AAPM task group 317 report: A joint AAPM and ESTRO report on brachytherapy catheter, needle, and applicator tracking technology
Bibliographic record
Abstract
In recent years, various tracking technologies that work independently of imaging systems have been proposed to automate, simplify, and enhance various tasks in the brachytherapy treatment workflow. These tasks, critical to the overall accuracy of the therapeutic dose delivery, include applicator, catheter and needle insertion guidance, and reconstruction as well as transfer tube connection in afterloading technique. Task Group 317 was established as a joint American Association of Physicists in Medicine (AAPM) and European Society for Radiotherapy and Oncology (ESTRO) committee to review: the current state-of-the-art scientific literature as it pertains to tracking technology in the field of brachytherapy; the benefits and issues related to the use of the technology for automated reconstruction of brachytherapy implants, quality control (QC) tasks such as channel path and tip reconstruction, and real-time guidance tasks; their limitations, in particular in the clinical environment and, finally, to develop recommendations related to commissioning, quality assurance (QA) and clinical use. The Task Group has looked in detail at key tracking technologies in advanced brachytherapy applications: infrared, electromagnetic, fiber optic shape sensing (fiber Bragg grating), and active radiofrequency coil tracking. For each, the performance and accuracy in well-controlled conditions as well as in clinically relevant environments are provided. Guidelines for clinical implementations, including target accuracy and performance needed for critical tasks, are summarized. Risk-based analysis is discussed in the context of an electromagnetic-based tracking system used as part of a clinical trial. The report concludes with the essential elements of an effective quality management program dedicated to the advanced features enabled by the above-described technology.
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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 | 0.040 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.017 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.035 |
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".