Linear energy transfer incorporated intensity modulated proton therapy optimization

Biological optimization for hybrid proton-photon radiotherapy

Objective.Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OARs), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OARs, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose.Approach.The proposed hybrid biological dose optimization method optimized proton and photon plan variables, along with the number of fractions for each modality, minimizing biological dose to the OARs and surrounding normal tissues. To mitigate underestimation of hot biological dose spots, proton biological dose was minimized within a ring structure surrounding the target. Hybrid plans were designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for the proton and photon fraction doses. A probabilistic formulation was utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit constraint and dose-volume histogram constraints, was solved using an iterative convex relaxation method.Main results.Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies.Significance.This study presents a novel hybrid biological treatment planning method capable of generating plans with reduced biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.

Linear Energy Transfer Measurements and Estimation of Relative Biological Effectiveness in Proton and Helium Ion Beams Using Fluorescent Nuclear Track Detectors

PURPOSE

Our objective was to develop a methodology for assessing the linear energy transfer (LET) and relative biological effectiveness (RBE) in clinical proton and helium ion beams using fluorescent nuclear track detectors (FNTDs).

METHODS AND MATERIALS

FNTDs were exposed behind solid water to proton and helium (4He) ion spread-out Bragg peaks. Detectors were imaged with a confocal microscope, and the LET spectra were derived from the fluorescence intensity. The track- and dose-averaged LET (LETF and LETD, respectively) were calculated from the LET spectra. LET measurements were used as input on RBE models to estimate the RBE. Human alveolar adenocarcinoma cells (A549) were exposed at the same positions as the FNTDs. The RBE was calculated from the resulting survival curves. All measurements were compared with Monte Carlo simulations.

RESULTS

For protons, average relative differences between measurements and simulations were 6% and 19% for LETF and LETD, respectively. For helium ions, the same differences were 11% for both quantities. The position of the experimental LET spectra primary peaks agreed with the simulations within 9% and 14% for protons and helium ions, respectively. For the RBE models using LETD as input, FNTD-based RBE values ranged from 1.02 ± 0.01 to 1.25 ± 0.04 and from 1.08 ± 0.09 to 2.68 ± 1.26 for protons and helium ions, respectively. The average relative differences between these values and simulations were 2% and 4%. For A549 cells, the RBE ranged from 1.05 ± 0.07 to 1.47 ± 0.09 and from 0.89 ± 0.06 to 3.28 ± 0.20 for protons and helium ions, respectively. Regarding the RBE-weighted dose (2.0 Gy at the spread-out Bragg peak), the differences between simulations and measurements were below 0.10 Gy.

CONCLUSIONS

This study demonstrates for the first time that FNTDs can be used to perform direct LET measurements and to estimate the RBE in clinical proton and helium ion beams.

Sensitivity of a mini-TEPC to radiation quality variations in clinical proton beams

PURPOSE

This work aims at studying the sensitivity of a miniaturized Tissue-Equivalent Proportional Counter to variations of beam quality in clinical radiation fields, to further investigate its performances as radiation quality monitor.

METHODS

Measurements were taken at the CATANA facility (INFN-LNS, Catania, Italy), in a monoenergetic and an energy-modulated proton beam with the same initial energy of 62 MeV. PMMA layers were placed in front of the detector to measure at different depths along the depth-dose profile. The frequency- and dose-mean lineal energy were compared to the track- and dose-averaged LET calculated by Monte Carlo simulations. A microdosimetric evaluation of the Relative Biological Effectiveness (RBE) was performed and compared with cell survival experiments.

RESULTS

Microdosimetric distributions measured at identical depths in the two beams show spectral differences reflecting their different radiation quality. Discrepancies are most evident at depths corresponding to the Spread-Out Bragg Peak, while spectra at the entrance and in the dose fall-off regions are similar. This can be explained by the different energy components that compose the pristine and spread-out peaks at each depth. The trend of microdosimetric mean values matches that of calculated LET averages along the entire penetration depth, and the microdosimetric estimation of RBE is consistent with radiobiological data not only at 2 Gy but also at lower dose levels, such as those absorbed by healthy tissues.

CONCLUSIONS

The mini-TEPC is sensitive to differences in radiation quality resulting from different modulations of the proton beam, confirming its potential for beam quality monitoring in proton therapy.

A Systematic Review of LET-Guided Treatment Plan Optimisation in Proton Therapy: Identifying the Current State and Future Needs

The well-known clinical benefits of proton therapy are achieved through higher target-conformality and normal tissue sparing than conventional radiotherapy. However, there is an increased sensitivity to uncertainties in patient motion/setup, proton range and radiobiological effect. Although recent efforts have mitigated some uncertainties, radiobiological effect remains unresolved due to a lack of clinical data for relevant endpoints. Therefore, RBE optimisations may be currently unsuitable for clinical treatment planning. LET optimisation is a novel method that substitutes RBE with LET, shifting LET hotspots outside critical structures. This review outlines the current status of LET optimisation in proton therapy, highlighting knowledge gaps and possible future research. Following the PRISMA 2020 guidelines, a search of the MEDLINE® and Scopus databases was performed in July 2023, identifying 70 relevant articles. Generally, LET optimisation methods achieved their treatment objectives; however, clinical benefit is patient-dependent. Inconsistencies in the reported data suggest further testing is required to identify therapeutically favourable methods. We discuss the methods which are suitable for near-future clinical deployment, with fast computation times and compatibility with existing treatment protocols. Although there is some clinical evidence of a correlation between high LET and adverse effects, further developments are needed to inform future patient selection protocols for widespread application of LET optimisation in proton therapy.

An iterative convex relaxation method for proton LET optimization

Objective:A constant relative biological effectiveness of 1.1 in current clinical practice of proton radiotherapy (RT) is a crude approximation and may severely underestimate the biological dose from proton RT to normal tissues, especially near the treatment target at the end of Bragg peaks that exhibits high linear energy transfer (LET). LET optimization can account for biological effectiveness of protons during treatment planning, for minimizing biological proton dose and hot spots to normal tissues. However, the LET optimization is usually nonlinear and nonconvex to solve, for which this work will develop an effective optimization method based on iterative convex relaxation (ICR).Approach: In contrast to the generic nonlinear optimization method, such as Quasi-Newton (QN) method, that does not account for specific characteristics of LET optimization, ICR is tailored to LET modeling and optimization in order to effectively and efficiently solve the LET problem. Specifically, nonlinear dose-averaged LET term is iteratively linearized and becomes convex during ICR, while nonconvex dose-volume constraint and minimum-monitor-unit constraint are also handled by ICR, so that the solution for LET optimization is obtained by solving a sequence of convex and linearized convex subproblems. Since the high LET mostly occurs near the target, a 1 cm normal-tissue expansion of clinical target volume (CTV) (excluding CTV), i.e. CTV1cm, is defined to as an auxiliary structure during treatment planning, where LET is minimized.Main results: ICR was validated in comparison with QN for abdomen, lung, and head-and-neck cases. ICR was effective for LET optimization, as ICR substantially reduced the LET and biological dose in CTV1cm the ring, with preserved dose conformality to CTV. Compared to QN, ICR had smaller LET, physical and biological dose in CTV1cm, and higher conformity index values; ICR was also computationally more efficient, which was about 3 times faster than QN.Significance: A LET-specific optimization method based on ICR has been developed for solving proton LET optimization, which has been shown to be more computationally efficient than generic nonlinear optimizer via QN, with better plan quality in terms of LET, biological and physical dose conformality.

Hyperfractionated intensity-modulated proton therapy for pharyngeal cancer with variable relative biological effectiveness: A simulation study

BACKGROUND

The relative biological effectiveness (RBE) of proton is considered to be dependent on biological parameters and fractional dose. While hyperfractionated photon therapy was effective in the treatment of patients with head and neck cancers, its effect in intensity-modulated proton therapy (IMPT) under the variable RBE has not been investigated in detail.

PURPOSE

To study the effect of variable RBE on hyperfractionated IMPT for the treatment of pharyngeal cancer. We investigated the biologically effective dose (BED) to determine the theoretical effective hyperfractionated schedule.

METHODS

The treatment plans of three pharyngeal cancer patients were used to define the ΔBED for the clinical target volume (CTV) and soft tissue (acute and late reaction) as the difference between the BED for the altered schedule with variable RBE and conventional schedule with constant RBE. The ΔBED with several combinations of parameters (treatment days, number of fractions, and prescribed dose) was comprehensively calculated. Of the candidate schedules, the one that commonly gave a higher ΔBED for CTV was selected as the resultant schedule. The BED volume histogram was used to compare the influence of variable RBE and fractionation.

RESULTS

In the conventional schedule, compared with the constant RBE, the variable RBE resulted in a mean 2.6 and 2.7 Gy reduction of BED_mean for the CTV and soft tissue (acute reaction) of the three plans, respectively. Moreover, the BED_mean for soft tissue (late reaction) increased by 7.4 Gy, indicating a potential risk of increased RBE. Comprehensive calculation of the ΔBED resulted in the hyperfractionated schedule of 80.52 Gy (RBE = 1.1)/66 fractions in 6.5 weeks. When variable RBE was used, compared with the conventional schedule, the hyperfractionated schedule increased the BED_mean for CTV by 7.6 Gy; however, this was associated with a 7.8 Gy increase for soft tissue (acute reaction). The BED_mean for soft tissue (late reaction) decreased by 2.4 Gy.

CONCLUSION

The results indicated a potential effect of the variable RBE on IMPT for pharyngeal cancer but with the possibility that hyperfractionation could outweigh this effect. Although biological uncertainties require conservative use of the resultant schedule, hyperfractionation is expected to be an effective strategy in IMPT for pharyngeal cancer.

Technical note: Investigation of dose and LETd effect to rectum and bladder by using non-straight laterals in prostate cancer receiving proton therapy

BACKGROUND

Parallel-opposed lateral beams are the conventional beam arrangements in proton therapy for prostate cancer. However, when considering linear energy transfer (LET) and RBE effects, alternative beam arrangements should be investigated.

PURPOSE

To investigate the dose and dose averaged LET (LET_d ) impact of using new beam arrangements rotating beams 5°-15° posteriorly to the laterals in prostate cancer treated with pencil-beam-scanning (PBS) proton therapy.

METHODS

Twenty patients with localized prostate cancer were included in this study. Four proton treatment plans for each patient were generated utilizing 0°, 5°, 10°, and 15° posterior oblique beam pairs relative to parallel-opposed lateral beams. Dose-volume histograms (DVHs) from posterior oblique beams were analyzed. Dose-LET_d -volume histogram (DLVH) was employed to study the difference in dose and LET_d with each beam arrangement. DLVH indices, V ( d , l ) $V( {d,l} )$ , defined as the cumulative absolute volume that has a dose of at least d (Gy[RBE]) and a LET_d of at least l (keV/µm), were calculated for both the rectum and bladder to the whole group of patients and two-sub groups with and without hydrogel spacer. These metrics were tested using Wilcoxon signed-rank test.

RESULTS

Rotating beam angles from laterals to slightly posterior by 5°-15° reduced high LET_d volumes while it increased the dose volume in the rectum and increased LET_d in bladders. Beam angles rotated five degrees posteriorly from laterals (i.e., gantry in 95° and 265°) are proposed since they achieved the optimal balance of better LET_d sparing and minimal dose increase in the rectum. A reduction of V(50 Gy[RBE], 2.6 keV/µm) from 7.41 to 3.96 cc (p < 0.01), and a slight increase of V(50 Gy[RBE], 0 keV/µm) from 20.1 to 21.6 cc (p < 0.01) were observed for the group without hydrogel spacer. The LET_d sparing was less effective for the group with hydrogel spacer, which achieved the reduction of V(50 Gy[RBE], 2.6 keV/µm) from 4.28 to 2.10 cc (p < 0.01).

CONCLUSIONS

Posterior oblique angle plans improved LET_d sparing of the rectum while sacrificing LET_d sparing in the bladder in the treatment of prostate cancer with PBS. Beam angle modification from laterals to slightly posterior may be a strategy to redistribute LET_d and perhaps reduce rectal toxicity risks in prostate cancer patients treated with PBS. However, the effect is reduced for patients with hydrogel spacer.

Three-dimensional dose and LETD prediction in proton therapy using artificial neural networks

PURPOSE

Challenges in proton therapy include identifying patients most likely to benefit; ensuring consistent, high-quality plans as its adoption becomes more widespread; and recognizing biological uncertainties that may be related to increased relative biologic effectiveness driven by linear energy transfer (LET). Knowledge-based planning (KBP) is a domain that may help to address all three.

METHODS

Artificial neural networks were trained using 117 unique treatment plans and associated dose and dose-weighted LET (LET_D ) distributions. The data set was split into training (n = 82), validation (n = 17), and test (n = 18) sets. Model performance was evaluated on the test set using dose- and LET_D -volume metrics in the clinical target volume (CTV) and nearby organs at risk and Dice similarity coefficients (DSC) comparing predicted and planned isodose lines at 50%, 75%, and 95% of the prescription dose.

RESULTS

Dose-volume metrics significantly differed (α = 0.05) between predicted and planned dose distributions in only one dose-volume metric, D_2% to the CTV. The maximum observed root mean square (RMS) difference between corresponding metrics was 4.3 Gy_RBE (8% of prescription) for D_1cc to optic chiasm. DSC were 0.90, 0.93, and 0.88 for the 50%, 75%, and 95% isodose lines, respectively. LET_D -volume metrics significantly differed in all but one metric, L_0.1cc of the brainstem. The maximum observed difference in RMS differences for LET_D metrics was 1.0 keV/μm for L_0.1cc to brainstem.

CONCLUSIONS

We have devised the first three-dimensional dose and LET_D -prediction model for cranial proton radiation therapy has been developed. Dose accuracy compared favorably with that of previously published models in other treatment sites. The agreement in LET_D supports future investigations with biological doses in mind to enable the full potential of KBP in proton therapy.

Linear Energy Transfer and Relative Biological Effectiveness Investigation of Various Structures for a Cohort of Proton Patients With Brain Tumors

Purpose

The current knowledge on biological effects associated with proton therapy is limited. Therefore, we investigated the distributions of dose, dose-averaged linear energy transfer (LET_d), and the product between dose and LET_d (DLET_d) for a patient cohort treated with proton therapy. Different treatment planning system features and visualization tools were explored.

Methods and Materials

For a cohort of 24 patients with brain tumors, the LET_d, DLET_d, and dose was calculated for a fixed relative biological effectiveness value and 2 variable models: plan-based and phenomenological. Dose threshold levels of 0, 5, and 20 Gy were imposed for LET_d visualization. The relationship between physical dose and LET_d and the frequency of LET_d hotspots were investigated.

Results

The phenomenological relative biological effectiveness model presented consistently higher dose values. For lower dose thresholds, the LET_d distribution was steered toward higher values related to low treatment doses. Differences up to 26.0% were found according to the threshold. Maximum LET_d values were identified in the brain, periventricular space, and ventricles. An inverse relationship between LET_d and dose was observed. Frequency information to the domain of dose and LET_d allowed for the identification of clusters, which steer the mean LET_d values, and the identification of higher, but sparse, LET_d values.

Conclusions

Identifying, quantifying, and recording LET distributions in a standardized fashion is necessary, because concern exists over a link between toxicity and LET hotspots. Visualizing DLET_d or dose × LET_d during treatment planning could allow for clinicians to make informed decisions.

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 (LET_d), energy depositions from high-LET protons or variable RBE-weighted dose (D_RBE) 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. LET_d, D_RBE (Wedenberg model, α/β_CTV = 10 Gy, α/β_OAR = 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 D_RBE in all patients, all BG plans significantly reduced near-maximum D_RBE to critical OARs with differences up to 8.2 Gy(RBE) (p < 0.05). Direct D_RBE optimization primarily reduced absorbed dose in OARs (average ΔD_mean = 2.0 Gy; average ΔLET_d,mean = 0.1 keV/µm), while the other strategies reduced LET_d (average ΔD_mean < 0.3 Gy; average ΔLET_d,mean = 0.5 keV/µm). LET-optimizing strategies were more robust against range and setup uncertaintes for high-dose CTVs than D_RBE 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 LET_d 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 LET_d 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.

Virtual particle Monte Carlo: A new concept to avoid simulating secondary particles in proton therapy dose calculation

BACKGROUND

In proton therapy dose calculation, Monte Carlo (MC) simulations are superior in accuracy but more time consuming, compared to analytical calculations. Graphic processing units (GPUs) are effective in accelerating MC simulations but may suffer thread divergence and racing condition in GPU threads that degrades the computing performance due to the generation of secondary particles during nuclear reactions.

PURPOSE

A novel concept of virtual particle (VP) MC (VPMC) is proposed to avoid simulating secondary particles in GPU-accelerated proton MC dose calculation and take full advantage of the computing power of GPU.

METHODS

Neutrons and gamma rays were ignored as escaping from the human body; doses of electrons, heavy ions, and nuclear fragments were locally deposited; the tracks of deuterons were converted into tracks of protons. These particles, together with primary and secondary protons, are considered to be the realistic particles. Histories of primary and secondary protons were replaced by histories of multiple VPs. Each VP corresponded to one proton (either primary or secondary). A continuous-slowing-down-approximation model, an ionization model, and a large angle scattering event model corresponding to nuclear interactions were developed for VPs by generating probability distribution functions (PDFs) based on simulation results of realistic particles using MCsquare. For efficient calculations, these PDFs were stored in the Compute Unified Device Architecture textures. VPMC was benchmarked with TOPAS and MCsquare in phantoms and with MCsquare in 13 representative patient geometries. Comparisons between the VPMC calculated dose and dose measured in water during patient-specific quality assurance (PSQA) of the selected 13 patients were also carried out. Gamma analysis was used to compare the doses derived from different methods and calculation efficiencies were also compared.

RESULTS

Integrated depth dose and lateral dose profiles in both homogeneous and inhomogeneous phantoms all matched well among VPMC, TOPAS, and MCsquare calculations. The 3D-3D gamma passing rates with a criterion of 2%/2 mm and a threshold of 10% was 98.49% between MCsquare and TOPAS and 98.31% between VPMC and TOPAS in homogeneous phantoms, and 99.18% between MCsquare and TOPAS and 98.49% between VPMC and TOPAS in inhomogeneous phantoms, respectively. In patient geometries, the 3D-3D gamma passing rates with 2%/2 mm/10% between dose distributions from VPMC and MCsquare were 98.56 ± 1.09% in patient geometries. The 2D-3D gamma analysis with 3%/2 mm/10% between the VPMC calculated dose distributions and the 2D measured planar dose distributions during PSQA was 98.91 ± 0.88%. VPMC calculation was highly efficient and took 2.84 ± 2.44 s to finish for the selected 13 patients running on four NVIDIA Ampere GPUs in patient geometries.

CONCLUSION

VPMC was found to achieve high accuracy and efficiency in proton therapy dose calculation.

Treatment-planning approaches to intensity modulated proton therapy and the impact on dose-weighted linear energy transfer

PURPOSE

We quantified the effect of various forward-based treatment-planning strategies in proton therapy on dose-weighted linear energy transfer (LETd). By maintaining the dosimetric quality at a clinically acceptable level, we aimed to evaluate the differences in LETd among various treatment-planning approaches and their practicality in minimizing biologic uncertainties associated with LETd.

METHOD

Eight treatment-planning strategies that are achievable in commercial treatment-planning systems were applied on a cylindrical water phantom and four pediatric brain tumor cases. Each planning strategy was compared to either an opposed lateral plan (phantom study) or original clinical plan (patient study). Deviations in mean and maximum LETd from clinically acceptable dose distributions were compared.

RESULTS

In the phantom study, using a range shifter and altering the robust scenarios during optimization had the largest effect on the mean clinical target volume LETd, which was reduced from 4.5 to 3.9 keV/μm in both cases. Variations in the intersection angle between beams had the largest effect on LETd in a ring defined 3 to 5 mm outside the target. When beam intersection angles were reduced from opposed laterals (180°) to 120°, 90°, and 60°, corresponding maximum LETd increased from 7.9 to 8.9, 10.9, and 12.2 keV/μm, respectively. A clear trend in mean and maximum LETd variations in the clinical cases could not be established, though spatial distribution of LETd suggested a strong dependence on patient anatomy and treatment geometry.

CONCLUSION

Changes in LETd from treatment-plan setup follow intuitive trends in a controlled phantom experiment. Anatomical and other patient-specific considerations, however, can preclude generalizable strategies in clinical cases. For pediatric cranial radiation therapy, we recommend using opposed lateral treatment fields to treat midline targets.

Exploratory study of seed spots analysis to characterize dose and linear energy transfer effect in adverse event initialization of pencil beam scanning proton therapy

BACKGROUND

Both dose and linear-energy-transfer (LET) could play a substantial role in adverse event (AE) initialization of cancer patients treated with pencil-beam-scanning proton therapy (PBS). However, not all the voxels within the AE regions are directly induced from the dose and LET effect. It is important to study the synergistic effect of dose and LET in AE initialization by only including a subset of voxels that are dosimetrically important.

PURPOSE

To perform exploratory investigation of the dose and LET effects upon AE initialization in PBS using seed spots analysis.

METHODS

113 head and neck (H&N) cancer patients receiving curative PBS were included. Among them, 20 patients experienced unanticipated CTCAEv4.0 grade≥3 AEs (AE group) and 93 patients did not (control group). Within the AE group, 13 AE patients were included in the seed spot analysis to derive the descriptive features of AE initialization and the remaining 7 mandible osteoradionecrosis patients and 93 control patients were used to derive the feature-based volume constraint of mandible osteoradionecrosis. The AE regions were contoured and the corresponding dose-LET volume histograms (DLVHs) of AE regions were generated for all patients in the AE group. We selected high LET voxels (the highest 5% of each dose bin) with a range of moderate to high dose (≥∼40 Gy[RBE]) as critical voxels. Critical voxels which were contiguous with each other were grouped into clusters. Each cluster was considered as a potential independent seed spot for AE initialization. Seed spots were displayed in a 2D dose-LET plane based on their mean dose and LET to derive the descriptive features of AE initialization. A volume constraint of mandible osteoradionecrosis was then established based on the extracted features using a receiver operating characteristic curve.

RESULTS

The product of dose and LET (xBD) was found to be a descriptive feature of seed spots leading to AE initialization in this preliminary study. The derived xBD volume constraint for mandible osteoradionecrosis showed good performance with an area-under-curve of 0.87 (sensitivity of 0.714 and specificity of 0.807 in the leave-one-out cross validation) for the very limited patient data included in this study.

CONCLUSION

Our exploratory study showed that both dose and LET were observed to be important in AE initializations. The derived xBD volume constraint could predict mandible osteoradionecrosis reasonably well in the very limited H&N cancer patient data treated with PBS included in this study. This article is protected by copyright. All rights reserved.

Reflections on beam configuration optimization for intensity-modulated proton therapy

Presumably, intensity-modulated proton radiotherapy (IMPT) is the most powerful form of proton radiotherapy. In the current state of the art, IMPT beam configurations (i.e. the number of beams and their directions) are, in general, chosen subjectively based on prior experience and practicality. Beam configuration optimization (BCO) for IMPT could, in theory, significantly enhance IMPT’s therapeutic potential. However, BCO is complex and highly computer resource-intensive. Some algorithms for BCO have been developed for intensity-modulated photon therapy (IMRT). They are rarely used clinically mainly because the large number of beams typically employed in IMRT renders BCO essentially unnecessary. Moreover, in the newer form of IMRT, volumetric modulated arc therapy, there are no individual static beams. BCO is of greater importance for IMPT because it typically employs a very small number of beams (2-4) and, when the number of beams is small, BCO is critical for improving plan quality. However, the unique properties and requirements of protons, particularly in IMPT, make BCO challenging. Protons are more sensitive than photons to anatomic changes, exhibit variable relative biological effectiveness along their paths, and, as recently discovered, may spare the immune system. Such factors must be considered in IMPT BCO, though doing so would make BCO more resource intensive and make it more challenging to extend BCO algorithms developed for IMRT to IMPT. A limited amount of research in IMPT BCO has been conducted; however, considerable additional work is needed for its further development to make it truly effective and computationally practical. This article aims to provide a review of existing BCO algorithms, most of which were developed for IMRT, and addresses important requirements specific to BCO for IMPT optimization that necessitate the modification of existing approaches or the development of new effective and efficient ones.

Empirical Relative Biological Effectiveness (RBE) for Mandible Osteoradionecrosis (ORN) in Head and Neck Cancer Patients Treated With Pencil-Beam-Scanning Proton Therapy (PBSPT): A Retrospective, Case-Matched Cohort Study

Purpose

To retrospectively investigate empirical relative biological effectiveness (RBE) for mandible osteoradionecrosis (ORN) in head and neck (H&N) cancer patients treated with pencil-beam-scanning proton therapy (PBSPT).

Methods

We included 1,266 H&N cancer patients, of which, 931 patients were treated with volumetric-modulated arc therapy (VMAT) and 335 were treated with PBSPT. Among them, 26 VMAT and 9 PBSPT patients experienced mandible ORN (ORN group), while all others were included in the control group. To minimize the impact of the possible imbalance in clinical factors between VMAT and PBSPT patients in the dosimetric comparison between these two modalities and the resulting RBE quantification, we formed a 1:1 case-matched patient cohort (335 VMAT patients and 335 PBSPT patients including both the ORN and control groups) using the greedy nearest neighbor matching of propensity scores. Mandible dosimetric metrics were extracted from the case-matched patient cohort and statistically tested to evaluate the association with mandibular ORN to derive dose volume constraints (DVCs) for VMAT and PBSPT, respectively. We sought the equivalent constraint doses for VMAT so that the critical volumes of VMAT were equal to those of PBSPT at different physical doses. Empirical RBEs of PBSPT for ORN were obtained by calculating the ratio between the derived equivalent constraint doses and physical doses of PBSPT. Bootstrapping was further used to get the confidence intervals.

Results

Clinical variables of age, gender, tumor stage, prescription dose, chemotherapy, hypertension or diabetes, dental extraction, smoking history, or current smoker were not statistically related to the incidence of ORN in the overall patient cohort. Smoking history was found to be significantly associated with the ORN incidence in PBSPT patients only. V40Gy[RBE], V50Gy[RBE], and V60Gy[RBE] were statistically different (p<0.05) between the ORN and control group for VMAT and PBSPT. Empirical RBEs of 1.58(95%CI: 1.34-1.64), 1.34(95%CI: 1.23-1.40), and 1.24(95%: 1.15-1.26) were obtained for proton dose at 40 Gy[RBE=1.1], 50 Gy[RBE=1.1] and 60 Gy[RBE=1.1], respectively.

Conclusions

Our study suggested that RBEs were larger than 1.1 at moderate doses (between 40 and 60 Gy[RBE=1.1]) with high LET for mandible ORN. RBEs are underestimated in current clinical practice in PBSPT. The derived DVCs can be used for PBSPT plan evaluation and optimization to minimize the incidence rate of mandible ORN.

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 (LET_d ) 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 data set 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 5 fractions using RBE of 1.1. For each patient, the LET_d 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 data set. RBE-weighted dose to the OARs was evaluated for all robustness scenarios and breathing phases. The variation (∆) in the mean LET_d and mean RBE-weighted dose from each group was recorded.

RESULTS

The mean LET_d 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 LET_d 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 LET_d 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 LET_d 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 LET_d distributions. The variations in the mean LET_d among 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 LET_d distributions in the CTV were less sensitive than those in the OARs to setup errors, range uncertainties, and breathing phases for robustly optimized PBS proton lung cancer plans. This article is protected by copyright. All rights reserved.

Quantifying the risk and dosimetric variables of symptomatic brainstem injury after proton beam radiation in pediatric brain tumors

BACKGROUND

Brainstem toxicity after radiation therapy (RT) is a devastating complication and a particular concern with proton radiation (PBT). We investigated the incidence and clinical correlates of brainstem injury in pediatric brain tumors treated with PBT.

METHODS

All patients <21 years with brain tumors treated with PBT at our institution from 2007-2019, with a brainstem Dmean >30 Gy and/or Dmax >50.4 Gy were included. Symptomatic brainstem injury (SBI) was defined as any new or progressive cranial neuropathy, ataxia, and/or motor weakness with corresponding radiographic abnormality within brainstem.

RESULTS

A total of 595 patients were reviewed and 468 (medulloblastoma = 200, gliomas = 114, ependymoma = 87, ATRT = 43) met our inclusion criteria. Median age at RT was 6.3 years and median prescribed RT dose was 54Gy [RBE]. Fifteen patients (3.2%) developed SBI, at a median of 4 months after RT. Grades 2, 3, 4, and 5 brainstem injuries were seen in 7, 5, 1, and 2 patients respectively. Asymptomatic radiographic changes were seen in 51 patients (10.9%). SBI was significantly higher in patients with age ≤3 years, female gender, ATRT histology, patients receiving high-dose chemotherapy with stem cell rescue, and those not receiving craniospinal irradiation. Patients with SBI had a significantly higher V50-52. In 2014, our institution started using strict brainstem dose constraints (Dmax ≤57 Gy, Dmean ≤52.4 Gy, and V54≤10%). There was a trend towards decrease in SBI from 4.4% (2007-2013) to 1.5% (2014-2019) (P = .089) without affecting survival.

