[IMCO(++)--a Monte Carlo based IMRT system]

Monte Carlo simulations to replace film dosimetry in IMRT verification

Patient-specific verification of intensity-modulated radiation therapy (IMRT) plans can be done by dosimetric measurements or by independent dose or monitor unit calculations. The aim of this study was the clinical evaluation of IMRT verification based on a fast Monte Carlo (MC) program with regard to possible benefits compared to commonly used film dosimetry. 25 head-and-neck IMRT plans were recalculated by a pencil beam based treatment planning system (TPS) using an appropriate quality assurance (QA) phantom. All plans were verified both by film and diode dosimetry and compared to MC simulations. The irradiated films, the results of diode measurements and the computed dose distributions were evaluated, and the data were compared on the basis of gamma maps and dose-difference histograms. Average deviations in the high-dose region between diode measurements and point dose calculations performed with the TPS and MC program were 0.7 ± 2.7% and 1.2 ± 3.1%, respectively. For film measurements, the mean gamma values with 3% dose difference and 3mm distance-to-agreement were 0.74 ± 0.28 (TPS as reference) with dose deviations up to 10%. Corresponding values were significantly reduced to 0.34 ± 0.09 for MC dose calculation. The total time needed for both verification procedures is comparable, however, by far less labor intensive in the case of MC simulations. The presented study showed that independent dose calculation verification of IMRT plans with a fast MC program has the potential to eclipse film dosimetry more and more in the near future. Thus, the linac-specific QA part will necessarily become more important. In combination with MC simulations and due to the simple set-up, point-dose measurements for dosimetric plausibility checks are recommended at least in the IMRT introduction phase.

Application of an inverse kernel concept to Monte Carlo based IMRT

Inverse treatment planning by means of pencil beam algorithms can lead to errors in the calculation of dose in areas without secondary electron equilibrium. Monte Carlo (MC) simulations give accurate results in such areas but result in increased computation times. We present a new, so-called inverse kernel concept that offers MC precision in inverse treatment planning with acceptable computation times and memory consumption. Inverse kernels are matrices that describe the dose contribution from all bixels of a beam to a distinct voxel of the patient phantom. The concept is similar to other generalized pencil-beam concepts, except that inverse kernel elements are precalculated using a single MC simulation and stored as binary trees. In this procedure a modified MC code (XVMC) is applied to trace the photon history for each dose deposition. Iterative optimization is then applied in a second step. The inverse process is separated into (i) a slower MC simulation and (ii) a faster iterative optimization, followed by (iii) the segmentation procedure, and (iv) a final MC dose calculation step including a segment weight reoptimization. Inverse kernel optimization, or IKO, with segmentation and reoptimization steps is demonstrated by means of a lung cancer case. To demonstrate the superiority of an inverse MC system over pencil-beam or collapsed-cone based systems, the final result of the IKO is compared to plans where all segments have been calculated by pencil beam or collapsed cone, respectively. Dose-volume histograms and dose-difference histograms show remarkable differences, which can be attributed to systematic errors in both algorithms. IKO is a precise, nonhybrid, inverse MC treatment planning system which suits current clinical needs, as several optimization steps can follow one single MC-simulation step for a distinct beam setup.

Application of the Inverse Monte Carlo Treatment Planning System IKO for an Inhomogeneous Dose Prescription in the Sense of Dose Painting* *This work was presented at the ICMP 2005 and awarded by the Siemens Prize

Biological imaging (PET SPECTJfMRI, MRS, etc.) is able to provide tri-dimensional biological information, i.e. proliferation, cell density, hypoxia or choline/citrate ratio. The implementation of this information in a treatment plan can be utilised to escalate the dose in target subvolumes. For this purpose, a treatment planning system has to be able to realise an inhomogeneous dose prescription with sufficient spatial resolution. The present study investigated to which extent the inverse Monte Carlo treatment planning system IKO (inverse kernel optimization), developed at our department, can modulate an inhomogeneous dose prescription. As a qualifier to describe this ability, we defined in analogy to imaging a modulation transfer function for treatment planning systems. In addition two clinical cases, a prostate case and a head-and-neck case, were set up with different dose prescriptions in different subtargets. The modulation transfer function revealed that IKO is able to modulate structures larger than 1.3 cm with sharp dose gradients. Also, IKO is able to modulate several subtargets inside a prostate with different escalated doses. The dose-volume histograms of the head-and-neck case showed a good dose coverage of the target volumes, as well as a good protection of the organs at risk according to the dose constraints. As a result, IKO is able to realise a heterogeneous dose prescription in the sense of "dose painting".