Dose-averaged Linear Energy Transfer Research Articles

Impact of porous lung substitute on linear energy transfer (LET) assessed via Monte Carlo simulation and CR-39 measurement with a carbon-ion beam.

Carbon-ion beam radiotherapy offers substantial physical and biological advantages due to its distinct Bragg peak (BP) depth dose distribution and higher linear energy transfer (LET) in the peak region that enhances its efficacy in tumor eradication compared to x-ray beams. Porous structures, such as those found in lung and lung-equivalent tissues, unfortunately, introduce significant uncertainties in both dose and LET distributions, which current treatment planning systems (TPS) inadequately address. This study aims to investigate the effects of porous lung-equivalent structures on LET distribution using Monte Carlo (MC) simulations and CR-39 measurements. It seeks to understand how porous structures influence LET spectra and dose-averaged LET (LETd) in carbon-ion beams. A Gammex LN300 phantom and a binary voxel virtual phantom composed of water and air were used to represent lung-equivalent tissues for measurements and MC simulations. LET spectra measured with CR-39 at different depths within the LN300 slabs were compared with MC-calculated LETd distributions. The impact of porous structures on dose and LETd distributions was evaluated using various beam configurations, including single-beam and multi-beam setups. Additionally, a convolution method with modulation power (Pmod) was proposed to improve LETd prediction in porous media. The study demonstrated that porous structures broaden both the dose and LETd distributions, especially around the BP region. Multiple beam angles helped mitigate dose degradation but did not resolve discrepancies in the LETd distributions. Compared with calculation results based on CT images, intensity-modulated particle therapy (IMPT) using a distal LETd patching method in porous structure increased the median LETd in the target from 67.2 to 69.6keV/µm, and the minimum LETd from 51.5 to 58.0keV/µm, respectively. Moreover, to improve the prediction of LETd in porous structures, analytical convolution-based predictions showed good agreement with the MC simulations, with mean LETd deviations of -1.9%±1.6% in the plateau, -3.1%±4.9% in the BP, and -1.1%±7.7% in the tail region. Porous lung-equivalent structures significantly affect LETd distributions in carbon-ion therapy, as confirmed by both CR-39 measurements and MC simulations. IMPT with LETd optimization may be more impacted by porous structures in terms of median and minimum LETd values within the target. The Gaussian convolution function shows promise for enhancing LETd calculation accuracy, but further validation in anatomically complex models is needed to assess its clinical feasibility.

Optimizing the dose-averaged linear energy transfer for the dominant intraprostatic lesions in high-risk localized prostate cancer patients

Optimizing the dose-averaged linear energy transfer for the dominant intraprostatic lesions in high-risk localized prostate cancer patients

A library of proton lineal energy spectra spanning the full range of clinically relevant energies.

In locations where the proton energy spectrum is broad, lineal energy spectrum-based proton biological effects models may be more accurate than dose-averaged linear energy transfer (LETd) based models. However, the development of microdosimetric spectrum-based biological effects models is hampered by the extreme computational difficulty of calculating microdosimetric spectra. Given a precomputed library of lineal energy spectra for monoenergetic protons, a weighted summation can be performed which yields the lineal energy spectrum of an arbitrary polyenergetic beam. Using this approach, lineal energy spectra can be rapidly calculated on a voxel-by-voxel level. Monoenergetic proton tracks generated using Geant4-DNA were imported into SuperTrack, a GPU-accelerated software for calculation of microdosimetric spectra. Libraries of proton lineal energy spectra which span the energy range of 0-300MeV were computed. The libraries were validated by comparison to Monte Carlo calculations in the literature, as well as lineal energy spectra measured experimentally with a tissue equivalent proportional counter. The lineal energy libraries have been made available in three data formats, two are plain-text,.csv and.les, and one binary encoded, root. Library files include the lineal energy bin abscissa in keV per micron and the unnormalized number of counts occurring within that bin. A computational technique for summation of the library files to yield the lineal energy of a polyenergetic beam is described in this work. The lineal energy libraries can be used to rapidly determine the lineal energy spectra at the location of cell cultures for in-vitro experiments and in each voxel of a treatment plan for in-vivo outcome modelling. These libraries have already been incorporated into RayStation 2023B-IonPG for lineal energy spectra calculation and we anticipate they will be incorporated into further dose calculation engines and Monte Carlo toolkits.

