title: Limitations of analytical dose calculations for small field proton radiosurgery.
abstract: 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.
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, 30 Fruit Street, Boston, MA 02114, USA.
authors.forename: Changran
authors.initials: C
authors.lastname: Geng
authors.forename: Juliane
authors.initials: J
authors.lastname: Daartz
authors.forename: Kimberley
authors.initials: K
authors.lastname: Lam-Tin-Cheung
authors.forename: Marc
authors.initials: M
authors.lastname: Bussiere
authors.forename: Helen A
authors.initials: HA
authors.lastname: Shih
authors.forename: Harald
authors.initials: H
authors.lastname: Paganetti
authors.forename: Jan
authors.initials: J
authors.lastname: Schuemann
mesh_terms: D000236:Adenoma / Q000532:radiotherapy; D000465:Algorithms; D001165:Arteriovenous Malformations / Q000532:radiotherapy; D006801:Humans; D008577:Meningeal Neoplasms / Q000532:radiotherapy; D008579:Meningioma / Q000532:radiotherapy; D009010:Monte Carlo Method; D009464:Neuroma, Acoustic / Q000532:radiotherapy; D010911:Pituitary Neoplasms / Q000532:radiotherapy; D061766:Proton Therapy; D011829:Radiation Dosage; D016634:Radiosurgery; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*