An algorithm to reconstruct delivered patient 3D doses from EPID exit dosimetry measurements was presented. The method was applied to phantom and patient data sets, as well as for dynamic IMRT and VMAT delivery techniques. Results indicate that the EPID dose reconstruction algorithm presented in this work is suitable for clinical implementation.
This study reports the development and validation of a model-based, 3D patient dose reconstruction method for pre-treatment quality assurance using EPID images. The method is also investigated for sensitivity to potential MLC delivery errors. Each cine-mode EPID image acquired during plan delivery was processed using a previously developed back-projection dose reconstruction model providing a 3D dose estimate on the CT simulation data. Validation was carried out using 24 SBRT-VMAT patient plans by comparing: (1) ion chamber point dose measurements in a solid water phantom, (2) the treatment planning system (TPS) predicted 3D dose to the EPID reconstructed 3D dose in a solid water phantom, and (3) the TPS predicted 3D dose to the EPID and our forward predicted reconstructed 3D dose in the patient (CT data). AAA and AcurosXB were used for TPS predictions. Dose distributions were compared using 3%/3 mm (95% tolerance) and 2%/2 mm (90% tolerance) γ-tests in the planning target volume (PTV) and 20% dose volumes. The average percentage point dose differences between the ion chamber and the EPID, AcurosXB, and AAA were 0.73 ± 1.25%, 0.38 ± 0.96% and 1.06 ± 1.34% respectively. For the patient (CT) dose comparisons, seven (3%/3 mm) and nine (2%/2 mm) plans failed the EPID versus AAA. All plans passed the EPID versus Acuros XB and the EPID versus forward model γ-comparisons. Four types of MLC sensitive errors (opening, shifting, stuck, and retracting), of varying magnitude (0.2, 0.5, 1.0, 2.0 mm), were introduced into six different SBRT-VMAT plans. γ-comparisons of the erroneous EPID dose and original predicted dose were carried out using the same criteria as above. For all plans, the sensitivity testing using a 3%/3 mm γ-test in the PTV successfully determined MLC errors on the order of 1.0 mm, except for the single leaf retraction-type error. A 2%/2 mm criteria produced similar results with two more additional detected errors.
The authors have customized and validated a robust, physics-based model that calculates the delivered dose to a patient for SBRT-VMAT delivery using on-treatment EPID images. The accuracy of the results indicates that this approach is suitable for clinical implementation. Future work will incorporate this model into both offline and real-time clinical adaptive radiotherapy.
In vivo dosimetry methods can verify the prescription dose is delivered to the patient during treatment. Unfortunately, in exit dosimetry, the megavoltage image is contaminated with patient-generated scattered photons. However, estimation and removal of the effect of this fluence improves accuracy of in vivo dosimetry methods. This work develops a ‘tri-hybrid’ algorithm combining analytical, Monte Carlo (MC) and pencil-beam scatter kernel methods to provide accurate estimates of the total patient-generated scattered photon fluence entering the MV imager.
For the multiply-scattered photon fluence, a modified MC simulation method was applied, using only a few histories. From each second- and higher-order interaction site in the simulation, energy fluence entering all pixels of the imager was calculated using analytical methods. For photon fluence generated by electron interactions in the patient (i.e. bremsstrahlung and positron annihilation), a convolution/superposition approach was employed using pencil-beam scatter fluence kernels as a function of patient thickness and air gap distance, superposed on the incident fluence distribution.
The total patient-scattered photon fluence entering the imager was compared with a corresponding full MC simulation (EGSnrc) for several test cases. These included three geometric phantoms (water, half-water/half-lung, computed tomography thorax) using monoenergetic (1.5, 5.5 and 12.5 MeV) and polyenergetic (6 and 18 MV) photon beams, 10 × 10 cm2 field, source-to-surface distance 100 cm, source-to-imager distance 150 cm and 40 × 40 cm2 imager.
The proposed tri-hybrid method is demonstrated to agree well with full MC simulation, with the average fluence differences and standard deviations found to be within 0.5% and 1%, respectively, for test cases examined here. The method, as implemented here with a single CPU (non-parallelized), takes ∼80 s, which is considerably shorter compared to full MC simulation (∼30 h). This is a promising method for fast yet accurate calculation of patient-scattered fluence at the imaging plane for in vivo dosimetry applications.
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