Using percolation networks to incorporate spatial-dose information for assessment of complication probability in radiotherapy

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    Abstract

    This study investigates an extension of recent cluster based methods of assessing the probability of complication in normal organs following radiotherapy treatment which delivers a spatially non-uniform radiation dose distribution. Current methods of assessing this complication probability are spatially degenerate and do not adequately assess the contiguity of damage done to tissue. Therefore, new measures of assessing complication after radiation exposure have been proposed for parallel and serial type organs. In parallel organs an interaction between cells within a functional subunit is stipulated and complication is regarded as a weighted sum of all clusters in the organ. This allows the assessment to account for all damage to the tissue whilst emphasising the importance of damage that accumulates into large and connected spatial regions addressing a deficiency in the current method of calculating complication probabilities. Several spatially-varying doses were analysed and simulated in silico. The simulations produce complication risk estimates for homogeneous dose distributions that are comparable to empirical results but which deviate with any dose inhomogeneity. The simulations also show that the standard method of dose transformation to an effective uniform dose is not valid in cluster based models.

    LanguageEnglish
    Pages869-880
    Number of pages12
    JournalAustralasian Physical and Engineering Sciences in Medicine
    Volume40
    Issue number4
    DOIs
    StatePublished - 1 Dec 2017

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    Radiotherapy
    Dosimetry
    Tissue
    Cell Communication
    Computer Simulation
    Radiation
    Therapeutics

    Cite this

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    title = "Using percolation networks to incorporate spatial-dose information for assessment of complication probability in radiotherapy",
    abstract = "This study investigates an extension of recent cluster based methods of assessing the probability of complication in normal organs following radiotherapy treatment which delivers a spatially non-uniform radiation dose distribution. Current methods of assessing this complication probability are spatially degenerate and do not adequately assess the contiguity of damage done to tissue. Therefore, new measures of assessing complication after radiation exposure have been proposed for parallel and serial type organs. In parallel organs an interaction between cells within a functional subunit is stipulated and complication is regarded as a weighted sum of all clusters in the organ. This allows the assessment to account for all damage to the tissue whilst emphasising the importance of damage that accumulates into large and connected spatial regions addressing a deficiency in the current method of calculating complication probabilities. Several spatially-varying doses were analysed and simulated in silico. The simulations produce complication risk estimates for homogeneous dose distributions that are comparable to empirical results but which deviate with any dose inhomogeneity. The simulations also show that the standard method of dose transformation to an effective uniform dose is not valid in cluster based models.",
    keywords = "Dose inhomogeneity, Normal tissue complication probability, Oncology, Percolation",
    author = "Nicholas Gale and Michael House and Ebert, {Martin A.}",
    year = "2017",
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    doi = "10.1007/s13246-017-0598-3",
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    AU - Gale,Nicholas

    AU - House,Michael

    AU - Ebert,Martin A.

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    Y1 - 2017/12/1

    N2 - This study investigates an extension of recent cluster based methods of assessing the probability of complication in normal organs following radiotherapy treatment which delivers a spatially non-uniform radiation dose distribution. Current methods of assessing this complication probability are spatially degenerate and do not adequately assess the contiguity of damage done to tissue. Therefore, new measures of assessing complication after radiation exposure have been proposed for parallel and serial type organs. In parallel organs an interaction between cells within a functional subunit is stipulated and complication is regarded as a weighted sum of all clusters in the organ. This allows the assessment to account for all damage to the tissue whilst emphasising the importance of damage that accumulates into large and connected spatial regions addressing a deficiency in the current method of calculating complication probabilities. Several spatially-varying doses were analysed and simulated in silico. The simulations produce complication risk estimates for homogeneous dose distributions that are comparable to empirical results but which deviate with any dose inhomogeneity. The simulations also show that the standard method of dose transformation to an effective uniform dose is not valid in cluster based models.

    AB - This study investigates an extension of recent cluster based methods of assessing the probability of complication in normal organs following radiotherapy treatment which delivers a spatially non-uniform radiation dose distribution. Current methods of assessing this complication probability are spatially degenerate and do not adequately assess the contiguity of damage done to tissue. Therefore, new measures of assessing complication after radiation exposure have been proposed for parallel and serial type organs. In parallel organs an interaction between cells within a functional subunit is stipulated and complication is regarded as a weighted sum of all clusters in the organ. This allows the assessment to account for all damage to the tissue whilst emphasising the importance of damage that accumulates into large and connected spatial regions addressing a deficiency in the current method of calculating complication probabilities. Several spatially-varying doses were analysed and simulated in silico. The simulations produce complication risk estimates for homogeneous dose distributions that are comparable to empirical results but which deviate with any dose inhomogeneity. The simulations also show that the standard method of dose transformation to an effective uniform dose is not valid in cluster based models.

    KW - Dose inhomogeneity

    KW - Normal tissue complication probability

    KW - Oncology

    KW - Percolation

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