Spectral analysis assisted photoacoustic imaging for lipid composition differentiation

Yingchun Cao, Ayeeshik Kole, Lu Lan, Pu Wang, Jie Hui, Michael Sturek, Ji Xin Cheng

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Recent advances in atherosclerotic plaque detection have shown that not only does lipid core size and depth play important roles in plaque rupture and thrombi formation, but lipid composition, especially cholesterol deposition, is equally important in determining lesion vulnerability. Here, we demonstrate a spectral analysis assisted photoacoustic imaging approach to differentiate and map lipid compositions within an artery wall. The approach is based on the classification of spectral curves obtained from the sliding windows along time-of-flight photoacoustic signals via a numerical k-means clustering method. The evaluation result on a vessel-mimicking phantom containing cholesterol and olive oil shows accuracy and efficiency of this method, suggesting the potential to apply this approach in assessment of atherosclerotic plaques.

Original languageEnglish (US)
Pages (from-to)12-19
Number of pages8
JournalPhotoacoustics
Volume7
DOIs
StatePublished - Sep 2017

Keywords

  • Atherosclerosis
  • Lipid composition
  • Photoacoustic imaging
  • Spectral analysis
  • k-means clustering

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Spectral analysis assisted photoacoustic imaging for lipid composition differentiation'. Together they form a unique fingerprint.

  • Cite this