First <scp>in‐human</scp> evaluation of a novel intravascular ultrasound and optical coherence tomography system for intracoronary imaging
Bibliographic record
Abstract
AIMS: We evaluated the first in-human performance of a novel hybrid imaging catheter that permits simultaneous and co-registered acquisition of intravascular ultrasound (IVUS) and optical coherence tomography (OCT) images. METHODS AND RESULTS: A total of 17 patients undergoing planned percutaneous coronary intervention (PCI) were imaged between August 2018 and August 2019. Eleven patients with both pre- and post-PCI IVUS and OCT images were included in the offline image analysis. IVUS and OCT images were analyzed separately then together with co-registered images for pre-stent findings, and only separately for post-stent findings. A total of 926 frames were analyzed (218 pre-PCI, 708 post-PCI). There was substantial agreement to detect calcific plaque between co-registered IVUS-OCT and standalone IVUS (Kappa 0.72 [0.65-0.79]) and standalone OCT (Kappa 0.75 [0.68-0.81]) while standalone imaging modalities showed lower agreement to detect lipidic and fibrotic plaques compared with co-registered IVUS-OCT. There were more frames with stent underexpansion on IVUS than OCT [72 (28.7%) vs. 58 (23.1%), respectively, p = 0.039]. Detection rates of incomplete stent apposition (present on 20 OCT frames vs. 2 IVUS frames, p < 0.001) and tissue protrusion (40 vs. 27 frames, p < 0.001) were higher on OCT than IVUS. One stent edge dissection was detected in the image analysis and was seen on OCT but not IVUS. All 177 frames with image artifacts contained at least one co-registered imaging modality with interpretable diagnostic content. There were no study device-related adverse events. CONCLUSIONS: Hybrid image acquisition was safe. The availability of both IVUS and OCT changed image interpretation compared to either modality alone, suggesting a complementary role of these two techniques.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".