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A Daily End-To-End Quality Assurance Workflow for MRI-Guided Online Adaptive Radiation Therapy

X Chen*, E Ahunbay , E Paulson , G Chen , X Allen Li , Medical College of Wisconsin, Milwaukee, WI


(Wednesday, 7/17/2019) 8:30 AM - 9:30 AM

Room: Stars at Night Ballroom 2-3

Purpose: MR-guided online adaptive radiation therapy (MRgOART), enabled with MR-Linac, has potential to revolutionize radiation therapy. MRgOART is a complex process. This work aims to introduce a comprehensive end-to-end quality assurance (QA) workflow to ensure accurate and efficient MRgOART in routine clinic.

Methods: Major components in MRgOART with a MR-Linac include: (1) a patient R&V system, (2) a treatment session manager, (3) an offline treatment planning system (TPS), (4) an online adaptive TPS, (5) a 1.5T MRI scanner, (6) 7MV Linac, (7) an EPID, and (8) a QA software (ArtQA) for plan data consistency checking and second dose verification. Our end-to-end QA workflow tests performance and connectivity of all these components by transferring, adapting and delivering a specifically-designed five-beam plan on a phantom. Beams 1 to 4 were designed to check MLC conformity on EPID images, while beam 5 checks daily output based on image-pixel conversion on EPID. 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 dose calculation, delivering the plan while acquiring MV imaging using EPID, acquiring real-time images of the phantom, and checking the delivering parameters with ArtQA.

Results: It takes 9 minutes to finish the end-to-end workflow. The workflow has detected communication problems, permitting resolution prior to setting up patients for MRgOART. Up to 0.9 mm discrepancies in isocenter shift based on the image registration were detected. The MLC shapes of beam 1 to 4 in all adaptive plans were conformal to the target and agreed with MV images. The variation of daily output was within ±2.0%.

Conclusion: The comprehensive end-to-end QA workflow can efficiently check the performance and communication between different components in MRgOART and has been successfully implemented in daily clinical practice.


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