Cancer radiotherapy based on femtosecond IR laser-beam filamentation yielding ultra-high dose rates and zero entrance dose
Bibliographic record
Abstract
Since the invention of cancer radiotherapy, its primary goal has been to maximize lethal radiation doses to the tumor volume while keeping the dose to surrounding healthy tissues at zero. Sadly, conventional radiation sources (γ or X rays, electrons) used for decades, including multiple or modulated beams, inevitably deposit the majority of their dose in front or behind the tumor, thus damaging healthy tissue and causing secondary cancers years after treatment. Even the most recent pioneering advances in costly proton or carbon ion therapies can not completely avoid dose buildup in front of the tumor volume. Here we show that this ultimate goal of radiotherapy is yet within our reach: Using intense ultra-short infrared laser pulses we can now deposit a very large energy dose at unprecedented microscopic dose rates (up to 10(11) Gy/s) deep inside an adjustable, well-controlled macroscopic volume, without any dose deposit in front or behind the target volume. Our infrared laser pulses produce high density avalanches of low energy electrons via laser filamentation, a phenomenon that results in a spatial energy density and temporal dose rate that both exceed by orders of magnitude any values previously reported even for the most intense clinical radiotherapy systems. Moreover, we show that (i) the type of final damage and its mechanisms in aqueous media, at the molecular and biomolecular level, is comparable to that of conventional ionizing radiation, and (ii) at the tumor tissue level in an animal cancer model, the laser irradiation method shows clear therapeutic benefits.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".