http://repub.eur.nl/res/aut/7590/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/34922/ 2012-01-01T00:00:00Z Purpose: To develop a model to assess the quality of an IMRT treatment plan using data of prior patients with pancreatic adenocarcinoma. Methods: The dose to an organ at risk (OAR) depends in large part on its orientation and distance to the planning target volume (PTV). A database of 33 previously treated patients with pancreatic cancer was queried to find patients with less favorable PTV-OAR configuration than a new case. The minimal achieved dose among the selected patients should also be achievable for the OAR of the new case. This way the achievable doses to the OARs of 25 randomly selected pancreas cancer patients were predicted. The patients were replanned to verify if the predicted dose could be achieved. The new plans were compared to their original clinical plans. Results: The predicted doses were achieved within 1 and 2 Gy for more than 82% and 94% of the patients, respectively, and were a good approximation of the minimal achievable doses. The improvement after replanning was 1.4 Gy (range 0-4.6 Gy) and 1.7 Gy (range 0-6.3 Gy) for the mean dose to the liver and the kidneys, respectively, without compromising target coverage or increasing radiation dose to the bowel, cord or stomach. Conclusions: The model could accurately predict the achievable doses, leading to a considerable decrease in dose to the OARs and an increase in treatment planning efficiency. http://repub.eur.nl/res/pub/2141/ 2000-01-01T00:00:00Z In this paper we propose a sequential testing procedure to determine the order of differencing in seasonally observed time series processes, which builds upon existing approaches developed for nonseasonal series. We allow for the possible presence of multiple unit roots at both the zero and seasonal frequencies of the data. Multiple seasonal unit roots can be useful in circumstances where one does not wish to take logarithms of the data-set at hand. Multiple unit roots at the seasonal frequencies also appear in commonly applied seasonal adjustment filters such as Census X-11. The testing procedure developed in this paper can therefore be used to obtain some a priori insight into the likely properties of seasonally adjusted time series. In particular it may be used to investigate whether or not the seasonally adjusted series can be expected to be strictly noninvertible at the seasonal frequencies of the data. The proposed testing procedure is shown be asymptotically consistent. The unit root statistics arising at each stage of the testing procedure are shown to have familiar limiting null distributions so that, at least to an approximation, existing critical values may be used. Empirical applications are provided to illustrate the practical usefulness of our approach.