Development of a Monte Carlo based robustness calculation and evaluation tool.

Loebner, H A; Volken, W; Mueller, S; Bertholet, J; Mackeprang, P-H; Guyer, G; Aebersold, D M; Stampanoni, Mfm; Manser, P; Fix, M K (2022). Development of a Monte Carlo based robustness calculation and evaluation tool. Medical physics, 49(7), pp. 4780-4793. American Association of Physicists in Medicine AAPM 10.1002/mp.15683

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BACKGROUND

Evaluating plan robustness is a key step in radiotherapy.

PURPOSE

To develop a flexible Monte Carlo (MC)-based robustness calculation and evaluation tool to assess and quantify dosimetric robustness of intensity modulated radiotherapy treatment plans by exploring the impact of systematic and random uncertainties resulting from patient setup, patient anatomy changes, and mechanical limitations of machine components.

METHODS

The robustness tool consists of two parts: the first part includes automated MC dose calculation of multiple user-defined uncertainty scenarios to populate a robustness space. An uncertainty scenario is defined by a certain combination of uncertainties in patient setup, rigid intra-fraction motion and in mechanical steering of the following machine components: angles of gantry, collimator, table-yaw, table-pitch, table-roll, translational positions of jaws, multi-leaf-collimator (MLC) banks, and single MLC leaves. The Swiss Monte Carlo Plan (SMCP) is integrated in this tool to serve as the backbone for the MC dose calculations incorporating the uncertainties. The calculated dose distributions serve as input for the second part of the tool, handling the quantitative evaluation of the dosimetric impact of the uncertainties. A graphical user interface (GUI) is developed to simultaneously evaluate the uncertainty scenarios according to user-specified conditions based on dose-volume histogram (DVH) parameters, fast and exact gamma analysis, and dose differences. Additionally, a robustness index (RI) is introduced with the aim to simultaneously evaluate and condense dosimetric robustness against multiple uncertainties into one number. The RI is defined as the ratio of scenarios passing the conditions on the dose distributions. Weighting of the scenarios in the robustness space is possible to consider their likelihood of occurrence. The robustness tool is applied on an intensity modulated radiotherapy (IMRT), a volumetric modulated arc therapy (VMAT), a dynamic trajectory radiotherapy (DTRT) and a dynamic mixed beam radiotherapy (DYMBER) plan for a brain case to evaluate the robustness to uncertainties of gantry-, table-, collimator angle, MLC, and intra-fraction motion. Additionally, the robustness of the IMRT, VMAT and DTRT plan against patient setup uncertainties are compared. The robustness tool is validated by Delta4 measurements for scenarios including all uncertainty types available.

RESULTS

The robustness tool performs simultaneous calculation of uncertainty scenarios, and the GUI enables their fast evaluation. For all evaluated plans and uncertainties, the PTV margin prevented major clinical target volume (CTV) coverage deterioration (maximum observed standard deviation of D98%CTV was 1.3 Gy). OARs close to the PTV experienced larger dosimetric deviations (maximum observed standard deviation of D2%chiasma was 14.5 Gy). Robustness comparison by RI evaluation against patient setup uncertainties revealed better dosimetric robustness of the VMAT and DTRT plans as compared to the IMRT plan. Delta4 validation measurements agreed with calculations by >96% gamma-passing rate (3%/2 mm).

CONCLUSION

The robustness tool was successfully implemented. Calculation and evaluation of uncertainty scenarios with the robustness tool were demonstrated on a brain case. Effects of patient and machine specific uncertainties and the combination thereof on the dose distribution are evaluated in a user-friendly GUI to quantitatively assess and compare treatment plans and their robustness. This article is protected by copyright. All rights reserved.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Radiation Oncology > Medical Radiation Physics
04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Radiation Oncology

UniBE Contributor:

Löbner, Hannes Anton; Volken, Werner; Müller, Silvan Andreas; Bertholet, Jenny; Mackeprang, Paul-Henry; Guyer, Gian Mauro Carlo; Aebersold, Daniel Matthias; Manser, Peter and Fix, Michael

Subjects:

600 Technology > 610 Medicine & health

ISSN:

0094-2405

Publisher:

American Association of Physicists in Medicine AAPM

Language:

English

Submitter:

Pubmed Import

Date Deposited:

25 Apr 2022 17:13

Last Modified:

17 Jul 2022 00:13

Publisher DOI:

10.1002/mp.15683

PubMed ID:

35451087

Uncontrolled Keywords:

Monte Carlo plan evaluation robustness (to patient and machine related uncertainties)

BORIS DOI:

10.48350/169467

URI:

https://boris.unibe.ch/id/eprint/169467

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