Robust treatment planning of dose painting for prostate cancer based on ADC-to-Gleason score mappings - what is the potential to increase the tumor control probability?

BACKGROUND AND PURPOSE: The aim of this study was to evaluate the potential to increase the tumor control probability (TCP) with 'dose painting by numbers' (DPBN) plans optimized in a treatment planning system (TPS) compared to uniform dose plans. The DPBN optimization was based on our earlier published formalism for prostate cancer that is driven by dose-responses of Gleason scores mapped from apparent diffusion coefficients (ADC). MATERIAL AND METHODS: For 17 included patients, a set of DPBN plans were optimized in a TPS by maximizing the TCP for an equal average dose to the prostate volume (CTVT) as for a conventional uniform dose treatment. For the plan optimizations we applied different photon energies, different precisions for the ADC-to-Gleason mappings, and different CTVT positioning uncertainties. The TCP increasing potential was evaluated by the DPBN efficiency, defined as the ratio of TCP increases for DPBN plans by TCP increases for ideal DPBN prescriptions (optimized without considering radiation transport phenomena, uncertainties of the CTVT positioning, and uncertainties of the ADC-to-Gleason mapping). RESULTS: The median DPBN efficiency for the most conservative planning scenario optimized with a low precision ADC-to-Gleason mapping, and a positioning uncertainty of 0.6 cm was 10%, meaning that more than half of the patients had a TCP gain of at least 10% of the TCP for an ideal DPBN prescription. By increasing the precision of the ADC-to-Gleason mapping, and decreasing the positioning uncertainty the median DPBN efficiency increased by up to 40%. CONCLUSIONS: TCP increases with DPBN plans optimized in a TPS were found more likely with a high precision mapping of image data into dose-responses and a high certainty of the tumor positioning. These findings motivate further development to ensure precise mappings of image data into dose-responses and to ensure a high spatial certainty of the tumor positioning when implementing DPBN clinically.

Universal field matching in craniospinal irradiation by a background-dose gradient-optimized method.

PURPOSE: The gradient-optimized methods are overcoming the traditional feathering methods to plan field junctions in craniospinal irradiation. In this note, a new gradient-optimized technique, based on the use of a background dose, is described. METHODS: Treatment planning was performed by RayStation (RaySearch Laboratories, Stockholm, Sweden) on the CT scans of a pediatric patient. Both proton (by pencil beam scanning) and photon (by volumetric modulated arc therapy) treatments were planned with three isocenters. An 'in silico' ideal background dose was created first to cover the upper-spinal target and to produce a perfect dose gradient along the upper and lower junction regions. Using it as background, the cranial and the lower-spinal beams were planned by inverse optimization to obtain dose coverage of their relevant targets and of the junction volumes. Finally, the upper-spinal beam was inversely planned after removal of the background dose and with the previously optimized beams switched on. RESULTS: In both proton and photon plans, the optimized cranial and the lower-spinal beams produced a perfect linear gradient in the junction regions, complementary to that produced by the optimized upper-spinal beam. The final dose distributions showed a homogeneous coverage of the targets. DISCUSSION: Our simple technique allowed to obtain high-quality gradients in the junction region. Such technique universally works for photons as well as protons and could be applicable to the TPSs that allow to manage a background dose.

Tuning spatially fractionated radiotherapy dose profiles using the moiré effect.

Spatially Fractionated Radiotherapy (SFRT) has demonstrated promising potential in cancer treatment, combining the advantages of reduced post-radiation effects and enhanced local control rates. Within this paradigm, proton minibeam radiotherapy (pMBRT) was suggested as a new treatment modality, possibly producing superior normal tissue sparing to conventional proton therapy, leading to improvements in patient outcomes. However, an effective and convenient beam generation method for pMBRT, capable of implementing various optimum dose profiles, is essential for its real-world application. Our study investigates the potential of utilizing the moiré effect in a dual collimator system (DCS) to generate pMBRT dose profiles with the flexibility to modify the center-to-center distance (CTC) of the dose distribution in a technically simple way.We employ the Geant4 Monte Carlo simulations tool to demonstrate that the angle between the two collimators of a DCS can significantly impact the dose profile. Varying the DCS angle from 10 ∘ to 50 ∘ we could cover CTC ranging from 11.8 mm to 2.4 mm, respectively. Further investigations reveal the substantial influence of the multi-slit collimator's (MSC) physical parameters on the spatially fractionated dose profile, such as period (CTC), throughput, and spacing between MSCs. These findings highlight opportunities for precision dose profile adjustments tailored to specific clinical scenarios.The DCS capacity for rapid angle adjustments during the energy transition stages of a spot scanning system can facilitate dynamic alterations in the irradiation profile, enhancing dose contrast in normal tissues. Furthermore, its unique attribute of spatially fractionated doses in both lateral directions could potentially improve normal tissue sparing by minimizing irradiated volume. Beyond the realm of pMBRT, the dual MSC system exhibits remarkable versatility, showing compatibility with different types of beams (X-rays and electrons) and applicability across various SFRT modalities.Our study illuminates the dual MSC system's potential as an efficient and adaptable tool in the refinement of pMBRT techniques. By enabling meticulous control over irradiation profiles, this system may expedite advancements in clinical and experimental applications, thereby contributing to the evolution of SFRT strategies.

