Plan delivery quality assurance for CyberKnife: Statistical process control analysis of 350 film-based patient-specific QAs

Bellec, J.; Delaby, N.; Jouyaux, F.; Perdrieux, M.; Bouvier, Jeanne; Sorel, S.; Henry, Olivier; Lafond, C.

doi:10.1016/j.ejmp.2017.06.016

Cited by 24 publications

(38 citation statements)

References 20 publications

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“…3 As the TG-218 report and previous studies recommended, all aspects of variation in IMRT/VMAT PSQA can be accounted for with the use of statistical process control (SPC) methods to set process-based tolerance and action limits. [3][4][5][6][7][8][9][10][11][12] Statistical process control is a powerful analytical decision-making tool used for monitoring production processes, achieving stability, and reducing variability, developed by Walter A. Shewhart nearly a century ago. 13 Using specific control charts, SPC provides a prescriptive method to identify random vs. systematic errors in a stream of time-resolved data.…”

Section: Introductionmentioning

confidence: 99%

“…[14][15][16] In IMRT/VMAT PSQA processes, the conventional Shewhart control charts and process capability indices (PCIs) have been widely used over the past decade to monitor the results of quality control (QC). [3][4][5][6][7][8][9][10][11][12]17 Previous codes of practice and studies on SPC in IMRT/ VMAT PSQA processes have typically adopted the conventional Shewhart control charts under the assumption of normality. [3][4][5][6][7][8][9][10][11][12] Several studies on SPC have demonstrated that using normal-based control charts may result in incorrect decisions when the distribution of the quality characteristic for a process is non-normal.…”

Section: Introductionmentioning

confidence: 99%

“…[3][4][5][6][7][8][9][10][11][12]17 Previous codes of practice and studies on SPC in IMRT/ VMAT PSQA processes have typically adopted the conventional Shewhart control charts under the assumption of normality. [3][4][5][6][7][8][9][10][11][12] Several studies on SPC have demonstrated that using normal-based control charts may result in incorrect decisions when the distribution of the quality characteristic for a process is non-normal. [18][19][20][21][22][23] For example, directly applying Shewhart control charts increases the type Ⅰ risk 21 and false alarm rate.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Statistical process control and process capability analysis for non‐normal volumetric modulated arc therapy patient‐specific quality assurance processes

Xiao

Bai

et al. 2020

Medical Physics

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Applying statistical process control (SPC) to intensity-modulated radiotherapy (IMRT)/ volumetric modulated arc therapy (VMAT) patient-specific quality assurance (PSQA) program was recommended by the American Association of Physics in Medicine Task Group 218 report, but a comprehensive analysis of PSQA processes with non-normal distributions is lacking. This study investigates SPC and process capability analysis (PCA) methods for non-normal IMRT/VMAT PSQA processes. Methods: 1119 VMAT PSQAs were performed on three beam-matched linear accelerators (linacs), using gamma analysis. The Anderson-Darling statistic was used to test normality. The control charts for each PSQA process were obtained using three non-normal-based methods and compared with the conventional Shewhart method. The ability of each PSQA process to produce an output within the specification limit was measured using the C pk index; in this study, the C pk index was calculated using two transformation methods and compared with that calculated using the conventional method. The performances of the three linacs were assessed using SPC and PCA methods. Results: All three PSQA processes were non-normal (P < 0.005). Compared to the non-normalbased SPC and PCA methods, the false alarm rates of the conventional method for linac1, linac2, and linac3 were 0.83%, 3.77%, and 4.95% respectively; the minimum overestimated C pk values were 0.59, 0.87, and 1.49, respectively. The process capabilities of the three beam-matched linacs were at different levels. Conclusion: For non-normal VMAT PSQA processes, the conventional SPC and PCA methods increase the false alarm rates and overestimate process capabilities. Instead, non-normal-based SPC and PCA methods are more reliable and accurate in non-normal PSQA processes. Statistical process control and PCA are useful tools for assessing the performance of beam-matched linacs.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Statistical process control and process capability analysis for non‐normal volumetric modulated arc therapy patient‐specific quality assurance processes

Xiao

Bai

et al. 2020

Medical Physics

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“…Mardirossian et al [13] evaluated dose distributions of eight patient plans generated in MultiPlan TPS using film dosimetry; the gamma-index value of 3%/2 mm criterion was found to be 98.6% in their study. Bellec et al [14] performed plan delivery quality assurance (DQA) test for the CK plans using Gafchromic EBT3 films. In their research, pre-treatment plans for 350 intracranial and extracranial cases were created on BabyBlue phantom.…”

