Generation and evaluation of anatomy-preserving virtual CT for online adaptive proton therapy

BACKGROUND

Daily CTs generated by CBCT correction are required for daily replanning in online-adaptive proton therapy (APT) to effectively deal with inter-fractional changes. Out of the currently available methods, the suitability of a daily CT generation method for proton dose calculation also depends on the anatomical site.

PURPOSE

We propose an anatomy-preserving virtual CT (APvCT) method as a hybrid method of CBCT correction, which is especially suitable for large anatomy deformations. The accuracy of the hybrid method was assessed by comparison with the corrected CBCT (cCBCT) and virtual CT (vCT) methods in the context of online APT.

METHODS

Seventy-one daily CBCTs of four prostate cancer patients treated with intensity modulated proton therapy (IMPT) were converted to daily CTs using cCBCT, vCT, and the newly proposed APvCT method. In APvCT, planning CT (pCT) were mapped to CBCT geometry using deformable image registration with boundary conditions on controlling regions of interest (ROIs) created with deep learning segmentation on cCBCT. The relative frequency distribution (RFD) of HU, mass density and stopping power ratio (SPR) values were assessed and compared with the pCT. The ROIs in the APvCT and vCT were compared with cCBCT in terms of Dice similarity coefficient (DSC) and mean distance-to-agreement (mDTA). For each patient, a robustly optimized IMPT plan was created on the pCT and subsequent daily adaptive plans on daily CTs. For dose distribution comparison on the same anatomy, the daily adaptive plans on cCBCT and vCT were recalculated on the corresponding APvCT. The dose distributions were compared in terms of isodose volumes and 3D global gamma-index passing rate (GPR) at γ(2%, 2 mm) criterion.

RESULTS

For all patients, no noticeable difference in RFDs was observed amongst APvCT, vCT, and pCT except in cCBCT, which showed a noticeable difference. The minimum DSC value was 0.96 and 0.39 for contours in APvCT and vCT respectively. The average value of mDTA for APvCT was 0.01 cm for clinical target volume and ≤0.01 cm for organs at risk, which increased to 0.18 cm and ≤0.52 cm for vCT. The mean GPR value was 90.9%, 64.5%, and 67.0% for APvCT versus cCBCT, vCT versus cCBCT, and APvCT versus vCT, respectively. When recalculated on APvCT, the adaptive cCBCT and vCT plans resulted in mean GPRs of 89.5 ± 5.1% and 65.9 ± 19.1%, respectively. The mean DSC values for 80.0%, 90.0%, 95.0%, 98.0%, and 100.0% isodose volumes were 0.97, 0.97, 0.97, 0.95, and 0.91 for recalculated cCBCT plans, and 0.89, 0.88, 0.87, 0.85, and 0.81 for recalculated vCT plans. Hausdorff distance for the 100.0% isodose volume in some cases of recalculated cCBCT plans on APvCT exceeded 1.00 cm.

CONCLUSIONS

APvCT contours showed good agreement with reference contours of cCBCT which indicates anatomy preservation in APvCT. A vCT with erroneous anatomy can result in an incorrect adaptive plan. Further, slightly lower values of GPR between the APvCT and cCBCT-based adaptive plans can be explained by the difference in the cCBCT's SPR RFD from the pCT.

A Novel Framework for Thermoradiotherapy Treatment Planning

PURPOSE

Thermoradiotherapy combines radiation therapy with hyperthermia to increase therapeutic effectiveness. Currently, both modalities are optimized separately and in state-of-the-art research the enhanced therapeutic effect is evaluated using equivalent radiation dose in 2-Gy fractions (EQD2). This study proposes a novel thermoradiotherapy treatment planning framework with voxelwise EQD2 radiation therapy optimizing including thermal radiosensitization and direct thermal cytotoxicity.

