Paired-agent Imaging Research Articles

Quantifying cancer cell receptors with paired-agent fluorescent imaging: a novel method to account for tissue optical property effects.

Dynamic fluorescence imaging approaches can be used to estimate the concentration of cell surface receptors in vivo. Kinetic models are used to generate the final estimation by taking the targeted imaging agent concentration as a function of time. However, tissue absorption and scattering properties cause the final readout signal to be on a different scale than the real fluorescent agent concentration. In paired-agent imaging approaches, simultaneous injection of a suitable control imaging agent with a targeted one can account for non-specific uptake and retention of the targeted agent. Additionally, the signal from the control agent can be a normalizing factor to correct for tissue optical property differences. In this study, the kinetic model used for paired-agent imaging analysis (i.e., simplified reference tissue model) is modified and tested in simulation and experimental data in a way that accounts for the scaling correction within the kinetic model fit to the data to ultimately extract an estimate of the targeted biomarker concentration.

Cranial nerve contrast using nerve-specific fluorophores improved by paired-agent imaging with indocyanine green as a control agent

Nerve preservation during surgery is critical because damage can result in significant morbidity. This remains a challenge especially for skull base surgeries where cranial nerves (CNs) are involved because visualization and access are particularly poor in that location. We present a paired-agent imaging method to enhance identification of CNs using nerve-specific fluorophores. Two myelin-targeting imaging agents were evaluated, Oxazine 4 and Rhodamine 800, and coadministered with a control agent, indocyanine green, either intravenously or topically in rats. Fluorescence imaging was performed on excised brains ex vivo, and nerve contrast was evaluated via paired-agent ratiometric data analysis. Although contrast was improved among all experimental groups using paired-agent imaging compared to conventional, solely targeted imaging, Oxazine 4 applied directly exhibited the greatest enhancement, with a minimum 3 times improvement in CNs delineation. This work highlights the importance of accounting for nonspecific signal of targeted agents, and demonstrates that paired-agent imaging is one method capable of doing so. Although staining, rinsing, and imaging protocols need to be optimized, these findings serve as a demonstration for the potential use of paired-agent imaging to improve contrast of CNs, and consequently, surgical outcome.

Generalized paired-agent kinetic model for in vivo quantification of cancer cell-surface receptors under receptor saturation conditions

New precision medicine drugs oftentimes act through binding to specific cell-surface cancer receptors, and thus their efficacy is highly dependent on the availability of those receptors and the receptor concentration per cell. Paired-agent molecular imaging can provide quantitative information on receptor status in vivo, especially in tumor tissue; however, to date, published approaches to paired-agent quantitative imaging require that only ‘trace’ levels of imaging agent exist compared to receptor concentration. This strict requirement may limit applicability, particularly in drug binding studies, which seek to report on a biological effect in response to saturating receptors with a drug moiety. To extend the regime over which paired-agent imaging may be used, this work presents a generalized simplified reference tissue model (GSRTM) for paired-agent imaging developed to approximate receptor concentration in both non-receptor-saturated and receptor-saturated conditions. Extensive simulation studies show that tumor receptor concentration estimates recovered using the GSRTM are more accurate in receptor-saturation conditions than the standard simple reference tissue model (SRTM) (% error (mean ± sd): GSRTM 0 ± 1 and SRTM 50 ± 1) and match the SRTM accuracy in non-saturated conditions (% error (mean ± sd): GSRTM 5 ± 5 and SRTM 0 ± 5). To further test the approach, GSRTM-estimated receptor concentration was compared to SRTM-estimated values extracted from tumor xenograft in vivo mouse model data. The GSRTM estimates were observed to deviate from the SRTM in tumors with low receptor saturation (which are likely in a saturated regime). Finally, a general ‘rule-of-thumb’ algorithm is presented to estimate the expected level of receptor saturation that would be achieved in a given tissue provided dose and pharmacokinetic information about the drug or imaging agent being used, and physiological information about the tissue. These studies suggest that the GSRTM is necessary when receptor saturation exceeds 20% and highlight the potential for GSRTM to accurately measure receptor concentrations under saturation conditions, such as might be required during high dose drug studies, or for imaging applications where high concentrations of imaging agent are required to optimize signal-to-noise conditions. This model can also be applied to PET and SPECT imaging studies that tend to suffer from noisier data, but require one less parameter to fit if images are converted to imaging agent concentration (quantitative PET/SPECT).