In Vivo Intrathecal Tracer Dispersion in Cynomolgus Monkey Validates Wide Biodistribution Along Neuraxis.

OBJECTIVE: It is commonly believed that in intrathecal (IT) drug delivery, agent distribution is confined to a narrow region close to the injection site, thereby undermining the efficacy of the method. METHODS: To test the claim, multimodal in vivo imaging was used to experimentally observe the effects of IT infusion in cynomolgus monkey, looking at cerebrospinal fluid flow, anatomy, and dispersion of a radiolabeled tracer. RESULTS: At high infusion rates, the tracer reached the cervical region after only 2 h, demonstrating rapid and wide distribution. The same in vivo nonhuman primate imaging data also provided evidence in support of a computational fluid dynamic model for the prediction of drug distribution following IT injection. Tracer dispersion was predicted in two specimens matching the distribution acquired with positron emission tomography (PET). For the third specimen, tracer dispersion simulations were conducted as a blind study: predictions were made before in vivo biodistribution data was known. In all cases, the computational fluid dynamics (CFD) predictions of drug dispersion after IT administration showed close spatio-temporal agreement with tracer biodistribution in vivo. CONCLUSION: Validation by in vivo nonhuman primate data confirms our ability to predict the biodistribution of intrathecally administered agents in subject-specific models of the central nervous system from first principles. SIGNIFICANCE: The experiments reinstate IT delivery as a viable administration method when targeting molecules to the whole spine or the brain. The proposed computational methodology enables rational design of novel therapies for neurological diseases that require reliable, efficient, and safe delivery of therapeutic agents to specific target sites in the central nervous system.

Brain pharmacology of intrathecal antisense oligonucleotides revealed through multimodal imaging.

Intrathecal (IT) delivery and pharmacology of antisense oligonucleotides (ASOs) for the CNS have been successfully developed to treat spinal muscular atrophy. However, ASO pharmacokinetic (PK) and pharmacodynamic (PD) properties remain poorly understood in the IT compartment. We applied multimodal imaging techniques to elucidate the IT PK and PD of unlabeled, radioactively labeled, or fluorescently labeled ASOs targeting ubiquitously expressed or neuron-specific RNAs. Following lumbar IT bolus injection in rats, all ASOs spread rostrally along the neuraxis, adhered to meninges, and were partially cleared to peripheral lymph nodes and kidneys. Rapid association with the pia and arterial walls preceded passage of ASOs across the glia limitans, along arterial intramural basement membranes, and along white-matter axonal bundles. Several neuronal and glial cell types accumulated ASOs over time, with evidence of probable glial accumulation preceding neuronal uptake. IT doses of anti-GluR1 and anti-Gabra1 ASOs markedly reduced the mRNA and protein levels of their respective neurotransmitter receptor protein targets by 2 weeks and anti-Gabra1 ASOs also reduced binding of the GABAA receptor PET ligand 18F-flumazenil in the brain over 4 weeks. Our multimodal imaging approaches elucidate multiple transport routes underlying the CNS distribution, clearance, and efficacy of IT-dosed ASOs.

Three-Dimensional Dosimetry for Radiation Safety Estimates from Intrathecal Administration.

Intrathecal administration is of growing interest for drug delivery, and its utility is being increasingly investigated through imaging. In this work, the 3-dimensional Voxel-Based Internal Dosimetry Application (VIDA) and 4D Extended Cardiac Torso Phantom (XCAT) were extended to provide radiation safety estimates specific to intrathecal administration. Methods: The 3-dimensional VIDA dosimetry application Monte Carlo simulation was run using a modified XCAT phantom with additional and edited cerebrospinal fluid (CSF) regions to produce voxel-level absorbed dose per unit cumulated activity maps for 9 selected source regions. Simulation validation was performed to compare absorbed dose estimates for common organs in a preexisting dosimetry tool (OLINDA/EXM). Dynamic planar imaging data were acquired in 6 healthy subjects using administered volumes of 5 or 15 mL (n = 3 each) of 185 MBq of 99mTc-diethylenetriaminepentaacetic acid. Absorbed dose was estimated for each subject using the intrathecal-specific dosimetry application. Results: Simulation results were within 6% of OLINDA estimates for common organs. Absorbed dose estimates were highest (0.3-0.8 mGy/MBq) in the lumbar CSF space. A whole-body effective dose estimate of 0.003 mSv/MBq was observed. An administered volume dependency was observed with a 15-mL volume, resulting in lower absorbed dose estimates for several intrathecal and nonintrathecal regions. Conclusion: The intrathecal-specific VIDA implementation enables tailored dosimetry estimation for regions most relevant in intrathecal administration. Absorbed doses are highly localized to CSF and spinal regions and should be taken into consideration when designing intrathecal imaging studies. A potentially interesting relationship was observed between absorbed dose and administered volume, which merits further investigation.

