Monitoring Tumor Lesion Progression Using Molecular Imaging

Molecular imaging allows researchers to capture a detailed image of cellular and molecular processes in vivo. When compared to ex vivo techniques, which tend to be cross-sectional and therefore destructive, such as immunohistochemistry and H&E staining, molecular imaging provides a number of advantages.

Molecular imaging facilitates the repetition of experiments on the sample as its non-destructive nature means the native environment of the target is preserved. Molecular imaging used alongside a green or red fluorescent protein (GFP or RFP), or another suitable reporter facilitates the localizing and further monitoring of molecular processes.

The use of fluorescent proteins, and other genetic reporters, allows gene targeting to take place. In addition, fluorophores can conjugate to proteins expressed downstream allowing information about a cells function and molecular constitution.

Molecular Imaging

Molecular imaging is a useful tool for therapeutic applications, one of which being the monitoring of tumors implanted in model species, such as mice, for cancer research. The growth of a tumor can be observed over time, allowing evaluation of chemotherapeutics in their ability to inhibit or reverse tumor growth.

Recent research has been conducted where, in mice, cancer cells expressing a fluorescent protein were imaged on a weekly basis with the iBox Scientia imaging system from Analytik-Jena. The iBox Scientia’s quantum efficiency camera, high specification lenses, interchangeable filter sets, and strong excitation light source, allows researchers to fluorescence image over the entire 450 nm to NIR wavelength range.

Materials and Methods

For this piece of research adult, nude female mice had direct injections of double-color cancer cells (3x106 human colon HCT-116) into their peritoneal cavity. Following growth of the tumors to 1 mm the mice underwent weekly fluorescent imaging (with RFP and GFP images taken) for a total of 6 weeks to monitor tumor cell growth.

Tumor growth inside the mice was observed via two-color channel imaging for RFP and GFP. The samples were excited using color specific excitation filters alongside Analytik-Jena’s 150W halogen BioLite™ MultiSpectral Light Source. RFP was excited using a green excitation filter (525 nm /45 nm) and GFP was excited using a blue excitation filter (475 nm/ 40 nm). An emission filter (605/50) was used to select for red fluorescence and another emission filter (535/44) used to select for green fluorescence.

All of the images were taken using a cooled, monochrome CCD camera of 4.2 MP resolution – the BioChemi 500. Following capture, the images were processed using Analytik-Jena’s VisionWorks®LS software which involved removing background fluorescence using histogram adjustments and pseudocoloration of the images following the emission specifications (RFP/GFP)

Area density data was then collected from the pseudocolored images. As shown in Figure 1, tumor size was evaluated according to the square of the pixel density for each tumor at each imaging session.

Snapshot of area density measurement of tumor mass within the abdomen of a nude mouse implanted with HCT-116 human colon cancer cells. The highlighted area is a luminescent lesion composed of GFP and RFP-expressing cells roughly 1 cm in diameter. VisionWorksLS software automatically selects for the brightest region and, with calibration, can yield quantitative information regarding light density.

Figure 1. Snapshot of area density measurement of tumor mass within the abdomen of a nude mouse implanted with HCT-116 human colon cancer cells. The highlighted area is a luminescent lesion composed of GFP and RFP-expressing cells roughly 1 cm in diameter. VisionWorksLS software automatically selects for the brightest region and, with calibration, can yield quantitative information regarding light density.

Results and Discussion

Figure one shows the growth of a single tumor over the course of weeks. The final image shows the emergence of metastasizing legions in the peritoneum, as indicated by the small areas of fluorescence.

Representative mouse highlighting the progressive increasing luminosity of an implanted lesion in the peritoneum. Each image was captured using both GFP and RFP filters and then multiplexed. The intense fluorescent signal shown in the implanted tumor is significantly brighter than the surrounding tissue. Note the formation of metastatic lesions beginning to develop distal to the site of implantation and becoming visible within the abdomen in the final slide (red arrows).

Figure 2. Representative mouse highlighting the progressive increasing luminosity of an implanted lesion in the peritoneum. Each image was captured using both GFP and RFP filters and then multiplexed. The intense fluorescent signal shown in the implanted tumor is significantly brighter than the surrounding tissue. Note the formation of metastatic lesions beginning to develop distal to the site of implantation and becoming visible within the abdomen in the final slide (red arrows).

Figure 3 shows the pooled data for tumor measurements. Monitoring the lesions over time reveals a linear increase in tumor burden, with an average maximum area density of 7.4 X 103 pixels squared.

Graphical representation of area density of tumor lesions over time of the implanted mouse population. All four mice show increase in tumor burden over time (weeks along the x-axis) as measured by light density (pixels squared X 103 along the y-axis). Each point represents a single lesion measurement or pooled area density of multiple lesions.

Figure 3. Graphical representation of area density of tumor lesions over time of the implanted mouse population. All four mice show increase in tumor burden over time (weeks along the x-axis) as measured by light density (pixels squared X 103 along the y-axis). Each point represents a single lesion measurement or pooled area density of multiple lesions.

Conclusion

In the research mentioned above the peritoneal cavity of four adult, nude female mice were injected with human colon cancer cells and then monitored over the course of weeks. Tumor growth was observed as an increase in tumor area density in all four mice, reaching a peak size following six weeks. VisionWorksLS software was used to measure the area density and therefore the increase of tumor volume.

As fluorescence imaging is non-destructive and non-invasive by nature it provides benefits over other more intrusive techniques such as immunohistochemistry. Fluoroescence imaging allows disease development to be observed by fluorophore tagging of downstream molecules, or by the transfection of a sample with a fluorescent protein, followed by real-time fluorescent imaging.

The iBox Scientia has a cooled, high-resolution CCD camera, a wide range of excitation and emission filters, high-specification optics and a powerful, direct illumination source, allowing it to provide an optimum signal to noise ratio for the fluorescence imaging of cells.

The wide range of different fluorophores and fluorescent proteins available to researchers means that the iBox Scientia can be used for many different types of life science research including oncology, immunology, and cardiovascular studies.

Analytik Jena logo

This information has been sourced, reviewed and adapted from materials provided by Analytik Jena US.

For more information on this source, please visit Analytik Jena US.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Analytik Jena US. (2019, October 31). Monitoring Tumor Lesion Progression Using Molecular Imaging. AZoM. Retrieved on November 18, 2019 from https://www.azom.com/article.aspx?ArticleID=16964.

  • MLA

    Analytik Jena US. "Monitoring Tumor Lesion Progression Using Molecular Imaging". AZoM. 18 November 2019. <https://www.azom.com/article.aspx?ArticleID=16964>.

  • Chicago

    Analytik Jena US. "Monitoring Tumor Lesion Progression Using Molecular Imaging". AZoM. https://www.azom.com/article.aspx?ArticleID=16964. (accessed November 18, 2019).

  • Harvard

    Analytik Jena US. 2019. Monitoring Tumor Lesion Progression Using Molecular Imaging. AZoM, viewed 18 November 2019, https://www.azom.com/article.aspx?ArticleID=16964.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this article?

Leave your feedback
Submit