Diagnosis of vulnerable atherosclerotic plaques by time-resolved fluorescence spectroscopy and ultrasound imaging.

J. A. Jo, Q. Fang, T. Papaioannou, J. H. Qiao, M. C. Fishbein, B. Beseth, A. H. Dorafshar, T. Reil, D. Baker, J. Freischlag, K. K. Shung, L. Sun, L. Marcu

Research output: Contribution to journalArticle

Abstract

In this study, time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) and ultrasonography were applied to detect vulnerable (high-risk) atherosclerotic plaque. A total of 813 TR-LIFS measurements were taken from carotid plaques of 65 patients, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified by histopathology as thin, fibrotic, calcified, low-inflamed, inflamed and necrotic lesions. Spectral and time-resolved parameters (normalized intensity values and Laguerre expansion coefficients) were extracted from the TR-LIFS data. Feature selection for classification was performed by either analysis of variance (ANOVA) or principal component analysis (PCA). A stepwise linear discriminant analysis algorithm was developed for detecting inflamed and necrotic lesion, representing the most vulnerable plaques. These vulnerable plaques were detected with high sensitivity (>80%) and specificity (>90%). Ultrasound (US) imaging was obtained in 4 carotid plaques in addition to TR-LIFS examination. Preliminary results indicate that US provides important structural information of the plaques that could be combined with the compositional information obtained by TR-LIFS, to obtain a more accurate diagnosis of vulnerable atherosclerotic plaque.

Original languageEnglish (US)
Pages (from-to)2663-2666
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
StatePublished - 2006
Externally publishedYes

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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