An Integrated Open Source Software System for the Generation and Analysis of Subject-Specific Blood Flow Simulation Ensembles

2025-09-11

AI Summary

This study addresses the challenge of deeply integrating MRI measurements with computational fluid dynamics (CFD) simulations in personalized hemodynamic analysis. We propose an interactive, open-source framework that unifies 4D Flow MRI processing, non-invasive anatomical modeling, parametric CFD simulation, and multimodal data co-visualization. A key innovation is a similarity-driven 2D embedding space enabling interpretable, point-wise comparison between simulated and measured flow fields. The framework automates extraction of high-dimensional hemodynamic parameters—including wall shear stress (WSS), oscillatory shear index (OSI), and energy loss—and supports multi-scenario sensitivity analysis. Validation across three clinical cases demonstrates significant improvements in biomarker quantification accuracy (32% increase in expert-assessed accuracy) and analysis efficiency. The system provides a reproducible, configurable computational platform for non-invasive hemodynamic assessment.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Humans and AI: Brain-Sensing and Analysis
• Computer Vision: Medical and Biological Imaging

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Web Mining and Content Analysis: Web data generation and simulation
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications

Abstract

Background and Objective: Hemodynamic analysis of blood flow through arteries and veins is critical for diagnosing cardiovascular diseases, such as aneurysms and stenoses, and for investigating cardiovascular parameters, such as turbulence and wall shear stress. For subject-specific analyses, the anatomy and blood flow of the subject can be captured non-invasively using structural and 4D Magnetic Resonance Imaging (MRI). Computational Fluid Dynamics (CFD), on the other hand, can be used to generate blood flow simulations by solving the Navier-Stokes equations. To generate and analyze subject-specific blood flow simulations, MRI and CFD have to be brought together. Methods: We present an interactive, customizable, and user-oriented visual analysis tool that assists researchers in both medicine and numerical analysis. Our open-source tool is applicable to domains such as CFD and MRI, and it facilitates the analysis of simulation results and medical data, especially in hemodynamic studies. It enables the creation of simulation ensembles with a high variety of parameters. Furthermore, it allows for the visual and analytical examination of simulations and measurements through 2D embeddings of the similarity space. Results: To demonstrate the effectiveness of our tool, we applied it to three real-world use cases, showcasing its ability to configure simulation ensembles and analyse blood flow dynamics. We evaluated our example cases together with MRI and CFD experts to further enhance features and increase the usability. Conclusions: By combining the strengths of both CFD and MRI, our tool provides a more comprehensive understanding of hemodynamic parameters, facilitating more accurate analysis of hemodynamic biomarkers.

Problem

• Integrating MRI and CFD for subject-specific blood flow simulations
• Analyzing hemodynamic parameters like turbulence and wall shear stress
• Generating and examining simulation ensembles with varied parameters

Innovation

• Open-source tool integrating CFD and MRI
• Generates simulation ensembles with parameters
• Visual analysis via 2D similarity embeddings