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Title: SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers

Abstract

Purpose: We compared conventionally optimized intensity-modulated proton therapy (IMPT) treatment plans against the worst-case robustly optimized treatment plans for lung cancer. The comparison of the two IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient set-up, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. Methods: For each of the 9 lung cancer cases two treatment plans were created accounting for treatment uncertainties in two different ways: the first used the conventional Method: delivery of prescribed dose to the planning target volume (PTV) that is geometrically expanded from the internal target volume (ITV). The second employed the worst-case robust optimization scheme that addressed set-up and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of the changes in patient anatomy due to respiratory motion was investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the two groups were compared using two-sided paired t-tests. Results: Without respiratory motion considered, we affirmed that worst-case robust optimization is superior tomore » PTV-based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, robust optimization still leads to more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality [D95% ITV: 96.6% versus 96.1% (p=0.26), D5% - D95% ITV: 10.0% versus 12.3% (p=0.082), D1% spinal cord: 31.8% versus 36.5% (p =0.035)]. Conclusion: Worst-case robust optimization led to superior solutions for lung IMPT. Despite of the fact that robust optimization did not explicitly account for respiratory motion it produced motion-resistant treatment plans. However, further research is needed to incorporate respiratory motion into IMPT robust optimization.« less

Authors:
; ;  [1]; ;  [2];  [3];  [4];  [5]; ;  [6];  [7];  [8]; ;  [9]
  1. Mayo Clinic Arizona, Phoenix, AZ (United States)
  2. MD Anderson Cancer Center, Houston, TX (United States)
  3. Scottsdale, GA (United States)
  4. M.D. Anderson Cancer Center, Houston, TX (United States)
  5. Varian Medical Systems, Houston, TX (United States)
  6. Mayo Clinic Arizona, Phoenix, AA (United States)
  7. Mayo Clinic Arizona, Phoenix (United States)
  8. Scripps Proton Therapy Center, San Diego, CA (United States)
  9. UT MD Anderson Cancer Center, Houston, TX (United States)
Publication Date:
OSTI Identifier:
22369601
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 41; Journal Issue: 6; Other Information: (c) 2014 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:
60 APPLIED LIFE SCIENCES; ANATOMY; LUNGS; METRICS; NEOPLASMS; OPTIMIZATION; PATIENTS; PERTURBATION THEORY; RADIATION DOSE DISTRIBUTIONS; RADIATION DOSES; SPINAL CORD; THERAPY

Citation Formats

Liu, W, Schild, S, Bues, M, Liao, Z, Sahoo, N, Park, P, Li, H, Li, Y, Li, X, Shen, J, Anand, A, Dong, L, Zhu, X, and Mohan, R. SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers. United States: N. p., 2014. Web. doi:10.1118/1.4888785.
Liu, W, Schild, S, Bues, M, Liao, Z, Sahoo, N, Park, P, Li, H, Li, Y, Li, X, Shen, J, Anand, A, Dong, L, Zhu, X, & Mohan, R. SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers. United States. https://doi.org/10.1118/1.4888785
Liu, W, Schild, S, Bues, M, Liao, Z, Sahoo, N, Park, P, Li, H, Li, Y, Li, X, Shen, J, Anand, A, Dong, L, Zhu, X, and Mohan, R. 2014. "SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers". United States. https://doi.org/10.1118/1.4888785.
@article{osti_22369601,
title = {SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers},
author = {Liu, W and Schild, S and Bues, M and Liao, Z and Sahoo, N and Park, P and Li, H and Li, Y and Li, X and Shen, J and Anand, A and Dong, L and Zhu, X and Mohan, R},
abstractNote = {Purpose: We compared conventionally optimized intensity-modulated proton therapy (IMPT) treatment plans against the worst-case robustly optimized treatment plans for lung cancer. The comparison of the two IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient set-up, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. Methods: For each of the 9 lung cancer cases two treatment plans were created accounting for treatment uncertainties in two different ways: the first used the conventional Method: delivery of prescribed dose to the planning target volume (PTV) that is geometrically expanded from the internal target volume (ITV). The second employed the worst-case robust optimization scheme that addressed set-up and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of the changes in patient anatomy due to respiratory motion was investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the two groups were compared using two-sided paired t-tests. Results: Without respiratory motion considered, we affirmed that worst-case robust optimization is superior to PTV-based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, robust optimization still leads to more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality [D95% ITV: 96.6% versus 96.1% (p=0.26), D5% - D95% ITV: 10.0% versus 12.3% (p=0.082), D1% spinal cord: 31.8% versus 36.5% (p =0.035)]. Conclusion: Worst-case robust optimization led to superior solutions for lung IMPT. Despite of the fact that robust optimization did not explicitly account for respiratory motion it produced motion-resistant treatment plans. However, further research is needed to incorporate respiratory motion into IMPT robust optimization.},
doi = {10.1118/1.4888785},
url = {https://www.osti.gov/biblio/22369601}, journal = {Medical Physics},
issn = {0094-2405},
number = 6,
volume = 41,
place = {United States},
year = {Sun Jun 01 00:00:00 EDT 2014},
month = {Sun Jun 01 00:00:00 EDT 2014}
}