Analysis of patient-specific quality assurance for Elekta Unity adaptive plans using statistical process control methodology.

The Elekta Unity MR-linac utilizes daily magnetic resonance imaging (MRI) for online plan adaptation. In the Unity workflow, adapt to position (ATP) and adapt to shape (ATS) treatment planning options are available which represent a virtual shift or full re-plan with contour adjustments respectively. Both techniques generate a new intensity modulated radiation therapy (IMRT) treatment plan while the patient lies on the treatment table and thus adapted plans cannot be measured prior to treatment delivery. A statistical process control methodology was used to analyze 512 patient-specific IMRT QA measurements performed on the MR-compatible SunNuclear ArcCheck with a gamma criterion of 3%/2 mm using global normalization and a 10% low dose threshold. The lower control limit (LCL) was determined from 68 IMRT reference plan measurements, and a one-sided process capability ratio ( C p , l ) was used to assess the pass rates from 432 measured ATP and 80 measured ATS plans. Further analysis was performed to assess differences between SBRT or conventional fractionation pass rates and to determine whether there was any correlation between the pass rates and plan complexity. The LCL of the reference plans was determined to be a gamma pass rate of 0.958, and the C p , l of the measured ATP plans and measured ATS plans were determined to be 1.403 and 0.940 for ATP and ATS plans, respectively, while a C p , l of 0.902 and 1.383 was found for SBRT and conventional fractionations respectively. For plan complexity, no correlation was found between modulation degree and gamma pass rate, but a statistically significant correlation was observed between the beam-averaged aperture area and gamma pass rate. All adaptive plans passed the TG-218 guidelines, but the ATS and SBRT plans tended to have a smaller beam-averaged aperture area with slightly lower gamma pass rates.

Commissioning of a 1.5T Elekta Unity MR-linac: A single institution experience.

MR image-guided radiotherapy has the potential to improve patient care, but integration of an MRI scanner with a linear accelerator adds complexity to the commissioning process. This work describes a single institution experience of commissioning an Elekta Unity MR-linac, including mechanical testing, MRI scanner commissioning, and dosimetric validation. Mechanical testing included multileaf collimator (MLC) positional accuracy, measurement of radiation isocenter diameter, and MR-to-MV coincidence. Key MRI tests included magnetic field homogeneity, geometric accuracy, image quality, and the accuracy of navigator-triggered imaging for motion management. Dosimetric validation consisted of comparison between measured and calculated PDDs and profiles, IMRT measurements, and end-to-end testing. Multileaf collimator positional accuracy was within 1.0 mm, the measured radiation isocenter walkout was 0.20 mm, and the coincidence between MR and MV isocenter was 1.06 mm, which is accounted for in the treatment planning system (TPS). For a 350-mm-diameter spherical volume, the peak-to-peak deviation of the magnetic field homogeneity was 4.44 ppm and the geometric distortion was 0.8 mm. All image quality metrics were within ACR recommendations. Navigator-triggered images showed a maximum deviation of 0.42, 0.75, and 3.0 mm in the target centroid location compared to the stationary target for a 20 mm motion at 10, 15, and 20 breaths per minute, respectively. TPS-calculated PDDs and profiles showed excellent agreement with measurement. The gamma passing rate for IMRT plans was 98.4 ± 1.1% (3%/ 2 mm) and end-to-end testing of adapted plans showed agreement within 0.4% between ion-chamber measurement and TPS calculation. All credentialing criteria were satisfied in an independent end-to-end test using an IROC MRgRT phantom.

Commissioning and performance evaluation of RadCalc for the Elekta unity MRI-linac.

Recent availability of MRI-guided linear accelerators has introduced a number of clinical challenges, particularly in the context of online plan adaptation. Paramount among these is verification of plan quality prior to patient treatment. Currently, there are no commercial products available for monitor unit verification that fully support the newly FDA cleared Elekta Unity 1.5 T MRI-linac. In this work, we investigate the accuracy and precision of RadCalc for this purpose, which is a software package that uses a Clarkson integration algorithm for point dose calculation. To this end, 18 IMRT patient plans (186 individual beams) were created and used for RadCalc point dose calculations. In comparison with the primary treatment planning system (Monaco), mean point dose deviations of 0.0 ± 1.0% (n = 18) and 1.7 ± 12.4% (n = 186) were obtained on a per-plan and per-beam basis, respectively. The dose plane comparison functionality within RadCalc was found to be highly inaccurate, however, modest improvements could be made by artificially shifting jaws and multi leaf collimator positions to account for the dosimetric shift due to the magnetic field (67.3% vs 96.5% mean 5%/5 mm gamma pass rate).

