title: Dose prescription in carbon ion radiotherapy: a planning study to compare NIRS and LEM approaches with a clinically-oriented strategy.
abstract: In carbon ion radiotherapy there is an urgent clinical need to develop objective tools for the conversion of relative biological effectiveness (RBE)-weighted doses based on different models. In this work we introduce a clinically oriented method to compare NIRS-based and LEM-based GyE systems, minimizing differences in physical dose distributions between treatment plans. Carbon ion plans were optimized on target volumes of cubic and spherical shapes, for RBE-weighted dose prescription levels ranging from 3.6 to 4.4 GyE. Plans were calculated for target sizes from 4 to 12 cm defining three beam geometries: single beam, opposed beam and orthogonal beam configurations. The two treatment planning systems currently employed in clinical practice were used, providing the NIRS-based and LEM-based GyE calculations. Physical dose distributions of NIRS-based and LEM-based treatment plans were compared. LEM-based prescription doses that minimize differences in physical dose distributions between the two systems were found. These doses were compared with the mean RBE-weighted dose obtained with a Monte Carlo code (FLUKA) interfaced with LEM I. In the investigated dose range, LEM-based RBE-weighted prescription doses, that minimize differences with NIRS plans, should be higher than NIRS reported prescription doses. The optimal dose depends on target size, shape and position, number of beams and dose level. The opposed beam configuration resulted in the smallest average prescription dose difference (0.45 ± 0.09 GyE). The second approach of recalculating NIRS RBE-weighted dose with a Monte Carlo code interfaced with LEM resulted in no significant difference with the results obtained from the planning study. The delivery of a voxel by voxel iso-effective plan, if different RBE models are employed, is not feasible; it is however possible to minimize differences in a treatment plan with the simple approach presented here. Dose prescription ultimately represents a clinical task under the responsibility of the radiation oncologist, the presented analysis intends to be a quantitative and objective way to assist the clinical decision.
authors.affiliation: Centro Nazionale di Adroterapia Oncologica, Pavia, Italy. fossati@cnao.it
authors.forename: Piero
authors.initials: P
authors.lastname: Fossati
authors.forename: Silvia
authors.initials: S
authors.lastname: Molinelli
authors.forename: Naruhiru
authors.initials: N
authors.lastname: Matsufuji
authors.forename: Mario
authors.initials: M
authors.lastname: Ciocca
authors.forename: Alfredo
authors.initials: A
authors.lastname: Mirandola
authors.forename: Andrea
authors.initials: A
authors.lastname: Mairani
authors.forename: Junetsu
authors.initials: J
authors.lastname: Mizoe
authors.forename: Azusa
authors.initials: A
authors.lastname: Hasegawa
authors.forename: Reiko
authors.initials: R
authors.lastname: Imai
authors.forename: Tadashi
authors.initials: T
authors.lastname: Kamada
authors.forename: Roberto
authors.initials: R
authors.lastname: Orecchia
authors.forename: Hirohiko
authors.initials: H
authors.lastname: Tsujii
mesh_terms: D002244:Carbon / Q000627:therapeutic use*; D006801:Humans; D009369:Neoplasms / Q000532:radiotherapy; D011829:Radiation Dosage; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012062:Relative Biological Effectiveness; D015203:Reproducibility of Results
chemical_list: D002244:Carbon