Arterial diseases of sclerosis and aneurysm are known to be related with a local blood flow. There are indeed decades of related studies, recently being with an aid of a computational approach on a patient-specific basis, but those have yet to be translated into clinical medicine. "Simply why?", and "how to achieve it?" Computational blood flow originates from theoretical and computational fluid dynamics. Understanding the underlying knowledge may be beyond the scope of medical professionals. Engineers have to be fully aware of a barrier on an interface with clinical medicine, and manage to translate the evolving technology with a special focus on balancing the efficacy and safety. Visual analytics is to facilitate to overcome an academic gap between engineering and clinical medicine. This paper deals with the recent development of visual analytics of malignant blood flows in cerebral aneurysms for medical professionals.

In this paper we present a new robotic palpation method to perform quantitative measurement of the material parameters of human tissues, for use in medical applications. The proposed method is achieved by the use of a system that integrates a robotic component and a numerical simulation component. The robotic component is used to measure the contact force and displacement at each point on the human body contacted by a robotic probe. The numerical simulation component identifies the material parameters using the proposed method, where two data sources are used, namely, (1) the measured data from the robotic part, and (2) simulated deformation data obtained by the finite element method. In order to validate the proposed system, we report initial results from several phantom tissue experiments, which demonstrate the ability of the system to quantitatively determine the elastic moduli of tissues. We also discuss several potential challenges in the future of the proposed system.

Needle insertion treatments require accurate placement of the needle tip into the target cancer. However, it is difficult to insert the needle accurately because of cancer displacement caused by organ deformation. Therefore, a path planning using numerical simulation to analyze the deformation of the organ is important for accurate needle insertion. The problem in developing a planning method is that puncture conditions, such as the force applied to the needle, is difficult to be decided deterministically, because the experimental data of puncture conditions have variations. Therefore, the purpose of this research was to develop a novel planning method to decide the robust paths of straight needle insertion for various puncture points. The basic idea of this planning method is to consider the puncture condition probabilistic and to evaluate the expected value of needle placement accuracy. First, a probability-based puncture condition was introduced, and then the expected value of needle placement accuracy was defined. Next, the optimization method was developed to search the insertion path in a way that minimizes the expected values of needle placement accuracy. Then, a numerical simulation and evaluation of the planning method was conducted, using a liver-shaped 2D model. Furthermore, an in-vitro experiment was carried out to measure needle placement accuracy from the optimized path. Experimental results show that the planning method realizes needle insertion with a mean accuracy of 1.5 mm.

We describe a control method, for a surgical robot, which prevents the overload at fragile tissues. In particular, we focused on the control parameter setting method to ensure the robustness of the performance relative to the variation of the organ stiffness parameter. Firstly, we present Position/ Limited Stress control to achieving both precise positioning and prevention of overload. FEM based organ model was used to estimate the stress in this control method. Secondly, we describe the control parameter setting method. The control parameter was set to realize sufficient performance within the range of stiffness variation. Finally, we carried out a numerical simulation and an in vitro experiment. The simulation result suggests that our control method and parameter setting method helps prevent stress overload, not depending on the stiffness of organ model. The in vitro experimental result suggests that our method helps prevent stress overload of the in vitro-liver, the stiffness parameter of which is unknown.

Needle insertion treatments require accurate placement of the needle tip into the target cancer. However, it is difficult to insert the needle into the cancer because of cancer displacement due to the organ deformation. Then, a path planning using numerical simulation to analyze the deformation of the organ and the timing of puncture is important for the accurate needle insertion. In this study, we have explained the modeling of conditions where the puncture occurs. Firstly, this paper shows needle insertion experiments for the hog liver in order to measure the needle force and displacement where the puncture occurs. According to the experimental results, significant variations in puncture force were observed. Accordingly, we proposed a novel condition of the force causing a puncture considering probability distribution. We summarized variations of the puncture force in the experimental data and represented conditions where a puncture occurs with probability distribution models where the force is random variable. In addition, the boundary conditions and liver shapes are considered by analyzing the stress status near the needle. Then, we derived the conditions of the puncture with probability distribution models where the stress is random variable.

Organs have many vulnerable tissues such as blood vessels and nerves which must never be damaged. This paper shows a control method which prevents the overload of vulnerable tissues. Firstly, the force control method, which prevents overload, is shown. Secondly, a FEM-based stress observer using the organ model is described. Finally, a control method incorporating the first and second steps, and which prevents overload at vulnerable tissue, is shown. Based on the experimental result of positional and stress data; it is shown that the stress at vulnerable tissues didn't widely exceed limit stress, in the event that a target position potentially resulting in damage to vulnerable tissue was ordered.

This paper shows the viscoelastic and nonlinear organ deformation model for organ model-based control of needle insertion, in which the deformation of an organ is calculated intraoperatively and the needle is manipulated with organ deformation taken into consideration. An organ model including such detailed material characteristics is important to achieve the control method in question. Firstly, the material properties of the liver are modeled from the measured data and its viscoelastic characteristics are represented by differential equations, including the term of the fractional derivative. Nonlinearity in terms of the fractional derivative was measured, and modeled using the quadratic function of strain. Next, a solution of an FE model using such material properties is shown. We use sampling time scaling property as the solution for the viscoelastic system. The solution for a nonlinear system using the Modified Newton-Raphson method is also shown. Finally, the organ deformation, assuming the needle is inserted, is simulated using an organ model and the overall deformation and distribution of the strain is computed in these simulations.