Novel radiation quality metrics accounting for proton energy spectra for RBE proton models.

BACKGROUND: For proton therapy, a relative biological effectiveness (RBE) of 1.1 is widely applied clinically. However, due to abundant evidence of variable RBE in vitro, and as suggested in studies of patient outcomes, RBE might increase by the end of the proton tracks, as described by several proposed variable RBE models. Typically, the dose averaged linear energy transfer ( LET d $\text{LET}_d$ ) has been used as a radiation quality metric (RQM) for these models. However, the optimal choice of RQM has not been fully explored. PURPOSE: This study aims to propose novel RQMs that effectively weight protons of different energies, and assess their predictive power for variable RBE in proton therapy. The overall objective is to identify an RQM that better describes the contribution of individual particles to the RBE of proton beams. METHODS: High-throughput experimental set-ups of in vitro cell survival studies for proton RBE determination are simulated utilizing the SHIELD-HIT12A Monte Carlo particle transport code. For every data point, the proton energy spectra are simulated, allowing the calculation of novel RQMs by applying different power levels to the spectra of LET or effective Q $Q$ ( Q eff $Q_\mathrm{eff}$ ) values. A phenomenological linear-quadratic-based RBE model is then applied to the in vitro data, using various RQMs as input variables, and the model performance is evaluated by root-mean-square-error (RMSE) for the logarithm of cell surviving fractions of each data point. RESULTS: Increasing the power level, that is, putting an even higher weight on higher LET particles when constructing the RQM is generally associated with an increased model performance, with dose averaged LET 3 $\text{LET}^3$ (i.e., dose averaged cubed LET, cLET d $\mathrm{cLET}_d$ ) resulting in a RMSE value 0.31, compared to 0.45 for a model based on (linearly weighted) LET d $\text{LET}_d$ , with similar trends also observed for track averaged and Q eff $Q_\mathrm{eff}$ -based RQMs. CONCLUSIONS: The results indicate that improved proton variable RBE models can be constructed assuming a non-linear RBE(LET) relationship for individual protons. If similar trends hold also for an in vitro-environment, variable RBE effects are likely better described by cLET d $\mathrm{cLET}_d$ or tracked averaged cubed LET ( cLET t $\mathrm{cLET}_t$ ), or corresponding Q eff $Q_\mathrm{eff}$ -based RQM, rather than linearly weighted LET d $\text{LET}_d$ or LET t $\text{LET}_t$ which is conventionally applied today.

Treatment planning of scanned proton beams in RayStation.

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

The dirty and clean dose concept: Towards creating proton therapy treatment plans with a photon-like dose response.

BACKGROUND: Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1. PURPOSE: This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon-like dose response for OAR and, thus, less uncertainties when applying photon-based tolerance doses. METHODS: The concept divides the 1.1-weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon-like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1-weighted dose, variable RBE-weighted dose using the Wedenberg RBE model and dose-average LETd distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives. RESULTS: In the water phantom studies, LET thresholds between 1.5 and 2.5 keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1-weighted dose in the OARs was slightly increased (patient 1: 0.45 Gy(RBE), patient 2: 0.08 Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1-weighted dose in healthy brain tissue was observed (patient 1: 0.81 Gy(RBE), patient 2: 0.53 Gy(RBE)). The variation of NTCP values due to variation of α/ß from 2 to 3 Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp). CONCLUSIONS: The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon-like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon-based tolerance doses for OAR.

Investigation on the physical dose filtered by linear energy transfer for treatment plan evaluation in carbon ion therapy.

