Statistical control of processes applied to geometric uncertainties for CTV expansion margins determination in prostate cancer patients treated with VMAT: a prospective study in 57 patients.
Control charts
Control state of geometric deviations
Prostate cancer patients
VMAT treatments uncertainties
Journal
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
ISSN: 1699-3055
Titre abrégé: Clin Transl Oncol
Pays: Italy
ID NLM: 101247119
Informations de publication
Date de publication:
Jun 2021
Jun 2021
Historique:
received:
01
05
2020
accepted:
03
09
2020
pubmed:
28
9
2020
medline:
15
12
2021
entrez:
27
9
2020
Statut:
ppublish
Résumé
To study the control graphs applicability for the geometric uncertainties of VMAT treatments in prostate cancer patients, and their use to verify the hypothesis of the data obtained randomness, to apply the margins of Van Herk expression. During the first 5 days of treatment, and then once a week, a Kv CBCT was performed, compared with the simulation CT and adjusted the displacements, to determine the inter-fraction errors. Immediately after radiation therapy, another CBCT was performed (for intra-fraction errors). With these data, the X, R position control charts have been made. The patients, not maintained the deviations within the charts control limits, were called "anomalies". Then, we compared the deviations and margins calculated with the van Herk expression for all patients and for those without anomalies. The margins determined show appreciable differences if there were calculated for the total set of patients or for the set of them without anomalies in the control charts. For the overall set of patients, the lateral, longitudinal, and vertical margins were 0.45 cm, 0.52 cm, 0.56 cm, while for the set of patients without anomalies were 0.29 cm, 0.35 cm, and 0.38 cm. The use of control charts allows tracking geometric deviations both inter and intra-fraction, variability real-time control and to detect situations in which it can change for non-random reasons, and require immediate investigation. Maintaining geometric deviations in the control state decreases the margins needed to administer a high dose to CTV in a high percentage of cancer prostate patients.
Identifiants
pubmed: 32981004
doi: 10.1007/s12094-020-02493-6
pii: 10.1007/s12094-020-02493-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1078-1084Références
van Herk M, Remeijer P, CoenRash Joos V L. The probability of correct dosage: Dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys. 2000;47(4):1121–35.
doi: 10.1016/S0360-3016(00)00518-6
van Herk M, Remeijer P, Lebesque JV. Inclusion of geometric uncertainties in treatment plan evaluation. Int J Radiat Oncol Biol Phys. 2000;47(4):1407–22.
Stroom JC, de Boer HCJ, Huizenga H, Visser AG. Inclusion of geometrical uncertainties in radiotherapy treatment planning by means of coverage probability. Int J Radiat Oncol Biol Phys. 1999;43(4):905–19.
doi: 10.1016/S0360-3016(98)00468-4
Langen KM, Meeks SL, Pouliot J. Quality assurance of onboard megavoltage computed tomography imaging and target localization systems for on- and off-line image-guided radiotherapy. Int J Radiat Oncol Biol Phys. 2008;71(1 supplement):S62–S6565.
doi: 10.1016/j.ijrobp.2007.04.094
W. Wunderink, “Accurate Targeting of liver tumors in stereotactic radiation therapy” (2011) Doctoral Thesis, Erasmus Universiteit Rotterdam.
D.C. Montgomery, G.C. Runger (2011) “Applied Statistics and Probability for Engineers”. Fifth Edition Ed John Wiley & Sons Inc, NJ, USA
D.C. Montgomery, “Introduction to statistical quality control”. Sixth Edition. 2009. Ed John Wiley & Sons Inc., NJ, USA
Li M, Li G-F, Hou X-Y, Gao H, Yong-Gan Xu, Zhao T. A dosimetric comparation between conventional fractionated and hypofractionated image-guided radiation therapies for localized prostate cancer. Chin Med J (Engl). 2016;129(12):1447–544. https://doi.org/10.4103/0366-6999.18349 .
doi: 10.4103/0366-6999.18349
Mellon EA, Javedan K, Strom TJ, Moros EG, Biagioli MC, Fernandez DC, Wasserman SG, Wilder RB. A dosimetric comparison of volumetric arc therapy with step-and-shot intensity modulated radiation therapy for prostate cancer. Pract Radiat Oncol. 2015;5(1):11–5. https://doi.org/10.1016/j.prro.2014.03.003 [Epub 2014 Apr 18].
doi: 10.1016/j.prro.2014.03.003
pubmed: 25413432
Myrehaug S, Chan G, Craig T, Weimberg V, Cheng C, Roach M 3rd, Cheung P, Sahgal A. A treatment planning and acute toxicity comparison of two pelvic nodal volume delineation techniques and delivery comparison of intensity-modulated radiotherapy versus volumetric arc therapy for hypofractionated high-risk prostate cancer radiotherapy. Int J Radiat Oncol Biol Phys. 2015;82(4):e657–e662662. https://doi.org/10.1016/j.ijrobp.2011.09.006 [Epub 2012 Jan 13].
doi: 10.1016/j.ijrobp.2011.09.006
Pawlicki T, Whitaker M, Boyer AL. Statistical process control for radiotherapy quality assurance. Med Phys. 2005;32(9):2777–866.
doi: 10.1118/1.2001209
Unkelbach J, Alber M, Bangert M, Bokrantz R, Chan TCY, Deasy JO, et al. Robust radiotherapy planning. Phys Med Biol. 2018;63(22):22TR02. https://doi.org/10.1088/1361-6560/aae659 .
doi: 10.1088/1361-6560/aae659
pubmed: 30418942
Kaoru Ishikawa (1989) “Introduction to Quality Control”
Muñoz Montplet C, Jurado Bruggeman D. Characterization of geometrical random uncertainty distribution for a group of patients in radiotherapy. Rev Fis Med. 2010;11(2):115–8.