CONCLUSION

Our results suggest a low risk of SBI after PBT for pediatric brain tumors, comparable to photon therapy. A lower risk was seen after adopting strict brainstem dose constraints.

Per-voxel constraints to minimize hot spots in linear energy transfer-guided robust optimization for base of skull head and neck cancer patients in IMPT

PURPOSE

Due to the employment of quadratic programming using soft constraints to implement dose volume constraints and the "trial-and-error" procedure needed to achieve a clinically acceptable plan, conventional dose volume constraints (upper limit) are not adequately effective in controlling small and isolated hot spots in the dose/linear energy transfer (LET) distribution. Such hot spots can lead to adverse events. In order to mitigate the risk of brain necrosis, one of the most clinically significant adverse events in patients receiving intensity-modulated proton therapy (IMPT) for base of skull (BOS) cancer, we propose per-voxel constraints to minimize hot spots in LET-guided robust optimization.

METHODS AND MATERIALS

Ten BOS cancer patients treated with IMPT were carefully selected by meeting one of the following conditions: (1) diagnosis of brain necrosis during follow-up; and (2) considered high risk for brain necrosis by not meeting dose constraints to the brain. An optimizing structure (BrainOPT) and an evaluating structure (BrainROI) that both contained the aforementioned hot dose regions in the brain were generated for optimization and evaluation, respectively. Two plans were generated for every patient: one using conventional dose-only robust optimization, the other using LET-guided robust optimization. The impact of LET was integrated into the optimization via a term of extra biological dose (xBD). A novel optimization tool of per-voxel constraints to control small and isolated hot spots in either the dose, LET, or combined (dose/LET) distribution was developed and used to minimize dose/LET hot spots of the selected structures. Indices from dose-volume histogram (DVH) and xBD dose-volume histogram (xBDVH) were used in the plan evaluation. A newly developed tool of the dose-LET-volume histogram (DLVH) was also adopted to illustrate the underlying mechanism. Wilcoxon signed-rank test was used for statistical comparison of the DVH and xBDVH indices between the conventional dose-only and the LET-guided robustly optimized plans.

RESULTS

Per-voxel constraints effectively and efficiently minimized dose hot spots in both dose-only and LET-guided robust optimization and LET hot spots in LET-guided robust optimization. Compared to the conventional dose-only robust optimization, the LET-guided robust optimization could generate plans with statistically lower xBD hot spots in BrainROI (VxBD,50 Gy[RBE], p = 0.009; VxBD,60 Gy[RBE], p = 0.025; xBD1cc, p = 0.017; xBD2cc, p = 0.022) with comparable dose coverage, dose hot spots in the target, and dose hot spots in BrainROI. DLVH analysis indicated that LET-guided robust optimization could either reduce LET at the same dose level or redistribute high LET from high dose regions to low dose regions.

CONCLUSION

Per-voxel constraint is a powerful tool to minimize dose/LET hot spots in IMPT. The LET-guided robustly optimized plans outperformed the conventional dose-only robustly optimized plans in terms of xBD hot spots control.

A Review of the Robust Optimization Process and Advances with Monte Carlo in the Proton Therapy Management of Head and Neck Tumors

In intensity-modulated proton therapy, robust optimization processes have been developed to manage uncertainties associated with (1) range, (2) setup, (3) anatomic changes, (4) dose calculation, and (5) biological effects. Here we review our experience using a robust optimization technique that directly incorporates range and setup uncertainties into the optimization process to manage those sources of uncertainty. We also review procedures for implementing adaptive planning to manage the anatomic uncertainties. Finally, we share some early experiences regarding the impact of uncertainties in dose calculation and biological effects, along with techniques to manage and potentially reduce these uncertainties.

Exploratory Investigation of Dose-Linear Energy Transfer (LET) Volume Histogram (DLVH) for Adverse Events Study in Intensity Modulated Proton Therapy (IMPT)

PURPOSE

We proposed a novel tool-a dose linear energy transfer (LET)-volume histogram (DLVH)-and performed an exploratory study to investigate rectal bleeding in prostate cancer treated with intensity modulated proton therapy.

METHODS AND MATERIALS

The DLVH was constructed with dose and LET as 2 axes, and the normalized volume of the structure was contoured in the dose-LET plane as isovolume lines. We defined the DLVH index, DLv%(d,l) (ie, v% of the structure) to have a dose of ≥d Gy and an LET of ≥l keV/μm, similar to the dose-volume histogram index Dv%. Nine patients with prostate cancer with rectal bleeding (Common Terminology Criteria for Adverse Events grade ≥2) were included as the adverse event group, and 48 patients with no complications were considered the control group. A P value map was constructed by comparison of the DLVH indices of all patients between the 2 groups using the Mann-Whitney U test. Dose-LET volume constraints (DLVCs) were derived based on the P value map with a manual selection procedure facilitated by Spearman's correlation tests. The obtained DLVCs were further cross-validated using a multivariate support vector machine (SVM)-based normal tissue complication probability (NTCP) model with an independent testing data set composed of 8 adverse event and 13 control patients.

RESULTS

We extracted 2 DLVC constraints. One DLVC was obtained, Vdose/LETboundary:2.5keVμmat 75 Gy to 3.2keVμmat8.65Gy <1.27% (DLVC1), revealing a high LET volume effect. The second DLVC, V(72.2Gy,0keVμm) < 2.23% (DVLC2), revealed a high dose volume effect. The SVM-based NTCP model with 2 DLVCs provided slightly superior performance than using dose only, with an area under the curve of 0.798 versus 0.779 for the testing data set.

CONCLUSIONS

Our results demonstrated the importance of rectal "hot spots" in both high LET (DLVC1) and high dose (DLVC2) in inducing rectal bleeding. The SVM-based NTCP model confirmed the derived DLVCs as good predictors for rectal bleeding when intensity modulated proton therapy is used to treat prostate cancer.

Linear Energy Transfer Incorporated Spot-Scanning Proton Arc Therapy Optimization: A Feasibility Study

Purpose

To integrate dose-averaged linear energy transfer (LET_d) into spot-scanning proton arc therapy (SPArc) optimization and to explore its feasibility and potential clinical benefits.

Methods

An open-source proton planning platform (OpenREGGUI) has been modified to incorporate LET_d into optimization for both SPArc and multi-beam intensity-modulated proton therapy (IMPT) treatment planning. SPArc and multi-beam IMPT plans with different beam configurations for a prostate patient were generated to investigate the feasibility of LET_d-based optimization using SPArc in terms of spatial LET_d distribution and plan delivery efficiency. One liver and one brain case were studied to further evaluate the advantages of SPArc over multi-beam IMPT.

Results

With similar dose distributions, the efficacy of spatially optimizing LET_d distributions improves with increasing number of beams. Compared with multi-beam IMPT plans, SPArc plans show substantial improvement in LET_d distributions while maintaining similar delivery efficiency. Specifically, for the liver case, the average LET_d in the GTV was increased by 124% for the SPArc plan, and only 9.6% for the 2-beam IMPT plan compared with the 2-beam non-LET_d optimized IMPT plan. In case of LET optimization for the brain case, the SPArc plan could effectively increase the average LET_d in the CTV and decrease the values in the critical structures while smaller improvement was observed in 3-beam IMPT plans.

Conclusion

This work demonstrates the feasibility and significant advantages of using SPArc for LET_d-based optimization, which could maximize the LET_d distribution wherever is desired inside the target and averts the high LET_d away from the adjacent critical organs-at-risk.

A Critical Review of LET-Based Intensity-Modulated Proton Therapy Plan Evaluation and Optimization for Head and Neck Cancer Management

In this review article, we review the 3 important aspects of linear-energy-transfer (LET) in intensity-modulated proton therapy (IMPT) for head and neck (H&N) cancer management. Accurate LET calculation methods are essential for LET-guided plan evaluation and optimization, which can be calculated either by analytical methods or by Monte Carlo (MC) simulations. Recently, some new 3D analytical approaches to calculate LET accurately and efficiently have been proposed. On the other hand, several fast MC codes have also been developed to speed up the MC simulation by simplifying nonessential physics models and/or using the graphics processor unit (GPU)–acceleration approach. Some concepts related to LET are also briefly summarized including (1) dose-weighted versus fluence-weighted LET; (2) restricted versus unrestricted LET; and (3) microdosimetry versus macrodosimetry. LET-guided plan evaluation has been clinically done in some proton centers. Recently, more and more studies using patient outcomes as the biological endpoint have shown a positive correlation between high LET and adverse events sites, indicating the importance of LET-guided plan evaluation in proton clinics. Various LET-guided plan optimization methods have been proposed to generate proton plans to achieve biologically optimized IMPT plans. Different optimization frameworks were used, including 2-step optimization, 1-step optimization, and worst-case robust optimization. They either indirectly or directly optimize the LET distribution in patients while trying to maintain the same dose distribution and plan robustness. It is important to consider the impact of uncertainties in LET-guided optimization (ie, LET-guided robust optimization) in IMPT, since IMPT is sensitive to uncertainties including both the dose and LET distributions. We believe that the advancement of the LET-guided plan evaluation and optimization will help us exploit the unique biological characteristics of proton beams to improve the therapeutic ratio of IMPT to treat H&N and other cancers.

