TU‐E‐BRC‐05: First MR Images Obtained During Megavoltage Photon Irradiation From An Integrated Linac‐MR System
Bibliographic record
Abstract
Purpose: To prove whether our hybrid linac‐MR design can sufficiently decrease mutual magnetic and radio frequency (RF) interferences to produce a MR image during linac‐irradiation that has similar geometric accuracy and image contrast to an MR image obtained without linac‐irradiation. Method and Materials: A hybrid prototype has been built consisting of a 6 MV linac mounted on the open end of a bi‐planar 0.2 T permanent‐magnet MR system. Both the linac waveguide and the MR system are mounted onto a single gantry that would rotate around a subject. The permanent magnet poles (82×82 cm2) are rigidly held apart to give 27.9cm pole‐to‐pole opening with flat gradients (40 mT/m max) running under a TMX NRC console (Canada). The linac components are comprised of salvaged magnetron‐based Varian 6 MV 600C decommissioned system. The distance from linac target to MR isocentre is 80 cm. Magnetic and RF shielding calculations were performed by finite element analysis and confirmed with appropriate measurements. Faraday cage shielding, typical of all MR installations, was also provided. The testing phantom was an acrylic rectangular cube, 15.95 × 15.95 × 25.4 mm with holes of diameters 2.52 mm, 3.45 mm and 4.78 mm drilled parallel to the length (25.4 mm) of rectangular cube. The cube was immersed in a 10 mM solution of within a plastic container 22.5 mm inner diameter. The container with the cube insert were placed inside an inductively tuned solenoid RF coil with an integrated pin‐diode transmit/receive switch. Results: Images (128×128) were obtained in about 38 secs using raw gradient echo sequences. Compared to no‐radiation, MR images during linac‐radiation had no geometric distortion but slightly reduced SNR. Conclusion: Our linac‐MR design produces MR images obtained during or without linac irradiation that are sufficiently similar to implement real‐time MR‐guided radiotherapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".