Myocardial perfusion scintigraphy - interpretation of gated imaging. Part 2.

The first part of the review describes the basic aspects of interpreting myocardial perfusion defects in single photon emission computed tomography (SPECT) scintigraphy. It also presents indications for invasive diagnostics based on stress perfusion defects. This article provides basic information concerning the interpretation of gated SPECT imaging, including such parameters as left ventricular wall motion and thickening as well as left ventricular wall systolic and diastolic function. Gated examination combined with the assessment of myocardial perfusion reduces the rate of false positives results of myocardial perfusion scintigraphy in perfusion tests, additionally providing data on left ventricular systolic and diastolic function.

Interpreting myocardial perfusion scintigraphy using single-photon emission computed tomography. Part 1.

This article discusses the protocol for myocardial perfusion scintigraphy performed with single-photon emission computed tomography (SPECT). Indications for SPECT are listed with consideration given to the results of the increasingly more common angio-CT examinations of the coronary arteries (multislice computed tomography). The paper also presents basic information about interpreting the results, including the scores of left ventricle myocardial perfusion using the 17-segment polar map, and explains the concept of total perfusion deficit.

Development of a new generation of high-resolution anatomical models for medical device evaluation: the Virtual Population 3.0.

The Virtual Family computational whole-body anatomical human models were originally developed for electromagnetic (EM) exposure evaluations, in particular to study how absorption of radiofrequency radiation from external sources depends on anatomy. However, the models immediately garnered much broader interest and are now applied by over 300 research groups, many from medical applications research fields. In a first step, the Virtual Family was expanded to the Virtual Population to provide considerably broader population coverage with the inclusion of models of both sexes ranging in age from 5 to 84 years old. Although these models have proven to be invaluable for EM dosimetry, it became evident that significantly enhanced models are needed for reliable effectiveness and safety evaluations of diagnostic and therapeutic applications, including medical implants safety. This paper describes the research and development performed to obtain anatomical models that meet the requirements necessary for medical implant safety assessment applications. These include implementation of quality control procedures, re-segmentation at higher resolution, more-consistent tissue assignments, enhanced surface processing and numerous anatomical refinements. Several tools were developed to enhance the functionality of the models, including discretization tools, posing tools to expand the posture space covered, and multiple morphing tools, e.g., to develop pathological models or variations of existing ones. A comprehensive tissue properties database was compiled to complement the library of models. The results are a set of anatomically independent, accurate, and detailed models with smooth, yet feature-rich and topologically conforming surfaces. The models are therefore suited for the creation of unstructured meshes, and the possible applications of the models are extended to a wider range of solvers and physics. The impact of these improvements is shown for the MRI exposure of an adult woman with an orthopedic spinal implant. Future developments include the functionalization of the models for specific physical and physiological modeling tasks.

A novel medical image data-based multi-physics simulation platform for computational life sciences.

Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.

Patient-specific simulations and measurements of the magneto-hemodynamic effect in human primary vessels.

This paper investigates the main characteristics of the magneto-hemodynamic (MHD) response for application as a biomarker of vascular blood flow. The induced surface potential changes of a volunteer exposed to a 3 T static B0 field of a magnetic resonance imaging (MRI) magnet were measured over time at multiple locations by an electrocardiogram device and compared to simulation results. The flow simulations were based on boundary conditions derived from MRI flow measurements restricted to the aorta and vena cava. A dedicated and validated low-frequency electromagnetic solver was applied to determine the induced temporal surface potential change from the obtained 4D flow distribution using a detailed whole-body model of the volunteer. The simulated MHD signal agreed with major characteristics of the measured signal (temporal location of main peak, magnitude, variation across chest and along torso) except in the vicinity of the heart. The MHD signal is mostly influenced by the aorta; however, more vessels and better boundary conditions are needed to analyze the finer details of the response. The results show that the MHD signal is strongly position dependent with highly variable but reproducibly measurable distinguished characteristics. Additional investigations are necessary before determining whether the MHD effect is a reliable reference for location-specific information on blood flow.

The Virtual Family--development of surface-based anatomical models of two adults and two children for dosimetric simulations.

The objective of this study was to develop anatomically correct whole body human models of an adult male (34 years old), an adult female (26 years old) and two children (an 11-year-old girl and a six-year-old boy) for the optimized evaluation of electromagnetic exposure. These four models are referred to as the Virtual Family. They are based on high resolution magnetic resonance (MR) images of healthy volunteers. More than 80 different tissue types were distinguished during the segmentation. To improve the accuracy and the effectiveness of the segmentation, a novel semi-automated tool was used to analyze and segment the data. All tissues and organs were reconstructed as three-dimensional (3D) unstructured triangulated surface objects, yielding high precision images of individual features of the body. This greatly enhances the meshing flexibility and the accuracy with respect to thin tissue layers and small organs in comparison with the traditional voxel-based representation of anatomical models. Conformal computational techniques were also applied. The techniques and tools developed in this study can be used to more effectively develop future models and further improve the accuracy of the models for various applications. For research purposes, the four models are provided for free to the scientific community.

