Comparison of quantitative and qualitative scoring approaches for radiation-induced pulmonary fibrosis as applied to a preliminary investigation into the efficacy of mesenchymal stem cell delivery methods in a rat model
Bibliographic record
Abstract
Objectives: Compare a quantitative, algorithm-driven, and qualitative, pathologist-driven, scoring of radiation-induced pulmonary fibrosis (RIPF). And using these scoring models to derive preliminary comparisons on the effects of different mesenchymal stem cell (MSC) administration modalities in reducing RIPF. Methods 25 rats were randomized into 5 groups: non-irradiated control (CG), irradiated control (CR), intraperitoneally administered granulocyte-macrophage colony stimulating factor or GM-CSF (Drug), intravascularly administered MSC (IV), and intratracheally administered MSC (IT). All groups, except CG, received an 18 Gy conformal dose to the right lung. Drug, IV and IT groups were treated immediately after irradiation. After 24 weeks of observation, rats were euthanized, their lungs excised, fixed and stained with Masson’s Trichrome. Samples were anonymized and RIPF was scored qualitatively by a certified pathologist and quantitatively using ImageScope. An analysis of association was conducted, and two binary classifiers trained to validate the integrity of both qualitative and quantitative scoring. Differences between the treatment groups, as assessed by the pathologist score, were then tested by variance component analysis and mixed models for differences in RIPF outcomes. Results: There is agreement between qualitative and quantitative scoring for RIPF grades from 4 to 7. Both classifiers performed similarly on the testing set (AUC = 0.923) indicating accordance between the qualitative and quantitative scoring. For comparisons between MSC infusion modalities, the Drug group had better outcomes (mean pathologist scoring of 3.96), correlating with significantly better RIPF outcomes than IV [lower by 0.97, p = 0.047, 95% CI = (0.013, 1.918)] and resulting in an improvement over CR [lower by 0.93, p = 0.037, 95% CI = (0.062, 1.800]. Conclusion: Quantitative image analysis may help in the assessment of therapeutic interventions for RIPF and can serve as a scoring surrogate in differentiating between severe and mild cases of RIPF. Preliminary data demonstrate that the use of GM-CSF was best correlated with lower RIPF severity. Advances in knowledge Quantitative image analysis can be a viable supplemental system of quality control and triaging in situations where pathologist work hours or resources are limited. The use of different MSC administration methods can result in different degrees of MSC efficacy and study outcomes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".