Abstract 14608: Non-Invasive Derivation of Resting Coronary Artery Flow Directly From CT Angiography (CTA) via the Transluminal Attenuation Gradient (TAG) in Left- versus Right-Dominant Circulation
Bibliographic record
Abstract
Introduction: The TAG characterizes the dropoff in CTA contrast enhancement along the length of a vessel. It can detect functionally significant CAD without additional CTA radiation or computation. However, its relationship to flow is not established. Hypothesis: We sought to establish how TAG relates to previously-reported values of coronary flow. Materials and Methods: TAG was measured in the 3 major coronary arteries (LAD,LCX,RCA) of 42 patients (35 right- [RD], 7 left/co-dominant [LD]) with <25% stenosis imaged with single heart-beat 320-row CT. TAG was adjusted for scan kVp based on the relationship of iodine concentration vs blood HU. First, the ratio of TAG in each artery for RD vs LD arteries was compared to that of invasively-measured flow reported in n=496 patients (PREDICTION trial, Sakamoto et al, Am J Cardiol 2013;111:1420). Second, in 34 patients with CTA bolus tracking images available, the rate at which contrast was increasing at CTA (ie, HU increase/sec) was measured as a linear fit of descending aortic attenuation in the tracking images vs time to calculate flow via the following theoretical relationship we derived for TAG and flow (Figure): Q[ml/sec]~Lumen Area[cm^2]*Contrast inflow slope[HU/sec]/TAG[HU/cm]. Lumen area was determined for the arterial length used for TAG measurement. Results: TAG LD-to-RD ratios were within 2%, 6% and 30% of flow ratios in the LAD, LCX and RCA respectively (Table). LAD and LCX flow derived from TAG was within 4-16% of reported flow; RCA flow was over-/underestimated by 51%/20% in RD/LD patients, respectively (Table). Conclusion: TAG in non-stenotic coronaries is related to resting coronary flow. Knowledge of the temporal change of inflowing contrast concentration enables derivation of reasonable values of coronary flow from CTA using the TAG. This is a critical step toward obtaining the flow boundary conditions for FFR-CT techniques to non-invasively detect functionally significant CAD.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".