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Statistical process control to monitor use of a web-based autoplanning tool.
Mehrens, Hunter; Douglas, Raphael; Gronberg, Mary; Nealon, Kelly; Zhang, Joy; Court, Laurence.
Afiliación
  • Mehrens H; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Douglas R; The University of Texas MD Anderson Graduate School of Biomedical Science, Houston, Texas, USA.
  • Gronberg M; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Nealon K; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Zhang J; The University of Texas MD Anderson Graduate School of Biomedical Science, Houston, Texas, USA.
  • Court L; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
J Appl Clin Med Phys ; 23(12): e13803, 2022 Dec.
Article en En | MEDLINE | ID: mdl-36300872
ABSTRACT

PURPOSE:

To investigate the use of statistical process control (SPC) for quality assurance of an integrated web-based autoplanning tool, Radiation Planning Assistant (RPA).

METHODS:

Automatically generated plans were downloaded and imported into two treatment planning systems (TPSs), RayStation and Eclipse, in which they were recalculated using fixed monitor units. The recalculated plans were then uploaded back to the RPA, and the mean dose differences for each contour between the original RPA and the TPSs plans were calculated. SPC was used to characterize the RPA plans in terms of two comparisons RayStation TPS versus RPA and Eclipse TPS versus RPA for three anatomical sites, and variations in the machine parameters dosimetric leaf gap (DLG) and multileaf collimator transmission factor (MLC-TF) for two algorithms (Analytical Anisotropic Algorithm [AAA]) and Acuros in the Eclipse TPS. Overall, SPC was used to monitor the process of the RPA, while clinics would still perform their routine patient-specific QA.

RESULTS:

For RayStation, the average mean percent dose differences across all contours were 0.65% ± 1.05%, -2.09% ± 0.56%, and 0.28% ± 0.98% and average control limit ranges were 1.89% ± 1.32%, 2.16% ± 1.31%, and 2.65% ± 1.89% for the head and neck, cervix, and chest wall, respectively. In contrast, Eclipse's average mean percent dose differences across all contours were -0.62% ± 0.34%, 0.32% ± 0.23%, and -0.91% ± 0.98%, while average control limit ranges were 1.09% ± 0.77%, 3.69% ± 2.67%, 2.73% ± 1.86%, respectively. Averaging all contours and removing outliers, a 0% dose difference corresponded with a DLG value of 0.202 ± 0.019 cm and MLC-TF value of 0.020 ± 0.001 for Acuros and a DLG value of 0.135 ± 0.031 cm and MLC-TF value of 0.015 ± 0.001 for AAA.

CONCLUSIONS:

Differences in mean dose and control limits between RPA and two separately commissioned TPSs were determined. With varying control limits and means, SPC provides a flexible and useful process quality assurance tool for monitoring a complex automated system such as the RPA.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador / Radioterapia de Intensidad Modulada Límite: Humans Idioma: En Revista: J Appl Clin Med Phys Asunto de la revista: BIOFISICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador / Radioterapia de Intensidad Modulada Límite: Humans Idioma: En Revista: J Appl Clin Med Phys Asunto de la revista: BIOFISICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos