Limitations of analytical dose calculations for small field proton radiosurgery.

The purpose of the work was to evaluate the dosimetric uncertainties of an analytical dose calculation engine and the impact on treatment plans using small fields in intracranial proton stereotactic radiosurgery (PSRS) for a gantry based double scattering system. 50 patients were evaluated including 10 patients for each of 5 diagnostic indications of: arteriovenous malformation (AVM), acoustic neuroma (AN), meningioma (MGM), metastasis (METS), and pituitary adenoma (PIT). Treatment plans followed standard prescription and optimization procedures for PSRS. We performed comparisons between delivered dose distributions, determined by Monte Carlo (MC) simulations, and those calculated with the analytical dose calculation algorithm (ADC) used in our current treatment planning system in terms of dose volume histogram parameters and beam range distributions. Results show that the difference in the dose to 95% of the target (D95) is within 6% when applying measured field size output corrections for AN, MGM, and PIT. However, for AVM and METS, the differences can be as great as 10% and 12%, respectively. Normalizing the MC dose to the ADC dose based on the dose of voxels in a central area of the target reduces the difference of the D95 to within 6% for all sites. The generally applied margin to cover uncertainties in range (3.5% of the prescribed range + 1 mm) is not sufficient to cover the range uncertainty for ADC in all cases, especially for patients with high tissue heterogeneity. The root mean square of the R90 difference, the difference in the position of distal falloff to 90% of the prescribed dose, is affected by several factors, especially the patient geometry heterogeneity, modulation and field diameter. In conclusion, implementation of Monte Carlo dose calculation techniques into the clinic can reduce the uncertainty of the target dose for proton stereotactic radiosurgery. If MC is not available for treatment planning, using MC dose distributions to adjust the delivered doses level can also reduce uncertainties below 3% for mean target dose and 6% for the D95.

Establishing Cost-Effective Allocation of Proton Therapy for Breast Irradiation.

PURPOSE: Cardiac toxicity due to conventional breast radiation therapy (RT) has been extensively reported, and it affects both the life expectancy and quality of life of affected women. Given the favorable oncologic outcomes in most women irradiated for breast cancer, it is increasingly paramount to minimize treatment side effects and improve survivorship for these patients. Proton RT offers promise in limiting heart dose, but the modality is costly and access is limited. Using cost-effectiveness analysis, we provide a decision-making tool to help determine which breast cancer patients may benefit from proton RT referral. METHODS AND MATERIALS: A Markov cohort model was constructed to compare the cost-effectiveness of proton versus photon RT for breast cancer management. The model was analyzed for different strata of women based on age (40 years, 50 years, and 60 years) and the presence or lack of cardiac risk factors (CRFs). Model entrants could have 1 of 3 health states: healthy, alive with coronary heart disease (CHD), or dead. Base-case analysis assumed CHD was managed medically. No difference in tumor control was assumed between arms. Probabilistic sensitivity analysis was performed to test model robustness and the influence of including catheterization as a downstream possibility within the health state of CHD. RESULTS: Proton RT was not cost-effective in women without CRFs or a mean heart dose (MHD) <5 Gy. Base-case analysis noted cost-effectiveness for proton RT in women with ≥1 CRF at an approximate minimum MHD of 6 Gy with a willingness-to-pay threshold of $100,000/quality-adjusted life-year. For women with ≥1 CRF, probabilistic sensitivity analysis noted the preference of proton RT for an MHD ≥5 Gy with a similar willingness-to-pay threshold. CONCLUSIONS: Despite the cost of treatment, scenarios do exist whereby proton therapy is cost-effective. Referral for proton therapy may be cost-effective for patients with ≥1 CRF in cases for which photon plans are unable to achieve an MHD <5 Gy.

Cost effectiveness of proton versus photon radiation therapy with respect to the risk of growth hormone deficiency in children.

BACKGROUND: Proton therapy in pediatrics may improve the risk/benefit profile of radiotherapy at a greater upfront financial cost, but it may prove to be cost effective if chronic medical complications can be avoided. Tools to assist with decision making are needed to aid in selecting pediatric patients for protons, and cost-effectiveness models can provide an objective method for this. METHODS: A Markov cohort-simulation model was developed to assess the expected costs and effectiveness for specific radiation doses to the hypothalamus with protons versus photons in pediatric patients. Costing data included cost of investment and the diagnosis and management of growth hormone deficiency. Longitudinal outcomes data were used to inform risk parameters for the model. With costs in 2012 US dollars and effectiveness measured in quality-adjusted life years, incremental cost-effectiveness ratios were used to measure outcomes. RESULTS: Proton therapy was cost effective for some scenarios based on the difference in hypothalamic sparing. Although some scenarios were not cost effective, others were not only cost effective for proton therapy but also demonstrated that protons were cost saving compared with photons. CONCLUSIONS: The current results provide the first evidence-based guide for identifying children with brain tumors who may benefit the most from proton therapy with respect to endocrine dysfunction. Proton therapy may be more cost effective for scenarios in which radiation dose to the hypothalamus can be spared, but protons may not be cost effective when tumors are involving or directly adjacent to the hypothalamus if there is a high dose to this structure.

Cost effectiveness of proton therapy compared with photon therapy in the management of pediatric medulloblastoma.

BACKGROUND: Proton therapy has been a hotly contested issue in both scientific publications and lay media. Proponents cite the modality's ability to spare healthy tissue, but critics claim the benefit gained from its use does not validate its cost compared with photon therapy. The objective of this study was to evaluate the cost effectiveness of proton therapy versus photon therapy in the management of pediatric medulloblastoma. METHODS: A cost-effective analysis was performed from the societal perspective using a Monte Carlo simulation model. A population of pediatric medulloblastoma survivors aged 18 years was studied who had received treatment at age 5 years and who were at risk of developing 10 adverse events, such as growth hormone deficiency, coronary artery disease, ototoxicity, secondary malignant neoplasm, and death. Costing data included the cost of investment and the costs of diagnosis and management of adverse health states from institutional and Medicare data. Longitudinal outcomes data and recent modeling studies informed risk parameters for the model. Incremental cost-effectiveness ratios were used to measure outcomes. RESULTS: Results from the base case demonstrated that proton therapy was associated with higher quality-adjusted life years and lower costs; therefore, it dominated photon therapy. In 1-way sensitivity analyses, proton therapy remained the more attractive strategy, either dominating photon therapy or having a very low cost per quality-adjust life year gained. Probabilistic sensitivity analysis illustrated the domination of proton therapy over photon therapy in 96.4% of simulations. CONCLUSIONS: By using current risk estimates and data on required capital investments, the current study indicated that proton therapy is a cost-effective strategy for the management of pediatric patients with medulloblastoma compared with standard of care photon therapy.