Cryosurgery is the destruction of undesired tissues by freezing. Despite the continuous development of devices and techniques for minimally invasive cryosurgery, modern cryosurgery frequently falls short of maximizing cryodestruction to the target region, while minimizing cryoinjury to the surrounding tissues. Here, one of the most significant difficulties - and probably the less intuitive obstacle to overcome - is the design and generation of a frozen region to adequately correlate with the shape of the target region and established criteria for cryosurgery success. This project focuses on medical training and education associated with planning and creation of the optimal 3D thermal field for cryosurgery, for the benefit of the surgeon, the medical researcher, and the clinical instrumentation developer. A computerized training tool is developed in this project, the objectives being to shorten the clinician's learning curve, reduce practice time, enable case studies of """"""""what-if"""""""" scenarios, and to enable revaluation of past clinical procedures via a cryosurgery database. While the training tool is designed for general purposes, due to its high clinical relevancy, a particular attention is given to prostate cryosurgery. The training tool consists of three modules: database, simulator, and tutor;the development of each represents one specific aim of the overall research plan. The database consists of three types of datasets: (i) volumetric images obtained from an imaging device such as ultrasound, (ii) reconstructed 3D target region models, and (iii) surgical- procedure outcomes, subject to specific surgical parameters such as number and type of cryoprobes, cryoprobe layout, cryoprobe freezing capabilities, and the resulting temperature field history. The simulator imitates the bioheat transfer process and its imaging with a standard ultrasound technique. Based on the simulated process, the tutor interactively guides the trainee to identify the optimal cryoprobes layout. The tutor may be used for planning future procedures or reevaluation of past cases, while further increasing the size of the database. Consistent with NIH Program Announcement (PA) PAR-07-344 - in the specific area of """"""""Surgery and Virtual Tools""""""""- this project integrates computational techniques for simulation of the surgical procedure, including the imaging effects unique to freezing, and predictions of the bioheat transfer process in the clinically treated area. Emphasis is placed on cryosurgery database design, data retrieval, visualization and graphical interfaces, where the database includes imaging data, geometrical modeling of the target region, cryodevice characteristics, and thermal field history. This project utilizes rapid simulation techniques for bioheat transfer, and recently developed algorithms for computerized planning of cryosurgery. The broader impact of this training tool can potentially far exceed its specific application to cryosurgery, by applying similar methodology to other thermal modalities in surgery, such as focused ultrasound, microwave, laser probes, and other multi-source heating elements.
The objective of this project is to develop a computerized training tool for minimally invasive cryosurgery, which is the destruction of undesired tissue, such as cancerous tumors and organs, by freezing. The training tool is comprised of three modules: (i) a simulator of the cryosurgery procedure for a specific clinical setup;(ii) a tutor to evaluate and systematically improve the quality of the procedure for a given clinical setup;and, (iii) a database to record tutorial sessions, as well as past clinical cases, for the purpose of ongoing education. Development of this training tool is directed toward shortening the learning curve for cryosurgeons by performing virtual cryosurgery cases, and enabling reevaluation of past clinical cases.
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| Sehrawat, Anjali; Shimada, Kenji; Rabin, Yoed (2013) Generating prostate models by means of geometric deformation with application to computerized training of cryosurgery. Int J Comput Assist Radiol Surg 8:301-12 |
