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Objective. Hybrid indirect tumor tracking strategies combine continuous monitoring of surrogate signals with episodic radiographic imaging of the target to check and update their models during the treatment. This validation process is traditionally performed at predetermined and fixed-rate time intervals. This study investigates a new validation procedure based on the real-time uncertainty associated with the predicted target positions. Approach. An adaptive version of a Bayesian method for indirect tracking is developed to simulate different validation processes within a single framework: no validation, regular validation and uncertainty-based validation. While regular validation involves measuring targets at fixed intervals, uncertainty-based validation takes advantage of a key Bayesian feature, which is the real-time confidence information associated with predictions. The validation processes are applied to ground truth breathing signals consisting of a lung target and two different surrogates (one internal, one external). Their impact on prediction accuracy is evaluated with root-mean-square error (RMSE) and incidence of large errors. The number of validation measurements triggered is also examined. Main results. When using the internal surrogate and compared to regular validation, uncertainty-based validation results in significantly better prediction accuracy while using fewer validation measurements: RMSE and fraction of large errors are reduced on average by 12% and 26% respectively, with 36% fewer validation measurements. With the external surrogate, whose correlation with the target is less stable over time, more validation measurements are automatically triggered, which leads to a substantial reduction of prediction errors: RMSE and fraction of large errors are reduced on average by 17% and 28% respectively compared to regular validation. It is also observed that depending on the initial instant, regular validation can result in worse prediction accuracy compared to no validation. Significance. Uncertainty-based validation has the potential to be more efficient and effective than a validation process performed at prescheduled and fixed-rate time intervals. [ABSTRACT FROM AUTHOR]

The accuracy of radiotherapy dose calculation relies crucially on patient composition data. The computed tomography (CT) calibration methods based on the stoichiometric calibration of Schneider et al (1996 Phys. Med. Biol.41 111–24) are the most reliable to determine electron density (ED) with commercial single energy CT scanners. Along with the recent developments in dual energy CT (DECT) commercial scanners, several methods were published to determine ED and the effective atomic number (EAN) for polyenergetic beams without the need for CT calibration curves. This paper intends to show that with a rigorous definition of the EAN, the stoichiometric calibration method can be successfully adapted to DECT with significant accuracy improvements with respect to the literature without the need for spectrum measurements or empirical beam hardening corrections. Using a theoretical framework of ICRP human tissue compositions and the XCOM photon cross sections database, the revised stoichiometric calibration method yields Hounsfield unit (HU) predictions within less than ±1.3 HU of the theoretical HU calculated from XCOM data averaged over the spectra used (e.g., 80 kVp, 100 kVp, 140 kVp and 140/Sn kVp). A fit of mean excitation energy (I-value) data as a function of EAN is provided in order to determine the ion stopping power of human tissues from ED–EAN measurements. Analysis of the calibration phantom measurements with the Siemens SOMATOM Definition Flash dual source CT scanner shows that the present formalism yields mean absolute errors of (0.3 ± 0.4)% and (1.6 ± 2.0)% on ED and EAN, respectively. For ion therapy, the mean absolute errors for calibrated I-values and proton stopping powers (216 MeV) are (4.1 ± 2.7)% and (0.5 ± 0.4)%, respectively. In all clinical situations studied, the uncertainties in ion ranges in water for therapeutic energies are found to be less than 1.3 mm, 0.7 mm and 0.5 mm for protons, helium and carbon ions respectively, using a generic reconstruction algorithm (filtered back projection). With a more advanced method (sinogram affirmed iterative technique), the values become 1.0 mm, 0.5 mm and 0.4 mm for protons, helium and carbon ions, respectively. These results allow one to conclude that the present adaptation of the stoichiometric calibration yields a highly accurate method for characterizing tissue with DECT for ion beam therapy and potentially for photon beam therapy. [ABSTRACT FROM AUTHOR]

The aim of radiation dosimetry is to evaluate, under specific conditions, absorbed dose in a medium of interest using a detection device. In comparison to what is meant to be evaluated, the distinctive composition of the detector causes particle fluence perturbation and shifted absorbed-dose response, both effects depending on beam quality. For electron and megavoltage photon beams, Spencer-Attix cavity theory further adapted by Nahum remains the accepted standard method used to convert absorbed dose in a wall-less detector to absorbed dose in the medium of interest. For several decades, the approach has been widely used in protocols to generate data for ionization chamber dosimetry. As a considerable effort was made towards accurate Monte Carlo methods, computation techniques are nowadays available to determine absorbed dose accurately in complex geometries, including radiation detectors. In the development of nonstandard beam protocols, direct Monte Carlo dose calculations using realistic models are being suggested and used to generate data for ionization chamber dosimetry. This indicates that for a general dosimetric context, including nonstandard beams, a more general cavity theory in agreement with what is currently being done could be adopted. Not only this could be of interest in the dosimetry standards community, but also for educational purposes. This paper re-examines Spencer-Attix theory from first principles, using a new general cavity theory rigorously derived from radiation transport equations. The approach is based on the same schematization as for Spencer-Attix's (i.e. groups of slow and fast electrons) and yields a general expression of absorbed dose for suitably implemented Monte Carlo methods. The Spencer-Attix-Nahum formulation is shown to be a special case of the presented model, outlining specific issues of the standardmethod. By providing an expression of absorbed dose which reflects the gold standard calculation method (i.e. Monte Carlo), the proposed theory could be adopted by the radiation dosimetry community. [ABSTRACT FROM AUTHOR]