Simultaneous optimization of sequential IMRT plans.
Radiotherapy often comprises two phases, in which irradiation of a volume at risk for microscopic disease is followed by a sequential dose escalation to a smaller volume either at a higher risk for microscopic disease or containing only gross disease. This technique is difficult to implement with intensity modulated radiotherapy, as the tolerance doses of critical structures must be respected over the sum of the two plans. Techniques that include an integrated boost have been proposed to address this problem. However, clinical experience with such techniques is limited, and many clinicians are uncomfortable prescribing nonconventional fractionation schemes. To solve this problem, we developed an optimization technique that simultaneously generates sequential initial and boost IMRT plans. We have developed an optimization tool that uses a commercial treatment planning system (TPS) and a high level programming language for technical computing. The tool uses the TPS to calculate the dose deposition coefficients (DDCs) for optimization. The DDCs were imported into external software and the treatment ports duplicated to create the boost plan. The initial, boost, and tolerance doses were specified and used to construct cost functions. The initial and boost plans were optimized simultaneously using a gradient search technique. Following optimization, the fluence maps were exported to the TPS for dose calculation. Seven patients treated using sequential techniques were selected from our clinical database. The initial and boost plans used to treat these patients were developed independently of each other by dividing the tolerance doses proportionally between the initial and boost plans and then iteratively optimizing the plans until a summation that met the treatment goals was obtained. We used the simultaneous optimization technique to generate plans that met the original planning goals. The coverage of the initial and boost target volumes in the simultaneously optimized plans was equivalent to the independently optimized plans actually used for treatment. Tolerance doses of the critical structures were respected for the plan sum; however, the dose to critical structures for the individual initial and boost plans was different between the simultaneously optimized and the independently optimized plans. In conclusion, we have demonstrated a method for optimization of initial and boost plans that treat volume reductions using the same dose per fraction. The method is efficient, as it avoids the iterative approach necessitated by currently available TPSs, and is generalizable to more than two treatment phases. Comparison with clinical plans developed independently suggests that current manual techniques for planning sequential treatments may be suboptimal.
Popple
Richard A
RA
Department of Radiation Oncology, The University of Alabama at Birmingham, Birmingham, Alabama 35233, USA. rpopple@uabmc.edu
Prellop
Perri B
PB
Spencer
Sharon A
SA
De Los Santos
Jennifer F
JF
Duan
Jun
J
Fiveash
John B
JB
Brezovich
Ivan A
IA
D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000532:radiotherapy; D003201:Computers; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D007890:Leiomyosarcoma / Q000532:radiotherapy; D015233:Models, Statistical; D009303:Nasopharyngeal Neoplasms / Q000532:radiotherapy; D010534:Peritoneal Neoplasms / Q000532:radiotherapy; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D011874:Radiometry; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D012542:Scattering, Radiation; D012984:Software; D013964:Thyroid Neoplasms / Q000532:radiotherapy; D014067:Tonsillar Neoplasms / Q000532:radiotherapy