Comparison of time- and angular-domain scatter rejection in mesoscopic optical projection tomography: a simulation study.

Optical imaging offers exquisite sensitivity and resolution for assessing biological tissue in microscopy applications; however, for samples that are greater than a few hundred microns in thickness (such as whole tissue biopsies), spatial resolution is substantially limited by the effects of light scattering. To improve resolution, time- and angular-domain methods have been developed to reject detection of highly scattered light. This work utilizes a modified version of a commonly used Monte Carlo light propagation software package (MCML) to present the first comparison of time- and angular-domain improvements in spatial resolution with respect to varying sample thickness and optical properties (absorption and scattering). Specific comparisons were made at various tissue thicknesses (1-6 mm) assuming either typical (average) soft tissue scattering properties, µs ' = 10 cm-1, or low scattering properties, µs ' = 3.4 cm-1, as measured in lymph nodes.

Design and characterization of a dead-time regime enhanced early photon projection imaging system.

Scattering of visible and near-infrared light in biological tissue reduces spatial resolution for imaging of tissues thicker than 100 µm. In this study, an optical projection imaging system is presented and characterized that exploits the dead-time characteristics typical of photon counting modules based on single photon avalanche diodes (SPADs). With this system, it is possible to attenuate the detection of more scattered late-arriving photons, such that detection of less scattered early-arriving photons can be enhanced with increased light intensity, without being impeded by the maximum count rate of the SPADs. The system has the potential to provide transmittance-based anatomical information or fluorescence-based functional information (with slight modification in the instrumentation) of biological samples with improved resolution in the mesoscopic domain (0.1-2 cm). The system design, calibration, stability, and performance were evaluated using simulation and experimental phantom studies. The proposed system allows for the detection of very-rare early-photons at a higher frequency and with a better signal-to-noise ratio. The experimental results demonstrated over a 3.4-fold improvement in the spatial resolution using early photon detection vs. conventional detection, and a 1000-fold improvement in imaging time using enhanced early detection vs. conventional early photon detection in a 4-mm thick phantom with a tissue-equivalent absorption coefficient of µa = 0.05 mm-1 and a reduced scattering coefficient of µs' = 5 mm-1.

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).

Accounting for pharmacokinetic differences in dual-tracer receptor density imaging.

Dual-tracer molecular imaging is a powerful approach to quantify receptor expression in a wide range of tissues by using an untargeted tracer to account for any nonspecific uptake of a molecular-targeted tracer. This approach has previously required the pharmacokinetics of the receptor-targeted and untargeted tracers to be identical, requiring careful selection of an ideal untargeted tracer for any given targeted tracer. In this study, methodology capable of correcting for tracer differences in arterial input functions, as well as binding-independent delivery and retention, is derived and evaluated in a mouse U251 glioma xenograft model using an Affibody tracer targeted to epidermal growth factor receptor (EGFR), a cell membrane receptor overexpressed in many cancers. Simulations demonstrated that blood, and to a lesser extent vascular-permeability, pharmacokinetic differences between targeted and untargeted tracers could be quantified by deconvolving the uptakes of the two tracers in a region of interest devoid of targeted tracer binding, and therefore corrected for, by convolving the uptake of the untargeted tracer in all regions of interest by the product of the deconvolution. Using fluorescently labeled, EGFR-targeted and untargeted Affibodies (known to have different blood clearance rates), the average tumor concentration of EGFR in four mice was estimated using dual-tracer kinetic modeling to be 3.9 ± 2.4 nM compared to an expected concentration of 2.0 ± 0.4 nM. However, with deconvolution correction a more equivalent EGFR concentration of 2.0 ± 0.4 nM was measured.

Kinetic model optimization for characterizing tumour physiology by dynamic contrast-enhanced near-infrared spectroscopy.

Dynamic contrast-enhanced (DCE) methods are widely used with magnetic resonance imaging and computed tomography to assess the vascular characteristics of tumours since these properties can affect the response to radiotherapy and chemotherapy. In contrast, there have been far fewer studies using optical-based applications despite the advantages of low cost and safety. This study investigated an appropriate kinetic model for optical applications to characterize tumour haemodynamics (blood flow, F, blood volume, V(b), and vascular heterogeneity) and vascular leakage (permeability surface-area product, PS). DCE data were acquired with two dyes, indocyanine green (ICG) and 800 CW carboxylate (IRD(cbx)), from a human colon tumour xenograph model in rats. Due to the smaller molecular weight of IRD(cbx) (1166 Da) compared to albumin-bound ICG (67 kDa), PS of IRD(cbx) was significantly larger; however, no significant differences in F and V(b) were found between the dyes as expected. Error analysis demonstrated that all parameters could be estimated with an uncertainty less than 5% due to the high temporal resolution and signal-to-noise ratio of the optical measurements. The next step is to adapt this approach to optical imaging to generate haemodynamics and permeability maps, which should enhance the clinical interest in optics for treatment monitoring.

Advantages of a dual-tracer model over reference tissue models for binding potential measurement in tumors.

The quantification of tumor molecular expression in vivo could have a significant impact for informing and monitoring emerging targeted therapies in oncology. Molecular imaging of targeted tracers can be used to quantify receptor expression in the form of a binding potential (BP) if the arterial input curve or a surrogate of it is also measured. However, the assumptions of the most common approaches (reference tissue models) may not be valid for use in tumors. In this study, the validity of reference tissue models is investigated for use in tumors experimentally and in simulations. Three different tumor lines were grown subcutaneously in athymic mice and the mice were injected with a mixture of an epidermal growth factor receptor-targeted fluorescent tracer and an untargeted fluorescent tracer. A one-compartment plasma input model demonstrated that the transport kinetics of both tracers was significantly different between tumors and all potential reference tissues, and using the reference tissue model resulted in a theoretical underestimation in BP of 50% ± 37%. On the other hand, the targeted and untargeted tracers demonstrated similar transport kinetics, allowing a dual-tracer approach to be employed to accurately estimate BP (with a theoretical error of 0.23% ± 9.07%). These findings highlight the potential for using a dual-tracer approach to quantify receptor expression in tumors with abnormal hemodynamics, possibly to inform the choice or progress of molecular cancer therapies.

A three-dimensional finite element model and image reconstruction algorithm for time-domain fluorescence imaging in highly scattering media.

In this work, development and evaluation of a three-dimensional (3D) finite element model (FEM) based on the diffusion approximation of time-domain (TD) near-infrared fluorescence light transport in biological tissue is presented. This model allows both excitation and fluorescence temporal point-spread function (TPSF) data to be generated for heterogeneous scattering and absorbing media of arbitrary geometry. The TD FEM is evaluated via comparisons with analytical and Monte Carlo (MC) calculations and is shown to provide a quantitative accuracy which has less than 0.72% error in intensity and less than 37 ps error for mean time. The use of the Born-Ratio normalized data is demonstrated to reduce data mismatch between MC and FEM to less than 0.22% for intensity and less than 22 ps in mean time. An image reconstruction framework, based on a 3D FEM formulation, is outlined and simulation results based on a heterogeneous mouse model with a source of fluorescence in the pancreas is presented. It is shown that using early photons (i.e. the photons detected within the first 200 ps of the TPSF) improves the spatial resolution compared to using continuous-wave signals. It is also demonstrated, as expected, that the utilization of two time gates (early and latest photons) can improve the accuracy both in terms of spatial resolution and recovered contrast.