MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

Abstract

Purpose: We present a hybrid direct MLC aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo 30 treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled 35 through a MatLab interface, which is based on the sequencing of a novel map, called 'biophysical' map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an 40 optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the 45 multileaf collimator (MLC). For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to 50 calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a 55 demanding dose-escalation; a partial breast irradiation case (Case II) solved with photon and electron modulated beams (IMRT+MERT); and a prostatic bed case (Case III) with a pronounced concave-shaped PTV by using VMAT. In all cases, the required target prescription doses and constraints on organs at risk were fulfilled using in a short enough time to allow routine clinical implementation of such a MC-TPS for similar specialized cases. The quality assurance protocol followed to check CARMEN system showed a high agreement with the experimental measurements. Conclusions: A Monte Carlo treatment planning model exclusively based on maps performed from patient imaging data has been presented. The sequencing of these maps allows obtaining deliverable apertures which are weighted for modulation under 65 a linear programming formulation. The model is able to solve complex radiotherapy treatments with high accuracy in an efficient computation time