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Title: SU-G-JeP3-09: Tumor Location Prediction Using Natural Respiratory Volume for Respiratory Gated Radiation Therapy (RGRT): System Verification Study

Abstract

Purpose: Respiratory gated radiation therapy (RGRT) gives accurate results when a patient’s breathing is stable and regular. Thus, the patient should be fully aware during respiratory pattern training before undergoing the RGRT treatment. In order to bypass the process of respiratory pattern training, we propose a target location prediction system for RGRT that uses only natural respiratory volume, and confirm its application. Methods: In order to verify the proposed target location prediction system, an in-house phantom set was used. This set involves a chest phantom including target, external markers, and motion generator. Natural respiratory volume signals were generated using the random function in MATLAB code. In the chest phantom, the target takes a linear motion based on the respiratory signal. After a four-dimensional computed tomography (4DCT) scan of the in-house phantom, the motion trajectory was derived as a linear equation. The accuracy of the linear equation was compared with that of the motion algorithm used by the operating motion generator. In addition, we attempted target location prediction using random respiratory volume values. Results: The correspondence rate of the linear equation derived from the 4DCT images with the motion algorithm of the motion generator was 99.41%. In addition, the average errormore » rate of target location prediction was 1.23% for 26 cases. Conclusion: We confirmed the applicability of our proposed target location prediction system for RGRT using natural respiratory volume. If additional clinical studies can be conducted, a more accurate prediction system can be realized without requiring respiratory pattern training.« less

Authors:
; ; ; ; ;  [1]
  1. The catholic university of Korea, Seoul (Korea, Republic of)
Publication Date:
OSTI Identifier:
22649416
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; COMPUTERIZED TOMOGRAPHY; EQUATIONS; FORECASTING; FOUR-DIMENSIONAL CALCULATIONS; PHANTOMS; RADIOTHERAPY; TRAINING

Citation Formats

Kim, M, Jung, J, Yoon, D, Shin, H, Kim, S, and Suh, T. SU-G-JeP3-09: Tumor Location Prediction Using Natural Respiratory Volume for Respiratory Gated Radiation Therapy (RGRT): System Verification Study. United States: N. p., 2016. Web. doi:10.1118/1.4957074.
Kim, M, Jung, J, Yoon, D, Shin, H, Kim, S, & Suh, T. SU-G-JeP3-09: Tumor Location Prediction Using Natural Respiratory Volume for Respiratory Gated Radiation Therapy (RGRT): System Verification Study. United States. doi:10.1118/1.4957074.
Kim, M, Jung, J, Yoon, D, Shin, H, Kim, S, and Suh, T. Wed . "SU-G-JeP3-09: Tumor Location Prediction Using Natural Respiratory Volume for Respiratory Gated Radiation Therapy (RGRT): System Verification Study". United States. doi:10.1118/1.4957074.
@article{osti_22649416,
title = {SU-G-JeP3-09: Tumor Location Prediction Using Natural Respiratory Volume for Respiratory Gated Radiation Therapy (RGRT): System Verification Study},
author = {Kim, M and Jung, J and Yoon, D and Shin, H and Kim, S and Suh, T},
abstractNote = {Purpose: Respiratory gated radiation therapy (RGRT) gives accurate results when a patient’s breathing is stable and regular. Thus, the patient should be fully aware during respiratory pattern training before undergoing the RGRT treatment. In order to bypass the process of respiratory pattern training, we propose a target location prediction system for RGRT that uses only natural respiratory volume, and confirm its application. Methods: In order to verify the proposed target location prediction system, an in-house phantom set was used. This set involves a chest phantom including target, external markers, and motion generator. Natural respiratory volume signals were generated using the random function in MATLAB code. In the chest phantom, the target takes a linear motion based on the respiratory signal. After a four-dimensional computed tomography (4DCT) scan of the in-house phantom, the motion trajectory was derived as a linear equation. The accuracy of the linear equation was compared with that of the motion algorithm used by the operating motion generator. In addition, we attempted target location prediction using random respiratory volume values. Results: The correspondence rate of the linear equation derived from the 4DCT images with the motion algorithm of the motion generator was 99.41%. In addition, the average error rate of target location prediction was 1.23% for 26 cases. Conclusion: We confirmed the applicability of our proposed target location prediction system for RGRT using natural respiratory volume. If additional clinical studies can be conducted, a more accurate prediction system can be realized without requiring respiratory pattern training.},
doi = {10.1118/1.4957074},
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}
}