BACKGROUND: Large tumor size has been reported as a predicting factor for inferior clinical outcome in carbon ion radiotherapy (CIRT). Besides the clinical factors accompanied with such tumors, larger tumors receive typically more low linear energy transfer (LET) contributions than small ones which may be the underlying physical cause. Although dose averaged LET is often used as a single parameter descriptor to quantify the beam quality, there is no evidence that this parameter is the optimal clinical predictor for the complex mixed radiation fields in CIRT. PURPOSE: Purpose of this study was to investigate on a novel dosimetric quantity, namely high-LET-dose ( D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the physical dose filtered based on an LET threshold) as a single parameter estimator to differentiate between carbon ion treatment plans (cTP) with a small and large tumor volume. METHODS: Ten cTPs with a planning target volume, PTV ≥ 500 cm 3 $\mathrm{PTV}\ge {500}\,{{\rm cm}^{3}}$ (large) and nine with a PTV < 500 cm 3 $\mathrm{PTV}<{500}\,{{\rm cm}^{3}}$ (small) were selected for this study. To find a reasonable LET threshold ( L thr $\textrm {L}_{\textrm {thr}}$ ) that results in a significant difference in terms of D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ , the voxel based normalized high-LET-dose ( D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) distribution in the clinical target volume (CTV) was studied on a subset (12 out of 19 cTPs) for 18 LET thresholds, using standard distribution descriptors (mean, variance and skewness). The classical dose volume histogram concept was used to evaluate the D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ distributions within the target of all 19 cTPs at the before determined L thr $\textrm {L}_{\textrm {thr}}$ . Statistical significance of the difference between the two groups in terms of mean D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ volume histogram parameters was evaluated by means of (two-sided) t-test or Mann-Whitney-U-test. In addition, the minimum target coverage at the above determined L thr $\textrm {L}_{\textrm {thr}}$ was compared and validated against three other thresholds to verify its potential in differentiation between small and large volume tumors. RESULTS: An L thr $\textrm {L}_{\textrm {thr}}$ of approximately 30 keV / µ m ${30}\,{\rm keV/}\umu {\rm m}$ was found to be a reasonable threshold to classify the two groups. At this threshold, the D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ were significantly larger ( p < 0.05 $p<0.05$ ) in small CTVs. For the small tumor group, the near-minimum and median D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ (and D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) in the CTV were in average 9.3 ± 1.5 Gy $9.3\pm {1.5}\,{\rm Gy}$ (0.31 ± 0.08) and 13.6 ± 1.6 Gy $13.6\pm {1.6}\,{\rm Gy}$ (0.46 ± 0.06), respectively. For the large tumors, these parameters were 6.6 ± 0.2 Gy $6.6\pm {0.2}\,{\rm Gy}$ (0.20 ± 0.01) and 8.6 ± 0.4 Gy $8.6\pm {0.4}\,{\rm Gy}$ (0.28 ± 0.02). The difference between the two groups in terms of mean near-minimum and median D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ ( D ̂ > L thr $\hat{\textrm {D}}_{>\textrm {L}_{\textrm {thr}}}$ ) was 2.7 Gy (11%) and 5.0 Gy (18%), respectively. CONCLUSIONS: The feasibility of high-LET-dose based evaluation was shown in this study where a lower D > L thr $\textrm {D}_{>\textrm {L}_{\textrm {thr}}}$ was found in cTPs with a large tumor size. Further investigation is needed to draw clinical conclusions. The proposed methodology in this work can be utilized for future high-LET-dose based studies.

Dose averaged linear energy transfer optimization for large sacral chordomas in carbon ion therapy.

