Adaptive liver stereotactic body radiation therapy: automated daily plan reoptimization prevents dose delivery degradation caused by anatomy deformations.
OBJECTIVE
To investigate how dose distributions for liver stereotactic body radiation therapy (SBRT) can be improved by using automated, daily plan reoptimization to account for anatomy deformations, compared with setup corrections only.


METHODS
For 12 tumors, 3 strategies for dose delivery were simulated. In the first strategy, computed tomography scans made before each treatment fraction were used only for patient repositioning before dose delivery for correction of detected tumor setup errors. In adaptive second and third strategies, in addition to the isocenter shift, intensity modulated radiation therapy beam profiles were reoptimized or both intensity profiles and beam orientations were reoptimized, respectively. All optimizations were performed with a recently published algorithm for automated, multicriteria optimization of both beam profiles and beam angles.


RESULTS
In 6 of 12 cases, violations of organs at risk (ie, heart, stomach, kidney) constraints of 1 to 6 Gy in single fractions occurred in cases of tumor repositioning only. By using the adaptive strategies, these could be avoided (<1 Gy). For 1 case, this needed adaptation by slightly underdosing the planning target volume. For 2 cases with restricted tumor dose in the planning phase to avoid organ-at-risk constraint violations, fraction doses could be increased by 1 and 2 Gy because of more favorable anatomy. Daily reoptimization of both beam profiles and beam angles (third strategy) performed slightly better than reoptimization of profiles only, but the latter required only a few minutes of computation time, whereas full reoptimization took several hours.


CONCLUSIONS
This simulation study demonstrated that replanning based on daily acquired computed tomography scans can improve liver stereotactic body radiation therapy dose delivery.
Erasmus Medical Center-Daniel den Hoed Cancer Center, Rotterdam, The Netherlands; Delft University of Technology, Delft, The Netherlands.
Suzanne M
SM
Leinders
Sebastiaan
S
Breedveld
Alejandra
A
Méndez Romero
Dennis
D
Schaart
Yvette
Y
Seppenwoolde
Ben J M
BJ
Heijmen
D000465:Algorithms; D019583:Dose Fractionation, Radiation; D005260:Female; D006801:Humans; D008113:Liver Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy / Q000601:surgery*; D008297:Male; D058958:Organs at Risk / Q000000981:diagnostic imaging; D056888:Patient Positioning / Q000379:methods; D016634:Radiosurgery / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D061106:Radiotherapy Setup Errors / Q000517:prevention & control*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods* / Q000592:standards; D012189:Retrospective Studies; D013997:Time Factors; D014057:Tomography, X-Ray Computed; D047368:Tumor Burden