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Proceedings Paper

Endoscopic Cerenkov luminescence imaging: in vivo small animal tumor model validation
Author(s): Tianming Song; Chengpeng Bao; Zhenhua Hu; Kun Wang; Xia Liu; Jie Tian
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Paper Abstract

Background: Cerenkov luminescence imaging (CLI) provides a great potential for clinical translation of optical molecular imaging techniques through using clinical approved radiotracers. However, it is difficult to obtain the Cerenkov luminescence signal of deeper biological tissues due to the small magnitude of the signal. To efficiently acquire the weak Cerenkov luminescence, we developed an endoscopic Cerenkov luminescence imaging (ECLI) system to reduce the in vivo imaging depth with minimum invasion, and validated the system on small animal tumor models. Methods: For the ECLI system, the laparoscope was connected to a high sensitive charge-couple device (CCD) camera (DU888+, Andor, UK) by a custom made adapter. We conducted a series of in vitro and in vivo experiments by use of the system. In the in vitro experiment, the endoscopic luminescence images of the 18F-FDG with various activities in EP tubes were acquired using ECLI system, and the sensitivity was compared with conventional CLI system. In the in vivo tumor experiment, 18F-FDG with the activity of 200μCi were intravenously injected into 3 tumor mice. Then the ECLI system was used to acquire the optical images for both non-invasive and invasive conditions. Conclusion: Experimental data showed the ECLI system could detect the 18F-FDG with the activity as low as 1μCi. Furthermore, our preliminary results indicated the possibility of ECLI technique for detecting Cerenkov signals inside the tumor tissue with deeper depth and guiding the surgical operation of tumor excision. We believe that this technique can help to accelerate the clinical translation of CLI.

Paper Details

Date Published: 19 March 2015
PDF: 6 pages
Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 94172U (19 March 2015); doi: 10.1117/12.2081369
Show Author Affiliations
Tianming Song, Harbin Univ. of Science and Technology (China)
Chengpeng Bao, Harbin Univ. of Science and Technology (China)
Zhenhua Hu, Institute of Automation (China)
Kun Wang, Institute of Automation (China)
Xia Liu, Harbin Univ. of Science and Technology (China)
Jie Tian, Institute of Automation (China)

Published in SPIE Proceedings Vol. 9417:
Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Robert C. Molthen, Editor(s)

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