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Coronary plaque classification with intravascular ultrasound radiofrequency data analysis.

Abstract

BACKGROUND

Atherosclerotic plaque stability is related to histological composition. However, current diagnostic tools do not allow adequate in vivo identification and characterization of plaques. Spectral analysis of backscattered intravascular ultrasound (IVUS) data has potential for real-time in vivo plaque classification.

METHODS AND RESULTS

Eighty-eight plaques from 51 left anterior descending coronary arteries were imaged ex vivo at physiological pressure with the use of 30-MHz IVUS transducers. After IVUS imaging, the arteries were pressure-fixed and corresponding histology was collected in matched images. Regions of interest, selected from histology, were 101 fibrous, 56 fibrolipidic, 50 calcified, and 70 calcified-necrotic regions. Classification schemes for model building were computed for autoregressive and classic Fourier spectra by using 75% of the data. The remaining data were used for validation. Autoregressive classification schemes performed better than those from classic Fourier spectra with accuracies of 90.4% for fibrous, 92.8% for fibrolipidic, 90.9% for calcified, and 89.5% for calcified-necrotic regions in the training data set and 79.7%, 81.2%, 92.8%, and 85.5% in the test data, respectively. Tissue maps were reconstructed with the use of accurate predictions of plaque composition from the autoregressive classification scheme.

CONCLUSIONS

Coronary plaque composition can be predicted through the use of IVUS radiofrequency data analysis. Autoregressive classification schemes performed better than classic Fourier methods. These techniques allow real-time analysis of IVUS data, enabling in vivo plaque characterization.

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  • Authors+Show Affiliations

    ,

    Department of Biomedical Engineering, The Cleveland Clinic Foundation, OH 44195, USA.

    , , , ,

    Source

    Circulation 106:17 2002 Oct 22 pg 2200-6

    MeSH

    Algorithms
    Automation
    Coronary Artery Disease
    Coronary Vessels
    Female
    Fourier Analysis
    Humans
    Male
    Middle Aged
    Ultrasonography

    Pub Type(s)

    Comparative Study
    Journal Article
    Research Support, Non-U.S. Gov't
    Research Support, U.S. Gov't, P.H.S.

    Language

    eng

    PubMed ID

    12390948

    Citation

    Nair, Anuja, et al. "Coronary Plaque Classification With Intravascular Ultrasound Radiofrequency Data Analysis." Circulation, vol. 106, no. 17, 2002, pp. 2200-6.
    Nair A, Kuban BD, Tuzcu EM, et al. Coronary plaque classification with intravascular ultrasound radiofrequency data analysis. Circulation. 2002;106(17):2200-6.
    Nair, A., Kuban, B. D., Tuzcu, E. M., Schoenhagen, P., Nissen, S. E., & Vince, D. G. (2002). Coronary plaque classification with intravascular ultrasound radiofrequency data analysis. Circulation, 106(17), pp. 2200-6.
    Nair A, et al. Coronary Plaque Classification With Intravascular Ultrasound Radiofrequency Data Analysis. Circulation. 2002 Oct 22;106(17):2200-6. PubMed PMID: 12390948.
    * Article titles in AMA citation format should be in sentence-case
    TY - JOUR T1 - Coronary plaque classification with intravascular ultrasound radiofrequency data analysis. AU - Nair,Anuja, AU - Kuban,Barry D, AU - Tuzcu,E Murat, AU - Schoenhagen,Paul, AU - Nissen,Steven E, AU - Vince,D Geoffrey, PY - 2002/10/23/pubmed PY - 2002/11/26/medline PY - 2002/10/23/entrez SP - 2200 EP - 6 JF - Circulation JO - Circulation VL - 106 IS - 17 N2 - BACKGROUND: Atherosclerotic plaque stability is related to histological composition. However, current diagnostic tools do not allow adequate in vivo identification and characterization of plaques. Spectral analysis of backscattered intravascular ultrasound (IVUS) data has potential for real-time in vivo plaque classification. METHODS AND RESULTS: Eighty-eight plaques from 51 left anterior descending coronary arteries were imaged ex vivo at physiological pressure with the use of 30-MHz IVUS transducers. After IVUS imaging, the arteries were pressure-fixed and corresponding histology was collected in matched images. Regions of interest, selected from histology, were 101 fibrous, 56 fibrolipidic, 50 calcified, and 70 calcified-necrotic regions. Classification schemes for model building were computed for autoregressive and classic Fourier spectra by using 75% of the data. The remaining data were used for validation. Autoregressive classification schemes performed better than those from classic Fourier spectra with accuracies of 90.4% for fibrous, 92.8% for fibrolipidic, 90.9% for calcified, and 89.5% for calcified-necrotic regions in the training data set and 79.7%, 81.2%, 92.8%, and 85.5% in the test data, respectively. Tissue maps were reconstructed with the use of accurate predictions of plaque composition from the autoregressive classification scheme. CONCLUSIONS: Coronary plaque composition can be predicted through the use of IVUS radiofrequency data analysis. Autoregressive classification schemes performed better than classic Fourier methods. These techniques allow real-time analysis of IVUS data, enabling in vivo plaque characterization. SN - 1524-4539 UR - https://www.unboundmedicine.com/medline/citation/12390948/full_citation L2 - http://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=linkout&SEARCH=12390948.ui DB - PRIME DP - Unbound Medicine ER -