Dynamic dual-tracer MRI-guided fluorescence tomography to quantify receptor density in vivo. Proc Natl Acad Sci U S A. 2013;110:9025-9030. [PMID: 23671066 DOI: 10.1073/pnas.1213490110]

Regularized reconstruction based on joint smoothly clipped absolute deviation regularization and graph manifold learning for fluorescence molecular tomography

Objective.Fluorescence molecular tomography (FMT) is an optical imaging modality that provides high sensitivity and low cost, which can offer the three-dimensional distribution of biomarkers by detecting the fluorescently labeled probe noninvasively. In the field of preclinical cancer diagnosis and treatment, FMT has gained significant traction. Nonetheless, the current FMT reconstruction results suffer from unsatisfactory morphology and location accuracy of the fluorescence distribution, primarily due to the light scattering effect and the ill-posed nature of the inverse problem.Approach.To address these challenges, a regularized reconstruction method based on joint smoothly clipped absolute deviation regularization and graph manifold learning (SCAD-GML) for FMT is presented in this paper. The SCAD-GML approach combines the sparsity of the fluorescent sources with the latent manifold structure of fluorescent source distribution to achieve more accurate and sparse reconstruction results. To obtain the reconstruction results efficiently, the non-convex gradient descent iterative method is employed to solve the established objective function. To assess the performance of the proposed SCAD-GML method, a comprehensive evaluation is conducted through numerical simulation experiments as well asin vivoexperiments.Main results.The results demonstrate that the SCAD-GML method outperforms other methods in terms of both location and shape recovery of fluorescence biomarkers distribution.Siginificance.These findings indicate that the SCAD-GML method has the potential to advance the application of FMT inin vivobiological research.

Fluorescence molecular optomic signatures improve identification of tumors in head and neck specimens

Background

Fluorescence molecular imaging using ABY-029, an epidermal growth factor receptor (EGFR)-targeted, synthetic Affibody peptide labeled with a near-infrared fluorophore, is under investigation for surgical guidance during head and neck squamous cell carcinoma (HNSCC) resection. However, tumor-to-normal tissue contrast is confounded by intrinsic physiological limitations of heterogeneous EGFR expression and non-specific agent uptake.

Objective

In this preliminary study, radiomic analysis was applied to optical ABY-029 fluorescence image data for HNSCC tissue classification through an approach termed "optomics." Optomics was employed to improve tumor identification by leveraging textural pattern differences in EGFR expression conveyed by fluorescence. The study objective was to compare the performance of conventional fluorescence intensity thresholding and optomics for binary classification of malignant vs. non-malignant HNSCC tissues.

Materials and Methods

Fluorescence image data collected through a Phase 0 clinical trial of ABY-029 involved a total of 20,073 sub-image patches (size of 1.8 × 1.8 mm2) extracted from 24 bread-loafed slices of HNSCC surgical resections originating from 12 patients who were stratified into three dose groups (30, 90, and 171 nanomoles). Each dose group was randomly partitioned on the specimen-level 75%/25% into training/testing sets, then all training and testing sets were aggregated. A total of 1,472 standardized radiomic features were extracted from each patch and evaluated by minimum redundancy maximum relevance feature selection, and 25 top-ranked features were used to train a support vector machine (SVM) classifier. Predictive performance of the SVM classifier was compared to fluorescence intensity thresholding for classifying testing set image patches with histologically confirmed malignancy status.

Results

Optomics provided consistent improvement in prediction accuracy and false positive rate (FPR) and similar false negative rate (FNR) on all testing set slices, irrespective of dose, compared to fluorescence intensity thresholding (mean accuracies of 89% vs. 81%, P = 0.0072; mean FPRs of 12% vs. 21%, P = 0.0035; and mean FNRs of 13% vs. 17%, P = 0.35).

