Technical Note: A fast online adaptive replanning method for VMAT using flattening filter free beams.
OBJECTIVE
To develop a fast replanning algorithm based on segment aperture morphing (SAM) for online replanning of volumetric modulated arc therapy (VMAT) with flattening filter free (FFF) beams.


METHODS
A software tool was developed to interface with a VMAT research planning system, which enables the input and output of beam and machine parameters of VMAT plans. The SAM algorithm was used to modify multileaf collimator positions for each segment aperture based on the changes of the target from the planning (CT/MR) to daily image [CT/CBCT/magnetic resonance imaging (MRI)]. The leaf travel distance was controlled for large shifts to prevent the increase of VMAT delivery time. The SAM algorithm was tested for 11 patient cases including prostate, pancreatic, and lung cancers. For each daily image set, three types of VMAT plans, image-guided radiation therapy (IGRT) repositioning, SAM adaptive, and full-scope reoptimization plans, were generated and compared.


RESULTS
The SAM adaptive plans were found to have improved the plan quality in target and/or critical organs when compared to the IGRT repositioning plans and were comparable to the reoptimization plans based on the data of planning target volume (PTV)-V100 (volume covered by 100% of prescription dose). For the cases studied, the average PTV-V100 was 98.85% ± 1.13%, 97.61% ± 1.45%, and 92.84% ± 1.61% with FFF beams for the reoptimization, SAM adaptive, and repositioning plans, respectively. The execution of the SAM algorithm takes less than 10 s using 16-CPU (2.6 GHz dual core) hardware.


CONCLUSIONS
The SAM algorithm can generate adaptive VMAT plans using FFF beams with comparable plan qualities as those from the full-scope reoptimization plans based on daily CT/CBCT/MRI and can be used for online replanning to address interfractional variations.
Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226.
Ozgur
O
Ates
Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226.
Ergun E
EE
Ahunbay
Elekta, Inc., Maryland Heights, Missouri 63043.
Michel
M
Moreau
Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226.
X Allen
XA
Li
D000465:Algorithms; D054893:Cone-Beam Computed Tomography / Q000379:methods; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D058958:Organs at Risk / Q000000981:diagnostic imaging / Q000528:radiation effects; D010190:Pancreatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000295:instrumentation / Q000379:methods*; D012984:Software