Inhibition of ATM Induces Hypersensitivity to Proton Irradiation by Upregulating Toxic End Joining

Proton Bragg peak irradiation has a higher ionizing density than conventional photon irradiation or the entrance of the proton beam profile. Whether targeting the DNA damage response (DDR) could enhance vulnerability to the distinct pattern of damage induced by proton Bragg peak irradiation is currently unknown. Here, we performed genetic or pharmacologic manipulation of key DDR elements and evaluated DNA damage signaling, DNA repair, and tumor control in cell lines and xenografts treated with the same physical dose across a radiotherapy linear energy transfer spectrum. Radiotherapy consisted of 6 MV photons and the entrance beam or Bragg peak of a 76.8 MeV spot scanning proton beam. More complex DNA double-strand breaks (DSB) induced by Bragg peak proton irradiation preferentially underwent resection and engaged homologous recombination (HR) machinery. Unexpectedly, the ataxia-telangiectasia mutated (ATM) inhibitor, AZD0156, but not an inhibitor of ATM and Rad3-related, rendered cells hypersensitive to more densely ionizing proton Bragg peak irradiation. ATM inhibition blocked resection and shunted more DSBs to processing by toxic ligation through nonhomologous end-joining, whereas loss of DNA ligation via XRCC4 or Lig4 knockdown rescued resection and abolished the enhanced Bragg peak cell killing. Proton Bragg peak monotherapy selectively sensitized cell lines and tumor xenografts with inherent HR defects, and the repair defect induced by ATM inhibitor coadministration showed enhanced efficacy in HR-proficient models. In summary, inherent defects in HR or administration of an ATM inhibitor in HR-proficient tumors selectively enhances the relative biological effectiveness of proton Bragg peak irradiation. SIGNIFICANCE: Coadministration of an ATM inhibitor rewires DNA repair machinery to render cancer cells uniquely hypersensitive to DNA damage induced by the proton Bragg peak, which is characterized by higher density ionization.See related commentary by Nickoloff, p. 3156.

How can scanned proton beam treatment planning for low-grade glioma cope with increased distal RBE and locally increased radiosensitivity for late MR-detected brain lesions?

A novel risk model has recently been proposed for the occurrence of late contrast-enhancing brain lesions (CEBLs) after proton irradiation of low-grade glioma (LGG) patients. It predicts a strong dependence on dose-weighted linear-energy transfer (LET_d effect) and an increased radiosensitivity of the ventricular proximity, a 4-mm fringe surrounding the ventricular system (VP_4mm effect). On this basis, we investigated (A) how these two risk factors and patient-specific anatomical and treatment plan (TP) features contribute to normal tissue complication probability (NTCP) and (B) if conventional LET_d -reduction techniques like multiple-field TP are able to reduce NTCP. (A) The LGG model cohort (N = 110) was stratified with respect to prescribed dose, tumor grade, and treatment field configuration. NTCP predictions and CEBL occurrence rates per strata were analyzed. (B) The effect of multiple-field TP was investigated in two patient groups: (i) nine high-risk subjects with extended lateral target volumes who had developed CEBLs after single-beam treatments were retrospectively replanned with a clinical standard two-field setting using almost orthogonal fields and strictly opposing fields, (ii) single-field treatments were simulated for seven low-risk patients with small central target volumes clinically treated with two strictly opposing fields. (A) In the model cohort, we identified the exposure of the radiosensitive VP_4mm fringe with proton field components of increased biological effectiveness as dominant NTCP driving factor. We observed that larger target volumes and location lateral to the main ventricles, both being characteristic for WHO°II tumors, presented with the highest complication risks. Among subjects of an equal dose prescription of 54 Gy(RBE), the highest median NTCP was obtained for the WHO°II group treated with two fields using sharp angles. (B) Regarding the effect of multiple-field plans, we found that an NTCP reduction was only achievable in the low-risk group where the LET_d effect dominates and the VP_4mm effect is small. NTCP of the single-field plans was 23% higher compared to the clinical opposing field plan. In the high-risk group, where the VP_4mm effect dominates the risk, both two-field scenarios yielded 44% higher NTCP predictions compared to the clinical single-field plans. The interplay of an increased radiosensitivity in the VP_4mm fringe with proton field components of increased biological effectiveness creates a geometric complexity that can hardly be managed by current clinical TP. Our results underline that advanced biologically guided TP approaches become crucial for an effective risk minimization in proton therapy of LGG.

Dual-storage phosphor proton therapy dosimetry: Simultaneous quantification of dose and linear energy transfer

PURPOSE

To investigate the feasibility of using the high Z_eff storage phosphor material BaFBrI:Eu²⁺ in conjunction with the low Z_eff storage phosphor material KCl:Eu²⁺ for simultaneous proton dose and linear energy transfer (LET) measurements by (a) measuring the fundamental optical and dosimetric properties of BaFBrI:Eu²⁺ , (b) evaluating its compatibility in being readout simultaneously with KCl:Eu²⁺ dosimeters, and (c) modeling and validating its LET dependence under elevated proton LET irradiation.

METHODS

A commercial BaFBrI:Eu²⁺ storage phosphor detector (Model ST-VI, Fujifilm) was characterized with energy dispersive x-ray spectroscopy (EDS) analysis to obtain its elemental composition. The dosimeters were irradiated using both a Mevion S250 proton therapy unit (at the center of a spread-out Bragg peak, SOBP) and a Varian Clinac iX linear accelerator with the latter being a low LET irradiation. The photostimulated luminescence (PSL) emission spectra, excitation spectra, and luminescent lifetimes of the detector were measured after proton and photon irradiations. Dosimetric properties including dose linearity, dose rate dependence, radiation hardness, temporal, and readout stabilities were studied using a laboratory optical reader after proton irradiations. In addition, its proton energy dependence was analytically modeled and experimentally validated by irradiating the detectors at various depths within the SOBP (Range: 15.0 g/cm² , Modulation: 10.0 g/cm² ).

RESULTS

The active detector composition for the high Z_eff storage phosphor detector was found to be BaFBr_0.85 I_0.15 :Eu²⁺ . The BaFBr_0.85 I_0.15 :Eu²⁺ material's excitation and emission spectra were in agreement under proton and photon irradiations, with peaks of 586 ± 1 nm and 400 ± 1 nm, respectively, with a full width at half maximum (FWHM) of 119 ± 3 nm and 30 ± 2 nm, respectively. As dosimeter response under photon irradiation is generally believed to be free from LET effect, these results suggest LET independence of charge storage center types resulted from ionizing radiations. There is sufficient spectral overlaps with KCl:Eu²⁺ dosimeters allowing both dosimeters to be readout under equivalent readout conditions, that is, 594 nm stimulation and 420 nm detection wavelengths. Its PSL characteristic lifetime was found to be less than 5 microseconds which would make it suitable for fast 2D readout post irradiation. Its 420 nm emission band intensity was found to be linear up to 10 Gy absolute proton dose under the same irradiation conditions, dose rate independent, stable in time and under multiple readouts, and with high radiation hardness under cumulative proton dose histories up to 200 Gy as tested in this study. BaFBr_0.85 I_0.15 :Eu²⁺ showed significant proton energy-dependent dose under-response in regions of high LET which could be modeled by stopping power ratio calculations with an accuracy of 3% in low LET regions and a distance-to-agreement (DTA) of 1 mm in high LET regions (>5 keV/μm).

CONCLUSION

We have proven the feasibility of dual-storage phosphor proton dosimetry for simultaneous proton dose and LET measurements. BaFBr_0.85 I_0.15 :Eu²⁺ has shown equally excellent dosimetry performance as its low Z_eff complement KCl:Eu²⁺ with distinctive LET dependence merely as a result of its higher Z_eff . These promising results pave the way for future studies involving simultaneous proton dose and LET measurements using this novel approach.

The impact of variable relative biological effectiveness in proton therapy for left-sided breast cancer when estimating normal tissue complications in the heart and lung

The aim of this study was to evaluate the clinical impact of relative biological effectiveness (RBE) variations in proton beam scanning treatment (PBS) for left-sided breast cancer versus the assumption of a fixed RBE of 1.1, particularly in the context of comparisons with photon-based three-dimensional conformal radiotherapy (3DCRT) and volumetric modulated arc therapy (VMAT). Ten patients receiving radiation treatment to the whole breast/chest wall and regional lymph nodes were selected for each modality. For PBS, the dose distributions were re-calculated with both a fixed RBE and a variable RBE using an empirical RBE model. Dosimetric indices based on dose-volume histogram analysis were calculated for the entire heart wall, left anterior descending artery (LAD) and left lung. Furthermore, normal tissue toxicity probabilities for different endpoints were evaluated. The results show that applying a variable RBE significantly increases the RBE-weighted dose and consequently the calculated dosimetric indices increases for all organs compared to a fixed RBE. The mean dose to the heart and the maximum dose to the LAD and the left lung are significantly lower for PBS assuming a fixed RBE compared to 3DCRT. However, no statistically significant difference is seen when a variable RBE is applied. For a fixed RBE, lung toxicities are significantly lower compared to 3DCRT but when applying a variable RBE, no statistically significant differences are noted. A disadvantage is seen for VMAT over both PBS and 3DCRT. One-to-one plan comparison on 8 patients between PBS and 3DCRT shows similar results. We conclude that dosimetric analysis for all organs and toxicity estimation for the left lung might be underestimated when applying a fixed RBE for protons. Potential RBE variations should therefore be considered as uncertainty bands in outcome analysis.

Linear energy transfer weighted beam orientation optimization for intensity-modulated proton therapy

PURPOSE

In intensity-modulated proton therapy (IMPT), unaccounted-for variation in biological effectiveness contributes to the discrepancy between the constant relative biological effectiveness (RBE) model prediction and experimental observation. It is desirable to incorporate biological doses in treatment planning to improve modeling accuracy and consequently achieve a higher therapeutic ratio. This study addresses this demand by developing a method to incorporate linear energy transfer (LET) into beam orientation optimization (BOO).

