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Detecting And Evaluating Therapy Induced Changes In Radiomics Features Measured From Non-Small Cell Lung Cancer To Predict Patient Outcomes, Xenia J. Fave
Dissertations & Theses (Open Access)
The purpose of this study was to investigate whether radiomics features measured from weekly 4-dimensional computed tomography (4DCT) images of non-small cell lung cancers (NSCLC) change during treatment and if those changes are prognostic for patient outcomes or dependent on treatment modality. Radiomics features are quantitative metrics designed to evaluate tumor heterogeneity from routine medical imaging. Features that are prognostic for patient outcome could be used to monitor tumor response and identify high-risk patients for adaptive treatment. This would be especially valuable for NSCLC due to the high prevalence and mortality of this disease.
A novel process was designed to …
Prediction Of Laser Ablation In Brain: Sensitivity, Calibration, And Validation, Samuel J. Fahrenholtz
Prediction Of Laser Ablation In Brain: Sensitivity, Calibration, And Validation, Samuel J. Fahrenholtz
Dissertations & Theses (Open Access)
The surgical planning of MR-guided laser induced thermal therapy (MRgLITT) stands to benefit from predictive computational modeling. The dearth of physical model parameter data leads to modeling uncertainty. This work implements a well-accepted framework with three key steps for model-building: model-parameter sensitivity analysis, model calibration, and model validation.
The sensitivity study is via generalized polynomial chaos (gPC) paired with a transient finite element (FEM) model. Uniform probability distribution functions (PDFs) capture the plausible range of values suggested by the literature for five model parameters. The five PDFs are input separately into the FEM model to gain a probabilistic sensitivity response …
Forecasting Longitudinal Changes In Oropharyngeal Tumor Volume, Position, And Morphology During Image-Guided Radiation Therapy, Adam D. Yock
Forecasting Longitudinal Changes In Oropharyngeal Tumor Volume, Position, And Morphology During Image-Guided Radiation Therapy, Adam D. Yock
Dissertations & Theses (Open Access)
The purpose of this work was to generate, evaluate, and compare models that predict longitudinal changes in oropharyngeal tumor volume, position, and morphology during radiation therapy.
One volume, one position, and two morphology (size, shape, and position) feature vectors were used to describe 35 oropharyngeal gross tumor volumes (GTVs) during radiation therapy. The two morphology feature vectors comprised the coordinates of the GTV centroids and one of two shape descriptors. One shape descriptor was based on radial distances between the GTV centroid and 614 surface landmarks. The other was based on a spherical harmonic decomposition of these distances. For a …