Section: Discussionmentioning

confidence: 99%

Verification of CyberKnife Dose Distributions with Gafchromic EBT2 Film

Koksal¹

2018

TJ Oncol

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OBJECTIVECyberKnife (CK) system is more sophisticated than the conventional methods; therefore, strict quality assurance tests are required. To ensure that the treatment is delivered as planned, the verification of the treatment plan should be performed with specific dosimetry tools. This study aims to verify the CK treatment plans generated for patients with intracranial tumors using Gafchromic EBT2 film. METHODSThe CK plans of ten patients with intracranial tumors were selected for this study. The plans were transferred to computed tomography images of the anthropomorphic head phantom. The phantom containing the film was irradiated using 6D skull tracking method. The dose distributions calculated by TPS were compared with those measured by film using gamma analysis method. RESULTSIn the gamma-index method, the average passing rate for the 3%/3 mm criterion was found to be 93.9±4.8%. The gamma passing rate for Iris-collimator-based plans yielded slightly lower than that for fixed-collimator-based plans. CONCLUSIONIn conclusion, this study indicates that Gafchromic EBT2 film is a utilizable dosimeter for quality assurance of the CK treatment plans. It is recommended to use the EBT2 film for verification of the CK treatment plans before delivery to the patient.

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“…1 Patient-specific QA measurements can be performed using chambers, film, or diode arrays. [2][3][4][5][6][7] Especially for stereotactic CyberKnife treatment plans, both measurement equipment and analysis require stringent quality criteria. Internationally acknowledged gamma criteria of 2% dose difference and 2 mm distanceto-agreement Γ(2,2) are insufficient to detect possible errors relevant during CyberKnife dose delivery.…”

Section: Introductionmentioning

confidence: 99%

Commissioning and clinical implementation of the first commercial independent Monte Carlo 3D dose calculation to replace CyberKnife M6™ patient‐specific QA measurements

Milder

Alber

Söhn³

et al. 2020

J Applied Clin Med Phys

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To report on the commissioning and clinical validation of the first commercially available independent Monte Carlo (MC) three-dimensional (3D) dose calculation for CyberKnife robotic radiosurgery system ® (Accuray, Sunnyvale, CA). Methods: The independent dose calculation (IDC) by SciMoCa ® (Scientific RT, Munich, Germany) was validated based on water measurements of output factors and dose profiles (unshielded diode, field-size dependent corrections). A set of 84 patient-specific quality assurance (QA) measurements for multi-leaf collimator (MLC) plans, using an Octavius two-dimensional SRS1000 array (PTW, Freiburg, Germany), was compared to results of respective calculations. Statistical process control (SPC) was used to detect plans outside action levels. Results: Of all output factors for the three collimator systems of the CyberKnife, 99% agreed within 2% and 81% within 1%, with a maximum deviation of 3.2% for a 5-mm fixed cone. The profiles were compared using a one-dimensional gamma evaluation with 2% dose difference and 0.5 mm distance-to-agreement (Γ(2,0.5)). The off-centre ratios showed an average pass rate >99% (92-100%). The agreement of the depth dose profiles depended on field size, with lowest pass rates for the smallest MLC field sizes. The average depth dose pass rate was 88% (35-99%). The IDCs showed a Γ(2,1) pass rate of 98%. Statistical process control detected six plans outside tolerance levels in the measurements, all of which could be attributed the measurement setup. Independent dose calculations showed problems in five plans, all due to differences in the algorithm between TPS and IDC. Based on these results changes were made in the class solution for treatment plans. Conclusion: The first commercially available MC 3D dose IDC was successfully commissioned and validated for the CyberKnife and replaced all routine patientspecific QA measurements in our clinic.

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Plan delivery quality assurance for CyberKnife: Statistical process control analysis of 350 film-based patient-specific QAs

Cited by 24 publications

References 20 publications

Statistical process control and process capability analysis for non‐normal volumetric modulated arc therapy patient‐specific quality assurance processes

Statistical process control and process capability analysis for non‐normal volumetric modulated arc therapy patient‐specific quality assurance processes

Verification of CyberKnife Dose Distributions with Gafchromic EBT2 Film

Commissioning and clinical implementation of the first commercial independent Monte Carlo 3D dose calculation to replace CyberKnife M6™ patient‐specific QA measurements

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