Salguero, F. J. | Search NASA

DOE OSTI2014

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

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo 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 through aMATLAB 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 In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear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 MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), 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 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 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 volumetric modulated arc therapy. In the three cases, the required target prescription doses and constraints on organs at risk were fulfilled in a short enough time to allow routine clinical implementation. 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 a linear programming formulation. The model is able to solve complex radiotherapy treatments with high accuracy in an efficient computation time.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

A method to evaluate dose errors introduced by dose mapping processes for mass conserving deformations

Purpose: To present a method to evaluate the dose mapping error introduced by the dose mapping process. In addition, apply the method to evaluate the dose mapping error introduced by the 4D dose calculation process implemented in a research version of commercial treatment planning system for a patient case. Methods: The average dose accumulated in a finite volume should be unchanged when the dose delivered to one anatomic instance of that volume is mapped to a different anatomic instance--provided that the tissue deformation between the anatomic instances is mass conserving. The average dose to a finite volume on image S is defined as d{sub S}=e{sub s}/m{sub S}, where e{sub S} is the energy deposited in the mass m{sub S} contained in the volume. Since mass and energy should be conserved, when d{sub S} is mapped to an image R(d{sub S{yields}R}=d{sub R}), the mean dose mapping error is defined as {Delta}d{sub m}=|d{sub R}-d{sub S}|=|e{sub R}/m{sub R}-e{sub S}/m{sub S}|, where the e{sub R} and e{sub S} are integral doses (energy deposited), and m{sub R} and m{sub S} are the masses within the region of interest (ROI) on image R and the corresponding ROI on image S, where R and S are the two anatomic instances from the same patient. Alternatively, application of simple differential propagation yields the differential dose mapping error, {Delta}d{sub d}=|({partial_derivative}d/{partial_derivative}e)*{Delta}e+({partial_derivative}d/{partial_derivative}m)*{Delta}m|=|((e{sub S}-e{sub R})/m{sub R})-((m{sub S}-m{sub R})/m{sub R}{sup 2})*e{sub R}|={alpha}|d{sub R}-d{sub S}| with {alpha}=m{sub S}/m{sub R}. A 4D treatment plan on a ten-phase 4D-CT lung patient is used to demonstrate the dose mapping error evaluations for a patient case, in which the accumulated dose, D{sub R}={Sigma}{sub S=0}{sup 9}d{sub S{yields}R}, and associated error values ({Delta}D{sub m} and {Delta}D{sub d}) are calculated for a uniformly spaced set of ROIs. Results: For the single sample patient dose distribution, the average accumulated differential dose mapping error is 4.3%, the average absolute differential dose mapping error is 10.8%, and the average accumulated mean dose mapping error is 5.0%. Accumulated differential dose mapping errors within the gross tumor volume (GTV) and planning target volume (PTV) are lower, 0.73% and 2.33%, respectively. Conclusions: A method has been presented to evaluate the dose mapping error introduced by the dose mapping process. This method has been applied to evaluate the 4D dose calculation process implemented in a commercial treatment planning system. The method could potentially be developed as a fully-automatic QA method in image guided adaptive radiation therapy (IGART).

61 RADIATION PROTECTION AND DOSIMETRY↗