Relative Biological Effectiveness (RBE) of Monoenergetic Protons: Comparison of Empirical and Biophysical Models

A constant proton relative biological effectiveness (RBE) of 1.1 for tumor control is currently used in proton therapy treatment planning. However, in vitro, in vivo and clinical experiences indicate that proton RBE varies with kinetic energy and, therefore, tissue depth within proton Bragg peaks. A number of published RBE models capture variations in proton RBE with depth. The published models can be sub-divided into empirical (or phenomenological) and biophysical (or mechanistic-inspired) RBE models. Empirical RBE models usually characterize the beam quality through the dose-averaged linear energy transfer (LETD), while most biophysical RBE models relate RBE to the dose-averaged lineal energy (yD). In this work, an analytic microdosimetry model and the Monte Carlo damage simulation code (MCDS) were utilized for the evaluation of the LETD and yD of monoenergetic proton beams in the clinically relevant energy range of 1–250 MeV. The calculated LETD and yD values were then used for the estimation of the RBE for five different cell types at three dose levels (2 Gy, 5 Gy and 7 Gy). Comparisons are made between nine empirical RBE models and two biophysical models, namely, the theory of dual radiation action (TDRA) and the microdosimetric kinetic model (MKM). The results show that, at conventional dose fractions (~2 Gy) and for proton energies which correspond to the proximal and central regions of the spread-out Bragg peak (SOBP), RBE varies from 1.0 to 1.2. At lower proton energies related to the distal SOBP, we find significant deviations from a constant RBE of 1.1, especially for late-responding tissues (low (α/β)R of ~1.5–3.5 Gy) where proton RBE may reach 1.3 to 1.5. For hypofractionated dose fractions (5–7 Gy), deviations from a constant RBE of 1.1 are smaller, but may still be sizeable, yielding RBE values between 1.15 and 1.3. However, large discrepancies among the different models were observed that make the selection of a variable RBE across the SOBP uncertain.

Prediction of normal tissue complication probability for rat spinal cord tolerance following ion irradiations

Objective.Currently, treatment planning in cancer hadrontherapy relies on dose-volume criteria and physical quantities constraints. However, incorporating biologically related models of tumor control probability and of normal tissue complication probability (NTCP) would help further minimizing adverse tissue reactions, and would allow achieving a more patient-specific strategy. The aim of this work was therefore the development of a mechanistic approach to predict NTCP for late tissue reactions following ion irradiation.Approach.A dataset on the tolerance of the rat spinal cord was considered, providing NTCP (for paresis of at least grade II) experimental data following irradiation by photons, protons, helium and carbon ions, under different fractionation schemes. The photon data were fit by a mechanistic NTCP model with four parameters, called Critical Element Model; this allowed fixing the two parameters that only depend on the tissue features. Afterwards, the two parameters depending on radiation quality were predicted by applying the BIophysical ANalysis of Cell death and chromosome Aberrations biophysical model, for each ion type and dose-averaged linear energy transfer value.Main results.The predicted NTCP curves for ion irradiation were tested against the ion experimental data, by Chi-Square andp-value calculations. The model passed a significance test at 1% for all the datasets, and 5% for 13 out of 16 datasets, thus showing a good predictive power. The Relative biological effectiveness (RBE) was also calculated and compared with the data for the endpoint of NTCP equal to 50%, and a considerable discrepancy with the commonly calculated RBE for cell survival was shown.Significance.This study highlights the importance of considering the endpoint of interest when computing the RBE, through the application of a NTCP model, and it represents a first step towards the development of an approach to improve treatment plan optimization in therapy. To this aim, the approach needs to be extended to other endpoints and to be applied to patients' data.

Investigating LETd optimization strategies in carbon ion radiotherapy for pancreatic cancer: a dosimetric study using an anthropomorphic phantom.

