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Real-Time 3D Scintillation Imaging Enables Rapid End-To-End Verification of Online Adaptive Replanning On MR-Linac

P Bruza1*, M Ashraf1 , J Cammin2 , B Maraghechi2 , B Pogue1 , O Green2 , (1) Dartmouth College, Hanover, NH, (2) Washington University, School of Medicine, St. Louis, MO

Presentations

(Thursday, 7/18/2019) 7:30 AM - 9:30 AM

Room: Stars at Night Ballroom 2-3

Purpose: Online adaptive replanning (OARP) in magnetic resonance guided radiotherapy offers unprecedented ability to improve beam targeting precision. The OARP workflow cannot accommodate measurement-based patient-specific quality assurance (QA). Instead, the re-optimized plans are verified against an independent Monte Carlo-based dose calculations. Due to the complexity of the re-planning process, a comprehensive end-to-end verification of software QA is pivotal. The purpose was to assess performance of volumetric scintillation imaging system for end-to-end OARP QA as a part of real-time scintillation-based 3D dosimetry solution.

Methods: A multi-target plan was delivered by ViewRay MR-linac (0.34T, 6MV FFF) to a water-based scintillator phantom (1g/L quinine sulphate, ø127x300mm). Intensified, gated CMOS camera recorded projected scintillation images through the base of the phantom at 20Hz framerate. Cumulative scintillation image served as surrogate to the projected dose distribution. First, gamma pass-rate was evaluated between the measured scintillation image and CT-based dose plan. Second, MR image of the phantom was recorded by MR-Linac and used for dose calculation with an artificially modified structure set. The adapted MR-based plan was delivered to the phantom and gamma pass-rate between scintillation image and MR-based dose image was evaluated. Finally, 3D geometrical beam volume was reconstructed from scintillation images and multi-leaf collimator position logs in order to allow 3-dimensional gamma and dose volume histogram (DVH) analysis.

Results: 2D gamma pass-rate of the measured dose distribution compared against the calculated CT-based dose was 96% at 3%/3mm criteria. The pass-rate of MR-based optimized plan dropped to 94%. The majority of non-passing pixels were found in the sub-surface area, most likely caused by an electron-return effect.

Conclusion: Scintillation images of both original and re-planned deliveries agreed with treatment planning system calculations. Scintillation surrogated dose real dose distribution and enabled high-resolution, rapid QA of online adaptive replanning, as well as a 3D DVH comparisons.

Funding Support, Disclosures, and Conflict of Interest: This work has been sponsored by NIH research grant R01EB023909. B Pogue is the president and co-founder of DoseOptics LLC. P Bruza is the principal investigator in SBIR subaward B02463 (prime award NCI R44CA199681, DoseOptics LLC). This work was not financially supported by DoseOptics.

Keywords

MRI, Image-guided Therapy, Quality Assurance

Taxonomy

IM/TH- MRI in Radiation Therapy: MRI/Linear accelerator combined Quality Assurance

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