OBJECTIVE: Carbon-ion radiotherapy (CiRT) has been used for the treatment of locally advanced pancreatic cancer (LAPC) with uniform dose plan. The aim of the present study is to investigate the effectiveness of a simultaneous integrated boost (SIB) technique with scanned CiRT against LAPC.
METHODS: Data of 21 patients with LAPC were used to compare two treatment planning approaches: a conventional uniform dose approach and a SIB approach. A relative biological effectiveness (RBE)-weighted dose (DRBE) of 55.2 Gy (RBE) in 12 fractions was prescribed to the planning target volume (PTV) in the conventional approach. In the SIB approach, DRBE of 67.2 Gy (RBE) and 43.2 Gy (RBE) in 12 fractions were prescribed to a high-risk PTV (HR-PTV) and low-risk PTV (LR-PTV), respectively. The DRBE and dose-averaged linear energy transfer (LETd) of targets and gastrointestinal tracts as organs at risk (OARs) were evaluated.
RESULTS: The HR-PTV D90% and LR-PTV D90% were 64.4±0.6 and 42.5±0.1 Gy (RBE) in SIB approach compared to the PTV D90% of 54.1±0.4 Gy (RBE) in the conventional approach. All SIB plans achieved the D2cc lower than 46 Gy (RBE) and V30 lower than 4 cm3 within OARs. The SIB approach increased the minimum LETd within the GTV to 44 keV/μm or higher for 20 out of 21 patients as compared to 16 out of 21 patients in the conventional approach.
CONCLUSIONS: The SIB approach effectively increased the RBE-weighted dose and LETd within the HR-PTV and GTV by accumulating the high-LET stopping carbon-ions into the HR-PTV in addition to the decreased RBE-weighted dose to OARs.

OBJECTIVE: This study aims to elucidate the dependence of the flat-panel detector\'s response on the linear energy transfer (LET) and evaluate the practical viability of employing flat-panel detectors in proton dosimetry applications through LET-dependent correction factors.
METHODS: The study assessed the flat-panel detector\'s response across varying depths using solid water and distinct 100, 150, and 200 MeV proton beams by comparing the flat-panel readings against reference doses measured with an ionization chamber. A Monte Carlo code was used to derive LET values, and an LET-dependent response correction factor was determined based on the ratio of the uncorrected flat-panel dose to the ionization chamber dose. The implications of this under-response correction were validated by applying it to a measurement involving a spread-out Bragg peak (SOBP), followed by a comparative analysis against doses calculated using the Monte Carlo code and MatriXX ONE measurement.
RESULTS: The association between LET and the flat-panel detector\'s under-response displayed a positive correlation that intensified with increasing LET values. Notably, with a 10 keV/µm LET value, the detector\'s under-response reached 50 %, while the measurement points in the SOBP demonstrated under-response greater than 20 %. However, post-correction, the adjusted flat-panel profile closely aligned with the Monte Carlo profile, yielding a 2-dimensional 3 %/3mm gamma passing rate of 100 % at various verification depths.
CONCLUSIONS: This study successfully defined the link between LET and the responsiveness of flat-panel detectors for proton dosimetric measurements and established a foundational framework for integrating flat-panel detectors in clinical proton dosimetry applications.