METHODS AND MATERIALS

To demonstrate proof-of-concept of the planning framework, 3 strategies consisting of 20 radiation therapy fractions were planned for 4 prostate cancer cases with substantially different temperature distributions: (1) Conventional radiation therapy plan of 60 Gy combined with 4 hyperthermia sessions (RT60 + HT), (2) standalone uniform dose escalation to 68 Gy without hyperthermia (RT68), and (3) uniform target EQD2 that maximizes the tumor control probability (TCP) accounting for voxelwise thermal effects of 4 hyperthermia sessions without increasing normal tissue doses (RTHT + HT). Assessment included dose, EQD2, TCP, and rectal normal tissue complication probability (NTCP), alongside robustness analyses for TCP and NTCP against parameter uncertainties.

RESULTS

The estimated TCP of around 76% for RT60 without hyperthermia was increased to an average of 85.9% (range, 81.3%-90.5%) for RT60 + HT, 92.5% (92.4%-92.5%) for RT68, and 94.4% (91.7%-96.6%) for RTHT + HT. The corresponding averaged rectal NTCPs were 8.7% (7.9%-10.0%), 14.9% (13.8%-17.1%), and 8.4% (7.5%-9.7%), respectively. RT68 and RTHT + HT exhibited slightly enhanced TCP robustness against parameter uncertainties compared with RT60 + HT, and RT68 presented higher and less robust rectal NTCP values compared with the other planning strategies.

CONCLUSIONS

This study introduces an innovative thermoradiotherapy planning approach, integrating thermal effects into EQD2-based radiation therapy optimization. Results demonstrate an ability to achieve enhanced and uniform target EQD2 and TCP across various temperature distributions without elevating normal tissue EQD2 or NTCP compared with conventional methods. Although promising for improving clinical outcomes, realizable enhancements depend on accurate tumor- and tissue-specific data and precise quantification of hyperthermic effects, which are seamlessly integrable in the planning framework as they emerge.

Technical note: Optimization functions for re-irradiation treatment planning

BACKGROUND

Although re-irradiation is increasingly used in clinical practice, almost no dedicated planning software exists.

PURPOSE

Standard dose-based optimization functions were adjusted for re-irradiation planning using accumulated equivalent dose in 2-Gy fractions (EQD2) with rigid or deformable dose mapping, tissue-specific α/β, treatment-specific recovery coefficients, and voxelwise adjusted EQD2 penalization levels based on the estimated previously delivered EQD2 (EQD2deliv ).

METHODS

To demonstrate proof-of-concept, 35 Gy in 5 fractions was planned to a fictitious spherical relapse planning target volume (PTV) in three separate locations following previous prostate treatment on a virtual human phantom. The PTV locations represented one repeated irradiation scenario and two re-irradiation scenarios. For each scenario, three re-planning strategies with identical PTV dose-functions but various organ at risk (OAR) EQD2-functions was used: 1) reRTregular : Regular functions with fixed EQD2 penalization levels larger than EQD2deliv for all OAR voxels. 2) reRTreduce : As reRTregular , but with lower fixed EQD2 penalization levels aiming to reduce OAR EQD2. 3) reRTvoxelwise : As reRTregular and reRTreduce , but with voxelwise adjusted EQD2 penalization levels based on EQD2deliv . PTV near-minimum and near-maximum dose (D98% /D2% ), homogeneity index (HI), conformity index (CI) and accumulated OAR EQD2 (α/β = 3 Gy) were evaluated.

RESULTS

For the repeated irradiation scenario, all strategies resulted in similar dose distributions. For the re-irradiation scenarios, reRTreduce and reRTvoxelwise reduced accumulated average and near-maximum EQD2 by ˜1-10 Gy for all relevant OARs compared to reRTregular . The reduced OAR doses for reRTreduce came at the cost of distorted dose distributions with D98% = 92.3%, HI = 12.0%, CI = 73.7% and normal tissue hot spots ≥150% for the most complex scenario, while reRTregular (D98% = 98.1%, HI = 3.2%, CI = 94.2%) and reRTvoxelwise (D98%  = 96.9%, HI = 6.1%, CI = 93.7%) fulfilled PTV coverage without hot spots.