Automated segmentation of MR imaging to determine normative central nervous system cerebrospinal fluid volumes in healthy volunteers.

An accurate non-invasive method to determine total body cerebrospinal fluid volume has a number of potential diagnostic and therapeutic applications. Herein we describe a technique for automated segmentation of total body MRI data to determine cranial and spinal CSF volume in 15 healthy adults. These in vivo estimates of CSF volume exceed the standard reported volume of 150mL in human adults and provide normative data for diagnosis of disease states such as hydrocephalus and therapy including pharmacologic dosimetry. No correlation was observed between patient height or weight and total body CSF volume.

Tomography of epidermal growth factor receptor binding to fluorescent Affibody in vivo studied with magnetic resonance guided fluorescence recovery in varying orthotopic glioma sizes.

The ability to image targeted tracer binding to epidermal growth factor receptor (EGFR) was studied in vivo in orthotopically grown glioma tumors of different sizes. The binding potential was quantified using a dual-tracer approach, which employs a fluorescently labeled peptide targeted to EGFR and a reference tracer with similar pharmacokinetic properties but no specific binding, to estimate the relative bound fraction from kinetic compartment modeling. The recovered values of binding potential did not vary significantly as a function of tumor size (1 to 33 mm3), suggesting that binding potential may be consistent in the U251 tumors regardless of size or stage after implantation. However, the fluorescence yield of the targeted fluorescent tracers in the tumor was affected significantly by tumor size, suggesting that dual-tracer imaging helps account for variations in absolute uptake, which plague single-tracer imaging techniques. Ex vivo analysis showed relatively high spatial heterogeneity in each tumor that cannot be resolved by tomographic techniques. Nonetheless, the dual-tracer tomographic technique is a powerful tool for longitudinal bulk estimation of receptor binding.

Comparison of Kinetic Models for Dual-Tracer Receptor Concentration Imaging in Tumors.

Molecular differences between cancerous and healthy tissue have become key targets for novel therapeutics specific to tumor receptors. However, cancer cell receptor expression can vary within and amongst different tumors, making strategies that can quantify receptor concentration in vivo critical for the progression of targeted therapies. Recently a dual-tracer imaging approach capable of providing quantitative measures of receptor concentration in vivo was developed. It relies on the simultaneous injection and imaging of receptor-targeted tracer and an untargeted tracer (to account for non-specific uptake of the targeted tracer). Early implementations of this approach have been structured on existing "reference tissue" imaging methods that have not been optimized for or validated in dual-tracer imaging. Using simulations and mouse tumor model experimental data, the salient findings in this study were that all widely used reference tissue kinetic models can be used for dual-tracer imaging, with the linearized simplified reference tissue model offering a good balance of accuracy and computational efficiency. Moreover, an alternate version of the full two-compartment reference tissue model can be employed accurately by assuming that the K1s of the targeted and untargeted tracers are similar to avoid assuming an instantaneous equilibrium between bound and free states (made by all other models).

Cherenkov excited phosphorescence-based pO2 estimation during multi-beam radiation therapy: phantom and simulation studies.

Megavoltage radiation beams used in External Beam Radiotherapy (EBRT) generate Cherenkov light emission in tissues and equivalent phantoms. This optical emission was utilized to excite an oxygen-sensitive phosphorescent probe, PtG4, which has been developed specifically for NIR lifetime-based sensing of the partial pressure of oxygen (pO2). Phosphorescence emission, at different time points with respect to the excitation pulse, was acquired by an intensifier-gated CCD camera synchronized with radiation pulses delivered by a medical linear accelerator. The pO2 distribution was tomographically recovered in a tissue-equivalent phantom during EBRT with multiple beams targeted from different angles at a tumor-like anomaly. The reconstructions were tested in two different phantoms that have fully oxygenated background, to compare a fully oxygenated and a fully deoxygenated inclusion. To simulate a realistic situation of EBRT, where the size and location of the tumor is well known, spatial information of a prescribed region was utilized in the recovery estimation. The phantom results show that region-averaged pO2 values were recovered successfully, differentiating aerated and deoxygenated inclusions. Finally, a simulation study was performed showing that pO2 in human brain tumors can be measured to within 15 mmHg for edge depths less than 10-20 mm using the Cherenkov Excited Phosphorescence Oxygen imaging (CEPhOx) method and PtG4 as a probe. This technique could allow non-invasive monitoring of pO2 in tumors during the normal process of EBRT, where beams are generally delivered from multiple angles or arcs during each treatment fraction.