OBJECTIVE: The energy deposition of photons and protons differs. It depends on the position in the proton Bragg peak (BP) and the linear energy transfer (LET) leading to a variable relative biological effectiveness (RBE). Here, we investigate LET dependent alterations on metabolic viability and proliferation of sarcoma and endothelium cell lines following proton irradiation in comparison to photon exposure. Approach: Using a multi-step range shifter (MSRS), each column of a 96-well plate was positioned in a different depth along four BP curves with increasing intensities. The high-throughput experimental setup covers dose, LET, and RBE changes seen in a treatment field. Photon irradiation was performed to calculate the RBE along the BP curve. Two biological information out of one experiment were extracted allowing a correlation between metabolic viability and proliferation of the cells. Main results: The metabolic viability and cellular proliferation were column-wise altered showing a depth-dose profile. Endothelium cell viability recovers within 96 h post BP irradiation while sarcoma cell viability remains reduced. Highest RBE values were observed at the BP distal fall-off regarding proliferation of the sarcoma and endothelial cells. Significance: The high-throughput experimental setup introduced here I) covers dose, LET, and RBE changes seen in a treatment field, II) measures short-term effects within 48 h to 96 h post irradiation, and III) can additionally be transferred to various cell types without time consuming experimental adaptations. Traditionally, RBE values are calculated from clonogenic cell survival. Measured RBE profiles strongly depend on physical characteristics such as dose and LET and biological characteristics for example cell type and time point. Metabolic viability and proliferation proofed to be in a similar effect range compared to clonogenic survival results. Based on limited data of combined irradiation with doxorubicin, future experiments will test combined treatment with systemic therapies applied in clinics e.g. cyclin-dependent inhibitors. .

OBJECTIVE: To model relative biological effectiveness (RBE) differences found in two studies which used spread-out Bragg-peaks (SOBP) placed at (a) superficial depth and (b) at the maximum range depth. For pencil beam scanning (PBS), RBE at similar points within the SOBP did not change between the two extreme SOBP placement depths; in passively scattered beams (PSB), high RBE values (typically 1.2-1.3) were found within superficially- placed SOBP but reduced to lower values (1-1.07) at similar points within the extreme-depth positioned SOBP. The dose, LET (linear energy transfer) distributions along each SOBP were closely comparable regardless of placement depth, but significant changes in dose rate occurred with depth in the PSB beam.
METHODS: The equations used allow α and β changes with falling dose rate (the converse to FLASH studies) in PSB, resulting in reduced α/β ratios, compatible with a reduction in micro-volumetric energy transfer (the product of Fluence and LET), with commensurate reductions in RBE. The experimental depth-distances, positions within SOBP, observed dose-rates and radiosensitivity ratios were used to estimate the changes in RBE.
RESULTS: RBE values within a 5 % tolerance limit of the experimental results for PSB were found at the deepest SOBP placement. No RBE changes were predicted for PBS beams, as in the published results.
CONCLUSIONS: Enhanced proton therapy toxicity might occur with PBS when compared with PSB for deeply positioned SOBP due to the maintenance of higher RBE. Scanned pencil beam users need to be vigilant about RBE and further research is indicated.

Carbon ion radiotherapy (CIRT) for pediatric cancer is currently limited because of the unknown risk of induction of secondary cancers. Medulloblastoma of Ptch1+/- mice offers a unique experimental system for radiation-induced carcinogenesis, in which tumors are classified into spontaneous and radiation-induced subtypes based on their features of loss of heterozygosity (LOH) that affect the wild-type Ptch1 allele. The present study aims to investigate in young Ptch1+/- mice the carcinogenic effect, and its age dependence, of the low-linear energy transfer (LET, ∼13 keV/µm) carbon ions, to which normal tissues in front of the tumor are exposed during therapy. We irradiated Ptch1+/- mice at postnatal day (P) 1, 4, or 10 with 290 MeV/u carbon ions (0.05-0.5 Gy; LET, 13 keV/µm) and monitored them for medulloblastoma development. Loss of heterozygosity of seven genetic markers on chromosome 13 (where Ptch1 resides) was studied to classify the tumors. Carbon ion exposure induced medulloblastoma most effectively at P1. The LOH patterns of tumors were either telomeric or interstitial, the latter occurring almost exclusively in the irradiated groups, allowing the use of interstitial LOH as a biomarker of radiation-induced tumors. Radiation-induced tumors developed during a narrow age window (most strongly at P1 and only moderately at P4, with suppressed tumorigenesis at P10). Calculated using previous results using 137Cs gamma rays, the values for relative biological effectiveness (RBE) regarding radiation-induced tumors were 4.1 (3.4, 4.8) and 4.3 (3.3, 5.2) (mean and 95% confidence interval) for exposure at P1 and 4, respectively. Thus, the RBE of carbon ions for medulloblastoma induction in Ptch1+/- mice was higher than the generally recognized RBE of 1-2 for cell killing, chromosome aberrations, and skin reactions.