METHODS

Instead of RBE-weighted dose, this LET weighted BOO (LETwBOO) framework uses the dose and LET product (LET  ×  D) as the biological surrogate. The problem is formulated with a physical dose fidelity term, a LET  ×  D constraint term, and a group sparsity term. The LET  ×  D of organs at risks is penalized for minimizing the biological effect while maintaining the physical dose objectives. Group sparsity is used to reduce the number of active beams from 600-800 non-coplanar candidate beams to between 2 and 4. This LETwBOO method was tested on three skull base tumor (SBT) patients and three bilateral head-and-neck (H&N) patients. The LETwBOO plans were compared with IMPT plans using manually selected beams with only physical dose constraint (MAN) and the initial MAN plan reoptimized with additional LET  ×  D constraint (LETwMAN).

RESULTS

The LETwBOO plans show superior physical dose and LET  ×  D sparing. On average, the [mean, maximal] doses of organs at risks (OARs) in LETwBOO are reduced by [2.85, 4.6] GyRBE from the MAN plans in the SBT cases and reduced by [0.9, 2.5] GyRBE in the H&N cases, while LETwMAN is comparable to MAN. cLET × Ds of PTVs are comparable in LETwBOO and LETwMAN, where c is a scaling factor of 0.04 μm/keV. On average, in the SBT cases, LETwBOO reduces the OAR [mean, maximal] cLET × D by [1.1, 2.9] Gy from the MAN plans, compared to the reduction by LETwMAN from MAN of [0.7, 1.7] Gy. In the H&N cases, LETwBOO reduces the OAR [mean, maximal] cLET × D by [0.8, 2.6] Gy from the MAN plans, compared to the reduction by LETwMAN from MAN of [0.3, 1.2] Gy.

CONCLUSION

We developed a novel LET weighted BOO method for IMPT to generate plans with improved physical and biological OAR sparing compared with the plans unaccounted for biological effects from BOO.

A biological effect-guided optimization approach using beam distal-edge avoidance for intensity-modulated proton therapy

PURPOSE

Linear energy transfer (LET)-guided methods have been applied to intensity-modulated proton therapy (IMPT) to improve its biological effect. However, using LET as a surrogate for biological effect ignores the topological relationship of the scanning spot to different structures of interest. In this study, we developed an optimization method that takes advantage of the continuing increase in LET beyond the physical dose Bragg peak. This method avoids placing high biological effect values in critical structures and increases biological effect in the tumor area without compromising target coverage.

METHODS

We selected the cases of two patients with brain tumors and two patients with head and neck tumors who had been treated with proton therapy at our institution. Three plans were created for each case: a plan based on conventional dose-based optimization (DoseOpt), one based on LET-incorporating optimization (LETOpt), and one based on the proposed distal-edge avoidance-guided optimization method (DEAOpt). In DEAOpt, an L₁ -norm sparsity term, in which the penalty of each scanning spot was set according to the topological relationship between the organ positions and the location of the peak scaled LET-weighted dose (c LETxD) was added to a conventional dose-based optimization objective function. All plans were normalized to give the same target dose coverage. Dose (assuming a constant relative biological effectiveness value of 1.1, as in clinical practice), biological effect (c LETxD), and computing time consumption were evaluated and compared among the three optimization approaches for each patient case.

RESULTS

For all four cases, all three optimization methods generated comparable dose coverage in both target and critical structures. The LETOpt plans and DEAOpt plans reduced biological effect hot spots in critical structures and increased biological effect in the target volumes to a similar extent. For the target, the c LETxD_98% and c LETxD_2% in the DEAOpt plans were on average 7.2% and 11.74% higher than in the DoseOpt plans, respectively. For the brainstem, the c LETxD_mean in the DEAOpt plans was on average 33.38% lower than in the DoseOpt plans. In addition, the DEAOpt method saved 30.37% of the computation cost over the LETOpt method.

CONCLUSIONS

DEAOpt is an alternative IMPT optimization approach that correlates the location of scanning spots with biological effect distribution. IMPT could benefit from the use of DEAOpt because this method not only delivers comparable biological effects to LETOpt plans, but also is faster.

Inter-patient variations in relative biological effectiveness for cranio-spinal irradiation with protons

Cranio-spinal irradiation (CSI) using protons has dosimetric advantages compared to photons and is expected to reduce risk of adverse effects. The proton relative biological effectiveness (RBE) varies with linear energy transfer (LET), tissue type and dose, but a variable RBE has not replaced the constant RBE of 1.1 in clinical treatment planning. We examined inter-patient variations in RBE for ten proton CSI patients. Variable RBE models were used to obtain RBE and RBE-weighted doses. RBE was quantified in terms of dose weighted organ-mean RBE ([Formula: see text] = mean RBE-weighted dose/mean physical dose) and effective RBE of the near maximum dose (D2%), i.e. RBED2% = [Formula: see text], where subscripts RBE and phys indicate that the D2% is calculated based on an RBE model and the physical dose, respectively. Compared to the median [Formula: see text] of the patient population, differences up to 15% were observed for the individual [Formula: see text] values found for the thyroid, while more modest variations were seen for the heart (6%), lungs (2%) and brainstem (<1%). Large inter-patient variation in RBE could be correlated to large spread in LET and dose for these organs at risk (OARs). For OARs with small inter-patient variations, the results show that applying a population based RBE in treatment planning may be a step forward compared to using RBE of 1.1. OARs with large inter-patient RBE variations should ideally be selected for patient-specific biological or RBE robustness analysis if the physical doses are close to known dose thresholds.

Proton therapy for head and neck squamous cell carcinomas: A review of the physical and clinical challenges

The quality of radiation therapy has been shown to significantly influence the outcomes for head and neck squamous cell carcinoma (HNSCC) patients. The results of dosimetric studies suggest that intensity-modulated proton therapy (IMPT) could be of added value for HNSCC by being more effective than intensity-modulated (photon) radiation therapy (IMRT) for reducing side effects of radiation therapy. However, the physical properties of protons make IMPT more sensitive than photons to planning uncertainties. This could potentially have a negative effect on the quality of IMPT planning and delivery. For this review, the three French proton therapy centers collaborated to evaluate the differences between IMRT and IMPT. The review explored the effects of these uncertainties and their management for developing a robust and optimized IMPT treatment delivery plan to achieve clinical outcomes that are superior to those for IMRT. We also provide practical suggestions for the management of HNSCC carcinoma with IMPT. Because metallic dental implants can increase range uncertainties (3-10%), patient preparation for IMPT may require more systematic removal of in-field alien material than is done for IMRT. Multi-energy CT may be an alternative to calculate more accurately the dose distribution. The practical aspects that we describe are essential to guarantee optimal quality in radiation therapy in both model-based and randomized clinical trials.

Difference in LET-based biological doses between IMPT optimization techniques: Robust and PTV-based optimizations

Purpose

While a large amount of experimental data suggest that the proton relative biological effectiveness (RBE) varies with both physical and biological parameters, current commercial treatment planning systems (TPS) use the constant RBE instead of variable RBE models, neglecting the dependence of RBE on the linear energy transfer (LET). To conduct as accurate a clinical evaluation as possible in this circumstance, it is desirable that the dosimetric parameters derived by TPS (DRBE=1.1) are close to the “true” values derived with the variable RBE models (DvRBE). As such, in this study, the closeness of DRBE=1.1 to DvRBE was compared between planning target volume (PTV)‐based and robust plans.

Methods

Intensity‐modulated proton therapy (IMPT) treatment plans for two Radiation Therapy Oncology Group (RTOG) phantom cases and four nasopharyngeal cases were created using the PTV‐based and robust optimizations, under the assumption of a constant RBE of 1.1. First, the physical dose and dose‐averaged LET (LET_d) distributions were obtained using the analytical calculation method, based on the pencil beam algorithm. Next, DvRBE was calculated using three different RBE models. The deviation of DvRBE from DRBE=1.1 was evaluated with D₉₉ and D_max, which have been used as the evaluation indices for clinical target volume (CTV) and organs at risk (OARs), respectively. The influence of the distance between the OAR and CTV on the results was also investigated. As a measure of distance, the closest distance and the overlapped volume histogram were used for the RTOG phantom and nasopharyngeal cases, respectively.

Results

As for the OAR, the deviations of DmaxvRBE from DmaxRBE=1.1 were always smaller in robust plans than in PTV‐based plans in all RBE models. The deviation would tend to increase as the OAR was located closer to the CTV in both optimization techniques. As for the CTV, the deviations of D99vRBE from D99RBE=1.1 were comparable between the two optimization techniques, regardless of the distance between the CTV and the OAR.

Conclusion

Robust optimization was found to be more favorable than PTV‐based optimization in that the results presented by TPS were closer to the “true” values and that the clinical evaluation based on TPS was more reliable.

Exploring the advantages of intensity-modulated proton therapy: experimental validation of biological effects using two different beam intensity-modulation patterns

In current treatment plans of intensity-modulated proton therapy, high-energy beams are usually assigned larger weights than low-energy beams. Using this form of beam delivery strategy cannot effectively use the biological advantages of low-energy and high-linear energy transfer (LET) protons present within the Bragg peak. However, the planning optimizer can be adjusted to alter the intensity of each beamlet, thus maintaining an identical target dose while increasing the weights of low-energy beams to elevate the LET therein. The objective of this study was to experimentally validate the enhanced biological effects using a novel beam delivery strategy with elevated LET. We used Monte Carlo and optimization algorithms to generate two different intensity-modulation patterns, namely to form a downslope and a flat dose field in the target. We spatially mapped the biological effects using high-content automated assays by employing an upgraded biophysical system with improved accuracy and precision of collected data. In vitro results in cancer cells show that using two opposed downslope fields results in a more biologically effective dose, which may have the clinical potential to increase the therapeutic index of proton therapy.

Robust Optimization for Intensity Modulated Proton Therapy to Redistribute High Linear Energy Transfer from Nearby Critical Organs to Tumors in Head and Neck Cancer

PURPOSE

We propose linear energy transfer (LET)-guided robust optimization in intensity modulated proton therapy for head and neck cancer. This method simultaneously considers LET and physical dose distributions of tumors and organs at risk (OARs) with uncertainties.

