Seán Walsh1, Wil van der Putten. 1. School of Physics, National University of Ireland Galway, Connacht, Ireland. Walshsharp@gmail.com
Abstract
PURPOSE: Biological models offer the ability to predict clinical outcomes. The authors describe a model to predict the clinical response of intermediate-risk prostate cancer to external beam radiotherapy for a variety of fractionation regimes. METHODS: A fully heterogeneous population averaged tumor control probability model was fit to clinical outcome data for hyper, standard, and hypofractionated treatments. The tumor control probability model was then employed to predict the clinical outcome of extreme hypofractionation regimes, as utilized in stereotactic body radiotherapy. RESULTS: The tumor control probability model achieves an excellent level of fit, R(2) value of 0.93 and a root mean squared error of 1.31%, to the clinical outcome data for hyper, standard, and hypofractionated treatments using realistic values for biological input parameters. Residuals ≤1.0% are produced by the tumor control probability model when compared to clinical outcome data for stereotactic body radiotherapy. CONCLUSIONS: The authors conclude that this tumor control probability model, used with the optimized radiosensitivity values obtained from the fit, is an appropriate mechanistic model for the analysis and evaluation of external beam RT plans with regard to tumor control for these clinical conditions.
PURPOSE: Biological models offer the ability to predict clinical outcomes. The authors describe a model to predict the clinical response of intermediate-risk prostate cancer to external beam radiotherapy for a variety of fractionation regimes. METHODS: A fully heterogeneous population averaged tumor control probability model was fit to clinical outcome data for hyper, standard, and hypofractionated treatments. The tumor control probability model was then employed to predict the clinical outcome of extreme hypofractionation regimes, as utilized in stereotactic body radiotherapy. RESULTS: The tumor control probability model achieves an excellent level of fit, R(2) value of 0.93 and a root mean squared error of 1.31%, to the clinical outcome data for hyper, standard, and hypofractionated treatments using realistic values for biological input parameters. Residuals ≤1.0% are produced by the tumor control probability model when compared to clinical outcome data for stereotactic body radiotherapy. CONCLUSIONS: The authors conclude that this tumor control probability model, used with the optimized radiosensitivity values obtained from the fit, is an appropriate mechanistic model for the analysis and evaluation of external beam RT plans with regard to tumor control for these clinical conditions.
Authors: Aaron N Hata; Harald Paganetti; Clemens Grassberger; David McClatchy; Changran Geng; Sophia C Kamran; Florian Fintelmann; Yosef E Maruvka; Zofia Piotrowska; Henning Willers; Lecia V Sequist Journal: Cancer Res Date: 2019-05-21 Impact factor: 12.701
Authors: Seán Walsh; Erik Roelofs; Peter Kuess; Yvonka van Wijk; Ben Vanneste; Andre Dekker; Philippe Lambin; Bleddyn Jones; Dietmar Georg; Frank Verhaegen Journal: Cancers (Basel) Date: 2018-02-18 Impact factor: 6.639