Open Access
19 September 2017 Facilitating in vivo tumor localization by principal component analysis based on dynamic fluorescence molecular imaging
Yang Gao, Maomao Chen, Junyu Wu, Yuan Zhou, Chuangjian Cai, Daliang Wang, Jianwen Luo
Author Affiliations +
Abstract
Fluorescence molecular imaging has been used to target tumors in mice with xenograft tumors. However, tumor imaging is largely distorted by the aggregation of fluorescent probes in the liver. A principal component analysis (PCA)-based strategy was applied on the in vivo dynamic fluorescence imaging results of three mice with xenograft tumors to facilitate tumor imaging, with the help of a tumor-specific fluorescent probe. Tumor-relevant features were extracted from the original images by PCA and represented by the principal component (PC) maps. The second principal component (PC2) map represented the tumor-related features, and the first principal component (PC1) map retained the original pharmacokinetic profiles, especially of the liver. The distribution patterns of the PC2 map of the tumor-bearing mice were in good agreement with the actual tumor location. The tumor-to-liver ratio and contrast-to-noise ratio were significantly higher on the PC2 map than on the original images, thus distinguishing the tumor from its nearby fluorescence noise of liver. The results suggest that the PC2 map could serve as a bioimaging marker to facilitate in vivo tumor localization, and dynamic fluorescence molecular imaging with PCA could be a valuable tool for future studies of in vivo tumor metabolism and progression.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 1083-3668/2017/$25.00 © 2017 SPIE
Yang Gao, Maomao Chen, Junyu Wu, Yuan Zhou, Chuangjian Cai, Daliang Wang, and Jianwen Luo "Facilitating in vivo tumor localization by principal component analysis based on dynamic fluorescence molecular imaging," Journal of Biomedical Optics 22(9), 096010 (19 September 2017). https://doi.org/10.1117/1.JBO.22.9.096010
Received: 24 June 2017; Accepted: 29 August 2017; Published: 19 September 2017
Lens.org Logo
CITATIONS
Cited by 5 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Tumors

Luminescence

Liver

Principal component analysis

In vivo imaging

Molecular imaging

Feature extraction

Back to Top