Validation of MLC leaf open time calculation methods for PSQA in adaptive radiotherapy with tomotherapy units.

adaptive radiation therapy (ART) leaf open time (LOT) patient specific quality assurance (PSQA) tomotherapy

Journal

Journal of applied clinical medical physics
ISSN: 1526-9914
Titre abrégé: J Appl Clin Med Phys
Pays: United States
ID NLM: 101089176

Informations de publication

Date de publication:
08 Aug 2024
Historique:
revised: 10 06 2024
received: 17 04 2024
accepted: 08 07 2024
medline: 8 8 2024
pubmed: 8 8 2024
entrez: 8 8 2024
Statut: aheadofprint

Résumé

Treatment delivery safety and accuracy are essential to control the disease and protect healthy tissues in radiation therapy. For usual treatment, a phantom-based patient specific quality assurance (PSQA) is performed to verify the delivery prior to the treatment. The emergence of adaptive radiation therapy (ART) adds new complexities to PSQA. In fact, organ at risks and target volume re-contouring as well as plan re-optimization and treatment delivery are performed with the patient immobilized on the treatment couch, making phantom-based pretreatment PSQA impractical. In this case, phantomless PSQA tools based on multileaf collimator (MLC) leaf open times (LOTs) verifications provide alternative approaches for the Radixact® treatment units. However, their validity is compromised by the lack of independent and reliable methods for calculating the LOT performed by the MLC during deliveries. To provide independent and reliable methods of LOT calculation for the Radixact® treatment units. Two methods for calculating the LOTs performed by the MLC during deliveries have been implemented. The first method uses the signal recorded by the build-in detector and the second method uses the signal recorded by optical sensors mounted on the MLC. To calibrate the methods to the ground truth, in-phantom ionization chamber LOT measurements have been conducted on a Radixact® treatment unit. The methods were validated by comparing LOT calculations with in-phantom ionization chamber LOT measurements performed on two Radixact® treatment units. The study shows a good agreement between the two LOT calculation methods and the in-phantom ionization chamber measurements. There are no notable differences between the two methods and the same results were observed on the different treatment units. The two implemented methods have the potential to be part of a PSQA solution for ART in tomotherapy.

Sections du résumé

BACKGROUND BACKGROUND
Treatment delivery safety and accuracy are essential to control the disease and protect healthy tissues in radiation therapy. For usual treatment, a phantom-based patient specific quality assurance (PSQA) is performed to verify the delivery prior to the treatment. The emergence of adaptive radiation therapy (ART) adds new complexities to PSQA. In fact, organ at risks and target volume re-contouring as well as plan re-optimization and treatment delivery are performed with the patient immobilized on the treatment couch, making phantom-based pretreatment PSQA impractical. In this case, phantomless PSQA tools based on multileaf collimator (MLC) leaf open times (LOTs) verifications provide alternative approaches for the Radixact® treatment units. However, their validity is compromised by the lack of independent and reliable methods for calculating the LOT performed by the MLC during deliveries.
PURPOSE OBJECTIVE
To provide independent and reliable methods of LOT calculation for the Radixact® treatment units.
METHODS METHODS
Two methods for calculating the LOTs performed by the MLC during deliveries have been implemented. The first method uses the signal recorded by the build-in detector and the second method uses the signal recorded by optical sensors mounted on the MLC. To calibrate the methods to the ground truth, in-phantom ionization chamber LOT measurements have been conducted on a Radixact® treatment unit. The methods were validated by comparing LOT calculations with in-phantom ionization chamber LOT measurements performed on two Radixact® treatment units.
RESULTS RESULTS
The study shows a good agreement between the two LOT calculation methods and the in-phantom ionization chamber measurements. There are no notable differences between the two methods and the same results were observed on the different treatment units.
CONCLUSIONS CONCLUSIONS
The two implemented methods have the potential to be part of a PSQA solution for ART in tomotherapy.

Identifiants

pubmed: 39115142
doi: 10.1002/acm2.14478
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e14478

Subventions

Organisme : Accuray Inc.

Informations de copyright

© 2024 The Author(s). Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.

