Superior Volumetric Modulated Arc Therapy Planning Solution for Prostate Patients

Abstract

Inverse planning is at the heart of prostate Volumetric Modulated Arc Therapy (VMAT) treatment procedure and critically determines its level of success. As practiced now, the capacity of VMAT is greatly underutilized because of inferior computing performance of existing optimization methods. An alternative mathematical approach that improves both the efficiency and the efficacy is needed and is the center of this research. We propose to develop a new innovative inverse planning tool, based on the novel idea of superiorization, to replace the classical constrained optimization approaches employed in clinics today for prostate VMAT cases. Year 1 of the training award focused on formulating the VMAT problem as a constrained superiorization problem and on the development of a framework of fast converging inverse planning algorithms. Empty solution sets and infeasibility constraints that often exist in real-world applications were incorporated into the model. The new framework was proven mathematically and its efficacy was demonstrated when it was compared to a classical optimization method. The superiorization methodology was Implemented, tested and evaluated on a previously treated prostate case where good initial results were obtained.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2013
Accession Number
ADA580356

Entities

People

  • Ran Davidi

Organizations

  • Stanford University

Tags

Communities of Interest

  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Algorithms
  • Bioengineering
  • Computations
  • Computer Science
  • Construction
  • Convex Sets
  • Detectors
  • Diagnostic Imaging
  • Mathematical Models
  • Mathematics
  • Medical Personnel
  • Neoplasms
  • Optimization
  • Radiation Oncology
  • Radiotherapy
  • Tomography
  • X-Ray Computed Tomography

Readers

  • Electrochemical Surface Science
  • Oncology
  • Systems Analysis and Design