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Nov 1, 2013 (Vol. 33, No. 19)

Raising the Bar in Preclinical Imaging

  • Integrated Imaging Systems

    Preclinical PET scanners with an integrated microCT have substantially improved the anatomical registration of PET predominately to the skeleton, yet little progress has been made in soft tissue contrast, even with the use of a CT contrast agent.

    Integrated PET/MRI or SPECT/MRI systems offer many benefits. MRI uses no radiation, offers better soft tissue contrast, and provides molecular readouts. To date, preclinical PET imaging combined with MRI has been performed using two independent systems and a bespoke co-registration algorithm to fuse the images.

    Mediso recently commercialized the first serially produced, fully integrated, automated PET/MRI system, the nanoScan PET/MRI, and a fully integrated, automated SPECT/MRI system, the nanoScan SPECT/MRI. Single systems enable use of the same imaging technology, imaging protocol, and biomarkers for small to large subjects.

    According to Illes J. Muller, managing partner, preclinical PET/MRI and SPECT/MRI allow combination of radionuclide biomarkers with an MRI contrast agent on a routine basis, an attractive prospect for evaluating new drugs for oncology, neurology, and cardiovascular disease. Now, physiological/metabolic readouts can be combined with high-resolution, soft-tissue contrast as well as dynamic functional perfusion imaging.

    In addition, SPECT provides the ability to perform multi-isotope imaging, probing two or more molecular pathways simultaneously by detecting isotopes with different emission energies, and has no physical limits in resolution. SPECT/MRI technology is less expensive. The labeling is easier, and no on-site cyclotron is required.

    A potential major application for multimodal emission tomography combined with MRI is quantitative 3D imaging of tumor heterogeneity. To assess the spatial distribution of a given PET or SPECT biomarker within a tumor requires ultra-high resolution and high sensitivity and corrections for tumor perfusion. MRI is able to differentiate between healthy and dead tumor tissue for tumor response evaluation.

  • Expanding Companion Diagnostics

    More and more, companion diagnostics, which are widely perceived in the field as in vitro tools, are relied upon to select the right patients for a targeted therapy, or to determine if the compound has brought about a therapeutic response.

    “The companion diagnostic definition will gradually broaden to include the use of in vivo imaging agents,” said Karen Linder, Ph.D., research alliances manager at GE Healthcare. “Compounds labeled with a detectable tag such as 18F can be imaged noninvasively, and the distributions in the body can be followed over time after intravenous injection to provide a temporal three-dimensional picture of the distribution of the target in the body.”

    “At its best, in vivo molecular imaging can allow selection of the right therapeutic for the right patient at the right time,” added Dr. Linder

    In vivo imaging provides different information than in vitro diagnostics. In vitro blood tests may detect the presence of a shed antigen, circulating tumor cells, or other markers of interest, but information about the location of disease is not revealed. Location and extent of the disease affect treatment choices; use of an imaging agent that could sensitively, and specifically, identify recurrence could help determine between local or systemic therapy choices.

    Furthermore, many in vitro diagnostic assays are typically performed on biopsy samples, and detect only what is present in the small sample. Accuracy can depend highly on when, and where, the biopsy was taken.

    “For oncology applications, it is becoming more apparent that dramatic changes in tumor molecular markers can occur over time in response to clonal mutations, selective response to therapy, and the development of resistance. In vivo imaging tools that can help to demonstrate such changes are likely to be more widely appreciated as experience with such agents and clinical evidence grows,” concluded Dr. Linder.

  • High-Content Imaging Laboratories

    Click Image To Enlarge +
    These images, generated by the high-content imaging group at Hoffmann-La Roche, display HeLa cells untreated (A) and treated (B) with a toxic compound. The phenotype of the toxic compound displays effects on cell morphology and structure as well as diminished cell numbers.

    The high-content imaging (HCI) laboratory provides expert information and guidance, and performs multiple imaging functions in a timely agreed-upon manner with key investigators.

    “As an exclusive HCI laboratory, we perform the assay development, which may mean cloning and expression of cell lines specific for the project, optimize the cellular and manual or robotic operational aspects of the assay, execute the campaign, design and perform the image analysis, as well as the statistical and computational solutions for advancing the drug discovery efforts,” explained Ann F. Hoffman, principal scientist, Roche discovery technologies, and group leader, high content imaging, Hoffmann-La Roche.

    For example, in analyzing for cellular cytotoxicity, a large net of imaging assays is cast to capture possible liabilities and then suggest additional in-depth studies that can be performed. With limited compound availabilities, the use of all reagents is then resourcefully relegated over a number of queries.

    The results of all the data from the therapeutic platform panels, upon completion, are able to be put in perspective with respect to “gold standards,” known reference compounds, and historical data. This focused approach impacts the direction of compound progression and may lead to research findings not necessarily apparent.

    As a better understanding of single cells and populations grows, such as stem and tumor cell differentiation and growth development, a way to link the results of HCI knowledge with the complicated and redundant signaling pathways and cellular processes will be required.

    In the future, HCI laboratories will need to embrace and participate in the big data world that translational medicine and bioinformatics is establishing. The goal is to incorporate experimental research, preclinical HCI data, omics data, and next-generation-sequencing data for predictive analytical modeling that enables the forecasting of hypotheses and better clinical outcomes in the early stages of drug development.



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