Reproducibility of Serial Left Ventricle Perfusion, Volume, and Ejection Fraction Measurements Using Multiplexed Multipinhole SPECT in Healthy Rats and Rats After Myocardial Infarction
Bibliographic record
Abstract
UNLABELLED: Assessment of small-animal cardiac data acquired using SPECT requires an accurate understanding of the reproducibility and the uncertainties associated with the technique. Furthermore, it is also useful to have a baseline of reference data against which to compare the outcome of a particular study. METHODS: We scanned both healthy and post-myocardial infarction rats injected with (99m)Tc-tetrofosmin in a multidetector, multipinhole small-animal SPECT scanner. In this paper, we report on the creation of a reference database of the relative myocardial blood perfusion of rats. We also evaluated the reproducibility of perfusion measurements and measurements of left ventricle volume and ejection fraction, defined as the SD of a particular measurement repeated on the same animal or over multiple animals. RESULTS: For the healthy rats, interscan reproducibility of volume measurements was 4%-7% of the total volume, and intersubject reproducibility was 9%-12% of the volume being measured. Interscan reproducibility remained unaffected after infarction (6%-8%), but intersubject reproducibility was much poorer (15%-26%). Ejection fraction in healthy animals was highly reproducible between scans and between rats: 3.1% and 3.3%, respectively. Interscan reproducibility of the postinfarction ejection fraction was 3.6%; intersubject reproducibility after infarction was 8.1%. CONCLUSION: We have created a reference database for small-animal SPECT perfusion measurements in healthy male Sprague-Dawley rats and quantified the reproducibility of perfusion and functional measurement made with small-animal SPECT in healthy and postinfarction rats.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".