Methodology to optimize detector geometry in fluorescence tomography of tissue using the minimized curvature of the summed diffuse sensitivity projections.

The dependence of the sensitivity function in fluorescence tomography on the geometry of the excitation source and detection locations can severely influence an imaging system's ability to recover fluorescent distributions. Here a methodology for choosing imaging configuration based on the uniformity of the sensitivity function is presented. The uniformity of detection sensitivity is correlated with reconstruction accuracy in silico, and reconstructions in a murine head model show that a detector configuration optimized using Nelder-Mead minimization improves recovery over uniformly sampled tomography.

Regularization functional semi-automated incorporation of anatomical prior information in image-guided fluorescence tomography.

The use of anatomical priors in fluorescence tomography is known to improve image quality and accuracy significantly. However, the use of prior information is often implemented by incorporating user segmented structural images into the optical reconstruction algorithm, a process requiring significant time and expertise. We propose an automated implementation which encodes the gray-scale prior image directly into the regularization term, eliminating the need for direct prior image segmentation, which is extendable to any spatially defined prior data. The proposed method is supported by in vivo studies.

Dual-tracer background subtraction approach for fluorescent molecular tomography.

Diffuse fluorescence tomography requires high contrast-to-background ratios to accurately reconstruct inclusions of interest. This is a problem when imaging the uptake of fluorescently labeled molecularly targeted tracers in tissue, which can result in high levels of heterogeneously distributed background uptake. We present a dual-tracer background subtraction approach, wherein signal from the uptake of an untargeted tracer is subtracted from targeted tracer signal prior to image reconstruction, resulting in maps of targeted tracer binding. The approach is demonstrated in simulations, a phantom study, and in a mouse glioma imaging study, demonstrating substantial improvement over conventional and homogenous background subtraction image reconstruction approaches.

Compressive sensing based reconstruction in bioluminescence tomography improves image resolution and robustness to noise.

Bioluminescence Tomography attempts to quantify 3-dimensional luminophore distributions from surface measurements of the light distribution. The reconstruction problem is typically severely under-determined due to the number and location of measurements, but in certain cases the molecules or cells of interest form localised clusters, resulting in a distribution of luminophores that is spatially sparse. A Conjugate Gradient-based reconstruction algorithm using Compressive Sensing was designed to take advantage of this sparsity, using a multistage sparsity reduction approach to remove the need to choose sparsity weighting a priori. Numerical simulations were used to examine the effect of noise on reconstruction accuracy. Tomographic bioluminescence measurements of a Caliper XPM-2 Phantom Mouse were acquired and reconstructions from simulation and this experimental data show that Compressive Sensing-based reconstruction is superior to standard reconstruction techniques, particularly in the presence of noise.

Computed tomography-guided time-domain diffuse fluorescence tomography in small animals for localization of cancer biomarkers.

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters. Compared to other visible wavelengths, tissue absorption for red and near-infrared (near-IR) light absorption dramatically decreases and non-elastic scattering becomes the dominant light-tissue interaction mechanism. The relatively recent development of fluorescent agents that absorb and emit light in the near-IR range (600-1000 nm), has driven the development of imaging systems and light propagation models that can achieve whole body three-dimensional imaging in small animals. Despite great strides in this area, the ill-posed nature of diffuse fluorescence tomography remains a significant problem for the stability, contrast recovery and spatial resolution of image reconstruction techniques and the optimal approach to FMI in small animals has yet to be agreed on. The majority of research groups have invested in charge-coupled device (CCD)-based systems that provide abundant tissue-sampling but suboptimal sensitivity, while our group and a few others have pursued systems based on very high sensitivity detectors, that at this time allow dense tissue sampling to be achieved only at the cost of low imaging throughput. Here we demonstrate the methodology for applying single-photon detection technology in a fluorescence tomography system to localize a cancerous brain lesion in a mouse model. The fluorescence tomography (FT) system employed single photon counting using photomultiplier tubes (PMT) and information-rich time-domain light detection in a non-contact conformation. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control, laser referencing, and co-registration with a small animal computed tomography (microCT) system. A nude mouse model was used for imaging. The animal was inoculated orthotopically with a human glioma cell line (U251) in the left cerebral hemisphere and imaged 2 weeks later. The tumor was made to fluoresce by injecting a fluorescent tracer, IRDye 800CW-EGF (LI-COR Biosciences, Lincoln, NE) targeted to epidermal growth factor receptor, a cell membrane protein known to be overexpressed in the U251 tumor line and many other cancers. A second, untargeted fluorescent tracer, Alexa Fluor 647 (Life Technologies, Grand Island, NY) was also injected to account for non-receptor mediated effects on the uptake of the targeted tracers to provide a means of quantifying tracer binding and receptor availability/density. A CT-guided, time-domain algorithm was used to reconstruct the location of both fluorescent tracers (i.e., the location of the tumor) in the mouse brain and their ability to localize the tumor was verified by contrast-enhanced magnetic resonance imaging. Though demonstrated for fluorescence imaging in a glioma mouse model, the methodology presented in this video can be extended to different tumor models in various small animal models potentially up to the size of a rat.

