Towards Non-Invasive Lung Tumor Tracking Based on Patient Specific Model of Respiratory System.

The goal of this paper is to calculate a complex internal respiratory and tumoral movements by measuring respiratory air flows and thorax movements. In this context, we present a new lung tumor tracking approach based on a patient-specific biomechanical model of the respiratory system, which takes into account the physiology of respiratory motion to simulate the real non-reproducible motion. The behavior of the lungs, is directly driven by the simulated actions of the breathing muscles, i.e. the diaphragm and the intercostal muscles (the rib cage). In this paper, the lung model is monitored and controlled by a personalized lung pressure/volume relationship during a whole respiratory cycle. The lung pressure and rib kinematics are patient specific and obtained by surrogate measurement. The rib displacement corresponding to the transformation which was computed by finite helical axis method from the end of exhalation (EE) to the end of inhalation (EI). The lung pressure is calculated by an optimization framework based on inverse finite element analysis, by minimizing the lung volume errors, between the respiratory volume (respiratory airflow exchange) and the simulated volume (calculated by biomechanical simulation). We have evaluated the model accuracy on five public datasets. We have also evaluated the lung tumor motion identified in 4D CT scan images and compared it with the trajectory that was obtained by finite element simulation. The effects of rib kinematics on lung tumor trajectory were investigated. Over all phases of respiration, our developed model is able to predict the lung tumor motion with an average landmark error of [Formula: see text]. The results demonstrate the effectiveness of our physics-based model. We believe that this model can be potentially used in 4D dose computation, removal of breathing motion artifacts in positron emission tomography (PET) or gamma prompt image reconstruction.

Particle-beam-dependent optimization for Monte Carlo simulation in hadrontherapy using tetrahedral geometries.

The use of tetrahedral-based phantoms in conjunction with Monte Carlo dose calculation techniques has shown high capabilities in radiation therapy. However, the generation of a precise dose distribution can be very time-consuming since a fine tetrahedral mesh is required. In this work, we propose a new method that defines the density distribution of patient-specific tetrahedral phantoms, based upon the CT-scans and the direction of the particle beam. The final purpose is to coarsen the tetrahedral mesh to improve computational performance in Monte Carlo simulations while guaranteeing a precise dose distribution in the target volume. Contrarily to the state of the art methods that calculate the density value of a tetrahedron, locally based only on the CT-scans, our approach also takes into account the direction of the beam to minimize the error of the water equivalent thickness of the tetrahedrons before the tumor volume. In this study, the experiments carried out on a multi-layer computational phantom, and a thorax geometry, show that by applying our method on a coarse mesh, we offer a better dose distribution inside the tumor compared to other density mapping methods, in the same level of detail. This is due to the reduction of the water equivalent path length error from 9.65 mm to 0.62 mm in the case of the multi-layer phantom, and from 2.42 mm to 0.48 mm for the thorax geometry. Moreover, a similar dose coverage is obtained with refined tetrahedral meshes. As a consequence of the reduction of the number of tetrahedrons, computational time is found to be 25% shorter than both the refined tetrahedral mesh and the voxel-based structure in most cases. Using a coarse tetrahedral mesh to have accurate dose distributions on a given target is feasible as long as the water equivalent path length in the direction of the beam is respected.

Four-dimensional radiotherapeutic dose calculation using biomechanical respiratory motion description.