Clinical carbon ion beams offer the potential to overcome hypoxia-induced radioresistance in pancreatic tumors, due to their high dose-averaged Linear Energy Transfer (LETd), as previous studies have linked a minimum LETd within the tumor to improved local control. Current clinical practices at the Heidelberg Ion-Beam Therapy Center (HIT), which use two posterior beams, do not fully exploit the LETd advantage of carbon ions, as the high LETd is primarily focused on the beams' distal edges. Different LETd-boosting strategies, such as Spot-scanning Hadron Arc (SHArc), could enhance LETd distribution by concentrating high-LETd values in potential hypoxic tumor cores while sparing organs at risk. This study aims to investigate and verify different LETd-boosting strategies using an anthropomorphic pancreas phantom. Various LETd-boosting strategies were investigated for a cylindrical and a pancreas-shaped target in an anthropomorphic pancreas phantom. Treatment plans were optimized using single field optimization (SFO) or multi field optimization (MFO), with objective functions based on either physical dose (Phys), relative biological effectiveness(RBE)-weighted dose, or a combination of RBE and LETd-based objectives (LETopt). The LETd-boosting planning strategies were optimized with the goal of increasing the minimum LETd in the tumor without compromising its homogeneous dose coverage. Beam configurations investigated included the two-beam in-house clinical standard (2-SFOPhys, 2-SFORBE and 2-MFORBE-LETopt), a three-beam configuration (3-MFORBE and 3-MFORBE-LETopt) and SHArc (SHArcPhys, SHArcRBE and SHArcRBE-LETopt) using step-and-shoot delivery. The different plans were verified using an anthropomorphic pancreas phantom at HIT and compared to treatment planning system (TPS) predictions. All investigated LETd-boosting strategies altered the LETd distribution while meeting optimization goals and constraints, resulting in varying degrees of LETd enhancement. For the cylindrical volume, the SHArc plan resulted in the highest LETd concentration in the tumor core, with the minimum LETd in the GTV scaling up to 91keV/µm. For the pancreas-shaped volume, however, the 3-MFORBE-LETopt achieved a higher minimum LETd in the GTV than SHArcRBE (75.6 and 62.3keV/µm, respectively). When combining SHArc with LETd optimization, a minimum LETd of 76.3keV/µm was achieved, suggesting a potential benefit from this combined approach. Most dosimetric verifications showed dose deviations to the TPS within a 5% range, for both beam-per-beam and total dose. LETd-optimized and SHArc plans exhibited slightly higher mean dose deviations (2.0%-4.6%) compared to the standard RBE-based plans (<1.5%). This study demonstrated the feasibility of enhancing LETd in pancreatic tumors using carbon ion arc delivery coupled with LETd optimization. The possibility of delivering these plans was verified through irradiation of an anthropomorphic pancreas phantom, which showed agreement between dose measurements and predictions.

Recommendations for reporting and evaluating proton therapy beyond dose and constant relative biological effectiveness.

In proton therapy, a relative biological effectiveness (RBE) of 1.1 is used to convert proton dose into an equivalent photon dose. However, RBE varies with tissue type, fraction dose, and beam quality parameters beyond dose such as linear energy transfer (LET) raising concerns about increased local effectiveness and potential toxicity. This work aims to harmonize quantities used for clinical consideration of variable RBE for proton therapy. A survey was distributed to proton centres to determine agreement on RBE-related concerns and clinical implementations. A subsequent clinical expert meeting facilitated by the European Particle Therapy Network was held to achieve consensus and to make clinical recommendations how to prescribe and report beyond using dose and constant RBE. The survey was answered by 17 out of 23 centres contacted (74%). For proton RBE, most concerns existed regarding toxicity in serial organs, while the assumption of an RBE of 1.1 was considered valid for targets. Most physicists intended to consider a physical quantity beyond dose in clinical decision making. A constant RBE of 1.1 was the consensus for prescribing dose. However, current practice of recording and reporting dose in proton therapy must be complemented: the recommended quantity beyond dose was the dose-averaged LET in water from primary and secondary protons, normalized to unit density. This will facilitate analyses of treatment data on effectiveness beyond dose and between centres. No consensus on a single variable RBE model was found. More clinical training on proton RBE is needed.

Commissioning of a commercial treatment planning system for scanned carbon-ion radiotherapy.

