SU‐D‐213CD‐06: Workflow and Safety Systems of a Linac‐MR Sim‐Brachytherapy MRgRT™ Facility
Bibliographic record
Abstract
PURPOSE: To develop the operational workflow and safety systems of a magnetic resonance-guided radiotherapy system (MRgRT™), which comprises an MR scanner on rails that travels between a linac vault, MR simulation room and brachytherapy suite. METHODS: To develop a safe and streamlined clinical workflow, we conducted a comprehensive process review based on a layered approach to overall MRgRT safety that included i) facility design, (ii) workflow iii) system design and interlocks and iv) policies and procedures. We applied existing guidelines for MR and radiation safety, and employed system-level failure modes and effects analyses to design the MRgRT facility and clinical procedures. RESULTS: In the MRgRT system configuration, the MR and treatment systems are physically decoupled and used independently requiring novel administration of existing MR and radiation guidelines. A key element for the safe operation of the moving MR unit is the concept that all three rooms represent zone 4 areas (American College of Radiology guidelines). Using this concept, we applied MR guidelines to develop safe procedures for the overall suite, including screening of all persons entering the suite in zone 2 and control of ferromagnetic materials. We generated a clinical workflow that ensures expedient and safe transition between MR imaging and treatment delivery in both the linac and brachytherapy rooms. In addition, we designed emergency protocols for MRgRT, which helped drive requirements for the facility and system design, e.g., need for an accessible MR-safe stretcher. CONCLUSIONS: We designed the first comprehensive description of the MRgRT workflow, interlocking systems and safety procedures. With this layered approach to safety, we addressed critical aspects regarding safe operation and workflow for the system and provided multiple redundancies for key processes. Coupled with customized staff training, the proposed design ensures the safe operation of the MRgRT facility. This work has received research personnel support from IMRIS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".