PURPOSE: Organ motion due to patient breathing introduces a technical challenge for dosimetry and lung tumor treatment by hadron therapy. Accurate dose distribution estimation requires patient-specific information on tumor position, size, and shape as well as information regarding the material density and stopping power of the media along the beam path. A new 4D dosimetry method was developed, which can be coupled to any motion estimation method. As an illustration, the new method was implemented and tested with a biomechanical model and clinical data. METHODS: First, an anatomical model of the lung and tumor was synthesized with deformable tetrahedral grids using computed tomography (CT) images. The CT attenuation values were estimated at the grid vertices. Respiratory motion was simulated biomechanically based on nonlinear finite element analysis. Contrary to classical image-based methods where motion is described using deformable image registration algorithms, the dose distribution was accumulated over tetrahedral meshes that are deformed using biomechanical modeling based on finite element analysis. RESULTS: The new method preserves the mass of the objects during simulation with an error between 1.6 and 3.6%. The new method was compared to an existing dose calculation method demonstrating significant differences between the two approaches and overall superior performance using the new method. CONCLUSION: A unified model of 4D radiotherapy respiratory effects was developed where biomechanical simulations are coupled with dose calculations. Promising results demonstrate that this approach has significant potential for the treatment for moving tumors.

Micro-to-nano biomechanical modeling for assisted biological cell injection.

To facilitate training of biological cell injection operations, we are developing an interactive virtual environment to simulate needle insertion into biological cells. This paper presents methodologies for dynamic modeling, visual/haptic display, and model validation of cell injection. We first investigate the challenging issues in the modeling of the biomechanical properties of living cells. We propose two dynamic models to simulate cell deformation and puncture. The first approach is based on the assumptions that the mechanical response of living cells is mainly determined by the cytoskeleton and that the cytoskeleton is organized as a tensegrity structure including microfilaments, microtubules, and intermediate filaments. Equivalent microtubules struts are represented with a linear mass-tensor finite-element model and equivalent microfilaments and intermediate filaments with viscoelastic Kelvin-Voigt elements. The second modeling method assumes the overall cell as an homogeneous hyperelastic model (St, Venant-Kirchhoff). Both graphic and haptic rendering are provided in real time to the operator through a 3-D virtual environment. Simulated responses are compared to experimental data to show the effectiveness of the proposed physically based model.

Mechanical phenotyping of mouse embryonic stem cells: increase in stiffness with differentiation.

Atomic force microscopy (AFM) has emerged as a promising tool to characterize the mechanical properties of biological materials and cells. In our studies, undifferentiated and early differentiating mouse embryonic stem cells (mESCs) were assessed individually using an AFM system to determine if we could detect changes in their mechanical properties by surface probing. Probes with pyramidal and spherical tips were assessed, as were different analytical models for evaluating the data. The combination of AFM probing with a spherical tip and analysis using the Hertz model provided the best fit to the experimental data obtained and thus provided the best approximation of the elastic modulus. Our results showed that after only 6 days of differentiation, individual cell stiffness increased significantly with early differentiating mESCs having an elastic modulus two- to threefold higher than undifferentiated mESCs, regardless of cell line (R1 or D3 mESCs) or treatment. Single-touch (indentation) probing of individual cells is minimally invasive compared to other techniques. Therefore, this method of mechanical phenotyping should prove to be a valuable tool in the development of improved methods of identification and targeted cellular differentiation of embryonic, adult, and induced-pluripotent stem cells for therapeutic and diagnostic purposes.

Mechanical characterization of mouse embryonic stem cells.

Current cell detection techniques are antibody staining of specific protein markers, morphometric parameters and transgenic markers. These assays are often qualitative and do not quantitatively define the outcome of a cell progression during differentiation. Consequently, we propose to characterize the mechanical behavior of embryonic stem cell, which will predict its stage of differentiation during lineage differentiation. Using the atomic force microscope, we have performed several experiments on mouse embryonic stem cells (mESC) roughly 7-17 microm in diameter and height at the interphase stage of the cell cycle process. Specifically, we conducted single indentation studies on undifferentiated and early differentiating (6 days under differentiation conditions) mESC with a cell indentation range of 2-2.5 microm. The data was used to analyze various contact models that can accurately model the geometry of the AFM tip and mESC interaction. With the choice of appropriate contact model, we can determine the accurate modulus of the cell membrane. The experimental results confirmed our research hypothesis that the mechanical property of undifferentiated mESC is different from differentiating (6th day) mESC.