METHODS AND MATERIALS

Fourteen patients with head and neck cancer were included in this retrospective study. Cord, brain stem, brain, and oral cavity were considered. Two algorithms, voxel-wise worst-case robust optimization and LET-guided robust optimization (LETRO), were used to generate intensity modulated proton therapy plans for each patient. The latter method directly optimized LET distributions rather than indirectly as in previous methods. LET-volume histograms (LETVHs) were generated, and high LET was redistributed from nearby OARs to tumors in a user-defined way via LET-volume constraints. Dose-volume histogram indices, such as clinical target volume (CTV) D_98% and D_2%-D_98%, cord D_max, brain stem D_max, brain D_max, and oral cavity D_mean, were calculated. Plan robustness was quantified using the worst-case analysis method. LETVH indices analogous to dose-volume histogram indices were used to characterize LET distributions. The Wilcoxon signed rank test was performed to measure statistical significance.

RESULTS

In the nominal scenario, LETRO provided higher LET distributions in the CTV (unit: keV/μm; CTV LET_98%: 1.18 vs 1.08, LETRO vs RO, P = .0031) while preserving comparable physical dose and plan robustness. LETRO achieved significantly reduced LET distributions in the cord, brain stem, and oral cavity compared with RO (cord LET_max: 7.20 vs 8.20, P = .0010; brain stem LET_max: 10.95 vs 12.05, P = .0007; oral cavity LET_mean: 2.11 vs 3.12, P = .0052) and had comparable physical dose and plan robustness in all OARs. In the worst-case scenario, LETRO achieved significantly higher LET_mean in the CTV, reduced LET_max in the brain, and was comparable to other LETVH indices (CTV LET_mean: 3.26 vs 3.35, P = .0012; brain LET_max: 24.80 vs 22.00, P = .0016).

CONCLUSIONS

LETRO robustly optimized LET and physical dose distributions simultaneously. It redistributed high LET from OARs to targets with slightly modified physical dose and plan robustness.

The relative biological effectiveness of proton irradiation in dependence of DNA damage repair

Clinical parameters and empirical evidence are the primary determinants for current treatment planning in radiation oncology. Personalized medicine in radiation oncology is only at the very beginning to take the genetic background of a tumor entity into consideration to define an individual treatment regimen, the total dose or the combination with a specific anticancer agent. Likewise, stratification of patients towards proton radiotherapy is linked to its physical advantageous energy deposition at the tumor site with minimal healthy tissue being co-irradiated distal to the target volume. Hence, the fact that photon and proton irradiation also induce different qualities of DNA damages, which require differential DNA damage repair mechanisms has been completely neglected so far. These subtle differences could be efficiently exploited in a personalized treatment approach and could be integrated into personalized treatment planning. A differential requirement of the two major DNA double-strand break repair pathways, homologous recombination and non-homologous end joining, was recently identified in response to proton and photon irradiation, respectively, and subsequently influence the mode of ionizing radiation-induced cell death and susceptibility of tumor cells with defects in DNA repair machineries to either quality of ionizing radiation.This review focuses on the differential DNA-damage responses and subsequent biological processes induced by photon and proton irradiation in dependence of the genetic background and discusses their impact on the unicellular level and in the tumor microenvironment and their implications for combined treatment modalities.

Towards proton arc therapy: physical and biologically equivalent doses with increasing number of beams in pediatric brain irradiation

Background: Proton arc therapy may improve physical dose conformity and reduce concerns of elevated linear energy transfer (LET) and relative biological effectiveness (RBE) at the end of the proton range, while offering more degrees of freedom for normal tissue sparing. To explore the potential of proton arc therapy, we studied the effect of increasing the number of beams on physical and biologically equivalent dose conformity in the setting of pediatric brain tumors. Material and methods: A cylindrical phantom (Ø = 150 mm) with central cylindrical targets (Ø = 25 and 30 mm) was planned with increasing number of equiangular coplanar proton beams (from 3 to 36). For four anonymized pediatric brain tumor patients, two 'surrogate' proton arc plans (18 equiangular coplanar or sagittal beams) and a reference plan with 3 non-coplanar beams were constructed. Biologically equivalent doses were calculated using two RBE scenarios: RBE_1.1; and RBE_LET, the physical dose weighted by the LET. For both RBE scenarios, dose gradients were assessed, and doses to cognitive brain structures were reported. Results: Increasing the number of beams resulted in an improved dose gradient and reduced volume exposed to intermediate LET levels, at the expense of increased low-dose and low-LET volumes. Most of the differences between the two RBE scenarios were seen around the prescription dose level, where the isodose volumes increased with the RBE_LET plans, e.g. up to 63% in the 3-beam plan for the smallest phantom target. Overall, the temporal lobes were better spared with the sagittal proton arc surrogate plans, e.g. a mean dose of 3.9 Gy compared to 6 Gy in the reference 3-beam plan (median value, RBE_1.1). Conclusion: Proton arc therapy has the potential to improve dose gradients to better spare cognitive brain structures. However, this is at the expense of increased low-dose/low-LET volumes, with possible implications for secondary cancer risks.

[Proton therapy for head and neck squamous cell carcinomas: From physics to clinic]

Intensity-modulated radiation therapy (IMRT) is presently the recommended technique for the treatment of locally advanced head and neck carcinomas. Proton therapy would allow to reduce the volume of irradiated normal tissue and, thus, to decrease the risk of late dysphagia, xerostomia, dysgeusia and hypothyroidism. An exhaustive research was performed with the search engine PubMed by focusing on the papers about the physical difficulties that slow down use of proton therapy for head and neck carcinomas. Range uncertainties in proton therapy (±3 %) paradoxically limit the use of the steep dose gradient in distality. Calibration uncertainties can be important in the treatment of head and neck cancer in the presence of materials of uncertain stoichiometric composition (such as with metal implants, dental filling, etc.) and complex heterogeneities. Dental management for example may be different with IMRT or proton therapy. Some uncertainties can be somewhat minimized at the time of optimization. Inter- and intrafractional variations and uncertainties in Hounsfield units/stopping power can be integrated in a robust optimization process. Additional changes in patient's anatomy (tumour shrinkage, changes in skin folds in the beam patch, large weight loss or gain) require rescanning. Dosimetric and small clinical studies comparing photon and proton therapy have well shown the interest of proton therapy for head and neck cancers. Intensity-modulated proton therapy is a promising treatment as it can reduce the substantial toxicity burden of patients with head and neck squamous cell carcinoma compared to IMRT. Robust optimization will allow to perform an optimal treatment and to use proton therapy in current clinical practice.

Increased risk of pseudoprogression among pediatric low-grade glioma patients treated with proton versus photon radiotherapy

BACKGROUND

Pseudoprogression (PsP) is a recognized phenomenon after radiotherapy (RT) for high-grade glioma but is poorly characterized for low-grade glioma (LGG). We sought to characterize PsP for pediatric LGG patients treated with RT, with particular focus on the role of RT modality using photon-based intensity-modulated RT (IMRT) or proton beam therapy (PBT).

METHODS

Serial MRI scans from 83 pediatric LGG patients managed at 2 institutions between 1998 and 2017 were evaluated. PsP was scored when a progressive lesion subsequently decreased or stabilized for at least a year without therapy.

RESULTS

Thirty-two patients (39%) were treated with IMRT, and 51 (61%) were treated with PBT. Median RT dose for the cohort was 50.4 Gy(RBE) (range, 45-59.4 Gy[RBE]). PsP was identified in 31 patients (37%), including 8/32 IMRT patients (25%) and 23/51 PBT patients (45%). PBT patients were significantly more likely to have post-RT enlargement (hazard ratio [HR] 2.15, 95% CI: 1.06-4.38, P = 0.048). RT dose >50.4 Gy(RBE) similarly predicted higher rates of PsP (HR 2.61, 95% CI: 1.20-5.68, P = 0.016). Multivariable analysis confirmed the independent effects of RT modality (P = 0.03) and RT dose (P = 0.01) on PsP incidence. Local progression occurred in 10 patients: 7 IMRT patients (22%) and 3 PBT patients (6%), with a trend toward improved local control for PBT patients (HR 0.34, 95% CI: 0.10-1.18, P = 0.099).

CONCLUSIONS

These data highlight substantial rates of PsP among pediatric LGG patients, particularly those treated with PBT. PsP should be considered when assessing response to RT in LGG patients within the first year after RT.

Robust optimization to reduce the impact of biological effect variation from physical uncertainties in intensity-modulated proton therapy

Robust optimization (RO) methods are applied to intensity-modulated proton therapy (IMPT) treatment plans to ensure their robustness in the face of treatment delivery uncertainties, such as proton range and patient setup errors. However, the impact of those uncertainties on the biological effect of protons has not been specifically considered. In this study, we added biological effect-based objectives into a conventional RO cost function for IMPT optimization to minimize the variation in biological effect. One brain tumor case, one prostate tumor case and one head & neck tumor case were selected for this study. Three plans were generated for each case using three different optimization approaches: planning target volume (PTV)-based optimization, conventional RO, and RO incorporating biological effect (BioRO). In BioRO, the variation in biological effect caused by IMPT delivery uncertainties was minimized for voxels in both target volumes and critical structures, in addition to a conventional voxel-based worst-case RO objective function. The biological effect was approximated by the product of dose-averaged linear energy transfer (LET) and physical dose. All plans were normalized to give the same target dose coverage, assuming a constant relative biological effectiveness (RBE) of 1.1. Dose, biological effect, and their uncertainties were evaluated and compared among the three optimization approaches for each patient case. Compared with PTV-based plans, RO plans achieved more robust target dose coverage and reduced biological effect hot spots in critical structures near the target. Moreover, with their sustained robust dose distributions, BioRO plans not only reduced variations in biological effect in target and normal tissues but also further reduced biological effect hot spots in critical structures compared with RO plans. Our findings indicate that IMPT could benefit from the use of conventional RO, which would reduce the biological effect in normal tissues and produce more robust dose distributions than those of PTV-based optimization. More importantly, this study provides a proof of concept that incorporating biological effect uncertainty gap into conventional RO would not only control the IMPT plan robustness in terms of physical dose and biological effect but also achieve further reduction of biological effect in normal tissues.

