Optical projection tomography as a quantitative tool for analysis of cell morphology and density in 3D hydrogels.

Assessing cell morphology and function, as well as biomaterial performance in cell cultures, is one of the key challenges in cell biology and tissue engineering (TE) research. In TE, there is an urgent need for methods to image actual three-dimensional (3D) cell cultures and access the living cells. This is difficult using established optical microscopy techniques such as wide-field or confocal microscopy. To address the problem, we have developed a new protocol using Optical Projection Tomography (OPT) to extract quantitative and qualitative measurements from hydrogel cell cultures. Using our tools, we demonstrated the method by analyzing cell response in three different hydrogel formulations in 3D with 1.5 mm diameter samples of: gellan gum (GG), gelatin functionalized gellan gum (gelatin-GG), and Geltrex. We investigated cell morphology, density, distribution, and viability in 3D living cells. Our results showed the usability of the method to quantify the cellular responses to biomaterial environment. We observed that an elongated morphology of cells, thus good material response, in gelatin-GG and Geltrex hydrogels compared with basic GG. Our results show that OPT has a sensitivity to assess in real 3D cultures the differences of cellular responses to the properties of biomaterials supporting the cells.

Gaussian Light Model in Brightfield Optical Projection Tomography.

This study focuses on improving the reconstruction process of the brightfield optical projection tomography (OPT). OPT is often described as the optical equivalent of X-ray computed tomography, but based on visible light. The detection optics used to collect light in OPT focus on a certain distance and induce blurring in those features out of focus. However, the conventionally used inverse Radon transform assumes an absolute focus throughout the propagation axis. In this study, we model the focusing properties of the detection by coupling Gaussian beam model (GBM) with the Radon transform. The GBM enables the construction of a projection operator that includes modeling of the blurring caused by the light beam. We also introduce the concept of a stretched GBM (SGBM) in which the Gaussian beam is scaled in order to avoid the modeling errors related to the determination of the focal plane. Furthermore, a thresholding approach is used to compress memory usage. We tested the GBM and SGBM approaches using simulated and experimental data in mono- and multifocal modes. When compared with the traditionally used filtered backprojection algorithm, the iteratively computed reconstructions, including the Gaussian models GBM and SGBM, provided smoother images with higher contrast.

A mathematical model and iterative inversion for fluorescent optical projection tomography.

Solving the fluorophore distribution in a tomographic setting has been difficult because of the lack of physically meaningful and computationally applicable propagation models. This study concentrates on the direct modelling of fluorescence signals in optical projection tomography (OPT), and on the corresponding inverse problem. The reconstruction problem is solved using emission projections corresponding to a series of rotational imaging positions of the sample. Similarly to the bright field OPT bearing resemblance with the transmission x-ray computed tomography, the fluorescent mode OPT is analogous to x-ray fluorescence tomography (XFCT). As an improved direct model for the fluorescent OPT, we derive a weighted Radon transform based on the XFCT literature. Moreover, we propose a simple and fast iteration scheme for the slice-wise reconstruction of the sample. The developed methods are applied in both numerical experiments and inversion of fluorescent OPT data from a zebrafish embryo. The results demonstrate the importance of propagation modelling and our analysis provides a flexible modelling framework for fluorescent OPT that can easily be modified to adapt to different imaging setups.