Murine models of radiation cardiotoxicity: A systematic review and recommendations for future studies
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The effects of radiation on the heart are dependent on dose, fractionation, overall treatment time, and pre-existing cardiovascular pathology. Murine models have played a central role in improving our understanding of the radiation response of the heart yet a wide range of exposure parameters have been used. We evaluated the study design of published murine cardiac irradiation experiments to assess gaps in the literature and to suggest guidance for the harmonisation of future study reporting. METHODS AND MATERIALS: A systematic review of mouse/rat studies published 1981-2021 that examined the effect of radiation on the heart was performed. The protocol was published on PROSPERO (CRD42021238921) and the findings were reported in accordance with the PRISMA guidance. Risk of bias was assessed using the SYRCLE checklist. RESULTS: 159 relevant full-text original articles were reviewed. The heart only was the target volume in 67% of the studies and simulation details were unavailable for 44% studies. Dosimetry methods were reported in 31% studies. The pulmonary effects of whole and partial heart irradiation were reported in 13% studies. Seventy-eight unique dose-fractionation schedules were evaluated. Large heterogeneity was observed in the endpoints measured, and the reporting standards were highly variable. CONCLUSIONS: Current murine models of radiation cardiotoxicity cover a wide range of irradiation configurations and latency periods. There is a lack of evidence describing clinically relevant dose-fractionations, circulating biomarkers and radioprotectants. Recommendations for the consistent reporting of methods and results of in vivo cardiac irradiation studies are made to increase their suitability for informing the design of clinical studies.
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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 | 0.089 | 0.187 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.015 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".