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.