To commission the RayStation (RS) TPS (treatment planning system) for scanned CIRT (carbon-ion radiotherapy) utilizing pencil beam algorithms (PBv4.2). The beam model commissioning entailed employing 1D single beams and 2D monoenergetic fields to validate spot profiles with films, assess beam range using Peakfinder measurements, and evaluate fragment spectra through dose-averaged linear energy transfer (LETd) calculations. 3D dose distributions were verified in homogeneous phantoms for both absorbed and relative biological effectiveness (RBE)-weighted doses, and further assessed in double wedge and anthropomorphic phantoms for absorbed dose only. Finally, RBE-weighted dose verification and patient-specific quality assurance were conducted using 58 beams from 20 clinically treated patient plans. The results demonstrated good agreement in absolute dose distribution between TPS calculations and measurements, with mean dose discrepancies within 3%. However, deviations were slightly higher (>1%) for the cases involving the range shifter (RaShi) compared to those without the RaShi (<1%). Beam range, depth dose distribution, and lateral profiles of spread-out Bragg peaks (SOBPs) closely matched between RS TPS calculations and measurements. Some discrepancies (less than 0.5mm) were observed at field edges and in penumbra regions due to limitations in simulating asymmetrical spots, but within clinical tolerance. After model tuning, RBE-weighted dose calculations in RS TPS were in agreement with those from the clinically used TPS, except for variations exceeding 3% observed at energies exceeding 408.07 MeV/u, primarily attributed to fragment spectra differences. Overall, this study validated the RS TPS for calculating absorbed doses against measurements and RBE-weighted doses against a clinically used TPS. The results suggested that the RS TPS could be utilized for CIRT treatment planning, except for energies exceeding 408.07 MeV/u.

Oxygen consumption measurements at ultra-high dose rate over a wide LET range.

The role of radiolytic oxygen consumption for the in-vitro "Ultra-High Dose Rate" (UHDR) sparing and in-vivo FLASH effect is subject to active debate, but data on key dependencies such as the radiation quality are lacking. The influence of "dose-averaged Linear Energy Transfer" (LETd) and dose rate on radiolytic oxygen consumption was investigated by monitoring the oxygen concentration during irradiation with electrons, protons, helium, carbon, and oxygen ions at UHDR and "Standard Dose Rates" (SDR). Sealed "Bovine Serum Albumin" (BSA) 5% samples were exposed to 15Gy of electrons and protons, and for the first time helium, carbon, and oxygen ions with LETd values of 1, 5.4, 14.4, 65, and 100.3keV/µm, respectively, delivered at mean dose rates of either 0.3-0.4Gy/s for SDR or approximately 100Gy/s for UHDR. The Oxylite (Oxford Optronics) system allowed measurements of the oxygen concentration before and after irradiation to calculate the oxygen consumption rate. The oxygen consumption rate was found to decrease with increasing LETd from 0.351mmHg/Gy for low LET electrons to 0.1796mmHg/Gy for high LET oxygen ions at SDR and for UHDR from 0.317 to 0.1556mmHg/Gy, respectively. A higher consumption rate for SDR irradiation compared to the corresponding UHDR irradiation persisted for all particle types. The measured consumption rates demonstrate a distinct LETd dependence. The obtained dataset, encompassing a wide range of LETd values, could serve as a benchmark for Monte Carlo simulations, which may aid in enhancing our comprehension of oxygen-related mechanisms after irradiations. Ultimately, they could help assess the viability of different hypotheses regarding UHDR sparing mechanisms and the FLASH effect. The found LETd dependence underscores the potential of heavy ion therapy, wherein elevated consumption rates in adjacent normal tissue offer protective benefits, while leaving tumor regions with generally higher "Linear Energy Transfer" (LET) vulnerable.

The association of linear energy transfer and dose with radiation necrosis after pencil beam scanning proton therapy in pediatric posterior fossa tumors: Association of dose and LET with radiation necrosis

IntroductionProton therapy is the preferred treatment modality for most pediatric central nervous system (CNS) tumors. The risk of radiation necrosis may be increased at the distal end of the beam due to an increase in linear energy transfer (LET) and relative biological effective (RBE) dose. We report on the association of linear energy transfer (LET) and dose with radiation necrosis after pencil beam scanning proton therapy in pediatric posterior fossa tumors using a case-control framework. Materials and MethodsFrom 2019 to 2022, 33 patients less than or equal to 18 years of age treated with first line proton therapy for primary tumors in the posterior fossa and with 6 or more months of follow up MRI imaging were retrospectively identified. Nine patients with imaging changes consistent with necrosis were matched with controls in a 1:2 fashion based on age, sex, dose, and follow-up time from proton therapy. Dose [Gy (RBE)] and dose-averaged LET (LETd) values for target structures and organs at risk (OAR) were computed and compared between cases and controls. ResultsWithin the whole cohort, mean age was 6.6 years (SD=4.77) with a median follow up time of 24.1 months. Within the case-control matched cohort (18 controls, 9 cases), there were no significant differences in age, sex, time to follow up, tumor location, dose, and use of concurrent chemotherapy. Mean time to necrotic imaging finding was 4.47 months (SD=2.03). Cases demonstrated significantly higher brainstem D50 (p=0.02). LETd was not different between cases and controls. However, when using a combined metric of higher brainstem dose (> 47.5 [Gy (RBE)]) and higher LETd (>3.5 keV/µm), a greater proportion of cases compared to controls met this metric (89% vs. 39%, p=0.02). ConclusionsCombined effects of intermediate-to-high dose and LETd in the brainstem may contribute to greater necrosis risk after pencil beam scanning proton therapy in children with posterior fossa tumors.

