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• W2913448414 abstract "Intensity Modulated Radiation Therapy (IMRT) is a complex form of radiation delivery for the treatment of malignant tumours and other diseases. In IMRT treatment planning, quantitative assessment is crucial to measure and improve the plan quality and treatment delivery. The search for simple and universal quantitative metrics to assess IMRT treatment plan quality has been identified as important but as yet not entirely successful. The aim of this thesis was to assess the IMRT treatment plan quality by establishing quantitative metrics for planning conformity and complexity. The metrics proposed in this work were simple, reproducible and universally applicable to all IMRT techniques, which included step-and-shoot IMRT (SSIMRT), volumetric modulated arc therapy (VMAT) and helical tomotherapy (HT).Two metrics, conformity index (CI) and conformation number (CN) were adopted to quantify the plan conformity. The data used for CI and CN calculations were easily retrieved from dose volume histogram (DVH). By reporting both of these metrics, comprehensive information on target coverage and irradiation of normal tissues could be provided. For the quantification of planning complexity, a new and novel spatial complexity matrix (SCM) was introduced to measure the average dose gradient of a dose profile. In addition, the spatial frequency ratio (SFR) was established to explore the proportion of rapidly varying dose with distance in a treatment plan by using one-dimensional power spectral density (1D PSD).Virtual phantoms were developed for the initial quantitative assessment, in order to form a basis for treatment plan inter-comparisons amongst the different IMRT techniques. A series of multi organs at risk (OARs) phantoms was developed to simulate the planning target volume (PTV) and OARs for different configurations. A virtual prostate phantom was also designed to include a unique shape of PTV and the OAR in close proximity to PTV, in order to mimic clinical prostate case. Quantitative assessments were undertaken on all the IMRT plans generated using the virtual phantoms. The results of these phantom studies have shown for the first time, the feasibility of the developed quantitative metrics for assessing plan quality. Following the successful application of SCM and SFR on the phantom plans, verification work was undertaken to demonstrate the clinical relevance of these self-developed complexity metrics. A retrospective study was carried out to assess the complexity of plans for the treatment of prostate and head and neck tumours. The information contained in DICOM-RT objects were utilised to acquire dose data from the corresponding dose plane. A qualitative survey on plan complexity was also conducted amongst treatment planners, to demonstrate the correlation between the qualitative and quantitative results. These preliminary studies demonstrated the successful application of the self-developed complexity metrics on clinical IMRT treatment plans. In conclusion, the work in this thesis has demonstrated the successful establishment of quantitative metrics for assessing plan conformity and complexity of different IMRT techniques. These metrics were considered as universal tools for the inter-comparison of plan quality for different IMRT techniques and were successfully applied and translated from phantom studies to the clinical setting. Whilst the judgment and experience of the treatment planner undoubtedly remains paramount for making a final decision on the best plan in the interest of the patient, it is expected that the use of quantitative metrics will provide an effective means of benchmarking performance, minimising treatment plan variability and enhancing the quality of IMRT treatment planning." @default.
• W2913448414 created "2019-02-21" @default.
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• W2913448414 date "2018-07-12" @default.
• W2913448414 modified "2023-09-27" @default.
• W2913448414 title "Quantitative metrics for assessing IMRT plan quality : comparing planning conformity and complexity" @default.
• W2913448414 hasPublicationYear "2018" @default.
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