Co-registration of Bioluminescence Tomography and Anatomical Imaging Modalities for Cell Tracking and Source Quantification

BLI;BLT;Bioluminescence Tomography;Coregistration;MRI;Magnetic Resonance;Source Quantification;Multimodal Imaging;Biomedical Engineering

Chehade, MoussaBulte, Jeff W. M. ;

Johns Hopkins University

关键词: BLI;    BLT;    Bioluminescence Tomography;    Coregistration;    MRI;    Magnetic Resonance;    Source Quantification;    Multimodal Imaging;    Biomedical Engineering;   

Others  :  https://jscholarship.library.jhu.edu/bitstream/handle/1774.2/38073/CHEHADE-THESIS-2014.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: JOHNS HOPKINS DSpace Repository

【 摘 要 】

Bioluminescence tomography (BLT) is a molecular imaging tool that provides three-dimensional, quantitative reconstructions of bioluminescent sources in vivo. A main limitation of BLT to date, however, has been a lack of validation and demonstrated utility in preclinical research. An approach employing a fusion of BLT with other, well-established imaging modalities was used in this work to validate results obtained with BLT and improve the performance of source quantification. In the first chapter of this thesis, a method was developed to co-register BLT to magnetic resonance (MR) and computed tomography (CT) anatomical data for tracking cell transplants using a specialized animal holder. Using a luciferase-expressing tumor model in mice, MRI was shown to be superior at locating cells while BLT provided a more sensitive measure of cell proliferation. A multimodal approach incorporating BLT can therefore provide a better understanding of cell dynamics in vivo in preclinical research than with anatomical imaging alone. In the second chapter of this thesis, anatomical MRI and CT images were segmented to provide hard spatial priors to quantify the power of calibrated luminescent sources implanted in mice. To do this, a finite element (FEM) implementation of the diffusion approximation was used as a forward model for light propagation and validated through a phantom experiment. Source powers quantified using hard prior information showed a 65% reduction in average deviation compared to traditional BLT using four spectral bins and comparable performance to eight bins. BLI imaging times using hard spatial priors were reduced by 16-fold and 100-fold compared to the four- and eight-bin BLT methods, respectively. Together with the results of the first chapter, these results show value in incorporating data from other imaging modalities into BLT.