Roadmap: medical physics technologies in brachytherapy
Bibliographic record
Abstract
Brachytherapy is a crucial modality of radiotherapy for cancer, known for its effectiveness in delivering high doses of radiation directly to tumours while sparing surrounding healthy tissues. Despite its clinical importance, recent years have witnessed a concerning decline in its utilization, which negatively impacts patient outcomes. This decline is attributed to several factors, with the inherent complexity of brachytherapy, fair reimbursement policies, and high dexterity being significant barriers. There are silver linings, however, as growing number of applications are seen in continents such as Africa, as well as advances in medical physics technology offering promising solutions to these challenges. This roadmap paper aims to provide a comprehensive overview and preview of advancements in brachytherapy, as well as strategies to address key challenges in four critical areas: 'Imaging and Image Guidance,' 'Treatment Planning,' 'Treatment Delivery,' and 'Brachytherapy Outcomes.' We anticipate that these advances will enhance therapeutic efficacy, equipping clinicians worldwide with the tools needed to deliver state-of-the-art cancer treatments and fostering a promising future in oncology care.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".