Modeling, Simulation, And Visualization Of 3d Lung Dynamics

Medical simulation has facilitated the understanding of complex biological phenomenon through its inherent explanatory power. It is a critical component for planning clinical interventions and analyzing its effect on a human subject. The success of medical simulation is evidenced by the fact that over one third of all medical schools in the United States augment their teaching curricula using patient simulators. Medical simulators present combat medics and emergency providers with video-based descriptions of patient symptoms along with step-by-step instructions on clinical procedures that alleviate the patient\u27s condition. Recent advances in clinical imaging technology have led to an effective medical visualization by coupling medical simulations with patient-specific anatomical models and their physically and physiologically realistic organ deformation. 3D physically-based deformable lung models obtained from a human subject are tools for representing regional lung structure and function analysis. Static imaging techniques such as Magnetic Resonance Imaging (MRI), Chest x-rays, and Computed Tomography (CT) are conventionally used to estimate the extent of pulmonary disease and to establish available courses for clinical intervention. The predictive accuracy and evaluative strength of the static imaging techniques may be augmented by improved computer technologies and graphical rendering techniques that can transform these static images into dynamic representations of subject specific organ deformations. By creating physically based 3D simulation and visualization, 3D deformable models obtained from subject-specific lung images will better represent lung structure and function. Variations in overall lung deformations may indicate tissue pathologies, thus 3D visualization of functioning lungs may also provide a visual tool to current diagnostic methods. The feasibility of medical visualization using static 3D lungs as an effective tool for endotracheal intubation was previously shown using Augmented Reality (AR) based techniques in one of the several research efforts at the Optical Diagnostics and Applications Laboratory (ODALAB). This research effort also shed light on the potential usage of coupling such medical visualization with dynamic 3D lungs. The purpose of this dissertation is to develop 3D deformable lung models, which are developed from subject-specific high resolution CT data and can be visualized using the AR based environment. A review of the literature illustrates that the techniques for modeling real-time 3D lung dynamics can be roughly grouped into two categories: Geometrically-based and Physically-based. Additional classifications would include considering a 3D lung model as either a volumetric or surface model, modeling the lungs as either a single-compartment or a multi-compartment, modeling either the air-blood interaction or the air-blood-tissue interaction, and considering either a normal or pathophysical behavior of lungs. Validating the simulated lung dynamics is a complex problem and has been previously approached by tracking a set of landmarks on the CT images. An area that needs to be explored is the relationship between the choice of the deformation method for the 3D lung dynamics and its visualization framework. Constraints on the choice of the deformation method and the 3D model resolution arise from the visualization framework. Such constraints of our interest are the real-time requirement and the level of interaction required with the 3D lung models. The work presented here discusses a framework that facilitates a physics-based and physiology-based deformation of a single-compartment surface lung model that maintains the frame-rate requirements of the visualization system. The framework presented here is part of several research efforts at ODALab for developing an AR based medical visualization framework. The framework consists of 3 components, (i) modeling the Pressure-Volume (PV) relation, (ii) modeling the lung deformation using a Green\u27s function based deformation operator, and (iii) optimizing the deformation using state-of-art Graphics Processing Units (GPU). The validation of the results obtained in the first two modeling steps is also discussed for normal human subjects. Disease states such as Pneumothorax and lung tumors are modeled using the proposed deformation method. Additionally, a method to synchronize the instantiations of the deformation across a network is also discussed

Modeling Real-Time 3-D Lung Deformations for Medical Visualization

In this paper, we propose a physics-based and physiology-based approach for modeling real-time deformations of 3-D high-resolution polygonal lung models obtained from high-resolution computed tomography (HRCT) images of normal human subjects. The physics-based deformation operator is nonsymmetric, which accounts for the heterogeneous elastic properties of the lung tissue and spatial-dynamic flow properties of the air. An iterative approach is used to estimate the deformation with the deformation operator initialized based on the regional alveolar expandability, a key physiology-based parameter. The force applied on each surface node is based on the airflow pattern inside the lungs, which is known to be based on the orientation of the human subject. The validation of lung dynamics is done by resimulating the lung deformation and comparing it with HRCT data and computing force applied on each node derived from a 4-D HRCT dataset of a normal human subject using the proposed deformation operator and verifying its gradient with the orientation

Modeling Air-flow in the Tracheobronchial Tree using Computational Fluid Dynamics

