What can statistical process control show us about ionization chamber stability?

López-Tarjuelo, Juan; Quirós-Higueras, Juan David; Bonaque-Alandí, Jorge; Luquero-Llopis, Naika; García-Mollá, Rafael; Juan-Senabre, X.J.; Marco-Blancas, N. de; Ferrer-Albiach, Carlos; Santos-Serra, Agustín

doi:10.1016/j.radmeas.2015.12.041

Cited by 2 publications

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References 32 publications

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“…Several medical physicists have now moved to an SPC-oriented approach in order to learn more about the intrinsic performance of radiotherapy treatment machines and their measurement equipment (Pawlicki et al 2005, Sanghangthum et al 2013a, 2013b, López-Tarjuelo et al 2015, 2016. However, to the best of the authors' knowledge, the results produced by a MSA tool called gauge repeatability and reproducibility (R&R), which is extensively used in engineering (Burdick et al 2003, Montgomery 2009b has not yet been tested in combination with the linac measurement methods used by medical physics departments or with any other pieces of equipment.…”

Section: Introductionmentioning

confidence: 99%

Optimal specifications for beam calibration checks in radiotherapy calculated with gauge repeatability and reproducibility, and sensitivity and specificity studies

López-Tarjuelo

Bonaque-Alandí

Vidueira-Martínez

et al. 2017

Biomed. Phys. Eng. Express

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Introduction. Several medical physicists have moved to a statistical process control-oriented approach to learn more about the intrinsic performance of radiotherapy equipment. Our aim is to report how gauge repeatability and reproducibility (R&R) and sensitivity and specificity studies can provide optimal specifications for radiotherapy-beam calibration checks. Methods. A team of three medical physicists performed gauge R&R studies on 6 megavolt (MV) photon, and 4, 9, and 15-megaelectron volt electron-beams. The operator order was randomized to reduce time-related biases. Checks were performed accurately using ionization chambers with a water phantom. These gauge R&R studies allowed us to determine the proportion of variation due to the repeatability, operator, and beam-tobeam components associated with repeated beam-calibration checking. We then calculated the conditional probabilities of misclassifying the check results as a false accept (β=1-sensitivity) and a false reject (δ=1-specificity) by changing the beam calibration specifications. Using this information we plotted the receiver operating characteristic curves in order to identify the sensitivity and specificity settings that maximize detection. Results. The main component of variation was due to the operator; the repeatability component was less than 30%. The intrinsic variation component for 6 MV photonbeams was approximately 20%, whereas it was over 34% for electron-beams. The optimal specification bands expressed as a percentage of the mean were ±0.7% for 6 MV photons and ±0.9% for electron-beams. Optimal sensitivity was over 50%, whereas specificity was not less than 0.995. The very low δ indicates that the system is unlikely to reject a correct beam calibration. However, the high β shows that should we require high levels of precision and therefore adopt such optimized specifications, the probability of accepting a drifted beam calibration would be fairly high. Therefore, the combination of 'medical physicist, water phantom, and ionization chamber' is an excellent tool for correctly adjusting beam calibrations to their specifications; moreover, this procedure could also be further improved in order to detect drifts in beam calibrations if the specifications required were to tighten in the future. Conclusion. Calculating the optimal specifications is feasible and leads to a very high detection specificity, but with low sensitivity. The operator-associated variation component contributed the most to the overall variation in check results. The beam calibration procedure might need to be adapted if the demand for precision in radiotherapy increases.

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