CONCLUSIONS

The proposed re-irradiation-specific EQD2-based optimization functions introduce novel planning possibilities with flexible options to guide the trade-off between target coverage and OAR sparing with voxelwise adapted penalization levels based on EQD2deliv .

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

BACKGROUND

Applying tolerance doses for organs at risk (OAR) from photon therapy introduces uncertainties in proton therapy when assuming a constant relative biological effectiveness (RBE) of 1.1.

PURPOSE

This work introduces the novel dirty and clean dose concept, which allows for creating treatment plans with a more photon-like dose response for OAR and, thus, less uncertainties when applying photon-based tolerance doses.

METHODS

The concept divides the 1.1-weighted dose distribution into two parts: the clean and the dirty dose. The clean and dirty dose are deposited by protons with a linear energy transfer (LET) below and above a set LET threshold, respectively. For the former, a photon-like dose response is assumed, while for the latter, the RBE might exceed 1.1. To reduce the dirty dose in OAR, a MaxDirtyDose objective was added in treatment plan optimization. It requires setting two parameters: LET threshold and max dirty dose level. A simple geometry consisting of one target volume and one OAR in water was used to study the reduction in dirty dose in the OAR depending on the choice of the two MaxDirtyDose objective parameters during plan optimization. The best performing parameter combinations were used to create multiple dirty dose optimized (DDopt) treatment plans for two cranial patient cases. For each DDopt plan, 1.1-weighted dose, variable RBE-weighted dose using the Wedenberg RBE model and dose-average LETd distributions as well as resulting normal tissue complication probability (NTCP) values were calculated and compared to the reference plan (RefPlan) without MaxDirtyDose objectives.

RESULTS

In the water phantom studies, LET thresholds between 1.5 and 2.5 keV/µm yielded the best plans and were subsequently used. For the patient cases, nearly all DDopt plans led to a reduced Wedenberg dose in critical OAR. This reduction resulted from an LET reduction and translated into an NTCP reduction of up to 19 percentage points compared to the RefPlan. The 1.1-weighted dose in the OARs was slightly increased (patient 1: 0.45 Gy(RBE), patient 2: 0.08 Gy(RBE)), but never exceeded clinical tolerance doses. Additionally, slightly increased 1.1-weighted dose in healthy brain tissue was observed (patient 1: 0.81 Gy(RBE), patient 2: 0.53 Gy(RBE)). The variation of NTCP values due to variation of α/β from 2 to 3 Gy was much smaller for DDopt (2 percentage points (pp)) than for RefPlans (5 pp).

CONCLUSIONS

The novel dirty and clean dose concept allows for creating biologically more robust proton treatment plans with a more photon-like dose response. The reduced uncertainties in RBE can, therefore, mitigate uncertainties introduced by using photon-based tolerance doses for OAR.

Brain Re-Irradiation Robustly Accounting for Previously Delivered Dose

(1) Background: The STRIDeR (Support Tool for Re-Irradiation Decisions guided by Radiobiology) planning pathway aims to facilitate anatomically appropriate and radiobiologically meaningful re-irradiation (reRT). This work evaluated the STRIDeR pathway for robustness compared to a more conservative manual pathway. (2) Methods: For ten high-grade glioma reRT patient cases, uncertainties were applied and cumulative doses re-summed. Geometric uncertainties of 3, 6 and 9 mm were applied to the background dose, and LQ model robustness was tested using α/β variations (values 1, 2 and 5 Gy) and the linear quadratic linear (LQL) model δ variations (values 0.1 and 0.2). STRIDeR robust optimised plans, incorporating the geometric and α/β uncertainties during optimisation, were also generated. (3) Results: The STRIDeR and manual pathways both achieved clinically acceptable plans in 8/10 cases but with statistically significant improvements in the PTV D98% (p < 0.01) for STRIDeR. Geometric and LQ robustness tests showed comparable robustness within both pathways. STRIDeR plans generated to incorporate uncertainties during optimisation resulted in a superior plan robustness with a minimal impact on PTV dose benefits. (4) Conclusions: Our results indicate that STRIDeR pathway plans achieved a similar robustness to manual pathways with improved PTV doses. Geometric and LQ model uncertainties can be incorporated into the STRIDeR pathway to facilitate robust optimisation.