BACKGROUND: Carbon ion beams are well accepted as densely ionizing radiation with a high linear energy transfer (LET). However, the current clinical practice does not fully exploit the highest possible dose-averaged LET (LETd) and, consequently, the biological potential in the target. This aspect becomes worse in larger tumors for which inferior clinical outcomes and corresponding lower LETd was reported. PURPOSE: The vicinity to critical organs in general and the inferior overall survival reported for larger sacral chordomas treated with carbon ion radiotherapy (CIRT), makes the treatment of such tumors challenging. In this work it was aimed to increase the LETd in large volume tumors while maintaining the relative biological effectiveness (RBE)-weighted dose, utilizing the LETd optimization functions of a commercial treatment planning system (TPS). METHODS: Ten reference sequential boost carbon ion treatment plans, designed to mimic clinical plans for large sacral chordoma tumors, were generated. High dose clinical target volumes (CTV-HD) larger than 250 cm 3 $250 \,{\rm cm}^{3}$ were considered as large targets. The total RBE-weighted median dose prescription with the local effect model (LEM) was D RBE , 50 % = 73.6 Gy $\textrm {D}_{\rm RBE, 50\%}=73.6 \,{\rm Gy}$ in 16 fractions (nine to low dose and seven to high dose planning target volume). No LETd optimization was performed in the reference plans, while LETd optimized plans used the minimum LETd (Lmin) optimization function in RayStation 2023B. Three different Lmin values were investigated and specified for the seven boost fractions: L min = 60 keV / µ m $\textrm {L}_{\rm min}=60 \,{\rm keV}/{\umu }{\rm m}$ , L min = 80 keV / µ m $\textrm {L}_{\rm min}=80 \,{\rm keV}/{\umu }{\rm m}$ and L min = 100 keV / µ m $\textrm {L}_{\rm min}=100 \,{\rm keV}/{\umu }{\rm m}$ . To compare the LETd optimized against reference plans, LETd and RBE-weighted dose based goals similar to and less strict than clinical ones were specified for the target. The goals for the organs at risk (OAR) remained unchanged. Robustness evaluation was studied for eight scenarios ( ± 3.5 % $\pm 3.5\%$ range uncertainty and ± 3 mm $\pm 3 \,{\rm mm}$ setup uncertainty along the main three axes). RESULTS: The optimization method with L min = 60 keV / µ m $\textrm {L}_{\rm min}=60 \,{\rm keV}/{\umu }{\rm m}$ resulted in an optimal LETd distribution with an average increase of LET d , 98 % ${\rm {LET}}_{{\rm {d,}}98\%}$ (and LET d , 50 % ${\rm {LET}}_{{\rm {d,}}50\%}$ ) in the CTV-HD by 8.9 ± 1.5 keV / µ m $8.9\pm 1.5 \,{\rm keV}/{\umu }{\rm m}$ ( 27 % $27\%$ ) (and 6.9 ± 1.3 keV / µ m $6.9\pm 1.3 \,{\rm keV}/{\umu }{\rm m}$ ( 17 % $17\%$ )), without significant difference in the RBE-weighted dose. By allowing ± 5 % $\pm 5\%$ over- and under-dosage in the target, the LET d , 98 % ${\rm {LET}}_{{\rm {d,}}98\%}$ (and LET d , 50 % ${\rm {LET}}_{{\rm {d,}}50\%}$ ) can be increased by 11.3 ± 1.2 keV / µ m $11.3\pm 1.2 \,{\rm keV}/{\umu }{\rm m}$ ( 34 % $34\%$ ) (and 11.7 ± 3.4 keV / µ m $11.7\pm 3.4 \,{\rm keV}/{\umu }{\rm m}$ ( 29 % $29\%$ )), using the optimization parameters L min = 80 keV / µ m $\textrm {L}_{\rm min}=80 \,{\rm keV}/{\umu }{\rm m}$ . The pass rate for the OAR goals in the LETd optimized plans was in the same level as the reference plans. LETd optimization lead to less robust plans compared to reference plans. CONCLUSIONS: Compared to conventionally optimized treatment plans, the LETd in the target was increased while maintaining the RBE-weighted dose using TPS LETd optimization functionalities. Regularly assessing RBE-weighted dose robustness and acquiring more in-room images remain crucial and inevitable aspects during treatment.

Modelling tissue specific RBE for different radiation qualities based on a multiscale characterization of energy deposition.

PURPOSE: We present the nanoCluE model, which uses nano- and microdosimetric quantities to model RBE for protons and carbon ions. Under the hypothesis that nano- and microdosimetric quantities correlates with the generation of complex DNA double strand breakes, we wish to investigate whether an improved accuracy in predicting LQ parameters may be achieved, compared to some of the published RBE models. METHODS: The model is based on experimental LQ data for protons and carbon ions. We generated a database of track structure data for a number of proton and carbon ion kinetic energies with the Geant4-DNA Monte Carlo code. These data were used to obtain both a nanodosimetric quantity and a set of microdosimetric quantities. The latter were tested with different parameterizations versus experimental LQ-data to select the variable and parametrization that yielded the best fit. RESULTS: For protons, the nanoCluE model yielded, for the ratio of the linear LQ term versus the test data, a root mean square error (RMSE) of 1.57 compared to 1.31 and 1.30 for two earlier other published proton models. For carbon ions the RMSE was 2.26 compared to 3.24 and 5.24 for earlier published carbon ion models. CONCLUSION: These results demonstrate the feasibility of the nanoCluE RBE model for carbon ions and protons. The increased accuracy for carbon ions as compared to two other considered models warrants further investigation.

Plan robustness and RBE influence for proton dose painting by numbers for head and neck cancers.

