| Literature DB >> 28717259 |
Yoed Rabin1,2, Kenji Shimada1, Purva Joshi1, Anjali Sehrawat1, Robert Keelan1, Dona M Wilfong2, James T McCormick3.
Abstract
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.Entities:
Keywords: Cryosurgery; Evaluation; Optimization; Planning; Prostate; Simulation; Training
Year: 2017 PMID: 28717259 PMCID: PMC5510662 DOI: 10.1117/12.2257151
Source DB: PubMed Journal: Proc SPIE Int Soc Opt Eng ISSN: 0277-786X