Research Papers:
A method of respiratory phase optimization for better dose sparing of organs at risks: A validation study in patients with lung cancer
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Abstract
Seong-Hee Kang1,5, Siyong Kim2, Dong-Su Kim1, Tae-Ho Kim1, So-Hyun Park3, Dong-Seok Shin1, Kyeong-Hyeon Kim1, Min-Seok Cho1, YeonSil Kim4 and Tae Suk Suh1
1 Department of Biomedical Engineering and Research Institute of Biomedical Engineering, The Catholic University of Korea, Seoul, South Korea
2 Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA
3 Department of Radiation Oncology, College of Medicine, Yonsei University, Seoul, South Korea
4 Department of Radiation Oncology, The Catholic University of Korea, Seoul, South Korea
5 Department of Radiation Oncology, Seoul National University Hospital, Seoul, South Korea
Correspondence to:
Tae Suk Suh, email:
Siyong Kim, email:
Keywords: respiratory gated radiotherapy; breath-hold; lung cancer; respiratory phase optimization; overlap volume histogram
Received: January 13, 2017 Accepted: November 26, 2017 Published: December 17, 2017
Abstract
Background: To propose an effective and simple cost value function to determine an optimal respiratory phase for lung treatment using either respiratory gating or breath-hold technique.
Results: The optimized phase was obtained at a phase close to end inhalation in 11 out of 15 patients. For the rest of patients, the optimized phase was obtained at a phase close to end exhalation indicating that optimal phase can be patient specific. The mean doses of the Organs-at-risk (OARs) significantly decreased at the optimized phase without compromising the planning target volume (PTV) coverage (about 8% for all 3 OARs considered).
Materials and Methods: Fifteen lung patients were included for the feasibility test of the cost function. For all patients and all phases, delineation of the target volume and selected OARs such as esophagus, heart, and spinal cord was performed, and then cost values were calculated for all phases. After the breathing phases were ranked according to the cost values obtained, the relationship between score and dose distribution was evaluated by comparing dose volume histogram (DVH).
Conclusions: The proposed cost value function can play an important role in choosing an optimal phase with minimal effort, that is, without actual plan optimization at all phases.
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