Characterising and modelling the normal tissue effects associated with prostate cancer radiotherapy

Noorazrul Azmie Bin Yahya

    Research output: ThesisDoctoral Thesis

    301 Downloads (Pure)

    Abstract

    This study characterised and modelled the normal tissue effects, especially urinary symptoms, in patients treated for prostate carcinoma. The associations between symptoms to treatment, clinical and dose factors were investigated with potentially predictive factors highlighted and methods accounting for longitudinal symptom persistence suggested. Potential improvements of predictive modelling in this context through modern statistical learning strategies were investigated. The urinary predictive models available in the literature were assessed independently and externally highlighting issues in model development. Generation of novel features from the dose to the urethra and through dose-surface maps of the bladder were investigated to quantitatively characterise dose-symptom associations.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • The University of Western Australia
    Award date3 Aug 2016
    Publication statusUnpublished - 2016

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    Urethra
    Prostate
    Prostatic Neoplasms
    Urinary Bladder
    Radiotherapy
    Learning
    Carcinoma
    Therapeutics

    Cite this

    @phdthesis{c00814f2efd3491a849f1b8b2649b5b5,
    title = "Characterising and modelling the normal tissue effects associated with prostate cancer radiotherapy",
    abstract = "This study characterised and modelled the normal tissue effects, especially urinary symptoms, in patients treated for prostate carcinoma. The associations between symptoms to treatment, clinical and dose factors were investigated with potentially predictive factors highlighted and methods accounting for longitudinal symptom persistence suggested. Potential improvements of predictive modelling in this context through modern statistical learning strategies were investigated. The urinary predictive models available in the literature were assessed independently and externally highlighting issues in model development. Generation of novel features from the dose to the urethra and through dose-surface maps of the bladder were investigated to quantitatively characterise dose-symptom associations.",
    keywords = "Radiotherapy, Prostate cancer, Predictive models, Urinary toxicity, Dose-surface maps, Dose-surface histograms, Normal tissue complications, External validation",
    author = "Yahya, {Noorazrul Azmie Bin}",
    year = "2016",
    language = "English",
    school = "The University of Western Australia",

    }

    Yahya, NAB 2016, 'Characterising and modelling the normal tissue effects associated with prostate cancer radiotherapy', Doctor of Philosophy, The University of Western Australia.

    Characterising and modelling the normal tissue effects associated with prostate cancer radiotherapy. / Yahya, Noorazrul Azmie Bin.

    2016.

    Research output: ThesisDoctoral Thesis

    TY - THES

    T1 - Characterising and modelling the normal tissue effects associated with prostate cancer radiotherapy

    AU - Yahya, Noorazrul Azmie Bin

    PY - 2016

    Y1 - 2016

    N2 - This study characterised and modelled the normal tissue effects, especially urinary symptoms, in patients treated for prostate carcinoma. The associations between symptoms to treatment, clinical and dose factors were investigated with potentially predictive factors highlighted and methods accounting for longitudinal symptom persistence suggested. Potential improvements of predictive modelling in this context through modern statistical learning strategies were investigated. The urinary predictive models available in the literature were assessed independently and externally highlighting issues in model development. Generation of novel features from the dose to the urethra and through dose-surface maps of the bladder were investigated to quantitatively characterise dose-symptom associations.

    AB - This study characterised and modelled the normal tissue effects, especially urinary symptoms, in patients treated for prostate carcinoma. The associations between symptoms to treatment, clinical and dose factors were investigated with potentially predictive factors highlighted and methods accounting for longitudinal symptom persistence suggested. Potential improvements of predictive modelling in this context through modern statistical learning strategies were investigated. The urinary predictive models available in the literature were assessed independently and externally highlighting issues in model development. Generation of novel features from the dose to the urethra and through dose-surface maps of the bladder were investigated to quantitatively characterise dose-symptom associations.

    KW - Radiotherapy

    KW - Prostate cancer

    KW - Predictive models

    KW - Urinary toxicity

    KW - Dose-surface maps

    KW - Dose-surface histograms

    KW - Normal tissue complications

    KW - External validation

    M3 - Doctoral Thesis

    ER -