In this paper, we present a biomechanical framework to model air-flow inside the bronchus and deformations across the tracheobronchial tree, pipeline for the simulator, theory and initial steps to realize this framework on a highly parallel graphical processing unit (GPU). We discuss the main challenges expected and encountered to date. By using computational fluid dynamics (CFD) and computational solid dynamics (CSD) principles, we propose a numerical simulation framework that includes a biomechanical model of the tracheobronchial tree to simulate air flow inside the tree, on GPU in real-time. The proposed 3D biomechanical model to simulate the air inside the lungs coupled with a deformation model of the tracheobronchial tree, expressed through fluid-structure interaction, can be used to predict the transformations of the voxels from a 4D computed tomography (4DCT) dataset. Additionally, the proposed multi-functional CFD and CSD based framework is suitable for clinical applications such as adaptive lung radiotherapy, and a regional alveolar ventilation estimation

The Multicellular Effects of VDAC1 N-Terminal-Derived Peptide

The mitochondrial voltage-dependent anion channel-1 (VDAC1) protein functions in a variety of mitochondria-linked physiological and pathological processes, including metabolism and cell signaling, as well as in mitochondria-mediated apoptosis. VDAC1 interacts with about 150 proteins to regulate the integration of mitochondrial functions with other cellular activities. Recently, we developed VDAC1-based peptides that have multiple effects on cancer cells and tumors including apoptosis induction. Here, we designed several cell-penetrating VDAC1 N-terminal-derived peptides with the goal of identifying the shortest peptide with improved cellular stability and activity. We identified the D-Δ(1-18)N-Ter-Antp comprising the VDAC1 N-terminal region (19-26 amino acids) fused to the Antp, a cell-penetrating peptide. We demonstrated that this peptide induced apoptosis, autophagy, senescence, cell volume enlargement, and the refusion of divided daughter cells into a single cell, it was responsible for reorganization of actin and tubulin filaments, and increased cell adhesion. In addition, the peptide induced alterations in the expression of proteins associated with cell metabolism, signaling, and division, such as enhancing the expression of nuclear factor kappa B and decreasing the expression of the nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha. These cellular effects may result from the peptide interfering with VDAC1 interaction with its interacting proteins, thereby blocking multiple mitochondrial/VDAC1 pathways associated with cell functions. The results of this study further support the role of VDAC1 as a mitochondrial gatekeeper protein in controlling a variety of cell functions via interaction with associated proteins

Physiologically-based Modeling and Visualization of Deformable Lungs

A real-time physiologically-based breathing model of lungs under normal and pathological scenario has been conceived and implemented. The algorithm developed for lung deformations under various breathing scenarios uses polygonal models of lungs. The method developed avoids the “stiffness” problem observed in Mass-Spring models. Hardware acceleration of the exhalation and the inhalation process is done using vertex shaders. The method of deformation is general and can be applied to any lung model

Distributed Augmented Reality with 3D Lung Dynamics - A Planning Tool Concept

Augmented Reality (AR) systems add visual information to the world by using advanced display techniques. The advances in miniaturization and reduced costs make some of these systems feasible for applications in a wide set of fields. We present a potential component of the cyber infrastructure for the operating room of the future; a distributed AR based software-hardware system that allows real-time visualization of 3D lung dynamics superimposed directly on the patient’s body. Several emergency events (e.g. closed and tension pneumothorax) and surgical procedures related to the lung (e.g. lung transplantation, lung volume reduction surgery, surgical treatment of lung infections, lung cancer surgery) could benefit from the proposed prototype

Physically-based Deformation of High-Resolution 3D Lung Models for Augmented Reality based Medical Visualization

Visualization tools using Augmented Reality Environments are effective in applications related to medical training, prognosis and expert interaction. Such medical visualization tools can also provide key visual insights on the physiology of deformable anatomical organs (e.g. lungs). In this paper we propose a deformation method that facilitates physically-based elastostatic deformations of 3D high-resolution polygonal models. The implementation of the deformation method as a pre-computation approach is shown for a 3D high-resolution lung model. The deformation is represented as an integration of the applied force and the local elastic property assigned to the 3D lung model. The proposed deformation method shows faster convergence to equilibrium as compared to other physically-based simulation methods. The proposed method also accounts for the anisotropic tissue elastic properties. The transfer functions are formulated in such a way that they overcome stiffness effects during deformations