Physics and biology of ultrahigh dose-rate (FLASH) radiotherapy: a topical review
Bibliographic record
Abstract
Ultrahigh dose-rate radiotherapy (RT), or 'FLASH' therapy, has gained significant momentum following various in vivo studies published since 2014 which have demonstrated a reduction in normal tissue toxicity and similar tumor control for FLASH-RT when compared with conventional dose-rate RT. Subsequent studies have sought to investigate the potential for FLASH normal tissue protection and the literature has been since been inundated with publications on FLASH therapies. Today, FLASH-RT is considered by some as having the potential to 'revolutionize radiotherapy'. FLASH-RT is considered by some as having the potential to 'revolutionize radiotherapy'. The goal of this review article is to present the current state of this intriguing RT technique and to review existing publications on FLASH-RT in terms of its physical and biological aspects. In the physics section, the current landscape of ultrahigh dose-rate radiation delivery and dosimetry is presented. Specifically, electron, photon and proton radiation sources capable of delivering ultrahigh dose-rates along with their beam delivery parameters are thoroughly discussed. Additionally, the benefits and drawbacks of radiation detectors suitable for dosimetry in FLASH-RT are presented. The biology section comprises a summary of pioneering in vitro ultrahigh dose-rate studies performed in the 1960s and early 1970s and continues with a summary of the recent literature investigating normal and tumor tissue responses in electron, photon and proton beams. The section is concluded with possible mechanistic explanations of the FLASH normal-tissue protection effect (FLASH effect). Finally, challenges associated with clinical translation of FLASH-RT and its future prospects are critically discussed; specifically, proposed treatment machines and publications on treatment planning for FLASH-RT are reviewed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".