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.

Towards harmonizing clinical linear energy transfer (LET) reporting in proton radiotherapy: a European multi-centric study

BACKGROUND

Clinical data suggest that the relative biological effectiveness (RBE) in proton therapy (PT) varies with linear energy transfer (LET). However, LET calculations are neither standardized nor available in clinical routine. Here, the status of LET calculations among European PT institutions and their comparability are assessed.

MATERIALS AND METHODS

Eight European PT institutions used suitable treatment planning systems with their center-specific beam model to create treatment plans in a water phantom covering different field arrangements and fulfilling commonly agreed dose objectives. They employed their locally established LET simulation environments and procedures to determine the corresponding LET distributions. Dose distributions D1.1 and DRBE assuming constant and variable RBE, respectively, and LET were compared among the institutions. Inter-center variability was assessed based on dose- and LET-volume-histogram parameters.

RESULTS

Treatment plans from six institutions fulfilled all clinical goals and were eligible for common analysis. D1.1 distributions in the target volume were comparable among PT institutions. However, corresponding LET values varied substantially between institutions for all field arrangements, primarily due to differences in LET averaging technique and considered secondary particle spectra. Consequently, DRBE using non-harmonized LET calculations increased inter-center dose variations substantially compared to D1.1 and significantly in mean dose to the target volume of perpendicular and opposing field arrangements (p < 0.05). Harmonizing LET reporting (dose-averaging, all protons, LET to water or to unit density tissue) reduced the inter-center variability in LET to the order of 10-15% within and outside the target volume for all beam arrangements. Consequentially, inter-institutional variability in DRBE decreased to that observed for D1.1.

CONCLUSION

Harmonizing the reported LET among PT centers is feasible and allows for consistent multi-centric analysis and reporting of tumor control and toxicity in view of a variable RBE. It may serve as basis for harmonized variable RBE dose prescription in PT.

Photon and Proton Dose Painting Based on Oxygen Distribution – Feasibility Study and Tumour Control Probability Assessment

Solid tumours may present hypoxic sub-regions of increased radioresistance. Hypoxia quantification requires of clinically implementable, non-invasive and reproducible techniques as positron emission tomography (PET). PET-based dose painting strategies aiming at targeting those sub-regions may be limited by the resolution gap between the PET imaging resolution and the smaller scale at which hypoxia occurs. The ultimate benefit of the usage of dose painting may be reached if the planned dose distribution can be performed and delivered consistently. This study aimed at assessing the feasibility of two PET-based dose painting strategies using two beam qualities (photon or proton beams) in terms of tumour control probability (TCP), accounting for underlying oxygen distribution at sub-millimetre scale.A tumour oxygenation model at submillimetre scale was created consisting of three regions with different oxygen partial pressure distributions, being hypoxia decreasing from core to periphery. A published relationship between uptake and oxygen partial pressure was used and a PET image of the tumour was simulated. The fundamental effects that limit the PET camera resolution were considered by processing the uptake distribution with a Gaussian 3D filter and re-binning to a PET image voxel size of 2 mm. Prescription doses to overcome tumour hypoxia were calculated based on the processed images, and planned using robust optimisation.Normal tissue complication probabilities and TCPs after the delivery of the planned doses were calculated for the nominal plan and the lowest bounds of the dose volume histograms resulting from the robust scenarios planned, taking into account the underlying oxygenation at submillimetre scale. Results were presented for the two beam qualities and the two dose painting strategies: by contours (DPBC) and by using a voxel grouping-based approach (DPBOX).In the studied case, DPBOX outperforms DPBC with respect to TCP regardless the beam quality, although both dose painting strategy plans demonstrated robust target coverage.

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.

