenital heart disease, coronary artery disease, vascular surgery, pulmonary artery disease, and medical device design. In support of these efforts, we discuss recent advances in modeling methodology, which are most impactful when driven by clinical needs. We describe pivotal recent developments in image processing, fluid-structure interaction, modeling under uncertainty, and reduced order modeling to enable simulations in clinically relevant timeframes. In all these areas, we argue that traditional CFD alone is insufficient to tackle increasingly complex clinical and biological problems across scales and systems. Rather, CFD should be coupled with appropriate multiscale biological, physical, and physiological models needed to produce comprehensive, impactful models of mechanobiological systems and complex clinical scenarios. With this perspective, we finally outline open problems and future challenges in the field.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.