Interpreting the biological effects of protons as a function of physical quantity: linear energy transfer or microdosimetric lineal energy spectrum?

The choice of appropriate physical quantities to characterize the biological effects of ionizing radiation has evolved over time coupled with advances in scientific understanding. The basic hypothesis in radiation dosimetry is that the energy deposited by ionizing radiation initiates all the consequences of exposure in a biological sample (e.g., DNA damage, reproductive cell death). Physical quantities defined to characterize energy deposition have included dose, a measure of the mean energy imparted per unit mass of the target, and linear energy transfer (LET), a measure of the mean energy deposition per unit distance that charged particles traverse in a medium. The primary advantage of using the “dose and LET” physical system is its relative simplicity, especially for presenting and recording results. Inclusion of additional information such as the energy spectrum of charged particles renders this approach adequate to describe the biological effects of large dose levels from homogeneous sources. The primary disadvantage of this system is that it does not provide a unique description of the stochastic nature of radiation interactions. We and others have used dose-averaged LET (LETd) as a correlative physical quantity to the relative biological effectiveness (RBE) of proton beams. This approach is based on established experimental findings that proton RBE increases with LETd. However, this approach might not be applicable to intensity-modulated proton therapy or other applications in which the proton energy spectrum is highly heterogeneous. In the current study, we irradiated cancer cells with scanning proton beams with identical LETd (3.4 keV/µm) but arising from two different proton energy/LET spectra (a narrow spectrum in group 1 and a widespread heterogeneous spectrum in group 2). Clonogenic survival after irradiation revealed significant differences in RBE at any cell surviving fraction: e.g., at a surviving fraction of 0.1, the RBE was 0.97 ± 0.03 in group 1 and 1.16 ± 0.04 in group 2 (p≤0.01), validating our hypothesis that LETd alone may not adequately indicate proton RBE. Further analysis showed that microdosimetric spectrum (the probability density function of the stochastic physical quantity lineal energy y) was helpful for interpreting observed differences in biological effects. However, more accurate use of microdosimetric spectrum to quantify RBE requires a cell line–specific mechanistic model.

Dose-averaged linear energy transfer within the gross tumor volume of non-small-cell lung cancer affects the local control in carbon-ion radiotherapy

Background and purposeHigh linear energy transfer (LET) radiation exhibits stronger tumor-killing effect. However, the correlation between LET and the therapeutic efficacy in Carbon-ion radiotherapy (CIRT) for locally advanced non-small-cell lung cancer (LA-NSCLC) is currently not clear. This study aimed to investigate the relationship between the dose-averaged LET (LETd) distribution within tumor and local recurrence for LA-NSCLC treated with CIRT. Methods and materialsAn analysis of 62 consecutive patients with LA-NSCLC who underwent CIRT from 2018 to 2022 was conducted. The LETd distribution was calculated based on their treated plans, and the correlation between local recurrence and LETd, relative biological effectiveness (RBE)-weighted doses (DRBE) and clinical factors was investigated. Receiver operating characteristic (ROC) curve, log-rank test, and Cox regression analysis were performed based on that. Results16 patients were defined as local recurrence. Overall survival (OS) and local control (LC) at 24 months were 76.9 % and 73.2 %, respectively. The mean LETd in internal gross tumor volume (iGTV) in the local recurrence group was 48.7 keV/µm, significantly lower than the mean LETd of 53.2 keV/µm in the local control group (p = 0.016). No significant difference was observed in DRBE between the local recurrence and local control groups. ROC curve analysis indicated that a percentage of 88 % of volume in iGTV receiving at least 40 keV/µm (V40keV/μm) is the optimal threshold for predicting local recurrence (Area under curve (AUC) = 0.7636). The log-rank test and Cox regression analysis revealed that the LETd value covering 98 % volume of iGTV (LETd98%) was a significant risk factor for LC (p = 0.020). ConclusionsOur study revealed an association between LETd distribution and local recurrence in patients with LA-NSCLC. These findings suggest that lower LETd may increase the probability of local recurrence. We suggest that LETd distribution within iGTV should be routinely assessed in CIRT for lung cancer.

