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.
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.
Authors: Christian Thieke; Karl-Heinz Küfer; Michael Monz; Alexander Scherrer; Fernando Alonso; Uwe Oelfke; Peter E Huber; Jürgen Debus; Thomas Bortfeld Journal: Radiother Oncol Date: 2007-09-24 Impact factor: 6.280
Authors: Jan Unkelbach; Thomas Bortfeld; David Craft; Markus Alber; Mark Bangert; Rasmus Bokrantz; Danny Chen; Ruijiang Li; Lei Xing; Chunhua Men; Simeon Nill; Dávid Papp; Edwin Romeijn; Ehsan Salari Journal: Med Phys Date: 2015-03 Impact factor: 4.071
Authors: Christos Moustakis; Mark K H Chan; Jinkoo Kim; Joakim Nilsson; Alanah Bergman; Tewfik J Bichay; Isabel Palazon Cano; Savino Cilla; Francesco Deodato; Raffaela Doro; Jürgen Dunst; Hans Theodor Eich; Pierre Fau; Ming Fong; Uwe Haverkamp; Simon Heinze; Guido Hildebrandt; Detlef Imhoff; Erik de Klerck; Janett Köhn; Ulrike Lambrecht; Britta Loutfi-Krauss; Fatemeh Ebrahimi; Laura Masi; Alan H Mayville; Ante Mestrovic; Maaike Milder; Alessio G Morganti; Dirk Rades; Ulla Ramm; Claus Rödel; Frank-Andre Siebert; Wilhelm den Toom; Lei Wang; Stefan Wurster; Achim Schweikard; Scott G Soltys; Samuel Ryu; Oliver Blanck Journal: Strahlenther Onkol Date: 2018-05-25 Impact factor: 3.621