Development of a quasi-3D dosimeter using radiochromic plastic for patient-specific quality assurance

BACKGROUND

Patient-specific QA verification ensures patient safety and treatment by verifying radiation delivery and dose calculations in treatment plans for errors. However, a two-dimensional (2D) dose distribution is insufficient for detecting information on the three-dimensional (3D) dose delivered to the patient. In addition, 3D radiochromic plastic dosimeters (RPDs) such as PRESAGE® represent the volume effect in which the dosimeters have different sensitivities according to the size of the dosimeters. Therefore, to solve the volume effect, a Quasi-3D dosimetry system was proposed to perform patient-specific QA using predetermined-sized and multiple RPDs.

PURPOSE

For patient-specific quality assurance (QA) in radiation treatment, this study aims to assess a quasi-3D dosimetry system using an RPD.

METHODS

Gamma analysis was performed to verify the agreement between the measured and estimated dose distributions of intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). We fabricated cylindrical RPDs and a quasi-3D dosimetry phantom. A practicability test for a pancreatic patient utilized a quasi-3D dosimetry device, an in-house RPD, and a quasi-3D phantom. The dose distribution of the VMAT design dictated the placement of nine RPDs. Moreover, a 2D diode array detector was used for 2D gamma analysis (MapCHECK2). The patient-specific QA was performed for IMRT, VMAT, and stereotactic ablative radiotherapy (SABR) in 20 prostate and head-and-neck patients. For each patient, six RPDs were positioned according to the dose distribution. VMAT SABR and IMRT/VMAT plans employed a 2%/2 mm gamma criterion, whereas IMRT/VMAT plans used a 3%/2 mm gamma criterion, a 10% threshold value, and a 90% passing rate tolerance. 3D gamma analysis was conducted using the 3D Slicer software.

RESULTS

The average gamma passing rates with 2%/2 mm and 3%/3 mm criteria for relative dose distribution were 91.6% ± 1.4% and 99.4% ± 0.7% for the 3D gamma analysis using the quasi-3D dosimetry system, respectively, and 97.5% and 99.3% for 2D gamma analysis using MapCHECK2, respectively. The 3D gamma analysis for patient-specific QA of 20 patients showed passing rates of over 90% with 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria.

CONCLUSIONS

The quasi-3D dosimetry system was evaluated by performing patient-specific QAs with RPDs and quasi-3D phantom. The gamma indices for all RPDs showed more than 90% for 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria. We verified the feasibility of a quasi-3D dosimetry system by performing the conventional patient-specific QA with the quasi-3D dosimeters.

Edge effects in 3D dosimetry: characterisation and correction of the non-uniform dose response of PRESAGE®

Previous work has shown that PRESAGE® can be used successfully to perform 3D dosimetric measurements of complex radiotherapy treatments. However, measurements near the sample edges are known to be difficult to achieve. This is an issue when the doses at air-material interfaces are of interest, for example when investigating the electron return effect (ERE) present in treatments delivered by magnetic resonance (MR)-linac systems. To study this effect, a set of 3.5 cm-diameter cylindrical PRESAGE® samples was uniformly irradiated with multiple dose fractions, using either a conventional linac or an MR-linac. The samples were imaged between fractions using an optical-CT, to read out the corresponding accumulated doses. A calibration between TPS-predicted dose and optical-CT pixel value was determined for individual dosimeters as a function of radial distance from the axis of rotation. This data was used to develop a correction that was applied to four additional samples of PRESAGE® of the same formulation, irradiated with 3D-CRT and IMRT treatment plans, to recover significantly improved 3D measurements of dose. An alternative strategy was also tested, in which the outer surface of the sample was physically removed prior to irradiation. Results show that for the formulation studied here, PRESAGE® samples have a central region that responds uniformly and an edge region of 6-7 mm where there is gradual increase in dosimeter response, rising to an over-response of 24%-36% at the outer boundary. This non-uniform dose response increases in both extent and magnitude over time. Both mitigation strategies investigated were successful. In our four exemplar studies, we show how discrepancies at edges are reduced from 13%-37% of the maximum dose to between 2 and 8%. Quantitative analysis shows that the 3D gamma passing rates rise from 90.4, 69.3, 63.7 and 43.6% to 97.3, 99.9, 96.7 and 98.9% respectively.

Investigating the effect of a magnetic field on dose distributions at phantom-air interfaces using PRESAGE® 3D dosimeter and Monte Carlo simulations

Dosimetric quality assurance (QA) of the new Elekta Unity (MR-linac) will differ from the QA performed of a conventional linac due to the constant magnetic field, which creates an electron return effect (ERE). In this work we aim to validate PRESAGE® dosimetry in a transverse magnetic field, and assess its use to validate the research version of the Monaco TPS of the MR-linac. Cylindrical samples of PRESAGE® 3D dosimeter separated by an air gap were irradiated with a cobalt-60 unit, while placed between the poles of an electromagnet at 0.5 T and 1.5 T. This set-up was simulated in EGSnrc/Cavity Monte Carlo (MC) code and relative dose distributions were compared with measurements using 1D and 2D gamma criteria of 3% and 1.5 mm. The irradiation conditions were adapted for the MR-linac and compared with Monaco TPS simulations. Measured and EGSnrc/Cavity simulated profiles showed good agreement with a gamma passing rate of 99.9% for 0.5 T and 99.8% for 1.5 T. Measurements on the MR-linac also compared well with Monaco TPS simulations, with a gamma passing rate of 98.4% at 1.5 T. Results demonstrated that PRESAGE® can accurately measure dose and detect the ERE, encouraging its use as a QA tool to validate the Monaco TPS of the MR-linac for clinically relevant dose distributions at tissue-air boundaries.

Technical Note: Evaluation of an iterative reconstruction algorithm for optical CT radiation dosimetry

PURPOSE

Iterative CT reconstruction algorithms are gaining popularity as GPU-based computation becomes more accessible. These algorithms are desirable in x-ray CT for their ability to achieve similar image quality at a fraction of the dose required for standard filtered backprojection reconstructions. In optical CT dosimetry, the noise reduction capability of such algorithms is similarly desirable because noise has a detrimental effect on the precision of dosimetric analysis, and can create misleading test results. In this study, we evaluate an iterative CT reconstruction algorithm for gel dosimetry, with special attention to the challenging dosimetry of small fields.

METHODS

An existing ordered subsets convex algorithm using total variation minimization regularization (OSC-TV) was implemented. Three datasets, which represent the extreme cases of gel dosimetry, were examined: a large, 15 cm diameter uniform phantom, a 1.35 cm diameter finger phantom, and a 15 cm gel dosimeter irradiated with 3 × 3, 2 × 2, 1 × 1, and 0.6 × 0.6 cm fields. These were scanned on an in-house scanning laser system, and reconstructed with both filtered backprojection and OSC-TV with a range of regularization constants. The contrast to artifact + noise ratio (CANR) and penumbra width measurements (80% to 20% and 95% to 5% distances) were used to compare reconstructions.

RESULTS

Our results showed that OSC-TV can achieve 3-5× improvement in contrast to artifact + noise ratio compared to filtered backprojection, while preserving the shape of steep dose gradients. For very small objects (≤ 0.6 × 0.6 cm fields in a 16 × 16 cm field of view), the mean value in the center of the object can be suppressed if the regularization constant is improperly set, which must be avoided.

CONCLUSIONS

Overall, the results indicate that OSC-TV is a suitable reconstruction algorithm for gel dosimetry, provided care is taken in setting the regularization parameter when reconstructing objects that are small compared to the scanner field of view.