Multi-modality intravascular imaging for guiding coronary intervention and assessing coronary atheroma: the Novasight Hybrid IVUS-OCT system
Bibliographic record
Abstract
Intravascular imaging has evolved alongside interventional cardiology as an adjunctive tool for assessing plaque pathology and for guiding and optimizing percutaneous coronary intervention (PCI) in challenging lesions. The two modalities which have dominated the field are intravascular ultrasound (IVUS), which relies on sound waves and optical coherence tomography (OCT), relying on light waves. These approaches however have limited efficacy in assessing plaque morphology and vulnerability that are essential for guiding PCI in complex lesions and identifying patient at risk that will benefit from emerging therapies targeting plaque evolution. These limitations are complementary and, in this context, it has been recognized and demonstrated in multi-modality studies that the concurrent use of IVUS and OCT can help overcome these deficits enabling a more complete and accurate plaque assessment. The Conavi Novasight Hybrid IVUS-OCT catheter is the first commercially available device that is capable of invasive clinical coronary assessment with simultaneously acquired and co-registered IVUS and OCT imaging. It represents a significant evolution in the field and is expected to have broad application in clinical practice and research. In this review article we present the limitations of standalone intravascular imaging techniques, summarize the data supporting the value of multimodality imaging in clinical practice and research, describe the Novasight Hybrid IVUS-OCT system and highlight the potential utility of this technology in coronary intervention and in the study of atherosclerosis.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".