Motion management with phase-adapted 4D-optimization.
Cancer treatment with ionizing radiation is often compromised by organ motion, in particular for lung cases. Motion uncertainties can significantly degrade an otherwise optimized treatment plan. We present a spatiotemporal optimization method, which takes into account all phases of breathing via the corresponding 4D-CTs and provides a 4D-optimal plan that can be delivered throughout all breathing phases. Monte Carlo dose calculations are employed to warrant for highest dosimetric accuracy, as pertinent to study motion effects in lung. We demonstrate the performance of this optimization method with clinical lung cancer cases and compare the outcomes to conventional gating techniques. We report significant improvements in target coverage and in healthy tissue sparing at a comparable computational expense. Furthermore, we show that the phase-adapted 4D-optimized plans are robust against irregular breathing, as opposed to gating. This technique has the potential to yield a higher delivery efficiency and a decisively shorter delivery time.
Nohadani
Omid
O
School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA. nohadani@purdue.edu
Seco
Joao
J
Bortfeld
Thomas
T
D000465:Algorithms; D056973:Four-Dimensional Computed Tomography / Q000379:methods*; D006801:Humans; D008175:Lung Neoplasms / Q000532:radiotherapy*; D009010:Monte Carlo Method; D009038:Motion; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012119:Respiration