Objective.This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LETd) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETdis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context.Approach.The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (n= 151). The best-performing model was identified and externally validated on patients from a different center (n= 107). LETdpredictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LETdpredictions to derive RBE-weighted doses, using the Wedenberg RBE model.Main results.We found NNs based solely on the planned dose distribution, i.e. without additional usage of CT images, can approximate MC-based LETddistributions. Root mean squared errors (RMSE) for the median LETdwithin the brain, brainstem, CTV, chiasm, lacrimal glands (ipsilateral/contralateral) and optic nerves (ipsilateral/contralateral) were 0.36, 0.87, 0.31, 0.73, 0.68, 1.04, 0.69 and 1.24 keV µm-1, respectively. Although model predictions showed statistically significant differences from MC outputs, these did not result in substantial changes in NTCP predictions, with RMSEs of at most 3.2 percentage points.Significance.The ability of NNs to predict LETdbased solely on planned dose distributions suggests a viable alternative to compute-intensive MC simulations in a variable-RBE setting. This is particularly useful in scenarios where MC simulation data are unavailable, facilitating resource-constrained proton therapy treatment planning, retrospective patient data analysis and further investigations on the variability of proton RBE.

Recurrent computed tomography (CT) examination has become a common diagnostic procedure for several diseases and injuries. Though each singular CT scan exposes individuals at low doses of low linear energy transfer (LET) radiation, the cumulative dose received from recurrent CT scans poses an increasing concern for potential health risks. Here, we evaluated the biological effects of recurrent CT scans on the DNA damage response (DDR) in human fibroblasts and retinal pigment epithelial cells maintained in culture for five months and subjected to four CT scans, one every four weeks. DDR kinetics and eventual accumulation of persistent-radiation-induced foci (P-RIF) were assessed by combined immunofluorescence for γH2AX and 53BP1, i.e., γH2AX/53BP1 foci. We found that CT scan repetitions significantly increased both the number and size of γH2AX/53BP1 foci. In particular, after the third CT scan, we observed the appearance of giant foci that might result from the overlapping of individual small foci and that do not associate with irreversible growth arrest, as shown by DNA replication in the foci-carrying cells. Whether these giant foci represent coalescence of unrepaired DNA damage as reported following single exposition to high doses of high LET radiation is still unclear. However, morphologically, these giant foci resemble the recently described compartmentalization of damaged DNA that should facilitate the repair of DNA double-strand breaks but also increase the risk of chromosomal translocations. Overall, these results indicate that for a correct evaluation of the damage following recurrent CT examinations, it is necessary to consider the size and composition of the foci in addition to their number.

Objective.This study aims to assess the composition of scattered particles generated in proton therapy for tumors situated proximal to some titanium (Ti) dental implants. The investigation involves decomposing the mixed field and recording Linear Energy Transfer (LET) spectra to quantify the influence of metallic dental inserts located behind the tumor.Approach.A therapeutic conformal proton beam was used to deliver the treatment plan to an anthropomorphic head phantom with two types of implants inserted in the target volume (made of Ti and plastic, respectively). The scattered radiation resulted during the irradiation was detected by a hybrid semiconductor pixel detector MiniPIX Timepix3 that was placed distal to the Spread-out Bragg peak. Visualization and field decomposition of stray radiation were generated using algorithms trained in particle recognition based on artificial intelligence neural networks (AI NN). Spectral sensitive aspects of the scattered radiation were collected using two angular positions of the detector relative to the beam direction: 0° and 60°.Results.Using AI NN, 3 classes of particles were identified: protons, electrons & photons, and ions & fast neutrons. Placing a Ti implant in the beam\'s path resulted in predominantly electrons and photons, contributing 52.2% of the total number of detected particles, whereas for plastic implants, the contribution was 65.4%. Scattered protons comprised 45.5% and 31.9% with and without metal inserts, respectively. The LET spectra were derived for each group of particles identified, with values ranging from 0.01 to 7.5 keVμm-1for Ti implants/plastic implants. The low-LET component was primarily composed of electrons and photons, while the high-LET component corresponded to protons and ions.Significance.This method, complemented by directional maps, holds the potential for evaluating and validating treatment plans involving stray radiation near organs at risk, offering precise discrimination of the mixed field, and enhancing in this way the LET calculation.