Conclusions

Optomics outperformed conventional fluorescence intensity thresholding for tumor identification using sub-image patches as the unit of analysis. Optomics mitigate diagnostic uncertainties introduced through physiological variability, imaging agent dose, and inter-specimen biases of fluorescence molecular imaging by probing textural image information. This preliminary study provides a proof-of-concept that applying radiomics to fluorescence molecular imaging data offers a promising image analysis technique for cancer detection in fluorescence-guided surgery.

Identification of a Suitable Untargeted Agent for the Clinical Translation of ABY-029 Paired-Agent Imaging in Fluorescence-Guided Surgery

PURPOSE

Non-specific uptake and retention of molecular targeted agents and heterogeneous tissue optical properties diminish the ability to differentiate between tumor and normal tissues using molecular targeted fluorescent agents. Paired-agent imaging (PAI) can increase the diagnostic ability to detect tumor tissue by mitigating these non-specific effects and providing true molecular contrast by co-administration of an untargeted control imaging agent with a targeted agent. This study evaluates the suitability of available clinically translatable untargeted agents for the translation of PAI in fluorescence-guided surgery using an affibody-based targeted imaging agent (ABY-029).

EXPERIMENTAL

DESIGN: Three untargeted agents that fluoresce near 700 nm and exhibit good clinical safety profiles (methylene blue, IRDye 700DX, and IRDye 680LT) were tested in combination with the clinically tested IRDye 800CW-labeled anti-epidermal growth factor receptor (EGFR) affibody molecule, ABY-029 (eIND 122,681). Properties of the untargeted agent important for human use and integrity of PAI were tested: (1) plasma protein binding; (2) fluorescence signal linearity in in vitro whole blood dilution; (3) in vivo pharmacokinetic matching to targeted agent in negative control tissue; and (4) in vivo diagnostic accuracy of PAI vs single agent imaging (SAI) of ABY-029 alone in orthotopic oral head and neck squamous cell carcinomas.

RESULTS

IRDye 680LT outperformed IRDye 700DX and methylene blue with the highest signal linearity (R² = 0.9998 ± 0.0002, 0.9995 ± 0.0004, 0.91 ± 0.02, respectively), the highest fluorescence yield in whole blood at 1 μM (10^{4.42 ± 0.05}, 10^{3.68 ± 0.09}, 10^{1.9 ± 0.2}, respectively), and the most closely matched ABY-029 pharmacokinetics in EGFR-negative tissues (binding potential error percentage = 0.31% ± 0.37%, 10.25% ± 1.30%, and 8.10% ± 5.37%, respectively). The diagnostic ability of PAI with ABY-029 and IRDye 680LT outperformed conventional SAI with an area-under-the-receiver-operating-characteristic curve (AUC) value of 0.964 vs. 0.854, and 0.978 vs. 0.925 in the Odyssey scanning system and Pearl wide field imaging system, respectively.

CONCLUSION

PAI is a highly promising methodology for increasing detection of tumors in fluorescence-guided surgery. Although not yet clinically approved, IRDye 680LT demonstrates promise as an untargeted agent when paired with ABY-029. The clinical translation of PAI to maximize tumor excision, while minimizing normal tissue removal, could improve both patient survival and life quality.

Development of a theranostic preclinical fluorescence molecular tomography/cone beam CT-guided irradiator platform

Image-guided small animal radiation research platforms allow more precise radiation treatment. Commercially available small animal X-ray irradiators are often equipped with a CT/cone-beam CT (CBCT) component for target guidance. Besides having poor soft-tissue contrast, CBCT unfortunately cannot provide molecular information due to its low sensitivity. Hence, there are extensive efforts to incorporate a molecular imaging component besides CBCT on these radiation therapy platforms. As an extension of these efforts, here we present a theranostic fluorescence tomography/CBCT-guided irradiator platform that provides both anatomical and molecular guidance, which can overcome the limitations of stand-alone CBCT. The performance of our hybrid system is validated using both tissue-like phantoms and mice ex vivo. Both studies show that fluorescence tomography can provide much more accurate quantitative results when CBCT-derived structural information is used to constrain the inverse problem. The error in the recovered fluorescence absorbance reduces nearly 10-fold for all cases, from approximately 60% down to 6%. This is very significant since high quantitative accuracy in molecular information is crucial to the correct assessment of the changes in tumor microenvironment related to radiation therapy.

