Volume XII: Special Volume: Computational Models for the Human Body
Guest Editor: N. Ayache, INRIA, 06902 Sophia-Antipolis, France
Description Computational Models for the Human Body is a recent and rapidly progressing area of research whose primary objective is to provide a better
understanding of the physiological and mechanical behavior of the human body and to design tools for their realistic numerical simulations.
This book describes concrete examples of such computational models. Although far from being exhaustive, the book covers a large range
of methods and an illustrative set of applications, and proposes a number of well defined mathematical and numerical modeling of physical
problems, (including formal analysis of existence and unicity of solutions for instance), followed by various numerical simulations.
Medical applications are addressed first, because physiological and biomechanical models of the human body already play a prominent
role in the prevention, diagnosis and therapy of many diseases. The generalized introduction of such models in medicine will in fact
strongly contribute to the development of a more individualized and preventive medicine. In effect, through the continuous progress of
medical imaging during the past decades, it is currently possible to extract an increasing flow of anatomical or functional information
on any individual, with an increasing resolution in space and time. The overwhelming quantity of available signals and images makes a
direct analysis of the data more and more difficult, when not impossible. New computational models are necessary to capture those parameters
pertinent to analyze the human system under study or to simulate it. There is also a number of important non medical applications of
these in silico human models, covering numerous human activities, like driving (safer design of vehicles), working (better ergonomy of
workplaces), exercising (more efficient training of athletes), entertaining (simulation for movies), etc.
There are basically three
levels of design for human models. The first level is mainly geometrical, and addresses the construction of a digital description of
the anatomy, often acquired from medical imagery. The second level is physical, involving mainly the biomechanical modeling of various
tissues, organs, vessels, muscles or bone structures. The third level is physiological, involving a modeling of the functions of the
major biological systems (e.g. cardiovascular, respiratory, digestive, hormonal, muscular, central or peripheral nervous system, etc.)
or some pathological metabolism (e.g. evolution of cancerous or inflammatory lesions, formation of vessel stenoses, etc.). A fourth
level (not described in this book) would be cognitive, modeling the higher functions of the human brain. These different levels of modeling
are closely related to each other, and several physiological systems may interact together (e.g. the cardiopulmonary interaction). The
choice of the resolution at which each level is described is important, and may vary from microscopic to macroscopic, ideally through
multiscale descriptions.
The first three chapters of the book study three important physiological models (vascular, cardiac, and
tumoral) from a mathematical and numerical perspective. The chapter by Quateroni and Formaggia addresses the problem of developing models
for the numerical simulation of the human circulatory system, focussing on the analysis of haemodynamics in arteries. Applications include
the prediction (and therefore the possible prevention) of stenoses (a local reduction of the lumen of the artery), a leading cause of
cardiovascular accidents. The chapter by Belik, Usyk and McCulloch describes computational methods for modeling and simulating the cardiac
electromechanical function. These methods provide tools to predict physiological function from quantitative measurements of tissue, cellular
or molecular structures. Applications include a better understanding of cardiac pathologies, and a quantitative modeling of their evolution
from various sources of measurements, including medical imagery. The chapter by Diaz and Tello studies the mathematical properties of
a simple model of tumor growth. Formal proofs are given for the existence and uniqueness of solutions and numerical simulations of the
model are presented.
The next two chapters are dedicated to the simulation of human body deformations in two different contexts.
The chapter by Haug, Choi, Robin and Beaugonin describes computational models for crash and impact simulation. It presents the latest
generation of virtual human models useful to study the consequences of car accidents on organs and important anatomical structures. These
models allow the interactive design of safer vehicles with an unrivaled flexibility. The chapter by Delingette and Ayache describes computational
models of soft tissue useful for surgery simulation. The real-time constraint imposed by the necessary realism of a training system leads
to specific models which are applied to the simulation of minimally invasive digestive surgery, including liver surgery.
The last
two chapters describe computational models dedicated to image-guided intervention and diagnosis. The chapter by Papademetris, Skinjar
and Duncan describes computational models of organs used to predict and track deformations of tissues from sparse information acquired
through medical imaging. This is a nice combination of biomechanical modeling with medical image analysis, with an application to image-guided
neurosurgery and an application to the image-based quantitative analysis of cardiac diseases. The chapter by Azar, Metaxas and Schnall
presents a computational model of the breast useful to predict deformations during interventions. The main applications are for image-guided
clinical biopsies and for image guided therapy.
The chapter by Azar, Metaxas and Schnall presents a computational model of the breast
useful to predict deformations during interventions. The main applications are for image-guided clinical biopsies and for image guided
therapy.
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