The objective of this study was to introduce a new iterative method to reconstruct multi leaf collimator (MLC) positions based on low resolution ionization detector array measurements and to evaluate its error detection performance. The iterative reconstruction method consists of a fluence model, a detector model and an optimizer. Expected detector response was calculated using a radiotherapy treatment plan in combination with the fluence model and detector model. MLC leaf positions were reconstructed by minimizing differences between expected and measured detector response. The iterative reconstruction method was evaluated for an Elekta SLi with 10.0 mm MLC leafs in combination with the COMPASS system and the MatriXX Evolution (IBA Dosimetry) detector with a spacing of 7.62 mm. The detector was positioned in such a way that each leaf pair of the MLC was aligned with one row of ionization chambers. Known leaf displacements were introduced in various field geometries ranging from −10.0 mm to 10.0 mm. Error detection performance was tested for MLC leaf position dependency relative to the detector position, gantry angle dependency, monitor unit dependency, and for ten clinical intensity modulated radiotherapy (IMRT) treatment beams. For one clinical head and neck IMRT treatment beam, influence of the iterative reconstruction method on existing 3D dose reconstruction artifacts was evaluated. The described iterative reconstruction method was capable of individual MLC leaf position reconstruction with millimeter accuracy, independent of the relative detector position within the range of clinically applied MU's for IMRT. Dose reconstruction artifacts in a clinical IMRT treatment beam were considerably reduced as compared to the current dose verification procedure. The iterative reconstruction method allows high accuracy 3D dose verification by including actual MLC leaf positions reconstructed from low resolution 2D measurements.
LINK
Background and purpose: Treatment plan verification of intensity modulated radiotherapy (IMRT) is generally performed with the gamma index (GI) evaluation method, which is difficult to extrapolate to clinical implications. Incorporating Dose Volume Histogram (DVH) information can compensate for this. The aim of this study was to evaluate DVH-based treatment plan verification in addition to the GI evaluation method for head and neck IMRT.Materials and methods: Dose verifications of 700 subsequent head and neck cancer IMRT treatment plans were categorised according to gamma and DVH-based action levels. Fractionation dependent absolute dose limits were chosen. The results of the gamma- and DVH-based evaluations were compared to the decision of the medical physicist and/or radiation oncologist for plan acceptance.Results: Nearly all treatment plans (99.7%) were accepted for treatment according to the GI evaluation combined with DVH-based verification. Two treatment plans were re-planned according to DVH-based verification, which would have been accepted using the evaluation alone. DVH-based verification increased insight into dose delivery to patient specific structures increasing confidence that the treatment plans were clinically acceptable. Moreover, DVH-based action levels clearly distinguished the role of the medical physicist and radiation oncologist within the Quality Assurance (QA) procedure.Conclusions: DVH-based treatment plan verification complements the GI evaluation method improving head and neck IMRT-QA.
DOCUMENT
PURPOSE: Advanced radiotherapy treatments require appropriate quality assurance (QA) to verify 3D dose distributions. Moreover, increase in patient numbers demand efficient QA-methods. In this study, a time efficient method that combines model-based QA and measurement-based QA was developed; i.e., the hybrid-QA. The purpose of this study was to determine the reliability of the model-based QA and to evaluate time efficiency of the hybrid-QA method.METHODS: Accuracy of the model-based QA was determined by comparison of COMPASS calculated dose with Monte Carlo calculations for heterogeneous media. In total, 330 intensity modulated radiation therapy (IMRT) treatment plans were evaluated based on the mean gamma index (GI) with criteria of 3%∕3mm and classification of PASS (GI ≤ 0.4), EVAL (0.4 < GI > 0.6), and FAIL (GI ≥ 0.6). Agreement between model-based QA and measurement-based QA was determined for 48 treatment plans, and linac stability was verified for 15 months. Finally, time efficiency improvement of the hybrid-QA was quantified for four representative treatment plans.RESULTS: COMPASS calculated dose was in agreement with Monte Carlo dose, with a maximum error of 3.2% in heterogeneous media with high density (2.4 g∕cm(3)). Hybrid-QA results for IMRT treatment plans showed an excellent PASS rate of 98% for all cases. Model-based QA was in agreement with measurement-based QA, as shown by a minimal difference in GI of 0.03 ± 0.08. Linac stability was high with an average GI of 0.28 ± 0.04. The hybrid-QA method resulted in a time efficiency improvement of 15 min per treatment plan QA compared to measurement-based QA.CONCLUSIONS: The hybrid-QA method is adequate for efficient and accurate 3D dose verification. It combines time efficiency of model-based QA with reliability of measurement-based QA and is suitable for implementation within any radiotherapy department.
DOCUMENT