Tetrahedral Mass Spring Model for Fast Soft Tissue Deformation

Virtual Surgical Planning: Modeling from the Present to the Future

Virtual surgery planning is a non-invasive procedure, which uses digital clinical data for diagnostic, procedure selection and treatment planning purposes, including the forecast of potential outcomes. The technique begins with 3D data acquisition, using various methods, which may or may not utilize ionizing radiation, such as 3D stereophotogrammetry, 3D cone-beam CT scans, etc. Regardless of the imaging technique selected, landmark selection, whether it is manual or automated, is the key to transforming clinical data into objects that can be interrogated in virtual space. As a prerequisite, the data require alignment and correspondence such that pre- and post-operative configurations can be compared in real and statistical shape space. In addition, these data permit predictive modeling, using either model-based, data-based or hybrid modeling. These approaches provide perspectives for the development of customized surgical procedures and medical devices with accuracy, precision and intelligence. Therefore, this review briefly summarizes the current state of virtual surgery planning.

Automatically Addressing System for Ultrasound-Guided Renal Biopsy Training Based on Augmented Reality

Chronic kidney disease has become one of the diseases with the highest morbidity and mortality in kidney diseases, and there are still some problems in surgery. During the operation, the surgeon can only operate on two-dimensional ultrasound images and cannot determine the spatial position relationship between the lesion and the medical puncture needle in real-time. The average number of punctures per patient will reach 3 to 4, Increasing the incidence of complications after a puncture. This article starts with ultrasound-guided renal biopsy navigation training, optimizes puncture path planning, and puncture training assistance. The augmented reality technology, combined with renal puncture surgery training was studied. This paper develops a prototype ultrasound-guided renal biopsy surgery training system, which improves the accuracy and reliability of the system training. The system is compared with the VR training system. The results show that the augmented reality training platform is more suitable as a surgical training platform. Because it takes a short time and has a good training effect.

Three-dimensional printing of facial contour based on preoperative computer simulation and its clinical application

Facial contouring is a complex procedure performed to alter tissue contents and restore facial appearance. However, it is difficult to measure the amount of the tissue volume that is needed. This study demonstrated the use of preoperative computer simulation (PCS) and 3-dimensional (3D) printing in contouring procedure to maximize outcomes.Three-dimensional surface imaging (3DSI) or computed tomography imaging (CTI) data were reconstructed into a 3D model by Mimics software. PCS was performed by simulating the changes in bone and soft tissue. The stimulating volume change was calculated by Boolean operations. Finally, the virtual model was exported into 3D printer to produce physical templates to guide surgical plan. PCS and actual postoperative results were compared using objective rating scales and by cephalometrical measurements.With the direct guidance of PCS and 3D templates, contouring procedure was performed accurately. Satisfactory facial contouring was achieved with less operative time. As the plastic surgery panel rated, 45.8% of the 3DSI results and 41.7% of the CTI results were identical with the actual outcome, and 0% of them was poor. There were no significant differences in patient satisfaction between the PCS of 3DSI and CTI.Preoperative computer simulation is an accurate method for designing contour adjustment plans, and can be an efficient and reliable predictor of outcomes with customized templates.

Integrating viscoelastic mass spring dampers into position-based dynamics to simulate soft tissue deformation in real time

We propose a novel method to simulate soft tissue deformation for virtual surgery applications. The method considers the mechanical properties of soft tissue, such as its viscoelasticity, nonlinearity and incompressibility; its speed, stability and accuracy also meet the requirements for a surgery simulator. Modifying the traditional equation for mass spring dampers (MSD) introduces nonlinearity and viscoelasticity into the calculation of elastic force. Then, the elastic force is used in the constraint projection step for naturally reducing constraint potential. The node position is enforced by the combined spring force and constraint conservative force through Newton's second law. We conduct a comparison study of conventional MSD and position-based dynamics for our new integrating method. Our approach enables stable, fast and large step simulation by freely controlling visual effects based on nonlinearity, viscoelasticity and incompressibility. We implement a laparoscopic cholecystectomy simulator to demonstrate the practicality of our method, in which liver and gallbladder deformation can be simulated in real time. Our method is an appropriate choice for the development of real-time virtual surgery applications.

Real-time deformation of human soft tissues: A radial basis meshless 3D model based on Marquardt's algorithm

BACKGROUND

When the meshless method is used to establish the mathematical-mechanical model of human soft tissues, it is necessary to define the space occupied by human tissues as the problem domain and the boundary of the domain as the surface of those tissues. Nodes should be distributed in both the problem domain and on the boundaries. Under external force, the displacement of the node is computed by the meshless method to represent the deformation of biological soft tissues. However, computation by the meshless method consumes too much time, which will affect the simulation of real-time deformation of human tissues in virtual surgery.

