The impact of dose algorithms on tumor control probability in intensity-modulated proton therapy for breast cancer

Xiaoying Liang, Julie A. Bradley, Dandan Zheng, Michael Rutenberg, Raymond Mailhot Vega, Nancy Mendenhall, Zuofeng Li

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Purpose: To evaluate the radiobiological impact of PB algorithm versus MC algorithm in intensity-modulated proton therapy (IMPT) plans for breast cancer treatment. Methods: 20 breast cancer patients who received IMPT to the breast/chest wall and regional lymphatics were included in this study. For each patient, 2 IMPT plans were generated: a PB-optimized plan and a MC-optimized plan. The radiobiological and dosimetric impact to the CTV of the dose algorithms was assessed. The Poisson Linear-Quadratic model was used to estimate the tumor control probability (TCP). The influence of the model parameter uncertainties on the TCP was tested against different sets of published model parameters. Results: The PB-optimized plans significantly under-dosed the target as compared to the MC-optimized plans. The median (range) differences in CTV D 95% and CTV Dmean were 1.9 (1.2–3.1) Gy and 1.2 (0.5–1.9) Gy, corresponding to 3.8% (2.4−6.2%) and 2.4% (1.0−3.8%) of the prescription dose. The TCP was lower in the PB-optimized plans than the MC-optimized plans. The median (range) of the TCP differences (ΔTCP) were 4% (2−6%), 3% (2−5%), and 2% (1−3%), respectively, when calculated using 3 different model parameter sets. The ΔTCP correlated with the CTV dose difference, and moderately correlated with the CTV volume. Conclusion: Due to the inaccurate dose modeling, PB-optimized plans under-dose the target and therefore yield a lower TCP compared to MC-optimized plans in breast IMPT. The magnitude of the resulting difference in TCP reached 6% in our study.

Original languageEnglish (US)
Pages (from-to)52-57
Number of pages6
JournalPhysica Medica
Volume61
DOIs
StatePublished - May 1 2019

Fingerprint

Proton Therapy
breast
therapy
tumors
cancer
Breast Neoplasms
dosage
protons
Neoplasms
Breast
Thoracic Wall
chest
Uncertainty
Prescriptions
Linear Models

Keywords

  • Breast cancer
  • Dose calculation algorithms
  • IMPT
  • TCP

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Physics and Astronomy(all)

Cite this

The impact of dose algorithms on tumor control probability in intensity-modulated proton therapy for breast cancer. / Liang, Xiaoying; Bradley, Julie A.; Zheng, Dandan; Rutenberg, Michael; Mailhot Vega, Raymond; Mendenhall, Nancy; Li, Zuofeng.

In: Physica Medica, Vol. 61, 01.05.2019, p. 52-57.

Research output: Contribution to journalArticle

Liang, Xiaoying ; Bradley, Julie A. ; Zheng, Dandan ; Rutenberg, Michael ; Mailhot Vega, Raymond ; Mendenhall, Nancy ; Li, Zuofeng. / The impact of dose algorithms on tumor control probability in intensity-modulated proton therapy for breast cancer. In: Physica Medica. 2019 ; Vol. 61. pp. 52-57.
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abstract = "Purpose: To evaluate the radiobiological impact of PB algorithm versus MC algorithm in intensity-modulated proton therapy (IMPT) plans for breast cancer treatment. Methods: 20 breast cancer patients who received IMPT to the breast/chest wall and regional lymphatics were included in this study. For each patient, 2 IMPT plans were generated: a PB-optimized plan and a MC-optimized plan. The radiobiological and dosimetric impact to the CTV of the dose algorithms was assessed. The Poisson Linear-Quadratic model was used to estimate the tumor control probability (TCP). The influence of the model parameter uncertainties on the TCP was tested against different sets of published model parameters. Results: The PB-optimized plans significantly under-dosed the target as compared to the MC-optimized plans. The median (range) differences in CTV D 95{\%} and CTV Dmean were 1.9 (1.2–3.1) Gy and 1.2 (0.5–1.9) Gy, corresponding to 3.8{\%} (2.4−6.2{\%}) and 2.4{\%} (1.0−3.8{\%}) of the prescription dose. The TCP was lower in the PB-optimized plans than the MC-optimized plans. The median (range) of the TCP differences (ΔTCP) were 4{\%} (2−6{\%}), 3{\%} (2−5{\%}), and 2{\%} (1−3{\%}), respectively, when calculated using 3 different model parameter sets. The ΔTCP correlated with the CTV dose difference, and moderately correlated with the CTV volume. Conclusion: Due to the inaccurate dose modeling, PB-optimized plans under-dose the target and therefore yield a lower TCP compared to MC-optimized plans in breast IMPT. The magnitude of the resulting difference in TCP reached 6{\%} in our study.",
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AB - Purpose: To evaluate the radiobiological impact of PB algorithm versus MC algorithm in intensity-modulated proton therapy (IMPT) plans for breast cancer treatment. Methods: 20 breast cancer patients who received IMPT to the breast/chest wall and regional lymphatics were included in this study. For each patient, 2 IMPT plans were generated: a PB-optimized plan and a MC-optimized plan. The radiobiological and dosimetric impact to the CTV of the dose algorithms was assessed. The Poisson Linear-Quadratic model was used to estimate the tumor control probability (TCP). The influence of the model parameter uncertainties on the TCP was tested against different sets of published model parameters. Results: The PB-optimized plans significantly under-dosed the target as compared to the MC-optimized plans. The median (range) differences in CTV D 95% and CTV Dmean were 1.9 (1.2–3.1) Gy and 1.2 (0.5–1.9) Gy, corresponding to 3.8% (2.4−6.2%) and 2.4% (1.0−3.8%) of the prescription dose. The TCP was lower in the PB-optimized plans than the MC-optimized plans. The median (range) of the TCP differences (ΔTCP) were 4% (2−6%), 3% (2−5%), and 2% (1−3%), respectively, when calculated using 3 different model parameter sets. The ΔTCP correlated with the CTV dose difference, and moderately correlated with the CTV volume. Conclusion: Due to the inaccurate dose modeling, PB-optimized plans under-dose the target and therefore yield a lower TCP compared to MC-optimized plans in breast IMPT. The magnitude of the resulting difference in TCP reached 6% in our study.

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