Non-invasive visualization of amyloid-beta deposits in Alzheimer amyloidosis mice using magnetic resonance imaging and fluorescence molecular tomography

Abnormal cerebral accumulation of amyloid-beta peptide (Aβ) is a major hallmark of Alzheimer's disease. Non-invasive monitoring of Aβ deposits enables assessing the disease burden in patients and animal models mimicking aspects of the human disease as well as evaluating the efficacy of Aβ-modulating therapies. Previous in vivo assessments of plaque load have been predominantly based on macroscopic fluorescence reflectance imaging (FRI) and confocal or two-photon microscopy using Aβ-specific imaging agents. However, the former method lacks depth resolution, whereas the latter is restricted by the limited field of view preventing a full coverage of the large brain region. Here, we utilized a fluorescence molecular tomography (FMT)-magnetic resonance imaging (MRI) pipeline with the curcumin derivative fluorescent probe CRANAD-2 to achieve full 3D brain coverage for detecting Aβ accumulation in the arcAβ mouse model of cerebral amyloidosis. A homebuilt FMT system was used for data acquisition, whereas a customized software platform enabled the integration of MRI-derived anatomical information as prior information for FMT image reconstruction. The results obtained from the FMT-MRI study were compared to those from conventional planar FRI recorded under similar physiological conditions, yielding comparable time courses of the fluorescence intensity following intravenous injection of CRANAD-2 in a region-of-interest comprising the brain. In conclusion, we have demonstrated the feasibility of visualizing Aβ deposition in 3D using a multimodal FMT-MRI strategy. This hybrid imaging method provides complementary anatomical, physiological and molecular information, thereby enabling the detailed characterization of the disease status in arcAβ mouse models, which can also facilitate monitoring the efficacy of putative treatments targeting Aβ.

Recent Technical Advances in Accelerating the Clinical Translation of Small Animal Brain Imaging: Hybrid Imaging, Deep Learning, and Transcriptomics

Small animal models play a fundamental role in brain research by deepening the understanding of the physiological functions and mechanisms underlying brain disorders and are thus essential in the development of therapeutic and diagnostic imaging tracers targeting the central nervous system. Advances in structural, functional, and molecular imaging using MRI, PET, fluorescence imaging, and optoacoustic imaging have enabled the interrogation of the rodent brain across a large temporal and spatial resolution scale in a non-invasively manner. However, there are still several major gaps in translating from preclinical brain imaging to the clinical setting. The hindering factors include the following: (1) intrinsic differences between biological species regarding brain size, cell type, protein expression level, and metabolism level and (2) imaging technical barriers regarding the interpretation of image contrast and limited spatiotemporal resolution. To mitigate these factors, single-cell transcriptomics and measures to identify the cellular source of PET tracers have been developed. Meanwhile, hybrid imaging techniques that provide highly complementary anatomical and molecular information are emerging. Furthermore, deep learning-based image analysis has been developed to enhance the quantification and optimization of the imaging protocol. In this mini-review, we summarize the recent developments in small animal neuroimaging toward improved translational power, with a focus on technical improvement including hybrid imaging, data processing, transcriptomics, awake animal imaging, and on-chip pharmacokinetics. We also discuss outstanding challenges in standardization and considerations toward increasing translational power and propose future outlooks.

