Medical imaging is a powerful tool that allows for in vivo and ex vivo quantification of various endpoints which can aid in oncology research and drug discovery. With a myriad of imaging options, how do you know which method is the most appropriate for your needs? The purpose of this blog is to bring clarity to the use of several preclinical imaging modalities available.
Images are generally desired to be used as aesthetically appealing data; however, the real magic is within the pixels that make up an image. Each pixel contains a value which relates to the brightness of that pixel. These numerical values may be used to quantify the images, thus providing data far more informative than a pretty picture.
There are a number of common preclinical imaging applications that may be used to address common key questions:
Can I Quantify Tumor Burden?
Tumor burden quantification is one of the most common analyses performed. When deciding which imaging modality is best suited to a study, some considerations need to be reviewed, such as, if the model of interest is luciferase enabled or if the model is disseminated or focal. The main imaging modalities used for tumor burden quantification are Bioluminescence Imaging (BLI), Magnetic Resonance Imaging (MRI), and Computed Tomography (CT).
Bioluminescence Imaging (BLI)
BLI is the most commonly used modality as it is both economical and generates 2D images that may be used to determine either tumor progression or regression by analyzing tumor flux (photons/second). BLI is typically suggested if the model of interest is luciferase enabled and is disseminated. In this setting, BLI is an ideal methodology to quantitatively understand the in vivo efficacy of a therapeutic test agent.
Magnetic Resonance Imaging (MRI)
MRI is our second most utilized modality and delivers a stack of 2D images which are used to calculate tumor volume. Unlike BLI, MRI provides a familiar measurement, mm3, which is highly accurate and does not require the tumor cells to be modified to express luciferase. In addition, MRI provides an accurate indication of tumor location. MR imaging is typically used in orthotopic models where calipers cannot be used.
Computed Tomography (CT)
CT is useful for analyzing lung tumor models due to its high resolution and strong tissue contrast against air. This is also the clinical standard for examining lung tissue. The output is a stack of 2D images and allows for tumor volume (mm3) determination. This is the only modality that uses radiation (x-rays) for tumor burden quantification.
Can I Determine Where My Therapeutic Agent Goes Inside the Animal?
Biodistribution is another common analysis we perform. Biodistribution determines test material distribution within a subject over time. Modalities used for biodistribution are Positron Emission Tomography (PET), Single-Photon Emission Computed Tomography (SPECT), and Fluorescence Imaging or Fluorescence Molecular Tomography (FLI or FMT). MRI and CT can also be used for biodistribution but this application is not as common.
Positron Emission Tomography (PET)
PET imaging is the preferred modality for biodistribution due to its great sensitivity, accuracy of quantification, and clinical translation. The resolution is ~1.2mm and delivers 2D image stacks which can be rendered into 3D images. Results can be delivered as percent injected dose or percent injected dose per gram over time. PET imaging does require the test material to be conjugated to a positron emitting radioisotope which is not always achievable. Proteins can usually be radiolabeled without issues while some small molecules can be difficult to radiolabel. We will help clients coordinate material labeling for biodistribution studies. PET is always suggested when dynamic images are desired.
Single-Photon Emission Computed Tomography (SPECT)
SPECT imaging is similar to PET imaging but differs in the type of isotope used. Gamma emitters are used, resulting in lower sensitivity than PET but slightly better resolution. SPECT imaging also delivers 2D image stacks and can be rendered into 3D images. Results can also be delivered as percent injected dose or percent injected dose/gram over time. The ability for radioisotope conjugation typically is the limiting factor on whether PET or SPECT is used. SPECT imaging can potentially image more than one tracer at once which is an advantage over PET.
Fluorescence Imaging (FLI) and Fluorescence Molecular Tomography (FMT)
Fluorescence imaging can provide 2D (FLI) or 3D (FMT) images depending on the instrument used. FLI provides 2D images and is used typically with subcutaneous tumors. The output is radiant efficiency which is a measurement of light from the fluorophore. Some tissues other than tumors can be quantified for uptake; however, tissue differentiation is difficult in 2D images. And, greater quantification error is associated with tissues deep within the animal. FLI is a great screening tool for comparing several different compounds head to head for tumor uptake. While not the focus of this blog, it is also worth noting that FLI can be used to address certain mechanistic questions with the availability of numerous fluorescently labeled probes suitable for in vivo use.
FMT uses a stronger light (laser) than FLI to excite fluorophores deep within the animal and generates 3D images. Quantification determines picomolar amounts of material in organs of interest. FMT is similar to FLI but offers superior quantitation and the ability to analyze tissues deeper within the animal other than the tumor. FMT can also be used as a first pass for biodistribution prior to radiolabeled studies with PET or SPECT.
In vivo imaging is a powerful technology that is poised to address numerous questions relevant to the preclinical oncology drug discovery and development setting. MI Bioresearch offers a wide range of small animal, in vivo imaging services, and information beyond these common applications can found on our website here.
Please contact us today to learn more about the ways preclinical imaging can impact your drug discovery programs.
Kevin Guley was a Biomedical Engineer and senior member of the Imaging Team at MI Bioresearch since 2013. Kevin previously worked at the Biomedical Research Imaging Center at UNC-Chapel Hill as an Imaging Specialist. At UNC he focused in preclinical imaging of stroke and oncology models but was often involved in imaging applications across the biomedical field.