Multispectral Cerenkov luminescence tomography for small animal optical imaging.

Quite recently Cerenkov luminescence imaging (CLI) has been introduced as a novel pre-clinical imaging for the in vivo imaging of small animals such as mice. The CLI method is based on the detection of Cerenkov radiation (CR) generated by beta particles as they travel into the animal tissues with an energy such that Cerenkov emission condition is satisfied. This paper describes an image reconstruction method called multi spectral diffuse Cerenkov luminescence tomography (msCLT) in order to obtain 3D images from the detection of CR. The multispectral approach is based on a set of 2D planar images acquired using a number of narrow bandpass filters, and the distinctive information content at each wavelength is used in the 3D image reconstruction process. The proposed msCLT method was tested both in vitro and in vivo using 32P-ATP and all the images were acquired by using the IVIS 200 small animal optical imager (Caliper Life Sciences, Alameda USA). Source depth estimation and spatial resolution measurements were performed using a small capillary source placed between several slices of chicken breast. The theoretical Cerenkov emission spectrum and optical properties of chicken breast were used in the modelling of photon propagation. In vivo imaging was performed by injecting control nude mice with 10 MBq of 32P-ATP and the 3D tracer bio-distribution was reconstructed. Whole body MRI was acquired to provide an anatomical localization of the Cerenkov emission. The spatial resolution obtained from the msCLT reconstructed images of the capillary source showed that the FWHM is about 1.5 mm for a 6 mm depth. Co-registered MRI images showed that the Cerenkov emission regions matches fairly well with anatomical regions, such as the brain, heart and abdomen. Ex vivo imaging of the different organs such as intestine, brain, heart and ribs further confirms these findings. We conclude that in vivo 3D bio-distribution of a pure beta-minus emitting radiopharmaceutical such as 32P-ATP can be obtained using the msCLT reconstruction approach.

Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging.

A new method is described for obtaining a 3-D reconstruction of a bioluminescent light source distribution inside a living animal subject, from multispectral images of the surface light emission acquired on charge-coupled device (CCD) camera. The method uses the 3-D surface topography of the animal, which is obtained from a structured light illumination technique. The forward model of photon transport is based on the diffusion approximation in homogeneous tissue with a local planar boundary approximation for each mesh element, allowing rapid calculation of the forward Green's function kernel. Absorption and scattering properties of tissue are measured a priori as input to the algorithm. By using multispectral images, 3-D reconstructions of luminescent sources can be derived from images acquired from only a single view. As a demonstration, the reconstruction technique is applied to determine the location and brightness of a source embedded in a homogeneous phantom subject in the shape of a mouse. The technique is then evaluated with real mouse models in which calibrated sources are implanted at known locations within living tissue. Finally, reconstructions are demonstrated in a PC3M-luc (prostate tumor line) metastatic tumor model in nude mice.

Monitoring bacterial burden, inflammation and bone damage longitudinally using optical and µCT imaging in an orthopaedic implant infection in mice.

BACKGROUND: Recent advances in non-invasive optical, radiographic and µCT imaging provide an opportunity to monitor biological processes longitudinally in an anatomical context. One particularly relevant application for combining these modalities is to study orthopaedic implant infections. These infections are characterized by the formation of persistent bacterial biofilms on the implanted materials, causing inflammation, periprosthetic osteolysis, osteomyelitis, and bone damage, resulting in implant loosening and failure. METHODOLOGY/PRINCIPAL FINDINGS: An orthopaedic implant infection model was used in which a titanium Kirshner-wire was surgically placed in femurs of LysEGFP mice, which possess EGFP-fluorescent neutrophils, and a bioluminescent S. aureus strain (Xen29; 1×10(3) CFUs) was inoculated in the knee joint before closure. In vivo bioluminescent, fluorescent, X-ray and µCT imaging were performed on various postoperative days. The bacterial bioluminescent signals of the S. aureus-infected mice peaked on day 19, before decreasing to a basal level of light, which remained measurable for the entire 48 day experiment. Neutrophil EGFP-fluorescent signals of the S. aureus-infected mice were statistically greater than uninfected mice on days 2 and 5, but afterwards the signals for both groups approached background levels of detection. To visualize the three-dimensional location of the bacterial infection and neutrophil infiltration, a diffuse optical tomography reconstruction algorithm was used to co-register the bioluminescent and fluorescent signals with µCT images. To quantify the anatomical bone changes on the µCT images, the outer bone volume of the distal femurs were measured using a semi-automated contour based segmentation process. The outer bone volume increased through day 48, indicating that bone damage continued during the implant infection. CONCLUSIONS/SIGNIFICANCE: Bioluminescent and fluorescent optical imaging was combined with X-ray and µCT imaging to provide noninvasive and longitudinal measurements of the dynamic changes in bacterial burden, neutrophil recruitment and bone damage in a mouse orthopaedic implant infection model.

In-vivo fluorescence imaging with a multivariate curve resolution spectral unmixing technique.

Spectral unmixing is a useful technique in fluorescence imaging for reducing the effects of native tissue autofluorescence and separating multiple fluorescence probes. While spectral unmixing methods are well established in fluorescence microscopy, they typically rely on precharacterized in-vitro spectra for each fluorophore. However, there are unique challenges for in-vivo applications, since the tissue absorption and scattering can have a significant impact on the measured spectrum of the fluorophore, and therefore make the in-vivo spectra substantially different to that of in vitro. In this work, we introduce a spectral unmixing algorithm tailored for in-vivo optical imaging that does not rely on precharacterized spectral libraries. It is derived from a multivariate curve resolution (MCR) method, which has been widely used in studies of chemometrics and gene expression. Given multispectral images and a few straightforward constraints such as non-negativity, the algorithm automatically finds the signal distribution and the pure spectrum of each component. Signal distribution maps help separate autofluorescence from other probes in the raw images and hence provide better quantification and localization for each probe. The algorithm is demonstrated with an extensive set of in-vivo experiments using near-infrared dyes and quantum dots in both epi-illumination and transillumination geometries.