Estimation of the relative biological effectiveness for double strand break induction of clinical kilovoltage beams using Monte Carlo simulations.

BACKGROUND: The Relative Biological Effectiveness (RBE) of kilovoltage photon beams has been previously investigated in vitro and in silico using analytical methods. The estimated values range from 1.03 to 1.82 depending on the methodology and beam energies examined. PURPOSE: The focus of this work was to independently estimate RBE values for a range of clinically used kilovoltage beams (70-200 kVp) while investigating the suitability of using TOPAS-nBio for this task. METHODS: Previously validated spectra of clinical beams were used to generate secondary electron spectra at several depths in a water tank phantom via TOPAS Monte Carlo (MC) simulations. Cell geometry was irradiated with the secondary electrons in TOPAS-nBio MC simulations. The deposited dose and the calculated number of DNA strand breaks were used to estimate RBE values. RESULTS: Monoenergetic secondary electron simulations revealed the highest direct and indirect double strand break yield at approximately 20 keV. The average RBE value for the kilovoltage beams was calculated to be 1.14. CONCLUSIONS: TOPAS-nBio was successfully used to estimate the RBE values for a range of clinical radiotherapy beams. The calculated value was in agreement with previous estimates, providing confidence in its clinical use in the future.

Clinical treatment planning for kilovoltage radiotherapy using EGSnrc and Python.

Kilovoltage radiotherapy dose calculations are generally performed with manual point dose calculations based on water dosimetry. Tissue heterogeneities, irregular surfaces, and introduction of lead cutouts for treatment are either not taken into account or crudely approximated in manual calculations. Full Monte Carlo (MC) simulations can account for these limitations but require a validated treatment unit model, accurately segmented patient tissues and a treatment planning interface (TPI) to facilitate the simulation setup and result analysis. EGSnrc was used in this work to create a model of Xstrahl kilovoltage unit extending the range of energies, applicators, and validation parameters previously published. The novel functionality of the Python-based framework developed in this work allowed beam modification using custom lead cutouts and shields, commonly present in kilovoltage treatments, as well as absolute dose normalization using the output of the unit. 3D user-friendly planning interface of the developed framework facilitated non-co-planar beam setups for CT phantom MC simulations in DOSXYZnrc. The MC models of 49 clinical beams showed good agreement with measured and reference data, to within 2% for percentage depth dose curves, 4% for beam profiles at various depths, 2% for backscatter factors, 0.5 mm of absorber material for half-value layers, and 3% for output factors. End-to-end testing of the framework using custom lead cutouts resulted in good agreement to within 3% of absolute dose distribution between simulations and EBT3 GafChromic film measurements. Gamma analysis demonstrated poor agreement at the field edges which was attributed to the limitations of simulating smooth cutout shapes. Dose simulated in a heterogeneous phantom agreed to within 7% with measured values converted using the ratio of mass energy absorption coefficients of appropriate tissues and air.

Energy-dependence investigation for a range of clinically used detectors from 70 kV to 6 MV.

PURPOSE: Accurate measurement of out-of-field dose in radiotherapy directly impacts beam data modeling in treatment planning systems, verification of implanted electronic devices/lens/fetus dose, secondary cancer risk estimation, and organ-at-risk dose reporting. When performing out-of-field dosimetry, it is therefore imperative that the response of the detector has been well characterized. Due to the softening of the radiation beam out-of-field, many detectors will exhibit energy dependence. This study investigated the energy dependence of a range of clinical available detectors over typical energies experienced out-of-field. METHODS: The response of detectors to photon beams from 70 kV to 6 MV was measured. The relative change in response from 6 MV down to 70 kV highlighted the expected deviation in the response of detectors that would typically be calibrated in-field for use out-of-field. RESULTS: The Pinpoint detector displayed the most energy-independent response over the energy range investigated. The Micro-Lion detector was the only detector to show an under-response to all low-energy beams relative to 6 MV. The diode-type detectors showed the largest energy dependence. CONCLUSIONS: When considering detectors for use in out-of-field dose measurements, it is important that the energy dependence is investigated over a low-energy range as out-of-field the energy spectra comprise a larger component of photons in the 50-100-keV range. This study highlights the variation in response of a range of clinically available detectors to low-energy radiation beams relative to 6 MV for out-of-field dosimetry. The Pinpoint detector was the most energy-independent detector with a response close to unity over the entire energy range investigated.