Study of the intracellular nanoparticle-based radiosensitization mechanisms in F98 glioma cells treated with charged particle therapy through synchrotron-based infrared microspectroscopy.

The use of nanoparticles (NP) as dose enhancers in radiotherapy (RT) is a growing research field. Recently, the use of NP has been extended to charged particle therapy in order to improve the performance in radioresistant tumors. However, the biological mechanisms underlying the synergistic effects involved in NP-RT approaches are not clearly understood. Here, we used the capabilities of synchrotron-based Fourier Transform Infrared Microspectroscopy (SR-FTIRM) as a bio-analytical tool to elucidate the NP-induced cellular damage at the molecular level and at a single-cell scale. F98 glioma cells doped with AuNP and GdNP were irradiated using several types of medical ion beams (proton, helium, carbon and oxygen). Differences in cell composition were analyzed in the nucleic acids, protein and lipid spectral regions using multivariate methods (Principal Component Analysis, PCA). Several NP-induced cellular modifications were detected, such as conformational changes in secondary protein structures, intensity variations in the lipid CHx stretching bands, as well as complex DNA rearrangements following charged particle therapy irradiations. These spectral features seem to be correlated with the already shown enhancement both in the DNA damage response and in the reactive oxygen species (ROS) production by the NP, which causes cell damage in the form of protein, lipid, and/or DNA oxidations. Vibrational features were NP-dependent due to the NP heterogeneous radiosensitization capability. Our results provided new insights into the molecular changes in response to NP-based RT treatments using ion beams, and highlighted the relevance of SR-FTIRM as a useful and precise technique for assessing cell response to innovative radiotherapy approaches.

A phenomenological relative biological effectiveness approach for proton therapy based on an improved description of the mixed radiation field.

Proton therapy treatment planning systems (TPSs) are based on the assumption of a constant relative biological effectiveness (RBE) of 1.1 without taking into account the found in vitro experimental variations of the RBE as a function of tissue type, linear energy transfer (LET) and dose. The phenomenological RBE models available in literature are based on the dose-averaged LET (LET D ) as an indicator of the physical properties of the proton radiation field. The LET D values are typically calculated taking into account primary and secondary protons, neglecting the biological effect of heavier secondaries. In this work, we have introduced a phenomenological RBE approach which considers the biological effect of primary protons, and of secondary protons, deuterons, tritons (Z = 1) and He fragments (3He and 4He, Z = 2). The calculation framework, coupled with a Monte Carlo (MC) code, has been successfully benchmarked against clonogenic in vitro data measured in this work for two cell lines and then applied to determine biological quantities for spread-out Bragg peaks and a prostate and a head case. The introduced RBE formalism, which depends on the mixed radiation field, the dose and the ratio of the linear-quadratic model parameters for the reference radiation [Formula: see text], predicts, when integrated in an MC code, higher RBE values in comparison to LET D -based parameterizations. This effect is particular enhanced in the entrance channel of the proton field and for low [Formula: see text] tissues. For the prostate and the head case, we found higher RBE-weighted dose values up to about 5% in the entrance channel when including or neglecting the Z = 2 secondaries in the RBE calculation. TPSs able to proper account for the mixed radiation field in proton therapy are thus recommended for an accurate determination of the RBE in the whole treatment field.

Biologically optimized helium ion plans: calculation approach and its in vitro validation.

Treatment planning studies on the biological effect of raster-scanned helium ion beams should be performed, together with their experimental verification, before their clinical application at the Heidelberg Ion Beam Therapy Center (HIT). For this purpose, we introduce a novel calculation approach based on integrating data-driven biological models in our Monte Carlo treatment planning (MCTP) tool. Dealing with a mixed radiation field, the biological effect of the primary (4)He ion beams, of the secondary (3)He and (4)He (Z = 2) fragments and of the produced protons, deuterons and tritons (Z = 1) has to be taken into account. A spread-out Bragg peak (SOBP) in water, representative of a clinically-relevant scenario, has been biologically optimized with the MCTP and then delivered at HIT. Predictions of cell survival and RBE for a tumor cell line, characterized by [Formula: see text] Gy, have been successfully compared against measured clonogenic survival data. The mean absolute survival variation ([Formula: see text]) between model predictions and experimental data was 5.3% ± 0.9%. A sensitivity study, i.e. quantifying the variation of the estimations for the studied plan as a function of the applied phenomenological modelling approach, has been performed. The feasibility of a simpler biological modelling based on dose-averaged LET (linear energy transfer) has been tested. Moreover, comparisons with biophysical models such as the local effect model (LEM) and the repair-misrepair-fixation (RMF) model were performed. [Formula: see text] values for the LEM and the RMF model were, respectively, 4.5% ± 0.8% and 5.8% ± 1.1%. The satisfactorily agreement found in this work for the studied SOBP, representative of clinically-relevant scenario, suggests that the introduced approach could be applied for an accurate estimation of the biological effect for helium ion radiotherapy.

Data-driven RBE parameterization for helium ion beams.

Helium ion beams are expected to be available again in the near future for clinical use. A suitable formalism to obtain relative biological effectiveness (RBE) values for treatment planning (TP) studies is needed. In this work we developed a data-driven RBE parameterization based on published in vitro experimental values. The RBE parameterization has been developed within the framework of the linear-quadratic (LQ) model as a function of the helium linear energy transfer (LET), dose and the tissue specific parameter (α/ß)ph of the LQ model for the reference radiation. Analytic expressions are provided, derived from the collected database, describing the RBEα = αHe/αph and Rß = ßHe/ßph ratios as a function of LET. Calculated RBE values at 2 Gy photon dose and at 10% survival (RBE10) are compared with the experimental ones. Pearson's correlation coefficients were, respectively, 0.85 and 0.84 confirming the soundness of the introduced approach. Moreover, due to the lack of experimental data at low LET, clonogenic experiments have been performed irradiating A549 cell line with (α/ß)ph = 5.4 Gy at the entrance of a 56.4 MeV u(-1)He beam at the Heidelberg Ion Beam Therapy Center. The proposed parameterization reproduces the measured cell survival within the experimental uncertainties. A RBE formula, which depends only on dose, LET and (α/ß)ph as input parameters is proposed, allowing a straightforward implementation in a TP system.