As a part of an ongoing effort to develop computerized training tools for cryosurgery, the current study presents a proof-of-concept for a computerized tool for cryosurgery tutoring. The tutoring system lists geometrical constraints of cryoprobes placement, simulates cryoprobe insertion, displays a rendered shape of the prostate, enables distance measurements, simulates the corresponding thermal history, and evaluates the mismatch between the target region shape and a pre-selected planning isotherm. The quality of trainee planning is measured in comparison with a computer-generated planning, created for each case study by previously developed planning algorithms. Two versions of the tutoring system have been tested in the current study: (i) an unguided version, where the trainee can practice cases in unstructured sessions, and (ii) an intelligent tutoring system (ITS), which forces the trainee to follow specific steps, believed by the authors to potentially shorten the learning curve. While the tutoring level in this study aims only at geometrical constraints on cryoprobe placement and the resulting thermal histories, it creates a unique opportunity to gain insight into the process outside of the operation room. Posttest results indicate that the ITS system maybe more beneficial than the non-ITS system, but the proof-of-concept is demonstrated with either system.

This study focuses on the implementation of an efficient numerical technique for cryosurgery simulations on a graphics processing unit (GPU) as an alternative means to accelerate run time. This study is part of an ongoing effort to develop computerized training tools for cryosurgery, with prostate cryosurgery as a developmental model. The ability to perform rapid simulations of varying test cases is critical to facilitate sound decision making associated with medical training. Consistent with clinical practice, the training tool aims at correlating the frozen region contour and the corresponding temperature field with the target region shape. The current study focuses on the feasibility of GPU-based computation using C++ accelerated massive parallelism (AMP), as one possible implementation. Benchmark results on a variety of computation platforms display between three-fold acceleration (laptop) and thirteen-fold acceleration (gaming computer) of cryosurgery simulation, in comparison with the more common implementation on a multi-core central processing unit (CPU). While the general concept of GPU-based simulations is not new, its application to phase-change problems, combined with the unique requirements for cryosurgery optimization, represents the core contribution of the current study.

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This study presents an efficient computational technique for the simulation of ultrasound imaging artifacts associated with cryosurgery based on nonlinear ray-tracing. This study is part of an ongoing effort to develop computerized training tools for cryosurgery, with prostate cryosurgery as a development model. The capability of performing virtual cryosurgical procedures on a variety of test cases is essential for effective surgical training. Simulated ultrasound imaging artifacts include reverberation and reflection of the cryoprobes in the unfrozen tissue, reflections caused by the freezing front, shadowing caused by the frozen region, and tissue-property changes in repeated freeze-thaw cycles procedures. The simulated artifacts appear to preserve the key features observed in a clinical setting. This study displays an example of how training may benefit from toggling between the undisturbed ultrasound image, the simulated temperature field, the simulated imaging artifacts, and an augmented hybrid presentation of the temperature field superimposed on the ultrasound image. The proposed method is demonstrated on a graphic processing unit (GPU) at 100 fps, on a mid-range personal workstation, at two orders of magnitude faster than a typical cryoprocedure. This performance is based on computation with C++ accelerated massive parallelism (AMP) and its interoperability with the DirectX rendering API.

A proof-of-concept for an advanced-level computerized training tool for cryosurgery is demonstrated, based on three-dimensional cryosurgery simulations and a variable insertion-depth strategy for cryoprobes. The objective for system development is twofold: to identify a cryoprobe layout in order to best-match a planning isotherm with the target region shape, and to verify that cryoprobe placement does not violate accepted geometric constraints. System validation has been performed by collecting training data from 17 surgical residents, having no prior experience or advanced knowledge of cryosurgery. This advanced-level study includes an improved training-session design, in order to enhance knowledge dissemination and elevate participant motivation to excel. In terms of match between a planning isotherm and the target region shape, results of this demonstrate trainee performance improvement from 4.4% in a pretest to 44.4% in a posttest over a course of 50 minutes of training. In terms of combined performance, including the above geometrical match and constraints on cryoprobe placement, this study demonstrates trainee performance improvement from 2.2% in the pretest to 31.1% in the posttest. Given the relatively short training session and the lack of prior knowledge, these improvements are significant and encouraging. These results are of particular significance, as they have been obtained from a surgical resident population, which are exposed to the typical stress and constraints in advanced surgical education.