Abstract 12919: Co-aligned and Inherently Co-registered Intravascular Ultrasound and Optical Coherence Tomography in a Hybrid Imaging Catheter is Feasible for Characterizing Coronary Artery Disease
Bibliographic record
Abstract
Introduction: Combined use of intravascular ultrasound (IVUS) and optical coherence tomography (OCT) demonstrates synergistic benefits, which may improve the characterization and therapeutics of coronary artery disease. However, sequential use of stand-alone catheters is impractical. Hypothesis: IVUS and OCT can be implemented in a dual-modality catheter with co-alignment of imaging beams, allowing simultaneous imaging of coronary lesions that are inherently co-registered. Methods: A 3-French rotational custom hybrid IVUS-OCT imaging catheter was built using a 40 MHz ultrasound transducer with embedded OCT imaging fiber optics, as well as co-alignment of the IVUS and OCT imaging centers. Ex-vivo intraluminal IVUS and OCT images of 70 coronary artery segments from 5 cadaveric autopsies were acquired simultaneously at 25 frames/sec with 5 mm/sec pull back. Imaging at 100 frames/sec was also briefly conducted. Thirty segments had potential pathological findings and underwent histologic slicing and hematoxylin-eosin staining at 250μm intervals. Morphological features were identified based on standard criteria for IVUS and OCT, then compared to corresponding histology findings. Results: IVUS and OCT were well co-registered based on fiduciary markings. A number of vascular pathologies were identified, including normal, fibrous, lipid-rich, calcified, and thrombus tissues. These findings were confirmed on corresponding histology. Complementary features of IVUS and OCT were also qualitatively apparent. IVUS showed deeper image depth to allow assessment of plaque size and vascular remodeling. OCT showed superior near field imaging, resolution and tissue contrast. Conclusions: We demonstrated feasibility of co-aligning IVUS and OCT, providing co-registered hybrid images that highlight the complementary advantages of both modalities. Quantitative comparison and validation of this technology is on-going.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".