LET-based approximation of the microdosimetric kinetic model for proton radiotherapy.

Phenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose-averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory-based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry-based models in LET-based proton therapy treatment planning systems poses challenges. This work presents a LET-based version of the MKM that is practical for clinical use in proton radiotherapy. At first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively-sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons. A simple allometric function was found able to describe the relationship between the dose-averaged LET of protons and the dose-mean lineal energy, which includes the contributions of secondary particles. The LET-based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread-out Bragg peak (SOBP) proton beams. The results of the LET-based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed. The LET-based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose-averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.

Variations in linear energy transfer distributions within a European proton therapy planning comparison of paediatric posterior fossa tumours

Background and PurposeRadiotherapy for paediatric posterior fossa tumours may cause complications in the brainstem and upper spinal cord due to high doses. With proton therapy (PT) this risk may increase due to higher relative biological effectiveness (RBE) from elevated linear energy transfer (LET). This study assesses variations in LET in the brainstem and spinal cord in proton treatment plans from European centres. Materials and MethodsTen European PT centres using spot-scanning PT planned two paediatric posterior fossa cases: One overlapping partly with the brainstem and upper spinal cord, prescribed 54 Gy(RBE), and the second wrapping around these organs, prescribed 59.4 Gy(RBE). Dose-averaged LET distributions were assessed in volumes of the brainstem and spinal cord irradiated to over 50 Gy(RBE = 1.1). The maximum hinge angle effect on near-maximum RBE-weighted doses using the Unkelbach RBE model was also investigated. ResultsIn the first case, the mean LET in brainstem volumes receiving more than 50 Gy(RBE = 1.1) ranged from 2.8 keV/µm to 3.6 keV/µm across centres (median: 3.3 keV/µm). In the second case, treatment plans showed a narrower range of mean LET in the brainstem, from 2.5 keV/µm to 2.8 keV/µm (median: 2.7 keV/µm). There was no statistically significant impact of the maximum hinge angle. ConclusionsLET distributions vary across centres due to different techniques but are also influenced significantly by factors like shape and position of the target volume.

A deep learning model for predicting the modified micro-dosimetric kinetic model-based dose and the dose-averaged linear energy transfer for prostate cancer in carbon ion therapy

Adaptive carbon ion radiotherapy for localized prostate cancer requires accurate evaluation of biological dose and dose-averaged linear energy transfer (LETd) changes. This study developed a deep learning model to rapidly predict the modified micro-dosimetric kinetic model (mMKM)-based dose and LETd distributions. Using data from fifty patients for training and testing, the model achieved gamma passing rates exceeding 96% compared to true mMKM-based dose and LETd recalculated from local effect model I (LEM I) plans. Incorporating computed tomography images, contours, physical dose, and LEM I-based dose as inputs, this model provided a rapid, accurate tool for comprehensive evaluations.

Investigate potential clinical benefits and linear energy transfer sparing utilizing proton arc therapy for hepatocellular carcinoma

PurposeTo investigate the potential clinical benefits and dose-averaged Linear Energy Transfer (LETd) sparing, utilizing proton arc plan for hepatocellular carcinoma (HCC) patients in comparison with Intensity Modulated Proton Therapy (IMPT). MethodsTen HCC patients have been retrospectively selected. Two planning groups were created: Proton Arc plans using Monaco ver. 6 and the clinical IMPT plan. Both planning groups used the same robustness parameters. The prescription dose is 67.5 Gy (RBE) in 15 fractions of the Clinical Target Volume (CTV). Robustness evaluations were performed to ensure dose coverage. Normal Tissue Complicated Probability (NTCP) model was utilized to predict the possibility of Radiation-Induced Liver Disease (RILD) and evaluate the potential benefit of proton arc therapy. LETd calculation and evaluation were performed as well. ResultsProton arc plan has shown better dosimetric improvements of most Organ-At-Risks (OARs). More specifically, the liver mean dose has been significantly reduced from 14.7 GyE to 10.62 GyE compared to the IMPT plan. The predicted possibility of RILD has also been significantly reduced for cases with a large and deep liver target where healthy liver tissue sparing is a challenge. Additionally, proton arc therapy could increase the average LETd in the target and reduce LETd in adjacent OARs. ConclusionsThe potential clinical benefit of utilizing proton arc therapy HCC varies depending on the patient-specific geometry. With more freedom, proton arc therapy can offer a better dosimetric plan quality in the challenge cases, which might not be feasible using the current IMPT technique.

