Risk of Second Malignant Neoplasms Following Proton Arc Therapy and Volumetric Modulated Arc Therapy for Prostate Cancer

The risk of second malignant neoplasms (SMNs) following prostate radiotherapy is a concern due to the large population of survivors and decreasing age at diagnosis. It is known that parallel-opposed beam proton therapy carries a lower risk than photon IMRT. However, a comparison of SMN risk following proton and photon arc therapies has not previously been reported. The purpose of this study was to predict the ratio of excess relative risk (RRR) of SMN incidence following proton arc therapy to that after volumetric modulated arc therapy (VMAT). Additionally, we investigated the impact of margin size and the effect of risk-minimized proton beam weighting on predicted RRR. Physician-approved treatment plans were created for both modalities for three patients. Therapeutic dose was obtained with differential dose-volume histograms from the treatment planning system, and stray dose was estimated from the literature or calculated with Monte Carlo simulations. Then, various risk models were applied to the total dose. Additional treatment plans were also investigated with varying margin size and risk-minimized proton beam weighting. The mean RRR ranged from 0.74 to 0.99, depending on risk model. The additional treatment plans revealed that the RRR remained approximately constant with varying margin size, and that the predicted RRR was reduced by 12% using a risk-minimized proton arc therapy planning technique. In conclusion, proton arc therapy was found to provide an advantage over VMAT in regard to predicted risk of SMN following prostate radiotherapy. This advantage was independent of margin size and was amplified with risk-optimized proton beam weighting

Impact of margin size on the predicted risk of radiogenic second cancers following proton arc therapy and volumetric modulated arc therapy for prostate cancer

We previously determined that the predicted risk of radiogenic second cancer in the bladder and rectum after proton arc therapy (PAT) was less than or equal to that after volumetric modulated arc therapy (VMAT) with photons, but we did not consider the impact of margin size on that risk. The current study was thus conducted to evaluate margin size\u27s effect on the predicted risks of second cancer for the two modalities and the relative risk between them. Seven treatment plans with margins ranging from 0 mm in all directions to 6 mm posteriorly and 8 mm in all other directions were considered for both modalities. We performed risk analyses using three risk models with varying amounts of cell sterilization and calculated ratios of risk for the corresponding PAT and VMAT plans. We found that the change in risk with margin size depended on the risk model but that the relative risk remained nearly constant with margin size, regardless of the amount of cell sterilization modeled. We conclude that while margin size influences the predicted risk of a second cancer for a given modality, it appears to affect both modalities in roughly equal proportions so that the relative risk between PAT and VMAT is approximately equivalent. © 2012 Institute of Physics and Engineering in Medicine

Risk of radiogenic second cancers following volumetric modulated arc therapy and proton arc therapy for prostate cancer

Prostate cancer patients who undergo radiotherapy are at an increased risk to develop a radiogenic second cancer. Proton therapy has been shown to reduce the predicted risk of second cancer when compared to intensity modulated radiotherapy. However, it is unknown if this is also true for the rotational therapies proton arc therapy and volumetric modulated arc therapy (VMAT). The objective of this study was to compare the predicted risk of cancer following proton arc therapy and VMAT for prostate cancer. Proton arc therapy and VMAT plans were created for three patients. Various risk models were combined with the dosimetric data (therapeutic and stray dose) to predict the excess relative risk (ERR) of cancer in the bladder and rectum. Ratios of ERR values (RRR) from proton arc therapy and VMAT were calculated. RRR values ranged from 0.74 to 0.99, and all RRR values were shown to be statistically less than 1, except for the value calculated with the linear-non-threshold risk model. We conclude that the predicted risk of cancer in the bladder or rectum following proton arc therapy for prostate cancer is either less than or approximately equal to the risk following VMAT, depending on which risk model is applied. © 2012 Institute of Physics and Engineering in Medicine

Risk-optimized proton therapy to minimize radiogenic second cancers

Proton therapy confers substantially lower predicted risk of second cancer compared with photon therapy. However, no previous studies have used an algorithmic approach to optimize beam angle or fluence-modulation for proton therapy to minimize those risks. The objectives of this study were to demonstrate the feasibility of risk-optimized proton therapy and to determine the combination of beam angles and fluence weights that minimizes the risk of second cancer in the bladder and rectum for a prostate cancer patient. We used 6 risk models to predict excess relative risk of second cancer. Treatment planning utilized a combination of a commercial treatment planning system and an in-house risk-optimization algorithm. When normal-tissue dose constraints were incorporated in treatment planning, the risk model that incorporated the effects of fractionation, initiation, inactivation, repopulation and promotion selected a combination of anterior and lateral beams, which lowered the relative risk by 21% for the bladder and 30% for the rectum compared to the lateral-opposed beam arrangement. Other results were found for other risk models

Benchmark measurements and simulations of dose perturbations due to metallic spheres in proton beams

