Endoscopic fluorescence lifetime imaging microscopy (FLIM) images of aortic plaque: An automated classification method

Jennifer Phipps, Yinghua Sun, Nisa Hatami, Michael C. Fishbein, Amit Rajaram, Ramez Saroufeem, Laura Marcu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The objective of this study was to develop an automated algorithm which uses fluorescence lifetime imaging microscopy (FLIM) images of human aortic atherosclerotic plaque to provide quantitative and spatial information regarding compositional features related to plaque vulnerability such as collagen degradation, lipid accumulation, and macrophage infiltration. Images were acquired through a flexible fiber imaging bundle with intravascular potential at two wavelength bands optimal to recognizing markers of vulnerability: F 377: 377/55 nm and F460: 460/50 nm (center wavelength/bandwidth). A classification method implementing principal components analysis and linear discriminant analysis to correlate FLIM data sets with histopathology was validated on a training set and then used to classify a validation set of FLIM images. The output of this algorithm was a false-color image with each pixel color coded to represent the chemical composition of the sample. Surface areas occupied by elastin, collagen, and lipid components were then calculated and used to define the vulnerability of each imaged location. Four groups were defined: early lesion, stable, mildly vulnerable and extremely vulnerable. Each imaged location was categorized in one of the groups based on histopathology and classification results; sensitivities (SE) and specificities (SP) were calculated (SE %/SP %): early lesion: 95/96, stable: 71/97, mildly vulnerable: 75/94, and extremely vulnerable: 100/93. The capability of this algorithm to use FLIM images to quickly determine the chemical composition of atherosclerotic plaque, particularly related to vulnerability, further enhances the potential of this system for implementation as an intravascular diagnostic modality.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7548
DOIs
StatePublished - 2010
EventPhotonic Therapeutics and Diagnostics VI - San Francisco, CA, United States
Duration: Jan 23 2010Jan 25 2010

Other

OtherPhotonic Therapeutics and Diagnostics VI
CountryUnited States
CitySan Francisco, CA
Period1/23/101/25/10

Keywords

  • atherosclerosis
  • classification
  • endoscopy
  • FLIM

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Endoscopic fluorescence lifetime imaging microscopy (FLIM) images of aortic plaque: An automated classification method'. Together they form a unique fingerprint.

  • Cite this

    Phipps, J., Sun, Y., Hatami, N., Fishbein, M. C., Rajaram, A., Saroufeem, R., & Marcu, L. (2010). Endoscopic fluorescence lifetime imaging microscopy (FLIM) images of aortic plaque: An automated classification method. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 7548). [754839] https://doi.org/10.1117/12.842724