Purpose/Objectives Stereotactic body radiotherapy (SBRT) is increasingly used to treat oligometastatic or unresectable primary malignancy, although proximity of organs-at-risk (OAR) may limit delivery of sufficiently ablative dose. Magnetic resonance (MR)-based online-adaptive radiotherapy (ART) has potential to improve SBRT’s therapeutic ratio. This study characterizes potential advantages of online-adaptive MR-guided SBRT to treat oligometastatic disease of the non-liver abdomen and central thorax. Materials/Methods Ten patients treated with RT for unresectable primary or oligometastatic disease of the non-liver abdomen (n=5) or central thorax (n=5) underwent imaging throughout treatment on a clinical MR-IGRT system. SBRT plans were created based on tumor/OAR anatomy at initial CT simulation (PI) and simulated adaptive plans were created based on observed MR-image set tumor/OAR “anatomy-of-the-day” (PA). Each PA was planned under workflow constraints to simulate online-ART. Prescribed dose was 50Gy/5fractions with goal coverage of 95% PTV by 95% of the prescription, subject to hard OAR constraints. PI was applied to each MR dataset and compared to PA to evaluate changes in dose delivered to tumor/OARs, with dose escalation when possible. Results Hard OAR constraints were met for all PI based on anatomy from initial CT simulation, and all PA based on anatomy from each daily MR-image set. Application of the PI to anatomy-of-the-day caused OAR constraint violation in 19/30 cases. Adaptive planning increased PTV coverage in 21/30 cases, including 14 cases where hard OAR constraints were violated by the non-adaptive plan. For 9 PA cases, decreased PTV coverage was required to meet hard OAR constraints that would have been violated in a non-adaptive setting. Conclusions Online-adaptive MRI-guided SBRT may allow PTV dose escalation and/or simultaneous OAR sparing compared to non-adaptive SBRT. A prospective clinical trial is underway at our institution to evaluate clinical outcomes of this technique.

Contouring of targets and normal tissues is one of the largest sources of variability in radiation therapy treatment plans. Contours thus require a time intensive and error-prone quality assurance (QA) evaluation, limitations which also impair the facilitation of adaptive radiotherapy (ART). Here, an automated system for contour QA is developed using historical data (the 'knowledge base'). A pilot study was performed with a knowledge base derived from 9 contours each from 29 head-and-neck treatment plans. Size, shape, relative position, and other clinically-relevant metrics and heuristically derived rules are determined. Metrics are extracted from input patient data and compared against rules determined from the knowledge base; a computer-learning component allows metrics to evolve with more input data, including patient specific data for ART. Nine additional plans containing 42 unique contouring errors were analyzed. 40/42 errors were detected as were 9 false positives. The results of this study imply knowledge-based contour QA could potentially enhance the safety and effectiveness of RT treatment plans as well as increase the efficiency of the treatment planning process, reducing labor and the cost of therapy for patients.

Purpose This work describes a patient-specific dosimetry quality assurance (QA) program for intensity modulated radiation therapy (IMRT) using ViewRay, the first commercial magnetic resonance imaging guided radiation therapy device. Methods and materials The program consisted of the following components: 1) one-dimensional multipoint ionization chamber measurement using a customized 15 cm3 cubic phantom, 2) two-dimensional (2D) radiographic film measurement using a 30×30×20 cm3 phantom with multiple inserted ionization chambers, 3) quasi- three-dimensional (3D) diode array (ArcCHECK) measurement with a centrally inserted ionization chamber, 4) 2D fluence verification using machine delivery log files, and 5) 3D Monte-Carlo (MC) dose reconstruction with machine delivery files and phantom CT. Results The ionization chamber measurements agreed well with treatment planning system (TPS) computed doses in all phantom geometries where the mean difference (mean ± SD) was 0.0% ± 1.3% (n=102, range, −3.0 % to 2.9%). The film measurements also showed excellent agreement with the TPS computed 2D dose distributions where the mean passing rate using 3% relative/3 mm gamma criteria was 94.6% ± 3.4% (n=30, range, 87.4% to 100%). For ArcCHECK measurements, the mean passing rate using 3% relative/3 mm gamma criteria was 98.9% ± 1.1% (n=34, range, 95.8% to 100%). 2D fluence maps with a resolution of 1×1 mm2 showed 100% passing rates for all plan deliveries (n=34). The MC reconstructed doses to the phantom agreed well with planned 3D doses where the mean passing rate using 3% absolute/3 mm gamma criteria was 99.0% ± 1.0% (n=18, range, 97.0% to100%), demonstrating the feasibility of evaluating the QA results in the patient geometry. Conclusions We have developed a dosimetry program for ViewRay’s patient-specific IMRT QA. The methodology will be useful for other ViewRay users. The QA results presented here can assist the RT community to establish appropriate tolerance and action limits for ViewRay’s IMRT QA.

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The onboard imaging unit of the first commercial MR-IGRT system meets ACR, NEMA, and vendor specifications.