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Radiation therapy today, on account of improvements in treatment procedures over the last 60 years, allows precise treatment of static tumors inside the human body. However, irradiation of moving tumors is still a challenging task as moving tumors often leave the treatment beam and the radiation dose delivered to the tumor reduces simultaneously increasing that on healthy tissue. This research work aims to push the frontiers of radiation therapy in order to enable precise treatment of moving tumors with focus on research and development of a unique real-time system enabling active motion compensation through robotic means to compensate tumor motion. During treatment, patients lie on a treatment couch which is normally used for static position corrections of patient set-up errors prior to radiation treatment. The treatment couch used, called HexaPOD, is a parallel manipulator with six degrees of freedom which can precisely position heavy loads inside a small region. Despite the HexaPOD not initially built with dynamics in mind, it is used in this work for sustained motion compensation by moving patients such that tumors stay precisely located at the center of the treatment beam during the complete course of treatment. In order to realize real-time tumor motion compensation by means of the HexaPOD, several challanges need to be addressed. Real-time aspects are covered by the adoption of a hard real-time operation system in combination with measurement and estimation of latencies of all physical quantities in the compensation system such as tumor or breathing position measurements. Accurate timing information is respected consistently in the whole system and all software-induced latencies are adaptively compensated for. This requires knowledge of future tumor positions from predictors. Several predictors for breathing and tumor motion predictions are proposed and evaluated in terms of a variety of different performance metrics. Extensions to prediction algorithms are introduced fusing both breathing and tumor position information to allow for predictions without the need of an explicit correlation model. Predictions determine the future motion path of the HexaPOD in order to compensate for tumor motion. Several control schemes are developed to enable reference tracking for the HexaPOD. Based on linear and non-linear dynamic modelling of the HexaPOD with system identification methods, a first controller is derived in the form of a model predictive controller. A second controller is proposed based on an assumption of the working principle of the HexaPOD's internal controller. Finally, a third controller is derived as combination of the first and second one. For each of these controllers, comparative results with real hardware experiments and humans in the loop as well as choices of free parameters are presented and discussed. Apart from precise tracking, emphasis is placed on patient comfort which is of crucial importance for acceptance of the system. It is demonstrated that smooth trajectories can be realized by the controllers to guarantee that patients feel comfortable while their tumor motion is compensated at sub-millimeter accuracies. Overall errors of the system are analyzed by relating them to tracking and prediction errors. By exploiting the properties of different predictors, it is shown that the startup time until tracking is reached can be reduced to only a few seconds, even in the case of an initially at-rest HexaPOD and with no initial knowledge of tumor motion. This makes the system especially suitable for the relatively short-fractionated treatment sessions for lung tumors. The tumor motion compensation system has been developed solely based on standard clinical hardware, found in most treatment rooms. With a simple and flexible design, existing treatment can be updated in a cost-efficient way to introduce motion compensation capabilities. Simultaneously, the system does not impose any constraints on state-of-the-art treatment types such as intensity modulated radiotherapy or volumetric modulated arc therapy. Supporting different compensation modes, the system can be applied to any moving tumor whether its motion is predictable (lung tumors) or unpredictable (prostate tumors). By integration of adequate tumor position determination methods, the system can be easily extended to other tumors as well.
Within the EURO-SKI trial, 132 chronic phase CML patients discontinued imatinib treatment. RNA was isolated from peripheral blood in order to analyze the expression of MDR1, ABCG2 and OCT1. ABCG2 was predictive for treatment-free remission in Cox regression analysis. High transcript levels of the ABCG2 efflux transporter (>4.5 parts per thousand) were associated with a twofold higher risk of relapse. Introduction: Tyrosine kinase inhibitors (TKIs) can safely be discontinued in chronic myeloid leukemia (CML) patients with sustained deep molecular response. ABCG2 (breast cancer resistance protein), OCT1 (organic cation transporter 1), and ABCB1 (multidrug resistance protein 1) gene products are known to play a crucial role in acquired pharmacogenetic TKI resistance. Their influence on treatment-free remission (TFR) has not yet been investigated. Materials and Methods: RNA was isolated on the last day of TKI intake from peripheral blood leukocytes of 132 chronic phase CML patients who discontinued TKI treatment within the European Stop Tyrosine Kinase Inhibitor Study trial. Plasmid standards were designed including subgenic inserts of OCT1, ABCG2, and ABCB1 together with GUSB as reference gene. For expression analyses, quantitative real-time polymerase chain reaction was used. Multiple Cox regression analysis was performed. In addition, gene expression cutoffs for patient risk stratification were investigated. Results: The TFR rate of 132 patients, 12 months after TKI discontinuation, was 54% (95% confidence interval [CI], 46%-62%). ABCG2 expression (parts per thousand) was retained as the only significant variable (P=.02; hazard ratio, 1.04; 95% CI, 1.01-1.07) in multiple Cox regression analysis. Only for the ABCG2 efflux transporter, a significant cutoff was found (P=.04). Patients with an ABCG2/GUSB transcript level >4.5 parts per thousand (n=93) showed a 12-month TFR rate of 47% (95% CI, 37%-57%), whereas patients with low ABCG2 expression (<= 4.5 parts per thousand; n=39) had a 12-month TFR rate of 72% (95% CI, 55%-82%). Conclusion: In this study, we investigated the effect of pharmacogenetics in the context of a CML treatment discontinuation trial. The transcript levels of the efflux transporter ABCG2 predicted TFR after TKI discontinuation. (C) 2018 The Authors. Published by Elsevier Inc.