A daily end-to-end quality assurance workflow for MR-guided online adaptive radiation therapy on MR-Linac. J Appl Clin Med Phys 2020 Jan;21(1):205-212
Date
12/05/2019Pubmed ID
31799753Pubmed Central ID
PMC6964761DOI
10.1002/acm2.12786Scopus ID
2-s2.0-85076117374 (requires institutional sign-in at Scopus site) 22 CitationsAbstract
PURPOSE: Magnetic Resonance (MR)-guided online adaptive radiation therapy (MRgOART), enabled with MR-Linac, has potential to revolutionize radiation therapy. MRgOART is a complex process. This work is to introduce a comprehensive end-to-end quality assurance (QA) workflow in routine clinic for MRgOART with a high-magnetic-field MR-Linac.
MATERIALS AND METHOD: The major components in MRgOART with a high-magnetic field MR-Linac (Unity, Elekta) include: (1) a patient record and verification (R&V) system (e.g., Mosaiq, Elekta), (2) a treatment session manager, (3) an offline treatment planning system (TPS), (4) an online adaptive TPS, (5) a 1.5T MRI scanner, (6) an 7MV Linac, (7) an MV imaging controller (MVIC), and (8) ArtQA: software for plan data consistency checking and secondary dose calculation. Our end-to-end QA workflow was designed to test the performance and connectivity of all these components by transferring, adapting and delivering a specifically designed five-beam plan on a phantom. Beams 1-4 were designed to check Multi-Leaves Collimator (MLC) position shift based on rigid image registration in TPS, while beam 5 was used to check daily radiation output based on image pixel factor of MV image of the field. The workflow is initiated in the R&V system and followed by acquiring and registering daily MRI of the phantom, checking isocenter shift, performing online adaptive replanning, checking plan integrity and secondary 3D dose calculation, delivering the plan while acquiring MV imaging using MVIC, acquiring real-time images of the phantom, and checking the delivering parameters with ArtQA.
RESULTS: It takes 10 min to finish the entire end-to-end QA workflow. The workflow has detected communication problems, permitted resolution prior to setting up patients for MRgOART. Up to 0.9 mm discrepancies in isocenter shift based on the image registration were detected. ArtQA performed the secondary 3D dose calculation, verified the plan integrity as well as the MR-MV isocenter alignment values in TPS. The MLC shapes of beam 1-4 in all adaptive plans were conformal to the target and agreed with MV images. The variation of daily output was within ±2.0%.
CONCLUSIONS: The comprehensive end-to-end QA workflow can efficiently check the performance and communication between different components in MRgOART and has been successfully implemented for daily clinical practice.
Author List
Chen X, Ahunbay E, Paulson ES, Chen G, Li XAAuthors
Ergun Ahunbay PhD Professor in the Radiation Oncology department at Medical College of WisconsinGuang-Pei Chen PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin
Eric Paulson PhD Chief, Professor in the Radiation Oncology department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
HumansImage Processing, Computer-Assisted
Magnetic Resonance Imaging
Neoplasms
Particle Accelerators
Phantoms, Imaging
Quality Assurance, Health Care
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted
Software
Workflow
