Yoshiyuki Kagiyama

Automated preoperative planning of femoral stem in total hip arthroplasty from 3D CT data: Atlas-based approach and comparative study

Atlas-based methods for automated preoperative planning of the femoral stem implant in total hip arthroplasty are described. Statistical atlases are constructed from a number of past preoperative plans prepared by experienced surgeons in order to represent the surgeons expertise of the planning. Two types of atlases are considered. One is a statistical distance map atlas, which represents surgeons preference of the contact pattern between the femoral canal (host bone) and stem (implant) surfaces. The other is an optimal reference plan, which is selected as the best representative plan expected to minimize the deviation from the surgeons preferred contact pattern. These atlases are fitted to the patient data to automatically generate the preoperative plan of the femoral stem. In this paper, we formulate a general framework of atlas-based implant planning, and then describe the methods for construction and utilization of the two proposed atlases. In the experiments, we used 40 cases to evaluate the proposed methods and compare them with previous methods by defining the errors as differences between automated and surgeons plans. By using the proposed methods, the positional and orientation errors were significantly reduced compared with the previous methods and the size error was superior to inter-surgeon variability in size selection using 2D templates on an X-ray image reported in previous work.

Expertise Modeling for Automated Planning of Acetabular Cup in Total Hip Arthroplasty Using Combined Bone and Implant Statistical Atlases

Intraoperative robotic and computer-guided assistances are now commonly used in total hip arthroplasty (THA) for accurate execution of the preoperative plan. Although the preoperative plan to be accurately executed is critical, it is still interactively prepared in a time-consuming and subjective manner. In this paper, atlas-based approach to automated surgical planning of the acetabular cup in THA is described to stabilize its quality as well as reduce its time-consuming nature. Surgeons expertise is embedded in two types of statistical atlases, which are constructed from training datasets of CT-based 3D plans prepared by experienced surgeons. One is a statistical shape model which encodes global spatial relationships between the patient anatomy and implant. The other is the statistical map of residual bone thickness on the implant surface, which encodes local spatial constraints of the anatomy and implant. Given the 3D pelvis shape of the patient, we formulate a procedure to determine the best size and position of the acetabular cup which satisfy the constraints derived from the two statistical atlases. We validated the proposed planning method by retrospective study using the datasets which were actually used in the THA surgery.

Tactile mapping approach using electrical stimulus pattern

The fine concavo-convex shape of the object surface is a critical component that determines its texture. A previous electrotactile display could not tactually present fine concavo-convex objects but only a line pattern on the plane. In this study, the authors proposed a physiology-based tactile mapping method by formulating nerve activities that stem from a mechanical stimulus. The proposed electrical stimulus allows a human to perceive a concavo-convex shape. A stimulus frequency coded the skin displacement given by a concavo-convex shape and represented the adaptation of receptors with exponential approximation. As an example of tactually presenting a concavo-convex shape, roughness was introduced by using a Brownian surface, which enables a user to touch a surface of varying degrees of roughness with a developed tactile display mounted on a computer mouse. The results of subjective experiments showed a statistical difference among the perceived roughness of displayed rough surfaces. This study concluded that the proposed tactile mapping method was effective to present a touch sensation for concavo-convex shapes corresponding to a stimulus frequency below 100 Hz.

Optimization of surgical planning of total hip arthroplasty based on computational anatomy

This paper describes a method for automated optimization of total hip arthroplasty (THA) planning incorporating joint functionalities. The optimal planning is formulated as maximum a posterior (MAP) estimation, which ensures the best-balance of joint functionalities and bone-implant spatial relations based on their statistical models derived from the training datasets prepared by an experienced surgeon. According to the performance evaluation, four of the six functionalities of the automatically optimized plans were almost equivalent to those of surgeons plans, and two of them were improved. We consider these results showed a potential usefulness of the proposed method.

Construction of a Statistical Surgical Plan Atlas for Automated 3D Planning of Femoral Component in Total Hip Arthroplasty

The problem of automating preoperative planning of the femoral component (stem) for total hip arthroplasty (THA) is addressed. In our previous method, time-consuming trial-and-error processes were involved in parameter tuning of the objective function. This problem prevents application in different stem systems. To overcome this problem, a statistical surgical plan atlas (SSPA) is constructed from training datasets of stem planning. The SSPA represents the average and variance of the distance distribution on the stem surface to the femoral canal surface. That is, it encodes the distribution of the degree of contact preferred by the surgeon. Automated planning is performed by minimizing the squared difference between distributions of the SSPA and planning solution. The proposed method involves no parameter tuning to define the objective function that evaluates differences from the planning the surgeon prefers. Experimental evaluations showed that the proposed method renders parameter tuning unnecessary while it still provides comparable accuracy to the previous method.

Force reflecting porous media with dynamic elasticity change

Liquid absorption affects the behavior of objects. Rain absorbed in the barrage can weaken its structure and cause the dam failure. A wet sponge ball bounces differently from a dry one. Porous media is a material that has internal pore space and is able to absorb liquid (e.g. a sponge or soil). Liquid absorption changes not only geometrical properties, e.g. volume, but also mechanical properties, e.g. elasticity. The aim of this study is to physically model the structural change of a porous media due to liquid absorption. Previous studies have focused on liquid flow inside the media[Lenaerts et al. 2008]. In contrast, this paper proposes a porous model that is able to simulate elastic change in a real sponge.

Mesh Fusion based Neurosurgical Simulation with Force Feedback

This paper proposes a finite element method (FEM)-based mesh-mesh interaction model with multi-modal 3D meshes for neurosurgical simulation. The proposed model considered energy preservation during collisions of objects. The method was implemented and applied to the surgical approach to the trigeminal nerve in neurosurgery. Simulation results showed real-time simulation of brain tissue deformation with force feedback.