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Towards Online Adaptive VMAT Sequencing for Multi-Fraction Radiotherapy On the MRI-Linac

C Kontaxis*, G H Bol, J J W Lagendijk, B W Raaymakers, University Medical Center Utrecht, Utrecht, The Netherlands


(Thursday, 8/2/2018) 7:30 AM - 9:30 AM

Room: Davidson Ballroom A

Purpose: To develop a fast sequencing methodology for Volumetric Modulated Arc Therapy (VMAT) able to include anatomical deformations into the optimization procedure under the context of MRI-guided radiotherapy.

Methods: We extended the previously developed Adaptive Sequencer (ASEQ)—a fixed-beam IMRT optimizer able to account for anatomical motion during plan optimization—to support VMAT plan generation. Given an ideal dose distribution, ASEQ iteratively generates one connected arc, calculates its dose and updates the remaining dose distribution to be delivered to the patient. The generated arcs satisfy the machine specific constraints of maximum leaf/jaw travel distance and MU per control point, calculated such that ideally the gantry rotates at full speed. Prior to delivery/calculation each arc is segment-weighted, an extra optimization step which adjusts the individual segment MU to better match the prescribed dose. For a multi-fraction treatment, after a specified number of arcs has been calculated, the dose difference between the delivered and ideal dose is calculated per voxel and transferred to the input prescription of the subsequent fraction. This process continues for each fraction ensuring convergence without the need of any post-processing steps.

Results: A 35-fraction prostate treatment was simulated using two full arcs per fraction. The treatment was able to converge to the ideal dose prescription after 9 fractions, satisfying all clinical target and OAR constraints (PTV D99%: 66.8 Gy, EBV D99% 73.8 Gy, Rectum V72Gy: 3.3%, Bladder V72Gy: 2.7%). The average fraction delivery time was 2.4 minutes. Each daily plan could be generated in approximately 3 minutes.

Conclusion: We demonstrate that the proof-of-concept VMAT ASEQ pipeline is able to generate clinical plans in a fast online regime. By iteratively calculating unique segment-weighted arcs, the method converges to the original ideal dose without relying on post-processing steps, enabling plan adaptation based on the anatomical changes captured by the MRI-linac.


Treatment Planning, Image-guided Therapy, Inverse Planning


TH- External beam- photons: Adaptive replanning

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