Références

Markus A, Sara B, Carlos DW, et al. Guidelines for the verification of imrt, ESTRO Booklet No. 9; 2008: 127 p. ISBN 90‐804532‐9.
Swiss Society of Radiobiology and Medical Physics. Quality control for Intensity‐modulated radiation therapy, Recommendations No. 15; 2007: 17 p. ISBN 3 908 125 41 3.
Hodapp N. Der ICRU‐Report 83: Verordnung, Dokumentation und Kommunikation der fluenzmodulierten Photonenstrahlentherapie (IMRT) [The ICRU Report 83: prescribing, recording and reporting photon‐beam intensity‐modulated radiation therapy (IMRT)]. Strahlenther Onkol. 2012;188(1):97‐99. doi:10.1007/s00066‐011‐0015‐x
Miften M, Olch A, Mihailidis D, et al. Tolerance limits and methodologies for IMRT measurement‐based verification QA: recommendations of AAPM Task Group No. 218. Med Phys. 2018;45(4):e53‐e83. doi:10.1002/mp.12810
Low DA, Moran JM, Dempsey JF, Dong L, Oldham M. Dosimetry tools and techniques for IMRT. Med Phys. 2011;38(3):1313‐1338. doi:10.1118/1.3514120
Mans A, Wendling M, McDermott LN, et al. Catching errors with in vivo EPID dosimetry. Med Phys. 2010;37(6):2638‐2644. doi:10.1118/1.3397807
van Elmpt W, McDermott L, Nijsten S, Wendling M, Lambin P, Mijnheer B. A literature review of electronic portal imaging for radiotherapy dosimetry. Radiother Oncol. 2008;88(3):289‐309. doi:10.1016/j.radonc.2008.07.008
Kruse JJ. On the insensitivity of single field planar dosimetry to IMRT inaccuracies. Med Phys. 2010;37(6):2516‐2524. doi:10.1118/1.3425781
Nelms BE, Zhen H, WA Tome. Per‐beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors. Med Phys. 2011;38(2):1037‐1044. doi:10.1118/1.3544657
Carrasco P, Jornet N, Latorre A, Eudaldo T, Ruiz A, Ribas M. 3D DVH‐based metric analysis versus per‐beam planar analysis in IMRT pretreatment verification. Med Phys. 2012;39(8):5040‐5049. doi:10.1118/1.4736949
Stasi M, Bresciani S, Miranti A, Maggio A, Sapino V, Gabriele P. Pretreatment patient‐specific IMRT quality assurance: a correlation study between gamma index and patient clinical dose volume histogram. Med Phys. 2012;39(12):7626‐7634. doi:10.1118/1.4767763
Fredh A, Scherman JB, Fog LS. Munck af Rosenschold P. Patient QA systems for rotational radiation therapy: a comparative experimental study with intentional errors. Med Phys. 2013;40(3):031716. doi:10.1118/1.4788645
Heilemann G, Poppe B, Laub W. On the sensitivity of common gamma‐index evaluation methods to MLC misalignments in Rapidarc quality assurance. Med Phys. 2013;40(3):031702. doi:10.1118/1.4789580
Kry SF, Molineu A, Kerns JR, et al. Institutional patient‐specific IMRT QA does not predict unacceptable plan delivery. Int J Radiat Oncol Biol Phys. 2014;90(5):1195‐1201. doi:10.1016/j.ijrobp.2014.08.334
McKenzie EM, Balter PA, Stingo FC, Jones J, Followill DS, Kry SF. Toward optimizing patient‐specific IMRT QA techniques in the accurate detection of dosimetrically acceptable and unacceptable patient plans. Med Phys. 2014;41(12):121702. doi:10.1118/1.4899177
Steers JM, Fraass BA. IMRT QA: selecting gamma criteria based on error detection sensitivity. Med Phys. 2016;43(4):1982. doi:10.1118/1.4943953
Nelms BE, Chan MF, Jarry G, et al. Evaluating IMRT and VMAT dose accuracy: practical examples of failure to detect systematic errors when applying a commonly used metric and action levels. Med Phys. 2013;40(11):111722. doi:10.1118/1.4826166
