The role of exposure time in computerized training of prostate cryosurgery: performance comparison of surgical residents with engineering students.

PURPOSE: This study aims at the evaluation of a prototype of a computerized trainer for cryosurgery-the controlled destruction of cancer tumors by freezing. The hypothesis in this study is that computer-based cryosurgery training for an optimal cryoprobe layout is essentially a matter of exposure time, rather than trainee background or the specific computer-generated planning target. Key geometric features under considerations are associated with spatial limitations on cryoprobes placement and the match between the resulted thermal field and the unique anatomy of the prostate. METHODS: All experiments in this study were performed on the cryosurgery trainer-a prototype platform for computerized cryosurgery training, which has been presented previously. Among its key features, the cryosurgery trainer displays the prostate shape and its contours and provides a distance measurement tool on demand, in order to address spatial constraints during ultrasound imaging guidance. Another unique feature of the cryosurgery trainer is an output movie, displaying the simulated thermal field at the end of the cryoprocedure. RESULTS: The current study was performed on graduate engineering students having no formal background in medicine, and the results were benchmarked against data obtained on surgical residents having no experience with cryosurgery. Despite fundamental differences in background and experience, neither group displayed superior performance when it comes to cryoprobe layout planning. CONCLUSIONS: This study demonstrates that computer-based training of an optimal cryoprobe layout is feasible. This study demonstrates that the training quality is essentially related to the training exposure time, rather than to a specific planning strategy from those investigated.

Computerized Planning of Prostate Cryosurgery and Shape Considerations.

The current study aims to explore possible relationships between various prostate shapes and the difficulty in creating a computer-based plan for cryosurgery. This research effort is a part of an ongoing study to develop computational means in order to improve cryosurgery training and education. This study uses a computerized planner-a key building block of a recently developed prototype for cryosurgery training. The quality of planning is measured by the overall defect volume, a proprietary concept which refers to undercooled areas internal to the target region and overcooled areas external to it. Results of this study numerically confirm that the overall defect volume decreases with an increasing number of cryoprobes, regardless of the geometry of the prostate. However, the number of cryoprobes required to achieve the smallest possible defect may be unrealistically high (<30). Results of this study also demonstrate that the optimal cryoprobe layout is associated with a smaller defect for symmetric prostate geometries and, independently, for prostate models that better resemble a sphere. Furthermore, a smaller defect is typically achieved when the urethra passes through the center of the prostate model. This study proposes to create a cryoprobe convex hull for the purpose of initial planning, which is a subdomain similar in shape to the prostate but at a reduced size. Parametric studies indicate that a cryoprobe convex hull contracted by 7 to 9 mm in all directions from the prostate capsule serves as a quasi-optimal initial condition for planning, that is, a preselected number of cryoprobes placed in the cryoprobe convex hull yields favorable results for optimization. The cryoprobe convex hull could accelerate computer-based planning, while also being adopted as a concept for traditional cryosurgery training, when computerized means are absent.

A Computerized Tutor Prototype for Prostate Cryotherapy: Key Building Blocks and System Evaluation.

This paper focuses on the evaluation of a prototype for a computer-based tutoring system for prostate cryosurgery, while reviewing its key building blocks and their benchmark performance. The tutoring system lists geometrical constraints of cryoprobe placement, displays a rendered shape of the prostate, simulates cryoprobe insertion, 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 plan, created for each case study by a previously developed planning algorithm, known as bubble-packing. While the tutoring level in this study aims only at geometrical constraints on cryoprobe placement and the resulting thermal history, it creates a unique opportunity to gain insight into the process outside of the operation room. System validation of the tutor has been performed by collecting training data from surgical residents, having no prior experience or advanced knowledge of cryotherapy. Furthermore, the system has been evaluated by graduate engineering students having no formal education in medicine. In terms of match between a planning isotherm and the target region shape, results demonstrate medical residents' performance improved from 4.4% in a pretest to 37.8% in a posttest over a course of 50 minutes of training (within 10% margins from a computer-optimized plan). Comparing those results with the performance of engineering students indicates similar results, suggesting that planning of the cryoprobe layout essentially revolves around geometric considerations.

Simulation-Based Cryosurgery Training: Variable Insertion Depth Planning in Prostate Cryosurgery.

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 two-fold: 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-mentioned 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.

Simulation-Based Cryosurgery Intelligent Tutoring System Prototype.

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 preselected 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. The following two versions of the tutoring system have been tested in the current study: (1) an unguided version, where the trainee can practice cases in unstructured sessions and (2) an intelligent tutoring system, which forces the trainee to follow specific steps, believed by the authors to potentially shorten the learning curve. Although 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 the operation room. Post-test results indicate that the intelligent tutoring system may be more beneficial than the nonintelligent tutoring system, but the proof of concept is demonstrated with either system.

Generating prostate models by means of geometric deformation with application to computerized training of cryosurgery.

PURPOSE: As a part of an ongoing project to develop computerized training tools for cryosurgery, the objective of the current study is twofold: to compile literature data on the likelihood of cancer tumor growth and its effect on the prostate shape and to present a deformation scheme for a 3D organ template in order to generate clinically relevant prostate models. The long-term objective of this study is to develop a database of prostate models for computerized training. METHODS: Cryosurgery is typically performed on patients with localized prostate cancer found in stage T3 or earlier. The distribution of key geometric features likely to be found in the prostate at stage T3 is integrated into a 3D prostate template by employing the extended free-form deformation (EFFD) method. The applied scheme combines two steps: pre-selecting a set of geometric parameter values and manipulating the lattice control points until the prostate model meets the desired criteria. RESULTS: Examples for model generation are displayed, based on two 3D prostate templates previously obtained from ultrasound imaging. These examples include selected cases with unilateral and bilateral stage T3 tumor growth, suitable for incorporation into a training database. CONCLUSIONS: EFFD is an efficient method for rapid generation of prostate models. The compiled criteria for model generation do not lead to a unique shape since the contours for template deformation are randomly selected. Nevertheless, these criteria do lead to shapes resembling cancer growth, as various growth histories can lead to a tumor characterized by the same key parameter values.