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Computerized planning of cryosurgery using bubble packing: An experimental validation on a phantom material
Authors:Michael R. Rossi  Daigo Tanaka  Kenji Shimada  Yoed Rabin
Affiliation:1. Department of Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, United States;2. Department of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, United States;1. University of St. Thomas, School of Engineering, Mail OSS101, 2115 Summit Avenue, St. Paul, MN 55105-1079, USA;2. University of Minnesota, Department of Mechanical Engineering, 111 Church Street S.E., Minneapolis, MN 55455, USA;1. Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576, Singapore;2. Department of Biomedical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576, Singapore
Abstract:The current study focuses on experimentally validating a planning scheme based on the so-called bubble packing method. This study is a part of an ongoing effort to develop computerized planning tools for cryosurgery, where bubble packing has been previously developed as a means to find an initial, uniform distribution of cryoprobes within a given domain; the so-called force-field analogy was then used to move cryoprobes to their optimum layout. However, due to the high quality of the cryoprobe distribution suggested by bubble packing and its low computational cost, it has been argued that a planning scheme based solely on bubble packing may be more clinically relevant. To test this argument, an experimental validation is performed on a simulated cross-section of the prostate, using gelatin solution as a phantom material, proprietary liquid nitrogen-based cryoprobes, and a cryoheater to simulate urethral warming. Experimental results are compared with numerically simulated temperature histories resulting from planning. Results indicate an average disagreement of 0.8 mm in identifying the freezing front location, which is an acceptable level of uncertainty in the context of prostate cryosurgery imaging.
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