Using in vivo respiratory-gated micro-computed tomography imaging to monitor pulmonary side effects in 10 MV FLASH and conventional radiotherapy
Bibliographic record
Abstract
Ultra-high dose-rate radiotherapy (FLASH-RT) shows the potential to eliminate tumors while sparing healthy tissues. Current FLASH-RT preclinical animal studies either euthanize animals for histological assessment or use blood tests and cytokine assays to evaluate normal tissue complications. Assessing the progression of complications in situ in live animals with a non-invasive, high-resolution, and sensitive diagnostic method is desired. This study demonstrated using in vivo respiratory-gated micro-computed tomography (micro-CT) to characterize the progression of irradiation-induced pulmonary complications caused by conventional and FLASH-RT in free-breathing mice. Twelve healthy male C57BL/6 mice completed baseline micro-CT scans. Mice were equally separated into three groups that received different treatments targeting the lungs. Treatments administered included no irradiation, 10 MV x-ray FLASH-RT, and 10 MV conventional radiotherapy with a single fraction 15 Gy prescribed dose. Post-treatment, chest cavities of mice were imaged by noninvasive in vivo prospective respiratory-gated micro-CT at 2, 4, 6, 9, and 12 weeks. The image acquisition was triggered using the measured respiratory signal to produce images representing end expiration and peak inspiration. Lung volume and lung CT number were measured for both respiratory phases to evaluate functional residual capacity and tidal volume. Micro-CT images revealed that two mice developed pneumonitis post-treatment after receiving radiotherapy. Here we demonstrated an imaging method to characterize the progression of radiation-induced pulmonary side effects in free-breathing animals.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".