Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 Feb;39(2):686-96.
doi: 10.1118/1.3675601.

Multicriteria VMAT optimization

David Craft  1 , Dualta McQuaid, Jeremiah Wala, Wei Chen, Ehsan Salari, Thomas Bortfeld
Affiliations

Multicriteria VMAT optimization

David Craft et al. Med Phys. 2012 Feb.

Abstract

Purpose: To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency.

Methods: A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and then delivers the merged maps together, simplifying delivery. Successive merges are made as long as the dose distribution quality is maintained. The complete algorithm is called VMERGE.

Results: VMERGE is applied to three cases: a prostate, a pancreas, and a brain. In each case, the selected Pareto-optimal plan is matched almost exactly with the VMAT merging routine, resulting in a high quality plan delivered with a single arc in less than 5 min on average.

Conclusions: VMERGE offers significant improvements over existing VMAT algorithms. The first is the multicriteria planning aspect, which greatly speeds up planning time and allows the user to select the plan, which represents the most desirable compromise between target coverage and organ at risk sparing. The second is the user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the user can explore the tradeoff between delivery time and plan quality, which is a fundamental aspect of VMAT that cannot be easily investigated with current commercial planning systems.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Results of the VMERGE algorithm for prostate VMAT. The merged plan that was determined to have the best tradeoff between quality and treatment time is indicated by the black arrow. Quality-time tradeoff plots are shown for the (a) prostate target and (b) the bladder, femoral heads and anterior rectum. (c) The DVH data for the original (solid) and merged (dashed) plan, (d) The arc portion plot for the merged plan, showing the gantry speed at different angles.
Figure 2
Figure 2
The sensitivity of VMERGE to different initial plans was tested on our prostate case. (a) DVH plots for the final merged plans for three different 1 80 beam initial plans: max beamlet smoothing, no smoothing, and SPG smoothing. (b) DVH plots for the final merged plans for three different initial plans, all with max beamlet smoothing: 1 80 beams, 90 beams, and 90 beams with small beamlets (0.5 cm × 1 cm).
Figure 3
Figure 3
Results of the VMERGE algorithm for pancreas VMAT. The merged plan that was determined to have the best tradeoff between quality and treatment time is indicated by the black arrow. Quality-time tradeoff plots are shown for the (a) pancreas target and (b) kidneys, liver and stomach. (c) The DVH data for the original (solid) and merged (dashed) plan. (d) The arc portion plot for the merged plan, showing the gantry speed at different angles.
Figure 4
Figure 4
Results of the VMERGE algorithm for brain VMAT. The merged plan that was determined to have the best tradeoff between quality and treatment time is indicated by the black arrow. Quality-time tradeoff plots are shown for the (a) tumor target and (b) the brain stem and optic chiasm. (c) The DVH data for the original (solid) and merged (dashed) plan. (d) The arc portion plot for the merged plan, showing the gantry speed at different angles.
See this image and copyright information in PMC

References

    1. Carol M. P., “Peacock: A system for planning and rotational delivery of intensity modulated fields,” Int. J. Imaging Syst. Technol. 6, 56–61 (1995).10.1002/ima.v6:1 - DOI
    1. Yu C., “Intensity-modulated arc therapy with dynamic multileaf collimation: An alternative to tomotherapy,” Phys. Med. Biol. 40(9), 1435–1449 (1995).10.1088/0031-9155/40/9/004 - DOI - PubMed
    1. Oliver M., Ansbacher W., and Beckham W., “Comparing planning time, delivery time and plan quality for IMRT, rapidarc and tomotherapy,” J. Appl. Clin. Med. Phys. 10(4), 117–131 (2009).10.1120/jacmp.v10i4.3068 - DOI - PMC - PubMed
    1. Rao M., Yang W., Chen F., Sheng K., Ye J., Mehta V., Shepard D., and Cao D., “Comparison of Elekta VMAT with helical tomotherapy and fixed field IMRT: plan quality, delivery efficiency and accuracy,” Med. Phys. 37(3), 1350–1359 (2010).10.1118/1.3326965 - DOI - PubMed
    1. K.-H. Küfer, Scherrer A., Monz M., Alonso F., Trinkaus H., Bortfeld T., and Thieke C., “Intensity modulated radiotherapy—A large scale multi-criteria programming problem,” OR Spectrum 25, 223–249 (2003).10.1007/s00291-003-0125-7 - DOI

Publication types