PURPOSE: To investigate the feasibility of dose painting by numbers (DPBN) with respect to robustness for proton therapy for head and neck cancers (HNC), and to study the influence of variable RBE on the TCP and OAR dose burden. METHODS AND MATERIALS: Data for 19 patients who have been scanned pretreatment with PET-FDG and subsequently treated with photon therapy were used in the study. A dose response model developed for photon therapy was implemented in a TPS, allowing DPBN plans to be created. Conventional homogeneous dose and DPBN plans were created for each patient, optimized with either fixed RBE = 1.1 or a variable RBE model. Robust optimization was used to create clinically acceptable plans. To estimate the maximum potential loss in TCP due to actual SUV variations from the pre-treatment imaging, we applied a test case with randomized SUV distribution. RESULTS: Regardless of the use of variable RBE for optimization or evaluation, a statistically significant increase (p < 0.001) in TCP was found for DPBN plans as compared to homogeneous dose plans. Randomizing the SUV distribution decreased the TCP for all plans. A correlation between TCP increase and variance of the SUV distribution and target volume was also found. CONCLUSION: DPBN for protons and HNC is feasible and could lead to a TCP gain. Risks associated with the temporal variation of SUV distributions could be mitigated by imposing minimum doses to targets. The correlation found between TCP increase and SUV variance and target volume may be used for patient selection.

Shoot-through proton FLASH irradiation lowers linear energy transfer in organs at risk for neurological tumors and is robust against density variations.

Objective. The goal of the study was to test the hypothesis that shoot-through FLASH proton beams would lead to lower dose-averaged LET (LETD) values in critical organs, while providing at least equal normal tissue sparing as clinical proton therapy plans.Approach. For five neurological tumor patients, pencil beam scanning (PBS) shoot-through plans were made, using the maximum energy of 227 MeV and assuming a hypothetical FLASH protective factor (FPF) of 1.5. The effect of different FPF ranging from 1.2 to 1.8 on the clinical goals were also considered. LETDwas calculated for the clinical plan and the shoot-through plan, applying a 2 Gy total dose threshold (RayStation 8 A/9B and 9A-IonRPG). Robust evaluation was performed considering density uncertainty (±3% throughout entire volume).Main results.Clinical plans showed large LETDvariations compared to shoot-through plans and the maximum LETDin OAR is 1.2-8 times lower for the latter. Although less conformal, shoot-through plans met the same clinical goals as the clinical plans, for FLASH protection factors above 1.4. The FLASH shoot-through plans were more robust to density uncertainties with a maximum OAR D2%increase of 0.6 Gy versus 5.7 Gy in the clinical plans.Significance.Shoot-through proton FLASH beams avoid uncertainties in LETDdistributions and proton range, provide adequate target coverage, meet planning constraints and are robust to density variations.

3D-conformal very-high energy electron therapy as candidate modality for FLASH-RT: A treatment planning study for glioblastoma and lung cancer.

BACKGROUND: Pre-clinical ultra-high dose rate (UHDR) electron irradiations on time scales of 100 ms have demonstrated a remarkable sparing of brain and lung tissues while retaining tumor efficacy when compared to conventional dose rate irradiations. While clinically-used gantries and intensity modulation techniques are too slow to match such time scales, novel very-high energy electron (VHEE, 50-250 MeV) radiotherapy (RT) devices using 3D-conformed broad VHEE beams are designed to deliver UHDR treatments that fulfill these timing requirements. PURPOSE: To assess the dosimetric plan quality obtained using VHEE-based 3D-conformal RT (3D-CRT) for treatments of glioblastoma and lung cancer patients and compare the resulting treatment plans to those delivered by standard-of-care intensity modulated photon RT (IMRT) techniques. METHODS: Seven glioblastoma patients and seven lung cancer patients were planned with VHEE-based 3D-CRT using 3 to 16 coplanar beams with equidistant angular spacing and energies of 100 and 200 MeV using a forward planning approach. Dose distributions, dose-volume histograms, coverage (V95% ) and homogeneity (HI98% ) for the planning target volume (PTV), as well as near-maximum doses (D2% ) and mean doses (Dmean ) for organs-at-risk (OAR) were evaluated and compared to clinical IMRT plans. RESULTS: Mean differences of V95% and HI98% of all VHEE plans were within 2% or better of the IMRT reference plans. Glioblastoma plan dose metrics obtained with VHEE configurations of 200 MeV and 3-16 beams were either not significantly different or were significantly improved compared to the clinical IMRT reference plans. All OAR plan dose metrics evaluated for VHEE plans created using 5 beams of 100 MeV were either not significantly different or within 3% on average, except for Dmean for the body, Dmean for the brain, D2% for the brain stem, and D2% for the chiasm, which were significantly increased by 1, 2, 6, and 8 Gy, respectively (however below clinical constraints). Similarly, the dose metrics for lung cancer patients were also either not significantly different or were significantly improved compared to the reference plans for VHEE configurations with 200 MeV and 5 to 16 beams with the exception of D2% and Dmean to the spinal canal (however below clinical constraints). For the lung cancer cases, the VHEE configurations using 100 MeV or only 3 beams resulted in significantly worse dose metrics for some OAR. Differences in dose metrics were, however, strongly patient-specific and similar for some patient cases. CONCLUSIONS: VHEE-based 3D-CRT may deliver conformal treatments to simple, mostly convex target shapes in the brain and the thorax with a limited number of critical adjacent OAR using a limited number of beams (as low as 3 to 7). Using such treatment techniques, a dosimetric plan quality comparable to that of standard-of-care IMRT can be achieved. Hence, from a treatment planning perspective, 3D-conformal UHDR VHEE treatments delivered on time scales of 100 ms represent a promising candidate technique for the clinical transfer of the FLASH effect.