OBJECTIVE: To investigate the role of dosiomics features extracted from physical dose (DPHYS), RBE-weighted dose (DRBE) and dose-averaged Linear Energy Transfer (LETd), to predict the risk of local recurrence (LR) in skull base chordoma (SBC) treated with Carbon Ion Radiotherapy (CIRT). Thus, define and evaluate dosiomics-driven tumor control probability (TCP) models.
METHODS: 54 SBC patients were retrospectively selected for this study. A regularized Cox proportional hazard model (r-Cox) and Survival Support Vector Machine (s-SVM) were tuned within a repeated Cross Validation (CV) and patients were stratified in low/high risk of LR. Models\' performance was evaluated through Harrell\'s concordance statistic (C-index), and survival was represented through Kaplan-Meier (KM) curves. A multivariable logistic regression was fit to the selected feature sets to generate a dosiomics-driven TCP model for each map. These were compared to a reference model built with clinical parameters in terms of f-score and accuracy.
RESULTS: The LETd maps reached a test C-index of 0.750 and 0.786 with r-Cox and s-SVM, and significantly separated KM curves. DPHYS maps and clinical parameters showed promising CV outcomes with C-index above 0.8, despite a poorer performance on the test set and patients stratification. The LETd-based TCP showed a significatively higher f-score (0.67[0.52-0.70], median[IQR]) compared to the clinical model (0.4[0.32-0.63], p < 0.025), while DPHYS achieved a significatively higher accuracy (DPHYS: 0.73[0.65-0.79], Clinical: 0.6 [0.52-0.72]).
CONCLUSIONS: This analysis supports the role of LETd as relevant source of prognostic factors for LR in SBC treated with CIRT. This is reflected in the TCP modeling, where LETd and DPHYS showed an improved performance with respect to clinical models.

The ionizing radiation with high linear energy transfer (LET), such as a heavy ion beam, induces more serious biological effects than low LET ones, such as gamma- and X-rays. This indicates a difference in the DNA damage produced by low and high LET radiations and their biological effects. We have been studying the differences in DNA damage produced by gamma-rays and carbon ion beams. Therefore, we analyze mutations induced by both ionizing radiations to discuss the differences in their biological effects in this study. pUC19 plasmid DNA was irradiated by carbon ion beams in the solution containing 1M dimethyl sulfoxide to mimic a cellular condition. The irradiated DNA was cloned in competent cells of Escherichia coli. The clones harboring some mutations in the region of lacZα were selected, and the sequence alterations were analyzed. A one-deletion mutation is significant in the carbon-irradiated DNA, and the C:G↔T:A transition is minor. On the other hand, the gamma-irradiated DNA shows mainly G:C↔T:A transversion. These results suggest that carbon ion beams produce complex DNA damage, and gamma-rays are prone to single oxidative base damage, such as 8-oxoguanine. Carbon ion beams can also introduce oxidative base damage, and the damage species is 5-hydroxycytosine. This was consistent with our previous results of DNA damage caused by heavy ion beams. We confirmed the causal DNA damage by mass spectrometry for these mutations.