Increased organ sparing using shape-based treatment plan optimization for intensity modulated radiation therapy of pancreatic adenocarcinoma

Steven F. Petit, Binbin Wu, Michael Kazhdan, André Dekker, Patricio Simari, Rachit Kumar, Russel Taylor, Joseph M. Herman, Todd McNutt

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: To develop a model to assess the quality of an IMRT treatment plan using data of prior patients with pancreatic adenocarcinoma. Methods: The dose to an organ at risk (OAR) depends in large part on its orientation and distance to the planning target volume (PTV). A database of 33 previously treated patients with pancreatic cancer was queried to find patients with less favorable PTV-OAR configuration than a new case. The minimal achieved dose among the selected patients should also be achievable for the OAR of the new case. This way the achievable doses to the OARs of 25 randomly selected pancreas cancer patients were predicted. The patients were replanned to verify if the predicted dose could be achieved. The new plans were compared to their original clinical plans. Results: The predicted doses were achieved within 1 and 2 Gy for more than 82% and 94% of the patients, respectively, and were a good approximation of the minimal achievable doses. The improvement after replanning was 1.4 Gy (range 0-4.6 Gy) and 1.7 Gy (range 0-6.3 Gy) for the mean dose to the liver and the kidneys, respectively, without compromising target coverage or increasing radiation dose to the bowel, cord or stomach. Conclusions: The model could accurately predict the achievable doses, leading to a considerable decrease in dose to the OARs and an increase in treatment planning efficiency.

Original languageEnglish (US)
Pages (from-to)38-44
Number of pages7
JournalRadiotherapy and Oncology
Volume102
Issue number1
DOIs
StatePublished - Jan 2012

Keywords

  • Intensity modulated radiotherapy (IMRT)
  • Overlap volume histogram (OVH)
  • Pancreas
  • Pancreatic cancer
  • Quality control
  • Treatment plan prediction and optimization

ASJC Scopus subject areas

  • Hematology
  • Oncology
  • Radiology Nuclear Medicine and imaging

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