How can computational simulation help make patient-specific cardiovascular medicine more interactive, predictive and accessible?
At VPH 2026 in Milan, RBF Morph will contribute to the scientific programme with two presentations showcasing different applications of RBF-based technologies in cardiovascular modelling — one developed with ENGYS within the ROMed2VR project, and one developed in collaboration with Ansys.
Taking place from 1–4 September at Politecnico di Milano, VPH 2026 brings together researchers, clinicians and industry experts working to advance the use of computational modelling and digital twins in healthcare.
From CFD to real-time surgical planning
The first contribution, developed within the ROMed2VR Project with ENGYS, is “CFD Reduced-Order Models for Interactive Assessment of Cardiac Hemodynamics for Pediatric Surgery”.
The work explores how open-source CFD, RBF-based geometry morphing, Reduced-Order Models (ROMs) and Virtual Reality can be integrated to enable interactive, patient-specific assessment of cardiac hemodynamics.
The objective is particularly relevant to pediatric cardiac surgery: rather than relying exclusively on computationally expensive high-fidelity simulations, the methodology makes it possible to explore alternative anatomical and surgical configurations and assess their impact on blood flow in a much more interactive environment.
RBF-based geometry morphing is a key element of this workflow, enabling controlled modifications of patient-specific geometries without the need to rebuild the computational model from scratch. Combined with ROM technology and VR, this creates a pathway towards real-time simulation-based exploration of surgical scenarios.
Controlling cardiovascular shape models with RBFs
The second contribution, “An RBF-based framework for geometric control of cardiovascular statistical shape models,” by A. Baldini, L. Geronzi and M.E. Biancolini, focuses on a different but complementary challenge: how to efficiently control and manipulate the geometry represented by statistical shape models (SSMs) of cardiovascular anatomy.
Statistical shape models provide a powerful way to describe anatomical variability by representing complex geometries through a statistical space of possible shapes. The challenge is turning that representation into a geometry that can be controlled, modified and used effectively in computational workflows.
The proposed RBF-based framework addresses this challenge by bringing Radial Basis Function methods and geometric control into the SSM workflow. This provides a flexible connection between statistical representations of cardiovascular anatomy and computational models that can be used for simulation, analysis and ultimately digital-twin applications.
The research builds on the broader cardiovascular modelling work developed by the RBF Morph and University of Rome Tor Vergata ecosystem, where RBF methods, reduced-order modelling and numerical simulation are being applied to patient-specific cardiovascular problems.
Two approaches, one direction
Although the two contributions address different aspects of the problem, they share a common objective: making patient-specific computational models more flexible, controllable and usable. From statistical representations of anatomical variability to interactive simulation of alternative surgical configurations, RBF-based methods can provide an important bridge between complex physiological data, high-fidelity simulation and the emerging generation of cardiovascular digital twins.
This is precisely the direction in which RBF Morph has been developing its research and technology: bringing geometry morphing, reduced-order modelling and advanced simulation closer to real-world clinical applications.
Learn more about VPH 2026 and the conference programme here.