Open Access
20 June 2022 Quantitative molecular bioluminescence tomography
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Abstract

Significance: Bioluminescence imaging and tomography (BLT) are used to study biologically relevant activity, typically within a mouse model. A major limitation is that the underlying optical properties of the volume are unknown, leading to the use of a “best” estimate approach often compromising quantitative accuracy.

Aim: An optimization algorithm is presented that localizes the spatial distribution of bioluminescence by simultaneously recovering the optical properties and location of bioluminescence source from the same set of surface measurements.

Approach: Measured data, using implanted self-illuminating sources as well as an orthotopic glioblastoma mouse model, are employed to recover three-dimensional spatial distribution of the bioluminescence source using a multi-parameter optimization algorithm.

Results: The proposed algorithm is able to recover the size and location of the bioluminescence source while accounting for tissue attenuation. Localization accuracies of <1  mm are obtained in all cases, which is similar if not better than current “gold standard” methods that predict optical properties using a different imaging modality.

Conclusions: Application of this approach, using in-vivo experimental data has shown that quantitative BLT is possible without the need for any prior knowledge about optical parameters, paving the way toward quantitative molecular imaging of exogenous and indigenous biological tumor functionality.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Alexander Bentley, Xiangkun Xu, Zijian Deng, Jonathan E. Rowe, Ken Kang-Hsin Wang, and Hamid Dehghani "Quantitative molecular bioluminescence tomography," Journal of Biomedical Optics 27(6), 066004 (20 June 2022). https://doi.org/10.1117/1.JBO.27.6.066004
Received: 8 February 2022; Accepted: 27 May 2022; Published: 20 June 2022
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Bioluminescence

Optical properties

Tomography

Data modeling

3D modeling

Reconstruction algorithms

Optimization (mathematics)

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