Monte Carlo simulations are increasingly used for dose calculations in proton therapy due to its inherent accuracy. However, dosimetric deviations have been found using Monte Carlo code when high density materials are present in the proton beamline. The purpose of this work was to quantify the magnitude of dose perturbation caused by metal objects. We did this by comparing measurements and Monte Carlo predictions of dose perturbations caused by the presence of small metal spheres in several clinical proton therapy beams as functions of proton beam range and drift space. Monte Carlo codes MCNPX, GEANT4 and Fast Dose Calculator (FDC) were used. Generally good agreement was found between measurements and Monte Carlo predictions, with the average difference within 5% and maximum difference within 17%. The modification of multiple Coulomb scattering model in MCNPX code yielded improvement in accuracy and provided the best overall agreement with measurements. Our results confirmed that Monte Carlo codes are well suited for predicting multiple Coulomb scattering in proton therapy beams when short drift spaces are involved. © 2013 Elsevier Ltd. All rights reserved

TEDDI : radiotherapy delivery in deep inspiration for pediatric patients - a NOPHO feasibility study

Background: Radiotherapy (RT) delivered in deep inspiration breath-hold (DIBH) is a simple technique, in which changes in patient anatomy can significantly reduce the irradiation of the organs at risk (OARs) surrounding the treatment target. DIBH is routinely used in the treatment of some adult patients to diminish the risk of late effects; however, no formalized studies have addressed the potential benefit of DIBH in children. Methods/Design: TEDDI is a multicenter, non-randomized, feasibility study. The study investigates the dosimetric benefit of RT delivered in DIBH compared to free breathing (FB) in pediatric patients. Also, the study aims to establish the compliance to DIBH and to determine the accuracy and reproducibility in a pediatric setting. Pediatric patients (aged 5-17 years) with a tumor in the mediastinum or upper abdomen with the possible need of RT will be included in the study. Written informed consent is obligatory. Prior to any treatment, patients will undergo a DIBH training session followed by a diagnostic PET/CT-or CT-staging scan in both DIBH and FB. If the patient proceeds to RT, a RT planning CT scan will be performed in both DIBH and FB and two separate treatment plans will be calculated. The superior treatment plan, i.e. equal target coverage and lowest overall dose to the OARs, will be chosen for treatment. Patient comfort will be assessed daily by questionnaires and by adherence to the respiratory management procedure. Discussion: RT in DIBH is expected to diminish irradiation of the OARs surrounding the treatment target and thereby reduce the risk of late effects in childhood cancer survivors.Peer reviewe

A phase 2 trial of deep-inspiration breath hold in radiotherapy of gastric lymphomas

BACKGROUND AND PURPOSE: Radiotherapy (RT) is an important part in the treatment of gastric lymphomas and the prognosis after radiotherapy is very good with a good chance of long-term survival, so prevention of long-term adverse effects is important. In patients with gastric lymphomas cardiac late effects are of most concern. The aim of this study was to assess if the dose to the heart could be reduced with deep inspiration breath-hold (DIBH) without compromising the dose to the target or increasing the risk of other late effects. METHODS AND PATIENTS: Fifteen patients with gastric lymphoma were included. RT plans were made using DIBH and Free breathing (FB) scans. Clinical target volume (CTV) was the stomach plus 1 cm margin. The heart and surrounding organs at risk (OAR) were contoured. Two sets of plan comparisons were made, one with 1 cm CTV to planning target volume (PTV) margin in both DIBH and FB and one set with an additional 5 mm CTV to PTV margin in cranio-caudal direction with FB. Datasets were analysed with Wilcoxon signed rank test for non-parametric paired data. RESULTS: All patients tolerated the procedures and were treated with volumetric arc therapy technique in DIBH. Target coverage was kept equal between FB and DIBH, while a statistically significant reduction of the estimated does to the heart was seen with DIBH. Median mean heart dose was reduced from 7.1 Gy (5.7–12) to a median of 3.2 Gy (1.2–7.0) and heart V20 from a median of 54 (17–106) cm(3) to 15. (0.0–78) cm(3). The estimated mean doses to the liver, duodenum, pancreas and spinal cord were at the same level. CONCLUSION: This clinical trial of RT with DIBH for gastric lymphomas showed that the heart dose could be reduced without compromising PTV coverage. The doses to abdominal OARs were similar with FB and DIBH

Outcome-based multiobjective optimization of lymphoma radiation therapy plans

At its core, radiation therapy (RT) requires balancing therapeutic effects against risk of adverse events in cancer survivors. The radiation oncologist weighs numerous disease and patient-level factors when considering the expected risk–benefit ratio of combined treatment modalities. As part of this, RT plan optimization software is used to find a clinically acceptable RT plan delivering a prescribed dose to the target volume while respecting pre-defined radiation dose–volume constraints for selected organs at risk. The obvious limitation to the current approach is that it is virtually impossible to ensure the selected treatment plan could not be bettered by an alternative plan providing improved disease control and/or reduced risk of adverse events in this individual. Outcome-based optimization refers to a strategy where all planning objectives are defined by modeled estimates of a specific outcome’s probability. Noting that various adverse events and disease control are generally incommensurable, leads to the concept of a Pareto-optimal plan: a plan where no single objective can be improved without degrading one or more of the remaining objectives. Further benefits of outcome-based multiobjective optimization are that quantitative estimates of risks and benefit are obtained as are the effects of choosing a different trade-off between competing objectives. Furthermore, patient-level risk factors and combined treatment modalities may be integrated directly into plan optimization. Here, we present this approach in the clinical setting of multimodality therapy for malignant lymphoma, a malignancy with marked heterogeneity in biology, target localization, and patient characteristics. We discuss future research priorities including the potential of artificial intelligence