Multiple-gate time domain diffuse fluorescence tomography allows more sparse tissue sampling without compromising image quality.

Diffuse fluorescence tomography systems that employ highly sensitive photo-multiplier tubes for single-photon detection are pushing the sensitivity limits of the field. However, each of these detectors only offers a single data projection to be collected, implying these imaging systems either require many detectors or long scan times to collect full data sets for image reconstruction. This study presents a method of utilizing the time-resolved collection capabilities of time-correlated single-photon counting techniques to increase spatial resolution and to reduce the number of data projections to produce reliable fluorescence reconstructions. Experimental tissue phantom results demonstrate that using data at 10 time gates in the fluorescence reconstructions for only 40 data projections provided superior image accuracy when compared to reconstructions on 320 continuous-wave data projections.

Information loss and reconstruction in diffuse fluorescence tomography.

This paper is a theoretical exploration of spatial resolution in diffuse fluorescence tomography. It is demonstrated that, given a fixed imaging geometry, one cannot-relative to standard techniques such as Tikhonov regularization and truncated singular value decomposition-improve the spatial resolution of the optical reconstructions via increasing the node density of the mesh considered for modeling light transport. Using techniques from linear algebra, it is shown that, as one increases the number of nodes beyond the number of measurements, information is lost by the forward model. It is demonstrated that this information cannot be recovered using various common reconstruction techniques. Evidence is provided showing that this phenomenon is related to the smoothing properties of the elliptic forward model that is used in the diffusion approximation to light transport in tissue. This argues for reconstruction techniques that are sensitive to boundaries, such as L1-reconstruction and the use of priors, as well as the natural approach of building a measurement geometry that reflects the desired image resolution.

Imaging workflow and calibration for CT-guided time-domain fluorescence tomography.

In this study, several key optimization steps are outlined for a non-contact, time-correlated single photon counting small animal optical tomography system, using simultaneous collection of both fluorescence and transmittance data. The system is presented for time-domain image reconstruction in vivo, illustrating the sensitivity from single photon counting and the calibration steps needed to accurately process the data. In particular, laser time- and amplitude-referencing, detector and filter calibrations, and collection of a suitable instrument response function are all presented in the context of time-domain fluorescence tomography and a fully automated workflow is described. Preliminary phantom time-domain reconstructed images demonstrate the fidelity of the workflow for fluorescence tomography based on signal from multiple time gates.

Toward whole-body optical imaging of rats using single-photon counting fluorescence tomography.

We used single-photon counting (SPC) detection for diffuse fluorescence tomography to image nanomolar (nM) concentrations of reporter dyes through a rat. Detailed phantom data are presented to show that every centimeter increase in tissue thickness leads to 1 order of magnitude decrease in the minimum fluorophore concentration detectable for a given detector sensitivity. Specifically, here, detection of Alexa Fluor 647 dyes is shown to be achievable for concentrations as low as 1 nM (<200 fM) through more than 5 cm in tissue phantoms, which indicates that this is feasible in larger rodent models. Because it is possible to detect sub-nM fluorescent inclusions with SPC technology in rats, it follows that it is possible to localize subpicomolar fluorophore concentrations in mice, putting the concentration sensitivity limits on the same order as nuclear medicine methods.

Strategy variability: how too much of a good thing can hurt performance.

Recent research (e.g., Siegler, 1996) has discovered the important and vital role that variability plays among strategy use and development over time. However, as many researchers have pointed out (e.g., Miller, 1993), the majority of the research addressing this issue has focused on the outcomes, rather than on the potentially more informative aspects of variability, strategy development, and the process of adaptation. In this study, we examined the role of variability during strategy development, utilizing a longitudinal method. Thirteen participants were studied over 3 months as they coached a simulated football team. The results suggest that variability plays a major role in adaptive skill acquisition in a dynamic environment--in the direction, however, opposite to that predicted by previous research done with simple static tasks.