skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Application of a spring-dashpot system to clinical lung tumor motion data

Abstract

Purpose: The treatment efficacy of radiation therapy for lung tumors can be increased by compensating for breath-induced tumor motion. In this study, we quantitatively examine a mathematical model of pseudomechanical linkages between an external surrogate signal and lung tumor motion. Methods: A spring-dashpot system based on the Voigt model was developed to model the correlation between abdominal respiratory motion and tumor motion during lung radiotherapy. The model was applied to clinical data obtained from 52 treatments ('beams') from 10 patients, treated on the Mitsubishi Real-Time Radiation Therapy system, Sapporo, Japan. In Stage 1, model parameters were optimized for individual patients and beams to determine reference values and to investigate how well the model can describe the data. In Stage 2, for each patient the optimal parameters determined for a single beam were applied to data from other beams to investigate whether a beam-specific set of model parameters is sufficient to model tumor motion over a course of treatment. Results: In Stage 1, the baseline root mean square (RMS) residual error for all individually optimized beam data was 0.90 {+-} 0.40 mm (mean {+-} 1 standard deviation). In Stage 2, patient-specific model parameters based on a single beam were found tomore » model the tumor position closely, even for irregular beam data, with a mean increase with respect to Stage 1 values in RMS error of 0.37 mm. On average, the obtained model output for the tumor position was 95% of the time within an absolute bound of 2.0 and 2.6 mm in Stages 1 and 2, respectively. The model was capable of dealing with baseline, amplitude and frequency variations of the input data, as well as phase shifts between the input abdominal and output tumor signals. Conclusions: These results indicate that it may be feasible to collect patient-specific model parameters during or prior to the first treatment, and then retain these for the rest of the treatment period. The model has potential for clinical application during radiotherapy treatment of lung tumors.« less

Authors:
;  [1];  [2];  [3];  [4]
  1. Department of Mathematics and Statistics, University of Canterbury, Private Bag 4800, Christchurch 8140 (New Zealand)
  2. Department of Physics and Astronomy, University of Canterbury, Private Bag 4800, Christchurch 8140 (New Zealand)
  3. Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States)
  4. Department of Physics and Astronomy, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand and Department of Radiation Oncology, University of Washington Medical Center, Box 356043, Seattle, Washington 98195-6043 (United States)
Publication Date:
OSTI Identifier:
22130517
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 40; Journal Issue: 2; Other Information: (c) 2013 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; 60 APPLIED LIFE SCIENCES; DIFFERENTIAL EQUATIONS; LUNGS; PATIENTS; PHASE SHIFT; RADIOTHERAPY; RESPIRATION

Citation Formats

Ackerley, E. J., Wilson, P. L., Cavan, A. E., Department of Medical Physics and Bioengineering, Christchurch Hospital, Private Bag 4710, Christchurch, Berbeco, R. I., and Meyer, J. Application of a spring-dashpot system to clinical lung tumor motion data. United States: N. p., 2013. Web. doi:10.1118/1.4788643.
Ackerley, E. J., Wilson, P. L., Cavan, A. E., Department of Medical Physics and Bioengineering, Christchurch Hospital, Private Bag 4710, Christchurch, Berbeco, R. I., & Meyer, J. Application of a spring-dashpot system to clinical lung tumor motion data. United States. https://doi.org/10.1118/1.4788643
Ackerley, E. J., Wilson, P. L., Cavan, A. E., Department of Medical Physics and Bioengineering, Christchurch Hospital, Private Bag 4710, Christchurch, Berbeco, R. I., and Meyer, J. 2013. "Application of a spring-dashpot system to clinical lung tumor motion data". United States. https://doi.org/10.1118/1.4788643.
@article{osti_22130517,
title = {Application of a spring-dashpot system to clinical lung tumor motion data},
author = {Ackerley, E. J. and Wilson, P. L. and Cavan, A. E. and Department of Medical Physics and Bioengineering, Christchurch Hospital, Private Bag 4710, Christchurch and Berbeco, R. I. and Meyer, J.},
abstractNote = {Purpose: The treatment efficacy of radiation therapy for lung tumors can be increased by compensating for breath-induced tumor motion. In this study, we quantitatively examine a mathematical model of pseudomechanical linkages between an external surrogate signal and lung tumor motion. Methods: A spring-dashpot system based on the Voigt model was developed to model the correlation between abdominal respiratory motion and tumor motion during lung radiotherapy. The model was applied to clinical data obtained from 52 treatments ('beams') from 10 patients, treated on the Mitsubishi Real-Time Radiation Therapy system, Sapporo, Japan. In Stage 1, model parameters were optimized for individual patients and beams to determine reference values and to investigate how well the model can describe the data. In Stage 2, for each patient the optimal parameters determined for a single beam were applied to data from other beams to investigate whether a beam-specific set of model parameters is sufficient to model tumor motion over a course of treatment. Results: In Stage 1, the baseline root mean square (RMS) residual error for all individually optimized beam data was 0.90 {+-} 0.40 mm (mean {+-} 1 standard deviation). In Stage 2, patient-specific model parameters based on a single beam were found to model the tumor position closely, even for irregular beam data, with a mean increase with respect to Stage 1 values in RMS error of 0.37 mm. On average, the obtained model output for the tumor position was 95% of the time within an absolute bound of 2.0 and 2.6 mm in Stages 1 and 2, respectively. The model was capable of dealing with baseline, amplitude and frequency variations of the input data, as well as phase shifts between the input abdominal and output tumor signals. Conclusions: These results indicate that it may be feasible to collect patient-specific model parameters during or prior to the first treatment, and then retain these for the rest of the treatment period. The model has potential for clinical application during radiotherapy treatment of lung tumors.},
doi = {10.1118/1.4788643},
url = {https://www.osti.gov/biblio/22130517}, journal = {Medical Physics},
issn = {0094-2405},
number = 2,
volume = 40,
place = {United States},
year = {Fri Feb 15 00:00:00 EST 2013},
month = {Fri Feb 15 00:00:00 EST 2013}
}