Technical note: In silico benchmarking of the linear energy transfer-based functionalities for carbon ion beams in a commercial treatment planning system.

BACKGROUND: The increasing number of studies dealing with linear energy transfer (LET)-based evaluation and optimization in the field of carbon ion radiotherapy (CIRT) indicates the rising demand for LET implementation in commercial treatment planning systems (TPS). Benchmarking studies could play a key role in detecting (and thus preventing) computation errors prior implementing such functionalities in a TPS. PURPOSE: This in silico study was conducted to benchmark the following two LET-related functionalities in a commercial TPS against Monte Carlo simulations: (1) dose averaged LET (LETd ) scoring and (2) physical dose filtration based on LET for future LET-based treatment plan evaluation and optimization studies. METHODS: The LETd scoring and LET-based dose filtering (in which the deposited dose can be separated into the dose below and above the user specified LET threshold) functionalities for carbon ions in the research version RayStation (RS) 9A-IonPG TPS (RaySearch Laboratories, Sweden) were benchmarked against GATE/Geant4 simulations. Pristine Bragg peaks (BPs) and cuboid targets, positioned at different depths in a homogeneous water phantom and a setup with heterogeneity were used for this study. RESULTS: For all setups (homogeneous and heterogeneous), the mean absolute (and relative) LETd difference was less than 1 keV/ µ $\umu$ m (3.5%) in the plateau and target and less than 2 keV/ µ $\umu$ m (8.3%) in the fragmentation tail. The maximum local differences were 4 and 6 keV/ µ $\umu$ m, respectively. The mean absolute (and relative) physical dose differences for both low- and high-LET doses were less than 1 cGy (1.5%) in the plateau, target and tail with a maximum absolute difference of 2 cGy. CONCLUSIONS: No computation error was found in the tested functionalities except for LETd in lateral direction outside the target, showing the limitation of the implemented monochrome model in the tested TPS version.

Detectability of Anatomical Changes With Prompt-Gamma Imaging: First Systematic Evaluation of Clinical Application During Prostate-Cancer Proton Therapy.

PURPOSE: The development of online-adaptive proton therapy (PT) is essential to overcome limitations encountered by day-to-day variations of the patient's anatomy. Range verification could play an essential role in an online feedback loop for the detection of treatment deviations such as anatomical changes. Here, we present the results of the first systematic patient study regarding the detectability of anatomical changes by a prompt-gamma imaging (PGI) slit-camera system. METHODS AND MATERIALS: For 15 patients with prostate cancer, PGI measurements were performed during 105 fractions (201 fields) with in-room control computed tomography (CT)acquisitions. Field-wise doses on control CT scans were manually classified as whether showing relevant or non-relevant anatomical changes. This manual classification of the treatment fields was then used to establish an automatic field-wise ground truth based on spot-wise dosimetric range shifts, which were retrieved from integrated depth-dose (IDD) profiles. To determine the detection capability of anatomical changes with PGI, spot-wise PGI-based range shifts were initially compared with corresponding dosimetric IDD range shifts. As final endpoint, the agreement of a developed field-wise PGI classification model with the field-wise ground truth was determined. Therefore, the PGI model was optimized and tested for a subcohort of 131 and 70 treatment fields, respectively. RESULTS: The correlation between PGI and IDD range shifts was high, ρpearson = 0.67 (p < 0.01). Field-wise binary PGI classification resulted in an area under the curve of 0.72 and 0.80 for training and test cohorts, respectively. The model detected relevant anatomical changes in the independent test cohort, with a sensitivity and specificity of 74% and 79%, respectively. CONCLUSIONS: For the first time, evidence of the detection capability of anatomical changes in prostate-cancer PT from clinically acquired PGI data is shown. This emphasizes the benefit of PGI-based range verification and demonstrates its potential for online-adaptive PT.

Measurement-based validation of a commercial Monte Carlo dose calculation algorithm for electron beams.

