Dosimetric characteristics of a new polymer gel and their dependence on post-preparation and post-irradiation time: Effect on X-ray beam profile measurements

The aim of this study is to dosimetrically characterize a new MRI based polymer gel system and to evaluate its usefulness in clinical practice just in terms of beam profile measurements.Normoxic N-vinylpyrrolidone based polymer gel (VIPET) phantoms were produced and used in order to perform three main sets of experiments: a) dose–response evaluation and reproducibility experiments, b) experiments for the evaluation of sensitivity of dose characteristics on ‘gel manufacture – irradiation’ time interval and c) experiments for the evaluation of sensitivity of dose characteristics on ‘irradiation – MRscanning’ time interval. It has been shown that this gel system can be used in a wide dose-range of 0–60 Gy. It exhibits a linear dose–response in the dose-range of 2–35 Gy. Following the proposed manufacturing method the dose–response characteristics are reproducible. Moreover, it seems that the optimum ‘gel manufacturing – irradiation’ time interval is 1 day. However, a ‘gel manufacturing – irradiation’ time interval up to ～1 week can be safely used. The optimum ‘irradiation – MRscanning’ time interval in terms of dose–response sensitivity and dose resolution can be reliably ranged from 1 day to 3 weeks. Finally, X-ray beam profile gel-measurements were performed and found to be in satisfying agreement with corresponding small sensitive volume ion chamber measurements. VIPET gel dosimeters preserved the spatial integrity of the dose distribution during a time period of 50 days post-irradiation. The studied gel system can be safely used in clinical practice within the practical limitations found and described in this work.     

Accurate Computation of Survival Statistics in Genome-Wide Studies

A key challenge in genomics is to identify genetic variants that distinguish patients with different survival time following diagnosis or treatment. While the log-rank test is widely used for this purpose, nearly all implementations of the log-rank test rely on an asymptotic approximation that is not appropriate in many genomics applications. This is because: the two populations determined by a genetic variant may have very different sizes; and the evaluation of many possible variants demands highly accurate computation of very small p-values. We demonstrate this problem for cancer genomics data where the standard log-rank test leads to many false positive associations between somatic mutations and survival time. We develop and analyze a novel algorithm, Exact Log-rank Test (ExaLT), that accurately computes the p-value of the log-rank statistic under an exact distribution that is appropriate for any size populations. We demonstrate the advantages of ExaLT on data from published cancer genomics studies, finding significant differences from the reported p-values. We analyze somatic mutations in six cancer types from The Cancer Genome Atlas (TCGA), finding mutations with known association to survival as well as several novel associations. In contrast, standard implementations of the log-rank test report dozens-hundreds of likely false positive associations as more significant than these known associations.