Uncertainty in tissue equivalent proportional counter assessments of microdosimetry and RBE estimates in carbon radiotherapy

Incorporating boron distribution variations in microdosimetric kinetic model-based relative biological effectiveness calculations for boron neutron capture therapy

This study introduces the MKM_B model, an approach derived from the MKM model, designed to evaluate the biological effectiveness of Boron Neutron Capture Therapy (BNCT) in the face of challenges from varying microscopic boron distributions. The model introduces a boron compensation factor, allowing for the assessment of compound Biological Effectiveness (CBE) values for different boron distributions. Utilizing the TOPAS simulation platform, the lineal energy spectrum of particles in BNCT was simulated, and the sensitivity of the MKM_B model to parameter variations and the influence of cell size on the model were thoroughly investigated. The CBE values for 10B-boronphenylalanine (BPA) and 10B-sodium (BSH) were determined to be 3.70 and 1.75, respectively. These calculations were based on using the nucleus radius of 2.5 μm and the cell radius of 5 μm while considering a 50% surviving fraction. It was observed that as cell size decreased, the CBE values for both BPA and BSH increased. Additionally, the model parameter rd was identified as having the most significant impact on CBE, with other parameters showing moderate effects. The development of the MKM_B model enables the accurate prediction of CBE under different boron distributions in BNCT. This model offers a promising approach to optimize treatment planning by providing increased accuracy in biological effectiveness.

State-of-the-art and potential of experimental microdosimetry in ion-beam therapy

In radiotherapy, radiation-quality should be an expression of the biological and physical characteristics of ionizing radiation such as spatial distribution of ionization or energy deposition. Linear energy transfer (LET) and lineal energy (y) are two descriptors used to quantify the radiation quality. These two quantities are connected and exhibit similar features. In ion-beam therapy (IBT), lineal energy can be measured with microdosimeters, which are specifically designed to cope with the high fluence of particles in clinical beams, while the quantification of LET is generally based on calculations. In pre-clinical studies, microdosimetric spectra are used for the indirect determination of relative biological effectiveness (RBE), e.g., using the microdosimetric kinetic model (MKM) or biophysical response functions. In this context it is important to consider saturation effects, which occur when the highest values of y become less biologically relevant compared to the relative contribution they make to the physical dose. Recent clinical data suggests that local tumor control and normal tissue effects can be linked to macroscopic and microscopic dosimetry parameters. In particular, positive clinical outcomes have been correlated to the highest LET values in the density distribution, and there is no evident link to the saturation discussed above. A systematic collection of microdosimetric information in combination with clinical data in retrospective studies may clarify the role of radiation quality at the highest LET. In the clinical setting, microdosimetry is not widely used yet, despite its potential to be linked with LET by experimentally-determined y values. Through this connection, both play an important role in complex therapy techniques such as intensity modulated particle therapy (IMPT), LET-painting and multi-ion optimization. This review summarizes the current state of microdosimetry for IBT and its potential, as well as research and development needed to make experimental microdosimetry a mature procedure in a clinical context.

A systematic study of the contribution of counting statistics to the final lineal energy uncertainty in microdosimetry

Objectives. Microdosimetry is proving to be a reliable and powerful tool to be applied in different fields such as radiobiology, radiation protection and hadron therapy. However, accepted standard protocols and codes of practice are still missing. With this regard, a systematic and methodical uncertainty analysis is fundamental to build an accredited uncertainty budget of practical use. This work studied the contribution of counting statistics (i.e. number of events collected) to the final frequency-mean and dose-mean lineal energy uncertainties, aiming at providing guidelines for good experimental and simulation practice. The practical limitation of current technologies and the non-negligible probability of nuclear reactions require careful considerations and nonlinear approaches. Approach. Microdosimetric data were obtained by means of the particle tracking Monte Carlo code Geant4. The uncertainty analysis was carried out relying on a Monte Carlo based numerical analysis, as suggested by the BIPM's ‘Guide to the expression of uncertainty in measurement’. Final uncertainties were systematically investigated for proton, helium and carbon ions at an increasing number of detected events, for a range of different clinical-relevant beam energies. Main results. Rare events generated by nuclear interactions in the detector sensitive volume were found to massively degrade microdosimetric uncertainties unless a very high statistics is collected. The study showed an increasing impact of such events for increasing beam energy and lighter ions. For instance, in the entrance region of a 250 MeV proton beam, about 5 ∗ 107 events need to be collected to obtain a dose-mean lineal energy uncertainty below 10%. Significance. The results of this study help define the necessary conditions to achieve appropriate statistics in computational microdosimetry, pointing out the importance of properly taking into account nuclear interaction events. Their impact on microdosimetric quantities and on their uncertainty is significant and cannot be overlooked, particularly when characterising clinical beams and radiobiological response. This work prepared the ground for deeper investigations involving dedicated experiments and for the development of a method to properly evaluate the counting statistics uncertainty contribution in the uncertainty budget, whose accuracy is fundamental for the clinical transition of microdosimetry.