A computational model of intussusceptive microvascular growth and remodeling.

Non-sprouting angiogenesis, also known as intussusceptive angiogenesis (IA), is an important modality of blood vessel morphogenesis in growing tissues. We present a novel computational framework for simulation of IA to answer some of the questions concerning the underlying mechanisms of the remodeling process. The model relies on mechanical interactions between blood and tissue, includes the structural maturation of the vessel wall, and is controlled by stimulating or inhibiting chemical agents. The model provides a simple explanation for the formation of microvessels and bifurcations from capillaries via IA, allowing for both maintenance and avoidance of shunt vessels. Detailed hemodynamic and transport properties for oxygen, metabolites or growth factors can be predicted. The model is an in silico framework for testing certain conceptual ideas about the mechanisms of intussusceptive growth and remodeling, in particular those related to mechanical and transport phenomena.

A computational framework for modelling solid tumour growth.

The biology of cancer is a complex interplay of many underlying processes, taking place at different scales both in space and time. A variety of theoretical models have been developed, which enable one to study certain components of the cancerous growth process. However, most previous approaches only focus on specific aspects of tumour development, largely ignoring the influence of the evolving tumour environment. In this paper, we present an integrative framework to simulate tumour growth, including those model components that are considered to be of major importance. We start by addressing issues at the tissue level, where the phenomena are modelled as continuum partial differential equations. We extend this model with relevant components at the cellular or even sub-cellular level in a vertical fashion. We present an implementation of this framework, covering the major processes and treat the mechanical deformation due to growth, the biochemical response to hypoxia, blood flow, oxygenation and the explicit development of a vascular system in a coupled way. The results demonstrate the feasibility of the approach and its applicability to in silico studies of the influence of different treatment strategies (like the usage of novel anti-cancer drugs) for more effective therapy design.

A multiphysics simulation of a healthy and a diseased abdominal aorta.

Abdominal Aortic Aneurysm is a potentially life-threatening disease if not treated adequately. Its pathogenesis is complex and multifactorial and is still not fully understood. Many biochemical and biomechanical mechanisms have been identified as playing a role in the formation of aneurysms but it is as yet unclear what triggers the process. We investigated the role of the relevant biomechanical factors, in particular the wall shear stress and the intramural wall stress by simulating fluid structure interaction between the blood flow and the deforming arterial wall in a healthy abdominal aortic bifurcation, the preferred location of the disease. We then extended this study by introducing a hypothetical weakening of the aortic wall. Intramural wall stress was considerably higher and wall shear stress considerably lower in this configuration, supporting the hypothesis that biomechanical aneurysmal growth factors are self-sustaining.

A coupled finite element model of tumor growth and vascularization.

We present a model of solid tumor growth which can account for several stages of tumorigenesis, from the early avascular phase to the angiogenesis driven proliferation. The model combines several previously identified components in a consistent framework, including neoplastic tissue growth, blood and oxygen transport, and angiogenic sprouting. First experiments with the framework and comparisons with observations made on solid tumors in vivo illustrate the plausibility of the approach. Explanations of several experimental observations are naturally provided by the model. To the best of our knowledge this is the first report of a model coupling tumor growth and angiogenesis.

Computational model of flow-tissue interactions in intussusceptive angiogenesis.

Angiogenesis, the growth of vascular structures, is a complex biological process which has long puzzled scientists. Better physiological understanding of this phenomenon could result in many useful medical applications such as the development of new methods for cancer therapy. We report on the development of a simple computational model of micro-vascular structure formation in intussusceptive angiogenesis observed in vivo. The tissue is represented by a discrete set of basic structural entities and flow conditions within the resulting domain are obtained by solving the Navier-Stokes equations. The tissue is then remodelled according to the tangential shear stress while approximating advection by means of simple non-diffusive heuristics. The updated tissue geometry then becomes the input for the next remodelling step. The model, consisting of steady-state flow and a simple mechanistic tissue response, successfully predicts bifurcation formation and micro-vessel separation in a porous cellular medium. This opens new modelling possibilities in computational studies of the cellular transport involved in micro-vascular growth.

Simulating vascular systems in arbitrary anatomies.

Better physiological understanding of principles regulating vascular formation and growth is mandatory to their efficient modeling for the purpose of physiologically oriented medical applications like training simulation or pre-operative planning. We have already reported on the implementation of a visually oriented modeling framework allowing to study various physiological aspects of the vascular systems on a macroscopic scale. In this work we describe our progress in this field including (i) extension of the presented model to three dimensions, (ii) addition of established mathematical approaches to modeling angiogenesis and (iii) embedding the structures in arbitrary anatomical elements represented by finite element meshes.