The commissioning and validation of Monaco treatment planning system on an Elekta VersaHD linear accelerator.

Accurate beam modeling is essential to help ensure overall accuracy in the radiotherapy process. This study describes our experience with beam model validation of a Monaco treatment planning system on a Versa HD linear accelerator. Data were collected such that Monaco beam models could be generated using three algorithms: collapsed cone (CC) and photon Monte Carlo (MC) for photon beams, and electron Monte Carlo (eMC) for electron beams. Validations are performed on measured percent depth doses (PDDs) and profiles, for open-field point-doses in homogenous and heterogeneous media, and for obliquely incident electron beams. Gamma analysis is used to assess the agreement between calculation and measurement for intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) plans, including volumetric modulated arc therapy for stereotactic body radiation therapy (VMAT SBRT). For all relevant conditions, gamma index values below 1 are obtained when comparing Monaco calculated PDDs and profiles with measured data. Point-doses in a water medium are found to be within 2% agreement of commissioning data in 99.5% and 98.6% of the points computed by MC and CC, respectively. All point-dose calculations for the eMC algorithm in water are within 4% agreement of measurement, and 92% of measurements are within 3%. In heterogeneous media of air and cortical bone, both CC and MC yielded better than 3% agreement with ion chamber measurements. eMC yielded 3% agreement to measurement downstream of air with oblique beams of up to 27°, 5% agreement distal to bone, and within 4% agreement at extended source to surface distance (SSD) for all electron energies except 6 MeV. The 6-MeV point of measurement is on a steep dose gradient which may impact the magnitude of discrepancy measured. The average gamma passing rate for IMRT/VMAT plans is 96.9% (±2.1%) and 98.0% (±1.9%) for VMAT SBRT when evaluated using 3%/2 mm criteria. Monaco beam models for the Versa HD linac were successfully commissioned for clinical use.

Evaluating inter-campus plan consistency using a knowledge based planning model.

BACKGROUND AND PURPOSE: We investigate whether knowledge based planning (KBP) can identify systematic variations in intensity modulated radiotherapy (IMRT) plans between multiple campuses of a single institution. MATERIAL AND METHODS: A KBP model was constructed from 58 prior main campus (MC) esophagus IMRT radiotherapy plans and then applied to 172 previous patient plans across MC and 4 regional sites (RS). The KBP model predicts DVH bands for each organ at risk which were compared to the previously planned DVHs for that patient. RESULTS: RS1's plans were the least similar to the model with less heart and stomach sparing, and more variation in liver dose, compared to MC. RS2 produced plans most similar to those expected from the model. RS3 plans displayed more variability from the model prediction but overall, the DVHs were no worse than those of MC. RS4 did not present any statistically significant results due to the small sample size (n=11). CONCLUSIONS: KBP can retrospectively highlight subtle differences in planning practices, even between campuses of the same institution. This information can be used to identify areas needing increased consistency in planning output and subsequently improve consistency and quality of care.

Interobserver variability in radiation therapy plan output: Results of a single-institution study.

PURPOSE: We investigated the sources of variability in radiation therapy treatment plan output between planners within a single institution. METHODS AND MATERIALS: Forty treatment planners across 5 campuses of an institution created a plan on the same thoracic esophagus patient computed tomography scan and structure set. Plans were scored and ranked based on the planner's adherence to an ordered list of target dose coverage and normal tissue evaluation criteria. A runs test was used to identify whether any of the studied planner qualities influenced the ranking. Spearman rank correlation was used to investigate whether plan score correlated with years of experience or planned monitor units. RESULTS: The distribution of scores, ranging from 80.24 to 135.89, was negatively skewed (mean, 128.7; median, 131.5). No statistically significant relationship between plan score and campus (P = .193), job title (P = .174), previous outside experience (P = .611), or number of gantry angles (P = .156) was discovered. No statistical correlation between plan score and monitor unit or years of experience was found. CONCLUSIONS: Despite clear and established critical organ dose criteria and well-documented planning guidelines, planning variation still occurs, even among members of the same institution. Because plan consistency does not seem to significantly correlate with experience, career path, or campus, investigation into alternate methods beyond additional education and training to reduce this variation, such as knowledge-based planning or advanced optimization techniques, is necessary.