METHODS

In this article, the Marquardt's Algorithm is proposed to fit the nodal displacement at the problem domain's boundary and obtain the relationship between surface deformation and force. When different external forces are applied, the deformation of soft tissues can be quickly obtained based on this relationship.

RESULTS AND CONCLUSIONS

The analysis and discussion show that the improved model equations with Marquardt's Algorithm not only can simulate the deformation in real-time but also preserve the authenticity of the deformation model's physical properties.

Prediction of soft tissue deformations after CMF surgery with incremental kernel ridge regression

Facial soft tissue deformation following osteotomy is associated with the corresponding biomechanical characteristics of bone and soft tissues. However, none of the methods devised to predict soft tissue deformation after osteotomy incorporates population-based statistical data. The aim of this study is to establish a statistical model to describe the relationship between biomechanical characteristics and soft tissue deformation after osteotomy. We proposed an incremental kernel ridge regression (IKRR) model to accomplish this goal. The input of the model is the biomechanical information computed by the Finite Element Method (FEM). The output is the soft tissue deformation generated from the paired pre-operative and post-operative 3D images. The model is adjusted incrementally with each new patient's biomechanical information. Therefore, the IKRR model enables us to predict potential soft tissue deformations for new patient by using both biomechanical and statistical information. The integration of these two types of data is critically important for accurate simulations of soft-tissue changes after surgery. The proposed method was evaluated by leave-one-out cross-validation using data from 11 patients. The average prediction error of our model (0.9103mm) was lower than some state-of-the-art algorithms. This model is promising as a reliable way to prevent the risk of facial distortion after craniomaxillofacial surgery.

A mathematical model to study the dynamics of epithelial cellular networks

Epithelia are sheets of connected cells that are essential across the animal kingdom. Experimental observations suggest that the dynamical behavior of many single-layered epithelial tissues has strong analogies with that of specific mechanical systems, namely large networks consisting of point masses connected through spring-damper elements and undergoing the influence of active and dissipating forces. Based on this analogy, this work develops a modeling framework to enable the study of the mechanical properties and of the dynamic behavior of large epithelial cellular networks. The model is built first by creating a network topology that is extracted from the actual cellular geometry as obtained from experiments, then by associating a mechanical structure and dynamics to the network via spring-damper elements. This scalable approach enables running simulations of large network dynamics: the derived modeling framework in particular is predisposed to be tailored to study general dynamics (for example, morphogenesis) of various classes of single-layered epithelial cellular networks. In this contribution, we test the model on a case study of the dorsal epithelium of the Drosophila melanogaster embryo during early dorsal closure (and, less conspicuously, germband retraction).

Image fusion in preoperative planning

This article presents a comprehensive overview of generating a digital Patient-Specific Anatomic Reconstruction (PSAR) model of the craniofacial complex as the foundation for a more objective surgical planning platform. The technique explores fusing the patient's 3D radiograph with the corresponding high-precision 3D surface image within a biomechanical context. As taking 3D radiographs has been common practice for many years, this article describes various approaches to 3D surface imaging and the importance of achieving high-precision anatomical results to simulate surgical outcomes that can be measured and quantified. With the PSAR model readily available for facial assessment and virtual surgery, the advantages of this surgical planning technique are discussed.

GPU-based physical cut in interactive haptic simulations

PURPOSE

Interactive, physics based, simulations of deformable bodies are a growing research area with possible applications to computer-aided surgery. Their aim is to create virtual environments where surgeons are free to practice. To ensure the needed realism, the simulations must be performed with deformable bodies. The goal of this paper is to describe the approach to the development of a physics-based surgical simulator with haptic feedback.

METHOD

The main development issue is the representation of the organ behavior at the high rates required by haptic realism. Since even high-end computers have inadequate performance, our approach exploits the parallelism of modern Graphics Processing Units (GPU). Particular attention is paid to the simulation of cuts because of their great importance in the surgical practice and the difficulty in handling topological changes in real time.

RESULTS

To prove the correctness of our approach, we simulated an interactive, physically based, virtual abdomen. The simulation allows the user to interact with deformable models. Deformable models are updated in real time, thus allowing the rendering of force feedback to the user. The method is optimized to handle high quality scenes: we report results of interactive simulation of two virtual tools interacting with a complex model.

CONCLUSIONS

The integration of physics-based deformable models in simulations greatly increases the realism of the virtual environment, taking into account real tissue properties and allowing the user to feel the actual forces exerted by organs on virtual tools. Our method proves the feasibility of exploiting GPU to simulate deformable models in interactive virtual environments.