Using Optical Coherence Tomography to Identify Lipid and Its Impact on Interventions and Clinical Events - A Scoping Review.


Journal

Circulation journal : official journal of the Japanese Circulation Society
ISSN: 1347-4820
Titre abrégé: Circ J
Pays: Japan
ID NLM: 101137683

Informations de publication

Date de publication:
25 10 2021
Historique:
pubmed: 27 7 2021
medline: 14 4 2022
entrez: 26 7 2021
Statut: ppublish

Résumé

Optical coherence tomographic (OCT) imaging has enabled identification of lipid, with increasing interest in how it may affect coronary interventions and clinical outcomes. This review summarizes the available evidence around OCT identification of lipid and its effect on interventions, clinical events, and the natural history of coronary disease.Methods and Results:We conducted a scoping review using the Medline, HealthStar, and Embase databases for articles published between 1996 and 2021. We screened 1,194 articles and identified 51 for inclusion in this study, summarizing the key findings. The literature supports a common OCT definition of lipid as low-signal regions with diffuse borders, validated against histology and other imaging modalities with acceptable intra- and inter-rater reliability. There is evidence that OCT-identified lipid at the site of stent implantation increases the risk of edge dissection, incomplete stent apposition, in-stent tissue protrusion, decreased coronary flow after stenting, side branch occlusion, and post-procedural cardiac biomarker increases. In mostly retrospective studies, lipid indices measured at non-stented sites are associated with plaque progression and the development of recurrent ischemic events. There is extensive literature supporting the ability of OCT to identify lipid and demonstrating a substantial impact of lipid on percutaneous coronary intervention outcomes. Future work to prospectively evaluate the effect of the characteristics of lipid-rich plaques on long-term clinical outcomes is needed.

Sections du résumé

BACKGROUND
Optical coherence tomographic (OCT) imaging has enabled identification of lipid, with increasing interest in how it may affect coronary interventions and clinical outcomes. This review summarizes the available evidence around OCT identification of lipid and its effect on interventions, clinical events, and the natural history of coronary disease.Methods and Results:We conducted a scoping review using the Medline, HealthStar, and Embase databases for articles published between 1996 and 2021. We screened 1,194 articles and identified 51 for inclusion in this study, summarizing the key findings. The literature supports a common OCT definition of lipid as low-signal regions with diffuse borders, validated against histology and other imaging modalities with acceptable intra- and inter-rater reliability. There is evidence that OCT-identified lipid at the site of stent implantation increases the risk of edge dissection, incomplete stent apposition, in-stent tissue protrusion, decreased coronary flow after stenting, side branch occlusion, and post-procedural cardiac biomarker increases. In mostly retrospective studies, lipid indices measured at non-stented sites are associated with plaque progression and the development of recurrent ischemic events.
CONCLUSIONS
There is extensive literature supporting the ability of OCT to identify lipid and demonstrating a substantial impact of lipid on percutaneous coronary intervention outcomes. Future work to prospectively evaluate the effect of the characteristics of lipid-rich plaques on long-term clinical outcomes is needed.

Identifiants

pubmed: 34305071
doi: 10.1253/circj.CJ-21-0377
doi:

Substances chimiques

Lipids 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

2053-2062

Auteurs

Matthew Sibbald (M)

Department of Medicine, McMaster University.

Natalia Pinilla-Echeverri (N)

Department of Medicine, McMaster University.

Mognee Alameer (M)

Department of Medicine, McMaster University.

Jorge Chavarria (J)

Department of Medicine, McMaster University.

Gustavo Dutra (G)

Department of Medicine, McMaster University.

Tej Sheth (T)

Department of Medicine, McMaster University.
Population Health Research Institute, McMaster University.

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