Integration of the reduced order constrained optimization algorithm into a commercial treatment planning system

Authors
Bakr, Shaimaa
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Other Contributors
Radke, Richard J., 1974-
Sanderson, A. C. (Arthur C.)
Wang, Meng
Issue Date
2014-05
Keywords
Electrical engineering
Degree
MS
Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
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Abstract
The Reduced-Order Constrained Optimization (ROCO) method addresses the computational and dimensionality issues in IMRT optimization to reduce planning time and cost. In previous work, ROCO was developed and designed to operate with the in-house TPS at Memorial Sloan Kettering Cancer Center (MSKCC). ROCO was previously applied to advanced cases in dierent tumor sites, including the prostate, lung, and head and neck and was proven to provide clinically acceptable results at signicant time savings in comparison with current standard procedure. This thesis focuses on the implementation of ROCO to interface with a commercial treatment planning system (Eclipse , by Varian Medical Systems, Inc, Palo Alto, CA) using an Application Programming Interface (API). Our challenge lies in demonstrating that the ROCO method performs successfully and reliably using different optimization and dose calculation modules from those used in previous implementations. We explore the new version 13.0 Eclipse Scripting API (ESAPI), as well as its planning and evaluation capabilities. To design a standalone ROCO application that works seamlessly with Eclipse, we use the API to access patient data, and call Eclipse's optimization and dose calculation modules. Moreover, we verify the performance of ROCO in the new environment and evaluate the quality of the resulting treatment plans with respect to deliverability and clinical acceptance.
Description
May 2014
School of Engineering
Department
Dept. of Electrical, Computer, and Systems Engineering
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
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