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Title: SU-C-BRB-02: Automatic Planning as a Potential Strategy for Dose Escalation for Pancreas SBRT?

Abstract

Purpose: Stereotactic body radiation therapy (SBRT) has been suggested to provide high rates of local control for locally advanced pancreatic cancer. However, the close proximity of highly radiosensitive normal tissues usually causes the labor-intensive planning process, and may impede further escalation of the prescription dose. The present study evaluates the potential of an automatic planning system as a dose escalation strategy. Methods: Ten pancreatic cancer patients treated with SBRT were studied retrospectively. SBRT was delivered over 5 consecutive fractions with 6 ∼ 8Gy/fraction. Two plans were generated by Pinnacle Auto-Planning with the original prescription and escalated prescription, respectively. Escalated prescription adds 1 Gy/fraction to the original prescription. Manually-created planning volumes were excluded in the optimization goals in order to assess the planning efficiency and quality simultaneously. Critical organs with closest proximity were used to determine the plan normalization to ensure the OAR sparing. Dosimetric parameters including D100, and conformity index (CI) were assessed. Results: Auto-plans directly generate acceptable plans for 70% of the cases without necessity of further improvement, and two more iterations at most are necessary for the rest of the cases. For the pancreas SBRT plans with the original prescription, autoplans resulted in favorable target coverage and PTVmore » conformity (D100 = 96.3% ± 1.48%; CI = 0.88 ± 0.06). For the plans with the escalated prescriptions, no significant target under-dosage was observed, and PTV conformity remains reasonable (D100 = 93.3% ± 3.8%, and CI = 0.84 ± 0.05). Conclusion: Automatic planning, without substantial human-intervention process, results in reasonable PTV coverage and PTV conformity on the premise of adequate OAR sparing for the pancreas SBRT plans with escalated prescription. The results highlight the potential of autoplanning as a dose escalation strategy for pancreas SBRT treatment planning. Further investigations with a larger number of patients are necessary. The project is partially supported by Philips Medical Systems.« less

Authors:
; ; ; ; ; ; ;  [1]
  1. University of Nebraska Medical Center, Omaha, NE (United States)
Publication Date:
OSTI Identifier:
22624320
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ANIMAL TISSUES; CRITICAL ORGANS; MANPOWER; NEOPLASMS; OPTIMIZATION; PANCREAS; PATIENTS; PLANNING; RADIATION DOSES; RADIOTHERAPY

Citation Formats

Wang, S, Zheng, D, Ma, R, Lin, C, Zhu, X, Lei, Y, Enke, C, and Zhou, S. SU-C-BRB-02: Automatic Planning as a Potential Strategy for Dose Escalation for Pancreas SBRT?. United States: N. p., 2016. Web. doi:10.1118/1.4955556.
Wang, S, Zheng, D, Ma, R, Lin, C, Zhu, X, Lei, Y, Enke, C, & Zhou, S. SU-C-BRB-02: Automatic Planning as a Potential Strategy for Dose Escalation for Pancreas SBRT?. United States. doi:10.1118/1.4955556.
Wang, S, Zheng, D, Ma, R, Lin, C, Zhu, X, Lei, Y, Enke, C, and Zhou, S. Wed . "SU-C-BRB-02: Automatic Planning as a Potential Strategy for Dose Escalation for Pancreas SBRT?". United States. doi:10.1118/1.4955556.
@article{osti_22624320,
title = {SU-C-BRB-02: Automatic Planning as a Potential Strategy for Dose Escalation for Pancreas SBRT?},
author = {Wang, S and Zheng, D and Ma, R and Lin, C and Zhu, X and Lei, Y and Enke, C and Zhou, S},
abstractNote = {Purpose: Stereotactic body radiation therapy (SBRT) has been suggested to provide high rates of local control for locally advanced pancreatic cancer. However, the close proximity of highly radiosensitive normal tissues usually causes the labor-intensive planning process, and may impede further escalation of the prescription dose. The present study evaluates the potential of an automatic planning system as a dose escalation strategy. Methods: Ten pancreatic cancer patients treated with SBRT were studied retrospectively. SBRT was delivered over 5 consecutive fractions with 6 ∼ 8Gy/fraction. Two plans were generated by Pinnacle Auto-Planning with the original prescription and escalated prescription, respectively. Escalated prescription adds 1 Gy/fraction to the original prescription. Manually-created planning volumes were excluded in the optimization goals in order to assess the planning efficiency and quality simultaneously. Critical organs with closest proximity were used to determine the plan normalization to ensure the OAR sparing. Dosimetric parameters including D100, and conformity index (CI) were assessed. Results: Auto-plans directly generate acceptable plans for 70% of the cases without necessity of further improvement, and two more iterations at most are necessary for the rest of the cases. For the pancreas SBRT plans with the original prescription, autoplans resulted in favorable target coverage and PTV conformity (D100 = 96.3% ± 1.48%; CI = 0.88 ± 0.06). For the plans with the escalated prescriptions, no significant target under-dosage was observed, and PTV conformity remains reasonable (D100 = 93.3% ± 3.8%, and CI = 0.84 ± 0.05). Conclusion: Automatic planning, without substantial human-intervention process, results in reasonable PTV coverage and PTV conformity on the premise of adequate OAR sparing for the pancreas SBRT plans with escalated prescription. The results highlight the potential of autoplanning as a dose escalation strategy for pancreas SBRT treatment planning. Further investigations with a larger number of patients are necessary. The project is partially supported by Philips Medical Systems.},
doi = {10.1118/1.4955556},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}