SU‐GG‐T‐417

Interpretation of Dosimetric Results in Terms of Expected Treatment Outcome When Optimizing Treatment Plans Using Different Methods of Regularizing Dose Inhomogeneity

G. Komisopoulos, P. Mavroidis, Nikos Papanikolaou, B. Lind

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Abstract

Purpose: Regularization techniques for determining the optimal dose distribution have been proposed because the dose distributions produced by different IMRT treatment planning optimization algorithms are highly non‐uniform in the target volume. In the present work, an analysis is made about the relation of the DVH gradient and the dose to the PTV and normal tissues. Method and Materials: In this study, two head & neck and prostate cancer cases treated with IMRT were employed. Three different dose distributions were obtained by using a dose‐based optimization technique, an EUD‐based optimization without regularization of non‐uniformity and an EUD‐based optimization using a variational regularization technique. The clinical effectiveness of the three dose distributions was investigated by using the complication‐free tumor control probability, P+ and the biologically effective uniform dose. Results: In the head & neck case, for the dose‐based optimization, the P+ value is 32.9%, the total control probability PB is 79.6% and the total complication probability PI is 49.0%. For the EUD‐based no‐reg optimization, the P+ value is 56.4%, the PB value is 71.9% and the PI value is 15.5%. For the EUD‐based reg optimization, the P+ value is 67.3%, the PB value is 87.4% and the PI value is 20.1%. In the prostate case, for the dose‐based optimization, the P+ value is 94.8%, the PB value is 97.8% and the PI value is 3.0%. For the EUD‐based no‐reg optimization, the P+ value is 86.0%, the PB value is 97.3% and the PI value is 11.3%. For the EUD‐based reg optimization, the P+ value is 95.3%, the PB value is 98.4% and the PI value is 3.1%. Conclusion: The radiobiological comparison shows that the EUD‐based optimization with regularization gives better results than the EUD‐based optimization without regularization and dose‐based optimization in both clinical cases, which indicates better clinical effectiveness.

Original languageEnglish (US)
Pages (from-to)2820
Number of pages1
JournalMedical Physics
Volume35
Issue number6
DOIs
StatePublished - 2008

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Head
Head and Neck Neoplasms
Prostate
Prostatic Neoplasms
Neck
Neoplasms

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Cite this

@article{0a45bc7e50cd49d69f17f98bbd7f8eef,
title = "SU‐GG‐T‐417: Interpretation of Dosimetric Results in Terms of Expected Treatment Outcome When Optimizing Treatment Plans Using Different Methods of Regularizing Dose Inhomogeneity",
abstract = "Purpose: Regularization techniques for determining the optimal dose distribution have been proposed because the dose distributions produced by different IMRT treatment planning optimization algorithms are highly non‐uniform in the target volume. In the present work, an analysis is made about the relation of the DVH gradient and the dose to the PTV and normal tissues. Method and Materials: In this study, two head & neck and prostate cancer cases treated with IMRT were employed. Three different dose distributions were obtained by using a dose‐based optimization technique, an EUD‐based optimization without regularization of non‐uniformity and an EUD‐based optimization using a variational regularization technique. The clinical effectiveness of the three dose distributions was investigated by using the complication‐free tumor control probability, P+ and the biologically effective uniform dose. Results: In the head & neck case, for the dose‐based optimization, the P+ value is 32.9{\%}, the total control probability PB is 79.6{\%} and the total complication probability PI is 49.0{\%}. For the EUD‐based no‐reg optimization, the P+ value is 56.4{\%}, the PB value is 71.9{\%} and the PI value is 15.5{\%}. For the EUD‐based reg optimization, the P+ value is 67.3{\%}, the PB value is 87.4{\%} and the PI value is 20.1{\%}. In the prostate case, for the dose‐based optimization, the P+ value is 94.8{\%}, the PB value is 97.8{\%} and the PI value is 3.0{\%}. For the EUD‐based no‐reg optimization, the P+ value is 86.0{\%}, the PB value is 97.3{\%} and the PI value is 11.3{\%}. For the EUD‐based reg optimization, the P+ value is 95.3{\%}, the PB value is 98.4{\%} and the PI value is 3.1{\%}. Conclusion: The radiobiological comparison shows that the EUD‐based optimization with regularization gives better results than the EUD‐based optimization without regularization and dose‐based optimization in both clinical cases, which indicates better clinical effectiveness.",
author = "G. Komisopoulos and P. Mavroidis and Nikos Papanikolaou and B. Lind",
year = "2008",
doi = "10.1118/1.2962165",
language = "English (US)",
volume = "35",
pages = "2820",
journal = "Medical Physics",
issn = "0094-2405",
publisher = "AAPM - American Association of Physicists in Medicine",
number = "6",

