Unmixing multi-spectral photoacoustic sources in human carotid plaques using non-negative independent component analysis.

ABSTRACT: Multi-spectral photoacoustic imaging (MSPAI) is promising for morphology assessment of carotid plaques; however, obtaining unique spectral characteristics of chromophores is cumbersome. We used MSPAI and non-negative independent component analysis (ICA) to unmix distinct signal sources in human carotid plaques blindly. The feasibility of the method was demonstrated on a plaque phantom with hemorrhage and cholesterol inclusions, and plaque endarterectomy samples ex vivo. Furthermore, the results were verified with histology using Masson's trichrome staining. Results showed that ICA could separate recent hemorrhages from old hemorrhages. Additionally, the signatures of cholesterol inclusion were also captured for the phantom experiment. Artifacts were successfully removed from signal

SUBMITTER: Arabul MU 

PROVIDER: S-EPMC6690666 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature