Noninvasive Fractional Flow Reserve Derived From Computed Tomography Angiography for Coronary Lesions of Intermediate Stenosis Severity
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Bibliographic record
Abstract
BACKGROUND: Fractional flow reserve derived from computed tomography angiography (FFRCT) is a noninvasive method for diagnosis of ischemic coronary lesions. To date, the diagnostic performance of FFRCT for lesions of intermediate stenosis severity remains unexamined. METHODS AND RESULTS: Among 407 vessels from 252 patients at 17 centers who underwent CT, FFRCT, invasive coronary angiography, and invasive FFR, we identified 150 vessels of intermediate stenosis by CT, defined as 30% to 69% stenosis. FFRCT, FFR, and CT were interpreted in blinded fashion by independent core laboratories. FFRCT and FFR ≤0.80 were considered hemodynamically significant, whereas CT stenosis ≥50% was considered obstructive. Diagnostic performance of FFRCT versus CT was assessed for accuracy, sensitivity, specificity, positive predictive values, and negative predictive values. Area under the receiver operating characteristic curve and net reclassification improvement were evaluated. For lesions of intermediate stenosis severity, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of FFRCT were 71%, 74%, 67%, 41%, and 90%, whereas accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CT stenosis were 63%, 34%, 72%, 27%, and 78%. FFRCT demonstrated superior discrimination compared with CT stenosis on per-patient (area under the receiver operating characteristic curve, 0.81 versus 0.50; P=0.0001) and per-vessel basis (area under the receiver operating characteristic curve, 0.79 versus 0.53; P<0.0001). FFRCT demonstrated significant reclassification of CT stenosis for lesion-specific ischemia (net reclassification improvement, 0.45; 95% confidence interval, 0.25-0.65; P=0.01). CONCLUSIONS: FFRCT possesses high diagnostic performance for diagnosis of ischemic for lesions of intermediate stenosis severity. Notably, the high sensitivity and negative predictive value suggest the ability of FFRCT to effectively rule out intermediate lesions that cause ischemia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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 it