Automated Closed- and Open-Loop Validation of Knowledge-Based Planning Routines Across Multiple Disease Sites.

Journal: Practical radiation oncology
PMID: 30826481

Abstract

PURPOSE: Knowledge-based planning (KBP) clinical implementation necessitates significant upfront effort, even within a single disease site. The purpose of this study was to demonstrate an efficient method for clinicians to assess the noninferiority of KBP across multiple disease sites and estimate any systematic dosimetric differences after implementation. We sought to establish these endpoints in a plurality of previously treated patients (validation set) with both closed-loop (training set overlapping validation set) and open-loop (independent training set) KBP routines.

Authors

  • Robert Kaderka
    Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California.
  • Robert C Mundt
    Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California.
  • Nan Li
    School of Basic Medical Sciences, Jiamusi University No. 258, Xuefu Street, Xiangyang District, Jiamusi 154007, Heilongjiang, China.
  • Benjamin Ziemer
    Department of Radiation Oncology, University of California San Francisco, San Francisco, California.
  • Victoria N Bry
    Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California.
  • Mariel Cornell
    Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California.
  • Kevin L Moore
    Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California 92093.

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