Lin J, Chen M, Lai Y, et al. ART2Dose: a comprehensive dose verification platform for online adaptive radiotherapy. Med Phys. 2024; 51(1): 18‐30. doi:10.1002/mp.16806
Zhao X, Stanley DN, Cardenas CE, Harms J, Popple RA. Do we need patient‐specific QA for adaptively generated plans? Retrospective evaluation of delivered online adaptive treatment plans on Varian Ethos. J Appl Clin Med Phys. 2023;24(2):e13876. doi:10.1002/acm2.13876
Valdes G, Chan MF, Lim SB, Scheuermann R, Deasy JO, Solberg TD. IMRT QA using machine learning: a multi‐institutional validation. J Appl Clin Med Phys. 2017;18(5):279‐284. doi:10.1002/acm2.12161
El Naqa I, Irrer J, Ritter TA, et al. Machine learning for automated quality assurance in radiotherapy: a proof of principle using EPID data description. Med Phys. 2019;46(4):1914‐1921. doi:10.1002/mp.13433
Pawlicki T, Whitaker M, Boyer AL. Statistical process control for radiotherapy quality assurance. Med Phys. 2005;32(9):2777‐2786. doi:10.1118/1.2001209
Mackie TR, Holmes T, Swerdloff S, et al. Tomotherapy: a new concept for the delivery of dynamic conformal radiotherapy. Med Phys. 1993;20(6):1709‐1719. doi:10.1118/1.596958
Westerly DC, Soisson E, Chen Q, et al. Treatment planning to improve delivery accuracy and patient throughput in helical tomotherapy. Int J Radiat Oncol Biol Phys. 2009;74(4):1290‐1297. doi:10.1016/j.ijrobp.2009.02.004
Handsfield LL, Jones R, Wilson DD, Siebers JV, Read PW, Chen Q. Phantomless patient‐specific TomoTherapy QA via delivery performance monitoring and a secondary Monte Carlo dose calculation. Med Phys. 2014;41(10):101703. doi:10.1118/1.4894721
Thiyagarajan R, Sharma DS, Kaushik S, et al. Leaf open time sinogram (LOTS): a novel approach for patient specific quality assurance of total marrow irradiation. Radiat Oncol. 2020;15(1):236. doi:10.1186/s13014‐020‐01669‐2
Schopfer M, Bochud FO, Bourhis J, Moeckli R. A delivery quality assurance tool based on the actual leaf open times in tomotherapy. Med Phys. 2020;47(9):3845‐3851. doi:10.1002/mp.14348
Schopfer M, Bochud FO, Bourhis J, Moeckli R. In air and in vivo measurement of the leaf open time in tomotherapy using the on‐board detector pulse‐by‐pulse data. Med Phys. 2019;46(5):1963‐1971. doi:10.1002/mp.13459
Mackie TR, Holmes T, Swerdloff S, et al. Tomotherapy: a new concept for the delivery of dynamic conformal radiotherapy. Med Phys. 2013;20(6):1709‐1719. doi: 10.1118/1.596958
Chen Q, Westerly D, Fang Z, Sheng K, Chen Y. TomoTherapy MLC verification using exit detector data. Med Phys. 2012;39(1):143‐151. doi:10.1118/1.3666762
Sevillano D, Minguez C, Sanchez A, Sanchez‐Reyes A. Measurement and correction of leaf open times in helical tomotherapy. Med Phys. 2012;39(11):6972‐6980. doi:10.1118/1.4762565

Auteurs

Marie Nasrallah (M)

Institute of Radiation Physics, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.

François Bochud (F)

Institute of Radiation Physics, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.

Neelima Tellapragada (N)

Accuray Incorporated, Madison, Wisconsin, USA.

Jean Bourhis (J)

Radiation Oncology Department, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.

Edward Chao (E)

Accuray Incorporated, Madison, Wisconsin, USA.

Dylan Casey (D)

Accuray Incorporated, Madison, Wisconsin, USA.

Raphaël Moeckli (R)

Institute of Radiation Physics, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.

Classifications MeSH