PURPOSE: This work presents the clinical validation of RayStation's electron Monte Carlo code by the use of diodes and plane parallel radiation detectors in homogenous and heterogeneous tissues. Results are evaluated against internationally accepted criteria. METHODS: The Monte Carlo-based electron beam dose calculation code was validated using diodes, air- and liquid-filled parallel radiation detectors on an Elekta linac with beam energies of 4, 6, 8, 10, and 12 MeV. Treatment setups with varying source-to-skin distances, different applicators, various cutouts, and oblique beam incidences were addressed, together with dose prediction behind lung-, air-, and bone-equivalent inserts. According to NCS (Netherlands Commission for Radiation Dosimetry) report 15 for nonstandard treatment setups, a dose agreement of 3% in the δ1 region (high-dose region around Zref ), a distance-to-agreement (DTA) of 3 mm or a dose agreement of 10% in the δ2 region (regions with high-dose gradients), and 4% in the δ4 region (photon tail/low-dose region) were applied. During validation, clinical routine settings of 2 × 2 × 2-mm3 dose voxels and a statistically dose uncertainty of 0.6% (250 000 histories/cm2 ) were used. RESULTS: RayStation's electron Monte Carlo code dose prediction was able to achieve the tolerances of NCS report 15. Output predictions as a function of the SSD improve with energy and applicator size. Cutout data revealed no field size or energy dependence on the accuracy of the dose prediction. Excellent agreement for the oblique incidence data was achieved and a maximum of one voxel difference was obtained for the DTA behind heterogeneous inserts. CONCLUSIONS: The accuracy of RayStation's Monte Carlo-based electron beam dose prediction for Elekta accelerators is confirmed for clinical treatment planning that is not only performed within an acceptable timeframe in terms of the number of histories but also addresses for homogenous and heterogeneous media.

Quantitative analysis of dose-averaged linear energy transfer (LETd ) robustness in pencil beam scanning proton lung plans.

PURPOSE: The primary objective of our study was to perform a quantitative robustness analysis of the dose-averaged linear energy transfer (LETd ) and related RBE-weighted dose in robustly optimized (in terms of the range and set up uncertainties) pencil beam scanning (PBS) proton lung cancer plans. METHODS: In this study, we utilized the 4DCT dataset of six anonymized lung patients. PBS lung plans were generated using a robust optimization technique (range uncertainty: ±3.5% and setup errors: ±5 mm) on the CTV for a total dose of 5000 cGy (RBE) in five fractions using the RBE of 1.1. For each patient, the LETd distributions were calculated for the nominal plan and three groups. Group 1: two plan robustness scenarios for range uncertainties of ±3.5%; Group 2: twelve plan robustness scenarios (range uncertainty (±3.5%) in conjunction with setup errors (±5 mm)); and Group 3: ten different breathing phases of the 4DCT dataset. The RBE-weighted dose to the OARs was evaluated for all robustness scenarios and breathing phases. The variation (∆) in the mean LETd and mean RBE-weighted dose from each group was recorded. RESULTS: The mean LETd in the CTV of nominal PBS lung plans among six patients ranged from 2.2 to 2.6 keV/µm. On average, for the combined range and setup uncertainties, the ∆ in the mean LETd among 12 scenarios of all six patients was 0.6 keV/µm, which is slightly higher than when only the range uncertainties were considered (0.4 keV/µm). The ∆ in the mean LETd in a patient was ≤1.7 keV/µm in the heart and ≤1.2 keV/µm in the esophagus and total lung. The ∆ in the mean RBE-weighted dose in a patient was up to 79 cGy for the total lung, 165 cGy for the heart, and 258 cGy for the esophagus. For ten breathing phases, the ∆ in the mean LETd in a patient was ≤0.3 keV/µm in the CTV, ≤0.5 keV/µm in the heart, ≤0.4 keV/µm in the esophagus, and ≤0.7 keV/µm in the total lung. CONCLUSION: The addition of setup errors to the range uncertainties resulted in slightly less homogeneous LETd distributions. The variations in the mean LETd among the ten breathing phases were slightly larger in the total lung than in the heart and esophagus. The combination of setup and range uncertainties had a greater impact than the effect of breathing phases on the variations in the mean RBE-weighted dose to the OARs. Overall, the LETd distributions in the CTV were less sensitive than those in the OARs to setup errors, range uncertainties, and breathing phases for robustly optimized (in terms of range and setup uncertainities) PBS proton lung cancer plans.

Treatment planning considerations for the development of FLASH proton therapy.

With increasing focus on the translation of the observed FLASH effect into clinical practice, this paper presents treatment planning considerations for its development using proton therapy. Potential requirements to induce a FLASH effect are discussed along with the properties of existing proton therapy delivery systems and the changes in planning and delivery approaches required to satisfy these prerequisites. For the exploration of treatment planning approaches for FLASH, developments in treatment planning systems are needed. Flexibility in adapting to new information will be important in such an evolving area. Variations in definitions, threshold values and assumptions can make it difficult to compare different published studies and to interpret previous studies in the context of new information. Together with the fact that much is left to be understood about the underlying mechanism behind the FLASH effect, a systematic and comprehensive approach to information storage is encouraged. Collecting and retaining more detailed information on planned and realised dose delivery as well as reporting the assumptions made in planning studies creates the potential for research to be revisited and re-evaluated in the light of future improvements in understanding. Forward thinking at the time of study development can help facilitate retrospective analysis. This, we hope, will increase the available evidence and accelerate the translation of the FLASH effect into clinical benefit.

Treatment planning for Flash radiotherapy: General aspects and applications to proton beams.

The increased radioresistence of healthy tissues when irradiated at very high dose rates (known as the Flash effect) is a radiobiological mechanism that is currently investigated to increase the therapeutic ratio of radiotherapy treatments. To maximize the benefits of the clinical application of Flash, a patient-specific balance between different properties of the dose distribution should be found, that is, Flash needs to be one of the variables considered in treatment planning. We investigated the Flash potential of three proton therapy planning and beam delivery techniques, each on a different anatomical region. Based on a set of beam delivery parameters, on hypotheses on the dose and dose rate thresholds needed for the Flash effect to occur, and on two definitions of Flash dose rate, we generated exemplary illustrations of the capabilities of current proton therapy equipment to generate Flash dose distributions. All techniques investigated could both produce dose distributions comparable with a conventional proton plan and reach the Flash regime, to an extent that was strongly dependent on the dose per fraction and the Flash dose threshold. The beam current, Flash dose rate threshold, and dose rate definition typically had a more moderate effect on the amount of Flash dose in normal tissue. A systematic estimation of the impact of Flash on different patient anatomies and treatment protocols is possible only if Flash-specific treatment planning features become readily available. Planning evaluation tools such as a voxel-based dose delivery time structure, and the inclusion in the optimization cost function of parameters directly associated with Flash (e.g., beam current, spot delivery sequence, and scanning speed), are needed to generate treatment plans that are taking full advantage of the potential benefits of the Flash effect.

Comparing biological effectiveness guided plan optimization strategies for cranial proton therapy: potential and challenges.

BACKGROUND: To introduce and compare multiple biological effectiveness guided (BG) proton plan optimization strategies minimizing variable relative biological effectiveness (RBE) induced dose burden in organs at risk (OAR) while maintaining plan quality with a constant RBE. METHODS: Dose-optimized (DOSEopt) proton pencil beam scanning reference treatment plans were generated for ten cranial patients with prescription doses ≥ 54 Gy(RBE) and ≥ 1 OAR close to the clinical target volume (CTV). For each patient, four additional BG plans were created. BG objectives minimized either proton track-ends, dose-averaged linear energy transfer (LETd), energy depositions from high-LET protons or variable RBE-weighted dose (DRBE) in adjacent serially structured OARs. Plan quality (RBE = 1.1) was assessed by CTV dose coverage and robustness (2 mm setup, 3.5% density), dose homogeneity and conformity in the planning target volumes and adherence to OAR tolerance doses. LETd, DRBE (Wedenberg model, α/ßCTV = 10 Gy, α/ßOAR = 2 Gy) and resulting normal tissue complication probabilities (NTCPs) for blindness and brainstem necrosis were derived. Differences between DOSEopt and BG optimized plans were assessed and statistically tested (Wilcoxon signed rank, α = 0.05). RESULTS: All plans were clinically acceptable. DOSEopt and BG optimized plans were comparable in target volume coverage, homogeneity and conformity. For recalculated DRBE in all patients, all BG plans significantly reduced near-maximum DRBE to critical OARs with differences up to 8.2 Gy(RBE) (p < 0.05). Direct DRBE optimization primarily reduced absorbed dose in OARs (average ΔDmean = 2.0 Gy; average ΔLETd,mean = 0.1 keV/µm), while the other strategies reduced LETd (average ΔDmean < 0.3 Gy; average ΔLETd,mean = 0.5 keV/µm). LET-optimizing strategies were more robust against range and setup uncertaintes for high-dose CTVs than DRBE optimization. All BG strategies reduced NTCP for brainstem necrosis and blindness on average by 47% with average and maximum reductions of 5.4 and 18.4 percentage points, respectively. CONCLUSIONS: All BG strategies reduced variable RBE-induced NTCPs to OARs. Reducing LETd in high-dose voxels may be favourable due to its adherence to current dose reporting and maintenance of clinical plan quality and the availability of reported LETd and dose levels from clinical toxicity reports after cranial proton therapy. These optimization strategies beyond dose may be a first step towards safely translating variable RBE optimization in the clinics.