}

TY - JOUR

T1 - SU‐GG‐T‐417

T2 - Interpretation of Dosimetric Results in Terms of Expected Treatment Outcome When Optimizing Treatment Plans Using Different Methods of Regularizing Dose Inhomogeneity

AU - Komisopoulos, G.

AU - Mavroidis, P.

AU - Papanikolaou, Nikos

AU - Lind, B.

PY - 2008

Y1 - 2008

N2 - Purpose: Regularization techniques for determining the optimal dose distribution have been proposed because the dose distributions produced by different IMRT treatment planning optimization algorithms are highly non‐uniform in the target volume. In the present work, an analysis is made about the relation of the DVH gradient and the dose to the PTV and normal tissues. Method and Materials: In this study, two head & neck and prostate cancer cases treated with IMRT were employed. Three different dose distributions were obtained by using a dose‐based optimization technique, an EUD‐based optimization without regularization of non‐uniformity and an EUD‐based optimization using a variational regularization technique. The clinical effectiveness of the three dose distributions was investigated by using the complication‐free tumor control probability, P+ and the biologically effective uniform dose. Results: In the head & neck case, for the dose‐based optimization, the P+ value is 32.9%, the total control probability PB is 79.6% and the total complication probability PI is 49.0%. For the EUD‐based no‐reg optimization, the P+ value is 56.4%, the PB value is 71.9% and the PI value is 15.5%. For the EUD‐based reg optimization, the P+ value is 67.3%, the PB value is 87.4% and the PI value is 20.1%. In the prostate case, for the dose‐based optimization, the P+ value is 94.8%, the PB value is 97.8% and the PI value is 3.0%. For the EUD‐based no‐reg optimization, the P+ value is 86.0%, the PB value is 97.3% and the PI value is 11.3%. For the EUD‐based reg optimization, the P+ value is 95.3%, the PB value is 98.4% and the PI value is 3.1%. Conclusion: The radiobiological comparison shows that the EUD‐based optimization with regularization gives better results than the EUD‐based optimization without regularization and dose‐based optimization in both clinical cases, which indicates better clinical effectiveness.

AB - Purpose: Regularization techniques for determining the optimal dose distribution have been proposed because the dose distributions produced by different IMRT treatment planning optimization algorithms are highly non‐uniform in the target volume. In the present work, an analysis is made about the relation of the DVH gradient and the dose to the PTV and normal tissues. Method and Materials: In this study, two head & neck and prostate cancer cases treated with IMRT were employed. Three different dose distributions were obtained by using a dose‐based optimization technique, an EUD‐based optimization without regularization of non‐uniformity and an EUD‐based optimization using a variational regularization technique. The clinical effectiveness of the three dose distributions was investigated by using the complication‐free tumor control probability, P+ and the biologically effective uniform dose. Results: In the head & neck case, for the dose‐based optimization, the P+ value is 32.9%, the total control probability PB is 79.6% and the total complication probability PI is 49.0%. For the EUD‐based no‐reg optimization, the P+ value is 56.4%, the PB value is 71.9% and the PI value is 15.5%. For the EUD‐based reg optimization, the P+ value is 67.3%, the PB value is 87.4% and the PI value is 20.1%. In the prostate case, for the dose‐based optimization, the P+ value is 94.8%, the PB value is 97.8% and the PI value is 3.0%. For the EUD‐based no‐reg optimization, the P+ value is 86.0%, the PB value is 97.3% and the PI value is 11.3%. For the EUD‐based reg optimization, the P+ value is 95.3%, the PB value is 98.4% and the PI value is 3.1%. Conclusion: The radiobiological comparison shows that the EUD‐based optimization with regularization gives better results than the EUD‐based optimization without regularization and dose‐based optimization in both clinical cases, which indicates better clinical effectiveness.

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