Computational methods in cardiovascular mechanics

TL;DR

Computational models in cardiovascular sciences enable noninvasive, patient-specific insights and therapeutic development, leveraging advances in imaging, measurement, and computational technologies, despite some limitations in model accuracy.

Contribution

This paper reviews the integration of computational methods in cardiovascular mechanics, highlighting their role in advancing diagnosis, understanding, and treatment planning.

Findings

Computational models provide noninvasive insights into cardiovascular physiopathology.

In silico approaches support personalized medicine and therapeutic design.

Limitations include the gap between real cases and virtual models affecting reliability.

Abstract

The introduction of computational models in cardiovascular sciences has been progressively bringing new and unique tools for the investigation of the physiopathology. Together with the dramatic improvement of imaging and measuring devices on one side, and of computational architectures on the other one, mathematical and numerical models have provided a new, clearly noninvasive, approach for understanding not only basic mechanisms but also patient-specific conditions, and for supporting the design and the development of new therapeutic options. The terminology in silico is, nowadays, commonly accepted for indicating this new source of knowledge added to traditional in vitro and in vivo investigations. The advantages of in silico methodologies are basically the low cost in terms of infrastructures and facilities, the reduced invasiveness and, in general, the intrinsic predictive capabilities based on the use of mathematical models. The disadvantages are generally identified in the distance between the real cases and their virtual counterpart required by the conceptual modeling that can be detrimental for the reliability of numerical simulations.