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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

K. Kopriva, Z. Chen, M. Mates, F. Holy, B. Stekla, M. Vesela, J. Pudil, M. Chval, A. Wahle, M. Sonka, T. Kovarnik

. 2024 ; 79 (2) : 206-214. [pub] 20240311

Jazyk angličtina Země Anglie, Velká Británie

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc24014448

BACKGROUND: 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: We aimed to assess the ability of detailed OCT analysis to identify coronary lipids, using NIRS as the reference method. METHODS: 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 (maxLCBI4mm) was assessed. OCT analysis was performed using a semi-automated method including measurement of the fibrous cap thickness (FCT) of all detected fibroatheromas. Subsequent quantitative volumetric evaluation furnished FCT, FC surface area (FC SA), lipid arc, and FC (fibrous cap) volume data. OCT features of lipid plaques were compared with maxLCBI4mm. Predictors of maxLCBI4mm >400 was assessed by using univariable and multivariable analysis. RESULTS: OCT features (mean FCT, total FC SA, FC volume, maximal, mean, and total lipid arcs) strongly correlated with the maxLCBI4mm (p = 0.012 for the mean FCT, respectively p < 0.001 for all other aforementioned features). The strongest predictors of maxLCBI4mm >400 were the maximal (p = 0.002) and mean (p = 0.002) lipid arc, and total FC SA (p = 0.012). CONCLUSIONS: 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.

Citace poskytuje Crossref.org

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$a BACKGROUND: Lipid-rich plaque covered by a thin fibrous cap (FC) has been identified as a frequent morphological substrate for the development of acute coronary syndrome. Optical coherence tomography (OCT) permits the identification and measurement of the FC. Near-infrared spectroscopy (NIRS) has been approved for detection of coronary lipids. AIMS: We aimed to assess the ability of detailed OCT analysis to identify coronary lipids, using NIRS as the reference method. METHODS: In total, 40 patients with acute coronary syndrome underwent imaging of a non-culprit lesion by both NIRS and OCT. For each segment, the NIRS-derived 4 mm segment with maximal lipid core burden index (maxLCBI4mm) was assessed. OCT analysis was performed using a semi-automated method including measurement of the fibrous cap thickness (FCT) of all detected fibroatheromas. Subsequent quantitative volumetric evaluation furnished FCT, FC surface area (FC SA), lipid arc, and FC (fibrous cap) volume data. OCT features of lipid plaques were compared with maxLCBI4mm. Predictors of maxLCBI4mm >400 was assessed by using univariable and multivariable analysis. RESULTS: OCT features (mean FCT, total FC SA, FC volume, maximal, mean, and total lipid arcs) strongly correlated with the maxLCBI4mm (p = 0.012 for the mean FCT, respectively p < 0.001 for all other aforementioned features). The strongest predictors of maxLCBI4mm >400 were the maximal (p = 0.002) and mean (p = 0.002) lipid arc, and total FC SA (p = 0.012). CONCLUSIONS: We found a strong correlation between the OCT-derived features and NIRS findings. Detailed OCT analysis may be reliably used for detection of the presence of coronary lipids.
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$a Chen, Zhi $u Department of Electrical & Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, USA
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$a Mates, Martin $u Department of Cardiology, Na Homolce Hospital, Prague, Czech Republic
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$a Holy, Frantisek $u Department of Cardiology, Na Homolce Hospital, Prague, Czech Republic
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$a Stekla, Barbora $u 2nd Department of Internal Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic
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$a Vesela, Michaela $u 2nd Department of Internal Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic
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$a Pudil, Jan $u 2nd Department of Internal Medicine - Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic
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$a Chval, Martin $u Institute for Research and Development of Education, Charles University in Prague, Prague, Czech Republic
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$a Wahle, Andreas $u Department of Electrical & Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, USA
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$a Sonka, Milan $u Department of Electrical & Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, USA
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$a Kovarnik, Tomas $u 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
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