First Dosimetric and Biological Verification for Spot-Scanning Hadron Arc Radiation Therapy With Carbon Ions

Purpose: Spot-scanning Hadron Arc therapy (SHArc) is a novel delivery technique for ion beams with potentially improved dose conformity and dose-averaged linear energy transfer (LETd) redistribution. The first dosimetric validation and in vitro verification of carbon ion arc delivery is presented. Methods: Intensity Modulated Particle Therapy (IMPT) and SHArc plans were designed to deliver homogenous physical dose or biological dose in a cylindrical PMMA phantom. Additional IMPT carbon plans were optimized for testing different LETd-boosting strategies. Verifications of planned doses were performed with an ionization chamber and clonogenic survival assay was conducted using A549 cancer lung cell line. Radiation-induced nuclear 53BP1 foci were assessed to evaluate the cellular response in both normoxic and hypoxic conditions. Results: Dosimetric measurements and clonogenic assay results showed a good agreement to planned dose and survival distributions. Measured survival fractions and foci confirmed carbon ions SHArc as potential modality to overcome hypoxia-induced radio-resistance. LETd-boosted IMPT plans reached similar LETd in the target as in SHArc plans promising similar features against hypoxia but at the cost of an increased entrance dose. SHArc resulted, however, in a lower dose bath but in a larger volume around the target. Conclusion: The first proof of principle of carbon ions SHArc delivery was performed and experimental evidence suggests this novel modality as an attractive approach for treating hypoxic tumor.

In Silico Study of Simultaneous Integrated Boost Carbon-Ion Radiotherapy for Locally Advanced Pancreatic Cancer.

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. 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. 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. 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.

A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy

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 (LET d ) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LET d is 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). LET d predictions were compared to MC-simulated results in clinically relevant regions of interest. We assessed the impact on NTCP models by leveraging LET d predictions 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 LET d distributions. Root mean squared errors (RMSE) for the median LET d within 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 LET d based 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.

Assessment of fluence- and dose-averaged linear energy transfer with passive luminescence detectors in clinical proton beams

Objective. This work investigates the use of passive luminescence detectors to determine different types of averaged linear energy transfer ( LET― ) for the energies relevant to proton therapy. The experimental results are compared to reference values obtained from Monte Carlo simulations. Approach. Optically stimulated luminescence detectors (OSLDs), fluorescent nuclear track detectors (FNTDs), and two different groups of thermoluminescence detectors (TLDs) were irradiated at four different radiation qualities. For each irradiation, the fluence- ( LET―f ) and dose-averaged LET ( LET―d ) were determined. For both quantities, two sub-types of averages were calculated, either considering the contributions from primary and secondary protons or from all protons and heavier, charged particles. Both simulated and experimental data were used in combination with a phenomenological model to estimate the relative biological effectiveness (RBE). Main results. All types of LET― could be assessed with the luminescence detectors. The experimental determination of LET―f is in agreement with reference data obtained from simulations across all measurement techniques and types of averaging. On the other hand, LET―d can present challenges as a radiation quality metric to describe the detector response in mixed particle fields. However, excluding secondaries heavier than protons from the LET―d calculation, as their contribution to the luminescence is suppressed by ionization quenching, leads to equal accuracy between LET―f and LET―d . Assessment of RBE through the experimentally determined LET―d values agrees with independently acquired reference values, indicating that the investigated detectors can determine LET― with sufficient accuracy for proton therapy. Significance. OSLDs, TLDs, and FNTDs can be used to determine LET― and RBE in proton therapy. With the capability to determine dose through ionization quenching corrections derived from LET― , OSLDs and TLDs can simultaneously ascertain dose, LET― , and RBE. This makes passive detectors appealing for measurements in phantoms to facilitate validation of clinical treatment plans or experiments related to proton therapy.