Coupling Radiation Transport and Track-Structure Simulations: Strategy Based on Analytical Formulas Representing DNA Damage Yields

Existing radiation codes for biomedical applications face the challenge of dealing with largely different spatial scales, from nanometer scales governing individual energy deposits to macroscopic scales of dose distributions in organs and tissues in radiotherapy. Event-by-event track-structure codes are needed to model energy deposition patterns at cellular and subcellular levels. In conjunction with DNA and chromatin models, they predict radiation-induced DNA damage and subsequent biological effects. Describing larger-scale effects is the realm of radiation transport codes and dose calculation algorithms. A coupling approach with a great potential consists in implementing into radiation transport codes the results of track-structure simulations captured by analytical formulas. This strategy allows extending existing transport codes to biologically relevant endpoints, without the need of developing dedicated modules and running new computationally expensive simulations. Depending on the codes used and questions addressed, alternative strategies can be adopted, reproducing DNA damage in dependence on different parameters extracted from the transport code, e.g., microdosimetric quantities, average linear energy transfer (LET), or particle energy. Recently, a comprehensive database on DNA damage induced by ions from hydrogen to neon, at energies from 0.5 GeV/u down to their stopping, has been created with PARTRAC biophysical simulations. The results have been captured as a function of average LET in the cell nucleus. However, the formulas are not applicable to slow particles beyond the Bragg peak, since these can have the same LET as faster particles but in narrower tracks, thus inducing different DNA damage patterns. Particle energy distinguishes these two cases. It is also more readily available than LET from some transport codes. Therefore, a set of new analytical functions are provided, describing how DNA damage depends on particle energy. The results complement the analysis of the PARTRAC database, widening its potential of application and use for implementation in transport codes.

Dose calculation accuracy for photon small fields in treatment planning systems with comparison by Monte Carlo simulations

Purpose: Advanced radiation therapy techniques use small fields in treatment planning and delivery. Small fields have the advantage of more accurate dose delivery, but with the cost of some complications in dosimetry. Different dose calculation algorithms imported in various treatment planning systems (TPSs) which each of them has different accuracy. Monte Carlo (MC) simulation has been reported as one of the accurate methods for calculating dose distribution in radiation therapy. The aim of this study was the evaluation of TPS dose calculation algorithms in small fields against 2 MC codes. Methods: A linac head was simulated in 2 MC codes, MCNPX, and GATE. Then three small fields (0.5×0.5, 1×1 and 1.5×1.5 cm2) were simulated with 2 MC codes, and also these fields were planned with different dose calculation algorithms in Isogray and Monaco TPS. PDDs and lateral dose profiles were extracted and compared between MC simulations and dose calculation algorithms. Results: For 0.5×0.5 cm2 field mean differences in PDDs with MCNPX were 2.28, 4.6, 5.3, and 7.4% and with GATE were -0.29, 2.3, 3 and 5% for CCC, superposition, FFT and Clarkson algorithms respectively. For 1×1 cm2 field mean differences in PDDs with MCNPX were 1.58, 0.6, 1.1 and 1.4% and with GATE were 0.77, 0.1, 0.6 and 0.9% for CCC, superposition, FFT and Clarkson algorithms respectively. For 1.5×1.5 cm2 field mean differences in PDDs with MCNPX were 0.82, 0.4, 0.6 and -0.4% and with GATE were 2.38, 2.5, 2.7 and 1.7% for CCC, superposition, FFT and Clarkson algorithms respectively. Conclusions: Different dose calculation algorithms were evaluated and compared with MC simulation in small fields. Mean differences with MC simulation decreased with the increase of field sizes for all algorithms.

Dose Calculation Algorithms for External Radiation Therapy: An Overview for Practitioners

Radiation therapy (RT) is a constantly evolving therapeutic technique; improvements are continuously being introduced for both methodological and practical aspects. Among the features that have undergone a huge evolution in recent decades, dose calculation algorithms are still rapidly changing. This process is propelled by the awareness that the agreement between the delivered and calculated doses is of paramount relevance in RT, since it could largely affect clinical outcomes. The aim of this work is to provide an overall picture of the main dose calculation algorithms currently used in RT, summarizing their underlying physical models and mathematical bases, and highlighting their strengths and weaknesses, referring to the most recent studies on algorithm comparisons. This handy guide is meant to provide a clear and concise overview of the topic, which will prove useful in helping clinical medical physicists to perform their responsibilities more effectively and efficiently, increasing patient benefits and improving the overall quality of the management of radiation treatment.

Assessing The Clinical Application Of The Van Herk Margin Formula For Lung Radiotherapy

In radiation therapy treatment planning, margins are added to the tumour volume to ensure that the correct radiation dose is delivered to the tumour in the presence of geometrical uncertainties. The van Herk margin formula (VHMF) was developed to calculate the minimum margin on the target to provide full coverage by 95% of the prescribed dose to 90% of the population. However, this formula is based on an ideal dose profile model that is not realistic for lung radiotherapy. The purpose of this study was to investigate the validity of the VHMF for lung radiotherapy with accurate dose calculation algorithms and respiratory motion modeling. Ultimately, the VHMF ensured sufficient target coverage, with the exception of small lesions in soft tissue; however, the derived PTV margins were larger than necessary. A novel planning approach using the VHMF was tested indicating the need to account for tumour motion trajectory and plan conformity.

Assessing The Clinical Application Of The Van Herk Margin Formula For Lung Radiotherapy

In radiation therapy treatment planning, margins are added to the tumour volume to ensure that the correct radiation dose is delivered to the tumour in the presence of geometrical uncertainties. The van Herk margin formula (VHMF) was developed to calculate the minimum margin on the target to provide full coverage by 95% of the prescribed dose to 90% of the population. However, this formula is based on an ideal dose profile model that is not realistic for lung radiotherapy. The purpose of this study was to investigate the validity of the VHMF for lung radiotherapy with accurate dose calculation algorithms and respiratory motion modeling. Ultimately, the VHMF ensured sufficient target coverage, with the exception of small lesions in soft tissue; however, the derived PTV margins were larger than necessary. A novel planning approach using the VHMF was tested indicating the need to account for tumour motion trajectory and plan conformity.