Improved robotic stereotactic body radiation therapy plan quality and planning efficacy for organ-confined prostate cancer utilizing overlap-volume histogram-driven planning methodology

Binbin Wu, Dalong Pang, Siyuan Lei, John Gatti, Michael Tong, Todd McNutt, Thomas Kole, Anatoly Dritschilo, Sean Collins

Research output: Contribution to journalArticlepeer-review

Abstract

Background and purpose This study is to determine if the overlap-volume histogram (OVH)-driven planning methodology can be adapted to robotic SBRT (CyberKnife Robotic Radiosurgery System) to further minimize the bladder and rectal doses achieved in plans manually-created by clinical planners.

Methods and materials A database containing clinically-delivered, robotic SBRT plans (7.25 Gy/fraction in 36.25 Gy) of 425 patients with localized prostate cancer was used as a cohort to establish an organ's distance-to-dose model. The OVH-driven planning methodology was refined by adding the PTV volume factor to counter the target's dose fall-off effect and incorporated into Multiplan to automate SBRT planning. For validation, automated plans (APs) for 12 new patients were generated, and their achieved dose/volume values were compared to the corresponding manually-created, clinically-delivered plans (CPs). A two-sided, Wilcoxon rank-sum test was used for statistical comparison with a significance level of p < 0.05.

Results PTV's V(36.25 Gy) was comparable: 95.6% in CPs comparing to 95.1% in APs (p = 0.2). On average, the refined approach lowered V(18.12 Gy) to the bladder and rectum by 8.2% (p < 0.05) and 6.4% (p = 0.14). A physician confirmed APs were clinically acceptable.

Conclusions The improvements in APs could further reduce toxicities observed in SBRT for organ-confined prostate cancer.

Original languageEnglish (US)
Pages (from-to)221-226
Number of pages6
JournalRadiotherapy and Oncology
Volume112
Issue number2
DOIs
StatePublished - Aug 1 2014

Keywords

  • CyberKnife
  • OVH
  • Prostate
  • SBRT

ASJC Scopus subject areas

  • Hematology
  • Oncology
  • Radiology Nuclear Medicine and imaging

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