Keisha C. McCall

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A new approach to the problem of modelling and predicting respiration motion has been implemented. This is a dual-component model, which describes the respiration motion as a non-periodic time series superimposed onto a periodic waveform. A periodic autoregressive moving average algorithm has been used to define a mathematical model of the periodic and(More)
BACKGROUND PET-based texture features have been used to quantify tumor heterogeneity due to their predictive power in treatment outcome. We investigated the sensitivity of texture features to tumor motion by comparing static (3D) and respiratory-gated (4D) PET imaging. METHODS Twenty-six patients (34 lesions) received 3D and 4D [18F]FDG-PET scans before(More)
The purpose of this study is to explain the unplanned longitudinal dose modulations that appear in helical tomotherapy (HT) dose distributions in the presence of irregular patient breathing. This explanation is developed by the use of longitudinal (1D) simulations of mock and surrogate data and tested with a fully 4D HT delivered plan. The 1D simulations(More)
Quantitative imaging of tumours represents the foundation of customized therapies and adaptive patient care. As such, we have investigated the effect of patient positioning errors on the reproducibility of images of biologically heterogeneous tumours generated by a clinical PET/CT system. A commercial multi-slice PET/CT system was used to acquire 2D and 3D(More)
Preclinical xenograft models have contributed to advancing our understanding of the molecular basis of prostate cancer and to the development of targeted therapy. However, traditional preclinical in vivo techniques using caliper measurements and survival analysis evaluate the macroscopic tumor behavior, whereas tissue sampling disrupts the microenvironment(More)
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