Quantitative dual-energy CT imaging for radiation therapy treatment planning

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DESCRIPTION (provided by applicant): Quantitative dual-energy CT imaging for radiation therapy treatment planning 6. Project Summary/Abstract Proton-beam therapy (PT) and low-energy (20-60 keV) photon-emitting brachytherapy (LEPBT) are rapidly evolving modalities with high potential for improving radiation therapy clinical outcomes because of their ability to deliver high doses to the target tissue while sparing surrounding normal tissues. Dose delivery from both modalities is sensitive to the atomic composition as well as election density of the irradiated tissues. For LEPBT, current dose-calculation practice ignores tissue inhomogeneity, introducing dose-prediction errors as large as a factor of 2. For PT, current quantitative single-energy computed tomography imaging (QSECT) leads to 3-6 mm range uncertainties that significantly increases exposure of adjacent organs to high doses. Recommended bulk tissue compositions are based upon inadequate data with large and essentially unknown patient-to-patient and intrapatient variability and cannot provide an adequate basis either for clinical treatment planning or assessing dose delivery uncertainty in PT or LEPBT. Conventional QSECT is inadequate for quantitative study of PT and LEPBT radiological tissue properties because tissue composition and electron density vary independently. The goal of this project is to develop and validate a novel quantitative dual-energy CT (QDECT) imaging technology able to accurately image the radiological properties and to demonstrate QDECT utility by assessing the magnitude and clinical significance of tissue inhomogeneities in a small patient sample. To achieve these goals, three specific aims are proposed. In Specific Aim 1, a novel statistical image reconstruction algorithm will be developed for reconstructing 3D cross-section maps derived from dual energy spiral sinograms exported from a clinical multi-slice CT imaging system. Specifically, an alternating minimization regularized, 3D reconstruction engine will be adapted and optimized to the problems of accurate tissue-map imaging for brachytherapy and proton-beam dose planning and a clinical prototype implemented. In Specific Aim 2, QDECT cross-section images reconstructed from experimentally-acquired dual-energy sinograms will be validated against experimental phantom, patient data, and computational benchmarks. Analysis of estimation errors will be used to focus AM reconstruction algorithm optimization efforts above. The developed QDECT process will be used to study the magnitude and variability of proton stopping-power and photon-cross section maps in our small patient population. Specific Aim 3 will study the dosimetric and clinical impact of more accurate patient-specific QDECT cross-section distributions on simulated brachytherapy, electron-beam and proton-beam treatment plans in head and neck, prostate, breast, and lung cancer sites using available treatment-planning systems and Monte Carlo dose-estimation codes.