Validation of videodensitometric myocardial perfusion assessment
Bibliographic record
Abstract
Introduction.Invasive methods for assessment of coronary microcirculatory function are time-and instrumentation-consuming tools.Recently, novel computer-assisted videodensitometric methods have been demonstrated to provide quantitative information on myocardial (re)perfusion.The aim of the present prospective study was to evaluate the accuracy of videodensitometry-derived perfusion parameters in patients with stable angina undergoing elective coronary angiography.Methods.The study comprised 13 patients with borderline epicardial coronary artery stenosis (40-70%).Coronary flow reserve and index of microcirculatory resistance were measured by using an intracoronary pressure and temperature sensor-tipped guidewire.A videodensitometric quantitative parameter of myocardial perfusion was calculated by the ratio of maximal density (G max ) and the time to reach maximum density (T max ) of the time-density curves in regions of interest on conventional coronary angiograms.Myocardium perfusion reserve was calculated as a ratio of hyperemic and baseline G max /T max .Results.At hyperemia a significant increase in G max /T max could be observed (p <0.0001).Significant correlations were found between myocardium perfusion reserve and coronary flow reserve (r =0.82, p =0.0008) and between hyperemic G max /T max and hyperemic index of microcirculatory resistance (r =-0.72, p =0.0058).Conclusions.Videodensitometric G max /T max assessment seems to be a promising method to assess the myocardial microcirculatory state.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".