The accuracy of detailed analysis of optical coherence tomography in detection of plaque lipid content: dual-imaging study with optical coherence tomography and near-infrared spectroscopy.

Coronary artery disease lipid-rich plaque near-infrared spectroscopy optical coherence tomography

Journal

Acta cardiologica
ISSN: 1784-973X
Titre abrégé: Acta Cardiol
Pays: England
ID NLM: 0370570

Informations de publication

Date de publication:
11 Mar 2024
Historique:
medline: 11 3 2024
pubmed: 11 3 2024
entrez: 11 3 2024
Statut: aheadofprint

Résumé

Lipid-rich plaque covered by a thin fibrous cap (FC) has been identified as a frequent morphological substrate for the development of acute coronary syndrome. Optical coherence tomography (OCT) permits the identification and measurement of the FC. Near-infrared spectroscopy (NIRS) has been approved for detection of coronary lipids. We aimed to assess the ability of detailed OCT analysis to identify coronary lipids, using NIRS as the reference method. In total, 40 patients with acute coronary syndrome underwent imaging of a non-culprit lesion by both NIRS and OCT. For each segment, the NIRS-derived 4 mm segment with maximal lipid core burden index (maxLCBI OCT features (mean FCT, total FC SA, FC volume, maximal, mean, and total lipid arcs) strongly correlated with the maxLCBI We found a strong correlation between the OCT-derived features and NIRS findings. Detailed OCT analysis may be reliably used for detection of the presence of coronary lipids.

Sections du résumé

BACKGROUND UNASSIGNED
Lipid-rich plaque covered by a thin fibrous cap (FC) has been identified as a frequent morphological substrate for the development of acute coronary syndrome. Optical coherence tomography (OCT) permits the identification and measurement of the FC. Near-infrared spectroscopy (NIRS) has been approved for detection of coronary lipids.
AIMS UNASSIGNED
We aimed to assess the ability of detailed OCT analysis to identify coronary lipids, using NIRS as the reference method.
METHODS UNASSIGNED
In total, 40 patients with acute coronary syndrome underwent imaging of a non-culprit lesion by both NIRS and OCT. For each segment, the NIRS-derived 4 mm segment with maximal lipid core burden index (maxLCBI
RESULTS UNASSIGNED
OCT features (mean FCT, total FC SA, FC volume, maximal, mean, and total lipid arcs) strongly correlated with the maxLCBI
CONCLUSIONS UNASSIGNED
We found a strong correlation between the OCT-derived features and NIRS findings. Detailed OCT analysis may be reliably used for detection of the presence of coronary lipids.

Identifiants

pubmed: 38465606
doi: 10.1080/00015385.2024.2324214
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-9

Auteurs

Karel Kopriva (K)

Department of Cardiology, Na Homolce Hospital, Prague, Czech Republic.
2nd Department of Internal Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic.

Zhi Chen (Z)

Department of Electrical & Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, USA.

Martin Mates (M)

Department of Cardiology, Na Homolce Hospital, Prague, Czech Republic.

Frantisek Holy (F)

Department of Cardiology, Na Homolce Hospital, Prague, Czech Republic.

Barbora Stekla (B)

2nd Department of Internal Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic.

Michaela Vesela (M)

2nd Department of Internal Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic.

Jan Pudil (J)

2nd Department of Internal Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic.

Martin Chval (M)

Institute for Research and Development of Education, Charles University in Prague, Prague, Czech Republic.

Andreas Wahle (A)

Department of Electrical & Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, USA.

Milan Sonka (M)

Department of Electrical & Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, USA.

Tomas Kovarnik (T)

2nd Department of Internal Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic.

Classifications MeSH