The influence of breathing motion and a variable relative biological effectiveness in proton therapy of left-sided breast cancer

BACKGROUND

Proton breast radiotherapy has been suggested to improve target coverage as well as reduce cardiopulmonary and integral dose compared with photon therapy. This study aims to assess this potential when accounting for breathing motion and a variable relative biological effectiveness (RBE).

METHODS

Photon and robustly optimized proton plans were generated to deliver 50 Gy (RBE) in 25 fractions (RBE = 1.1) to the CTV (whole left breast) for 12 patients. The plan evaluation was performed using the constant RBE and a variable RBE model. Robustness against breathing motion, setup, range and RBE uncertainties was analyzed using CT data obtained at free-breathing, breath-hold-at-inhalation and breath-hold-at-exhalation.

RESULTS

All photon and proton plans (RBE = 1.1) met the clinical goals. The variable RBE model predicted an average RBE of 1.18 for the CTVs (range 1.14-1.21) and even higher RBEs in organs at risk (OARs). However, the dosimetric impact of this latter aspect was minor due to low OAR doses. The normal tissue complication probability (NTCP) for the lungs was low for all patients (<1%), and similar for photons and protons. The proton plans were generally considered robust for all patients. However, in the most extreme scenarios, the lowest dose received by 98% of the CTV dropped from 96 to 99% of the prescribed dose to around 92-94% for both protons and photons. Including RBE uncertainties in the robustness analysis resulted in substantially higher worst-case OAR doses.

CONCLUSIONS

Breathing motion seems to have a minor effect on the plan quality for breast cancer. The variable RBE might impact the potential benefit of protons, but could probably be neglected in most cases where the physical OAR doses are low. However, to be able to identify outlier cases at risk for high OAR doses, the biological evaluation of proton plans taking into account the variable RBE is recommended.

Incorporation of relative biological effectiveness uncertainties into proton plan robustness evaluation

BACKGROUND

The constant relative biological effectiveness (RBE) of 1.1 is typically assumed in proton therapy. This study presents a method of incorporating the variable RBE and its uncertainties into the proton plan robustness evaluation.

MATERIAL AND METHODS

The robustness evaluation was split into two parts. In part one, the worst-case physical dose was estimated using setup and range errors, including the fractionation dependence. The results were fed into part two, in which the worst-case RBE-weighted doses were estimated using a Monte Carlo method for sampling the input parameters of the chosen RBE model. The method was applied to three prostate, breast and head and neck (H&N) plans for several fractionation schedules using two RBE models. The uncertainties in the model parameters, linear energy transfer and α/β were included. The resulting DVH error bands were compared with the use of a constant RBE without uncertainties.

RESULTS

All plans were evaluated as robust using the constant RBE. Applying the proposed methodology using the variable RBE models broadens the DVH error bands for all structures studied. The uncertainty in α/β was the dominant factor. The variable RBE also shifted the nominal DVHs towards higher doses for most OARs, whereas the direction of this shift for the clinical target volumes (CTVs) depended on the treatment site, RBE model and fractionation schedule. The average RBE within the CTV, using one of the RBE models and 2 Gy(RBE) per fraction, varied between 1.11-1.26, 1.06-1.16 and 1.14-1.25 for the breast, H&N and prostate patients, respectively.

CONCLUSIONS

A method of incorporating RBE uncertainties into the robustness evaluation has been proposed. By disregarding the variable RBE and its uncertainties, the variation in the RBE-weighted CTV and OAR doses may be underestimated. This could be an essential factor to take into account, especially in normal tissue complication probabilities based comparisons between proton and photon plans.

Inclusion of a variable RBE into proton and photon plan comparison for various fractionation schedules in prostate radiation therapy

PURPOSE

A constant relative biological effectiveness (RBE) of 1.1 is currently used in proton radiation therapy to account for the increased biological effectiveness compared to photon therapy. However, there is increasing evidence that proton RBE vary with the linear energy transfer (LET), the dose per fraction, and the type of the tissue. Therefore, this study aims to evaluate the impact of disregarding variations in RBE when comparing proton and photon dose plans for prostate treatments for various fractionation schedules using published RBE models and several α/β assumptions.

