Hybrid intravascular ultrasound and optical coherence tomography catheter for imaging of coronary atherosclerosis
Bibliographic record
Abstract
OBJECTIVE: To demonstrate the feasibility of imaging human coronary atherosclerosis using a novel hybrid intravascular ultrasound (IVUS) and optical coherence tomography (OCT) imaging catheter. BACKGROUND: IVUS and OCT have synergistic advantages and recent studies involving both modalities suggest the use of a hybrid imaging catheter may offer improved guidance of coronary interventions and plaque characterization. METHODS: A 1.3 m custom hybrid IVUS-OCT imaging probe was built within a 4F catheter using a 42 MHz ultrasound transducer and an OCT imaging fiber. Coplanar images were simultaneously acquired ex vivo by both modalities in 31 arterial segments from 11 cadaveric human coronaries. IVUS and OCT images were acquired at 250 μm intervals, of which 13 of the arterial segments were selected as representative of a diverse set of pathological findings. The selected segments were then imaged with either digital X-ray or micro-CT, processed for histological analysis and compared with the corresponding IVUS and OCT images. RESULTS: Images of human coronary atherosclerosis using the hybrid IVUS-OCT catheter demonstrated a range of vascular pathologies that were confirmed on histology. The anticipated synergistic advantages of each modality were qualitatively apparent, including the deeper tissue penetration of IVUS and the superior contrast, resolution and near-field image quality of OCT. CONCLUSIONS: Preliminary ex vivo images using a hybrid IVUS-OCT catheter demonstrated feasibility in using the device for intracoronary imaging of atherosclerosis. Future studies will include in vivo imaging and larger samples sizes to enable quantitative comparisons of tissue characterization and feature identification using hybrid imaging catheters versus standalone IVUS and OCT imaging techniques. © 2012 Wiley Periodicals, Inc.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".