Multispectral hybrid Cerenkov luminescence tomography based on the finite element SPn method.
Cerenkov luminescence tomography (CLT) is a promising tool that enables three-dimensional noninvasive in vivo detection of radiopharmaceuticals. Conventionally, multispectral information and diffusion theory were introduced to achieve whole-body tomographic reconstruction. However, the diffusion theory inevitably causes systematic error in blue bands of the electromagnetic spectrum due to high-tissue absorption, and CL has a blue-weighted broad spectrum. Therefore, it is challenging to improve the accuracy of CLT. The performance of the n -order simplified spherical harmonics approximation (SPn) in different spectra is evaluated, and a multispectral hybrid CLT based on the combination of different SPn models is proposed to handle the Cerenkov photon transport problem in complex media. The in vivo xenograft experiment shows that this approach can effectively improve the quality and accuracy of the reconstructed light source. We believe that the new reconstruction method will advance the development of CLT for more in vivo imaging applications
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging, Institute of Automation, Zhongguancun East Road No. 95, Beijing 100190, ChinabBeijing Key Laboratory of Molecular Imaging, Zhongguancun East Road No. 95, Beijing 100190, China.
Haixiao
H
Liu
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging, Institute of Automation, Zhongguancun East Road No. 95, Beijing 100190, ChinabBeijing Key Laboratory of Molecular Imaging, Zhongguancun East Road No. 95, Beijing 100190, China.
Xin
X
Yang
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging, Institute of Automation, Zhongguancun East Road No. 95, Beijing 100190, China.
Tianming
T
Song
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging, Institute of Automation, Zhongguancun East Road No. 95, Beijing 100190, China.
Chengpeng
C
Bao
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging, Institute of Automation, Zhongguancun East Road No. 95, Beijing 100190, ChinabBeijing Key Laboratory of Molecular Imaging, Zhongguancun East Road No. 95, Beijing 100190, China.
Liangliang
L
Shi
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging, Institute of Automation, Zhongguancun East Road No. 95, Beijing 100190, ChinabBeijing Key Laboratory of Molecular Imaging, Zhongguancun East Road No. 95, Beijing 100190, China.
Zhenhua
Z
Hu
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging, Institute of Automation, Zhongguancun East Road No. 95, Beijing 100190, ChinabBeijing Key Laboratory of Molecular Imaging, Zhongguancun East Road No. 95, Beijing 100190, China.
Kun
K
Wang
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging, Institute of Automation, Zhongguancun East Road No. 95, Beijing 100190, ChinabBeijing Key Laboratory of Molecular Imaging, Zhongguancun East Road No. 95, Beijing 100190, China.
Jie
J
Tian
D000465:Algorithms; D000818:Animals; D001943:Breast Neoplasms / Q000473:pathology*; D045744:Cell Line, Tumor; D020342:Finite Element Analysis; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008163:Luminescent Measurements / Q000379:methods*; D051379:Mice; D008807:Mice, Inbred BALB C; D008819:Mice, Nude; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D041622:Tomography, Optical / Q000379:methods*