METHODS

Photon and proton dose plans were created for three generic prostate cancer cases. Three BED_3Gy equivalent schedules were studied, 78, 57.2, and 42.8 Gy in 39, 15, and 7 fractions, respectively. The proton plans were optimized assuming a constant RBE of 1.1. By using the Monte Carlo calculated dose-averaged LET (LET_d ) distribution and assuming α/β values on voxel level, three variable RBE models were applied to the proton dose plans. The impact of the variable RBE was studied in the plan comparison, which was based on the dose distribution, DVHs, and normal tissue complication probabilities (NTCP) for the rectum. Subsequently, the physical proton dose was reoptimized for each proton plan based on the LET_d distribution, to achieve a homogeneous RBE-weighted target dose when applying a specific RBE model and still fulfill the clinical goals for the rectum and bladder.

RESULTS

All the photon and proton plans assuming RBE = 1.1 met the clinical goals with similar target coverage. The proton plans fulfilled the robustness criteria in terms of range and setup uncertainty. Applying the variable RBE models generally resulted in higher target doses and rectum NTCP compared to the photon plans. The increase was most pronounced for the fractionation dose of 2 Gy(RBE), whereas it was of less magnitude and more dependent on model and α/β assumption for the hypofractionated schedules. The reoptimized proton plans proved to be robust and showed similar target coverage and doses to the organs at risk as the proton plans optimized with a constant RBE.

CONCLUSIONS

Model predicted RBE values may differ substantially from 1.1. This is most pronounced for fractionation doses of around 2 Gy(RBE) with higher doses to the target and the OARs, whereas the effect seems to be of less importance for the hypofractionated schedules. This could result in misleading conclusions when comparing proton plans to photon plans. By accounting for a variable RBE in the optimization process, robust and clinically acceptable dose plans, with the potential of lowering rectal NTCP, may be generated by reoptimizing the physical dose. However, the direction and magnitude of the changes in the physical proton dose to the prostate are dependent on RBE model and α/β assumptions and should therefore be used conservatively.

Dosimetric comparison between intra-cavitary breast brachytherapy techniques for accelerated partial breast irradiation and a novel stereotactic radiotherapy device for breast cancer: GammaPod™

The GammaPod™ device, manufactured by Xcision Medical Systems, is a novel stereotactic breast irradiation device. It consists of a hemispherical source carrier containing 36 Cobalt-60 sources, a tungsten collimator with two built-in collimation sizes, a dynamically controlled patient support table and a breast immobilization cup also functioning as the stereotactic frame for the patient. The dosimetric output of the GammaPod™ was modelled using a Monte Carlo based treatment planning system. For the comparison, three-dimensional (3D) models of commonly used intra-cavitary breast brachytherapy techniques utilizing single lumen and multi-lumen balloon as well as peripheral catheter multi-lumen implant devices were created and corresponding 3D dose calculations were performed using the American Association of Physicists in Medicine Task Group-43 formalism. Dose distributions for clinically relevant target volumes were optimized using dosimetric goals set forth in the National Surgical Adjuvant Breast and Bowel Project Protocol B-39. For clinical scenarios assuming similar target sizes and proximity to critical organs, dose coverage, dose fall-off profiles beyond the target and skin doses at given distances beyond the target were calculated for GammaPod™ and compared with the doses achievable by the brachytherapy techniques. The dosimetric goals within the protocol guidelines were fulfilled for all target sizes and irradiation techniques. For central targets, at small distances from the target edge (up to approximately 1 cm) the brachytherapy techniques generally have a steeper dose fall-off gradient compared to GammaPod™ and at longer distances (more than about 1 cm) the relation is generally observed to be opposite. For targets close to the skin, the relative skin doses were considerably lower for GammaPod™ than for any of the brachytherapy techniques. In conclusion, GammaPod™ allows adequate and more uniform dose coverage to centrally and peripherally located targets with an acceptable dose fall-off and lower relative skin dose than the brachytherapy techniques considered in this study.