Simultaneous optimization of RBE-weighted dose and nanometric ionization distributions in treatment planning with carbon ions

Inverse treatment planning in intensity modulated particle therapy (IMPT) with scanned carbon-ion beams is currently based on the optimization of RBE-weighted dose to satisfy requirements of target coverage and limited toxicity to organs-at-risk (OARs) and healthy tissues. There are many feasible IMPT plans that meet these requirements, which allows the introduction of further criteria to narrow the selection of a biologically optimal treatment plan. We propose a novel treatment planning strategy based on the simultaneous optimization of RBE-weighted dose and nanometric ionization details (ID) as a new physical characteristic of the delivered plan beyond LET. In particular, we focus on the distribution of large ionization clusters (more than 3 ionizations) to enhance the biological effect across the target volume while minimizing biological effect in normal tissues. Carbon-ion treatment plans for different patient geometries and beam configurations generated with the simultaneous optimization strategy were compared against reference plans obtained with RBE-weighted dose optimization alone. Quality indicators, inhomogeneity index and planning volume histograms of RBE-weighted dose and large ionization clusters were used to evaluate the treatment plans. We show that with simultaneous optimization, ID distributions can be optimized in carbon-ion radiotherapy without compromising the RBE-weighted dose distributions. This strategy can potentially be used to account for optimization of endpoints closely related to radiation quality to achieve better tumor control and reduce risks of complications.

Fixed- versus Variable-RBE Computations for Intensity Modulated Proton Therapy

Purpose

To evaluate how using models of proton therapy that incorporate variable relative biological effectiveness (RBE) versus the current practice of using a fixed RBE of 1.1 affects dosimetric indices on treatment plans for large cohorts of patients treated with intensity modulated proton therapy (IMPT).

Methods and Materials

Treatment plans for 4 groups of patients who received IMPT for brain, head-and-neck, thoracic, or prostate cancer were selected. Dose distributions were recalculated in 4 ways: 1 with a fast-dose Monte Carlo calculator with fixed RBE and 3 with RBE calculated to 3 different models—McNamara, Wedenberg, and repair-misrepair-fixation. Differences among dosimetric indices (D02, D50, D98, and mean dose) for target volumes and organs at risk (OARs) on each plan were compared between the fixed-RBE and variable-RBE calculations.

Results

In analyses of all target volumes, for which the main concern is underprediction or RBE less than 1.1, none of the models predicted an RBE less than 1.05 for any of the cohorts. For OARs, the 2 models based on linear energy transfer, McNamara and Wedenberg, systematically predicted RBE >1.1 for most structures. For the mean dose of 25% of the plans for 2 OARs, they predict RBE equal to or larger than 1.4, 1.3, 1.3, and 1.2 for brain, head-and-neck, thorax, and prostate, respectively. Systematically lower increases in RBE are predicted by repair-misrepair-fixation, with a few cases (eg, femur) in which the RBE is less than 1.1 for all plans.

Conclusions

The variable-RBE models predict increased doses to various OARs, suggesting that strategies to reduce high-dose linear energy transfer in critical structures should be developed to minimize possible toxicity associated with IMPT.

Proton therapy for treatment of intracranial benign tumors in adults: A systematic review

INTRODUCTION

The depth-dose distribution of a proton beam, materialized by the Bragg peak makes it an attractive radiation modality as it reduces exposure of healthy tissues to radiations, compared with photon therapy Prominent indications, based on a long-standing experience are: intraocular melanomas, low-grade skull-base and spinal canal malignancies. However, many others potential indications are under investigations such as the benign morbid conditions that are compatible with an extended life-expectancy: low grade meningiomas, paragangliomas, pituitary adenomas, neurinomas craniopharyngioma or recurrent pleomorphic adenomas.

MATERIALS

Given the radiation-induced risk of secondary cancer and the potential neurocognitive and functional alteration with photonic radiotherapy, we systematically analyzed the existing clinical literature about the use of proton therapy as an irradiation modality for cervical or intracranial benign tumors. The aim of this review was to report clinical outcomes of adult patients with benign intracranial or cervical tumors treated with proton therapy and to discuss about potential advantages of proton therapy over intensity modulated radiotherapy or radiosurgery.

RESULTS

Twenty-four studies were included. There was no randomized studies. Most studies dealt with low grade meningiomas (n = 9). Studies concerning neurinoma (n = 4), pituitary adenoma (n = 5), paraganglioma (n = 5), or craniopharyngioma (n = 1) were fewer. Whatever the indication, long term local control was systematically higher than 90% and equivalent to series with conventional radiotherapy.

CONCLUSION

Proton-therapy for treatment of adult benign intracranial and cervical tumors is safe. Randomized or prospective cohorts with long term cognitive evaluations are needed to assess the real place of proton-therapy in the treatment of adults benign head and neck tumors.

Introducing Proton Track-End Objectives in Intensity Modulated Proton Therapy Optimization to Reduce Linear Energy Transfer and Relative Biological Effectiveness in Critical Structures

PURPOSE

We propose the use of proton track-end objectives in intensity modulated proton therapy (IMPT) optimization to reduce the linear energy transfer (LET) and the relative biological effectiveness (RBE) in critical structures.

METHODS AND MATERIALS

IMPT plans were generated for 3 intracranial patient cases (1.8 Gy (RBE) in 30 fractions) and 3 head-and-neck patient cases (2 Gy (RBE) in 35 fractions), assuming a constant RBE of 1.1. Two plans were generated for each patient: (1) physical dose objectives only (DOSEopt) and (2) same dose objectives as the DOSEopt plan, with additional proton track-end objectives (TEopt). The track-end objectives penalized protons stopping in the risk volume of choice. Dose evaluations were made using a RBE of 1.1 and the LET-dependent Wedenberg RBE model, together with estimates of normal tissue complication probabilities (NTCPs). In addition, the distributions of proton track-ends and dose-average LET (LET_d) were analyzed.

RESULTS

The TEopt plans reduced the mean LET_d in the critical structures studied by an average of 37% and increased the mean LET_d in the primary clinical target volume (CTV) by an average of 23%. This was achieved through a redistribution of the proton track-ends, concurrently keeping the physical dose distribution virtually unchanged compared to the DOSEopt plans. This resulted in substantial RBE-weighted dose (D_RBE) reductions, allowing the TEopt plans to meet all clinical goals for both RBE models and reduce the NTCPs by 0 to 19 percentage points compared to the DOSEopt plans, assuming the Wedenberg RBE model. The DOSEopt plans met all clinical goals assuming a RBE of 1.1 but failed 10 of 19 normal tissue goals assuming the Wedenberg RBE model.

CONCLUSIONS

Proton track-end objectives allow for LET_d reductions in critical structures without compromising the physical target dose. This approach permits the lowering of D_RBE and NTCP in critical structures, independent of the variable RBE model used, and it could be introduced in clinical practice without changing current protocols based on the constant RBE of 1.1.

Can differences in linear energy transfer and thus relative biological effectiveness compromise the dosimetric advantage of intensity-modulated proton therapy as compared to passively scattered proton therapy?

PURPOSE

To investigate the effect of differences in linear energy transfer (LET) and thus the relative biological effectiveness (RBE) between passively scattered proton therapy (PS) and pencil-beam scanning intensity-modulated proton therapy (IMPT).

METHODS

IMPT treatment plans were generated for six ependymoma patients, originally treated with PS, using the original plan's computed tomography image sets and beam directions, and its dose-volume values as optimization constraints. Two beam spot sizes and both single-field optimization (SFO) and multi-field optimization (MFO) techniques were used for each patient. Three-dimensional variable-RBE-weighted dose distributions were computed, using Monte Carlo calculated dose and LET distributions, and a linear dose and LET-based RBE model, and were compared between the two delivery methods.

RESULTS

Increased target dose coverage and decreased mean and maximum dose to the OARs was achieved with IMPT compared to PS, for constant RBE value of 1.1. Nevertheless, the maximum variable-RBE-weighted dose to the brainstem, was increased up to 6% for the IMPT plans compared to the corresponding PS plans.

CONCLUSIONS

IMPT can be dosimetrically superior to PS for ependymoma patients. However, caution should be exercised so that the increased dose conformity is not counteracted by an increase in radiobiological effect in adjacent critical structures.

Physical parameter optimization scheme for radiobiological studies of charged particle therapy

We have developed an easy-to-implement method to optimize the spatial distribution of a desired physical quantity for charged particle therapy. The basic methodology requires finding the optimal solutions for the weights of the constituent particle beams that together form the desired spatial distribution of the specified physical quantity, e.g., dose or dose-averaged linear energy transfer (LET_d), within the target region. We selected proton, ⁴He ion, and ¹²C ion beams to demonstrate the feasibility and flexibility of our method. The pristine dose Bragg curves in water for all ion beams and the LET_d for proton beams were generated from Geant4 Monte Carlo simulations. The optimization algorithms were implemented using the Python programming language. High-accuracy optimization results of the spatial distribution of the desired physical quantity were then obtained for different cases. The relative difference between the real value and the expected value of a given quantity was approximately within ±1.0% in the whole target region. The optimization examples include a flat dose spread-out Bragg peak (SOBP) for the three selected ions, an upslope dose SOBP for protons, and a downslope dose SOBP for protons. The relative difference was approximately within ±2.0% for the case with a flat LET_d (target value = 4 keV/µm) distribution for protons. These one-dimensional optimization algorithms can be extended to two or three dimensions if the corresponding physical data are available. In addition, this physical quantity optimization strategy can be conveniently extended to encompass biological dose optimization if appropriate biophysical models are invoked.