Whole-brain MR-registered cryo-imaging of a porcine-human glioma model to compare contrast agent biodistributions

As rapidly accelerating technology, fluorescence guided surgery (FGS) has the potential to place molecular information directly into the surgeon's field of view by imaging administered fluorescent contrast agents in real time, circumnavigating pre-operative MR registration challenges with brain deformation. The most successful implementation of FGS is 5-ALA-PpIX guided glioma resection which has been linked to improved patient outcomes. While FGS may offer direct in-field guidance, fluorescent contrast agent distributions are not as familiar to the surgical community as Gd-MRI uptake, and may provide discordant information from previous Gd-MRI guidance. Thus, a method to assess and validate consistency between fluorescence-labeled tumor regions and Gd-enhanced tumor regions could aid in understanding the correlation between optical agent fluorescence and Gd-enhancement. Herein, we present an approach for comparing whole-brain fluorescence biodistributions with Gd-enhancement patterns on a voxel-by-voxel basis using co-registered fluorescent cryo-volumes and Gd-MRI volumes. In this initial study, a porcine-human glioma xenograft model was administered 5-ALA-PpIX, imaged with MRI, and euthanized 22 hours following 5-ALA administration. Following euthanization, the extracted brain was imaged with the cryo-macrotome system. After image processing steps and non-rigid, point-based registration, the fluorescence cryo-volume and Gd-MRI volume were compared for similarity metrics including: image similarity, tumor shape similarity, and classification similarity. This study serves as a proof-of-principle in validating our screening approach for quantitatively comparing 3D biodistributions between optical agents and Gd-based agents.

Macroscopic Fluorescence Lifetime Imaging for Monitoring of Drug-Target Engagement

Precision medicine promises to improve therapeutic efficacy while reducing adverse effects, especially in oncology. However, despite great progresses in recent years, precision medicine for cancer treatment is not always part of routine care. Indeed, the ability to specifically tailor therapies to distinct patient profiles requires still significant improvements in targeted therapy development as well as decreases in drug treatment failures. In this regard, preclinical animal research is fundamental to advance our understanding of tumor biology, and diagnostic and therapeutic response. Most importantly, the ability to measure drug-target engagement accurately in live and intact animals is critical in guiding the development and optimization of targeted therapy. However, a major limitation of preclinical molecular imaging modalities is their lack of capability to directly and quantitatively discriminate between drug accumulation and drug-target engagement at the pathological site. Recently, we have developed Macroscopic Fluorescence Lifetime Imaging (MFLI) as a unique feature of optical imaging to quantitate in vivo drug-target engagement. MFLI quantitatively reports on nanoscale interactions via lifetime-sensing of Förster Resonance Energy Transfer (FRET) in live, intact animals. Hence, MFLI FRET acts as a direct reporter of receptor dimerization and target engagement via the measurement of the fraction of labeled-donor entity undergoing binding to its respective receptor. MFLI is expected to greatly impact preclinical imaging and also adjacent fields such as image-guided surgery and drug development.

Examining the Feasibility of Quantifying Receptor Availability Using Cross-Modality Paired-Agent Imaging

Purpose

The ability to noninvasively quantify receptor availability (RA) in solid tumors is an aspirational goal of molecular imaging, often challenged by the influence of non-specific accumulation of the contrast agent. Paired-agent imaging (PAI) techniques aim to compensate for this effect by imaging the kinetics of a targeted agent and an untargeted isotype, often simultaneously, and comparing the kinetics of the two agents to estimate RA. This is usually accomplished using two spectrally distinct fluorescent agents, limiting the technique to superficial tissues and/or preclinical applications. Applying the approach in humans using conventional imaging modalities is generally infeasible since most modalities are unable to routinely image multiple agents simultaneously. We examine the ability of PAI to be implemented in a cross-modality paradigm, in which the targeted and untargeted agent kinetics are imaged with different modalities and used to recover receptor availability.

Procedures

Eighteen mice bearing orthotopic brain tumors were administered a solution containing three contrast agents: (1) a fluorescent agent targeted to epidermal growth factor receptor (EGFR), (2) an untargeted fluorescent isotype, and (3) a gadolinium-based contrast agent (GBCA) for MRI imaging. The kinetics of all three agents were imaged for 1 h after administration using an MRI-coupled fluorescence tomography system. Paired-agent receptor availability was computed using (1) the conventional all-optical approach using the targeted and untargeted optical agent images and (2) the cross-modality approach using the targeted optical and untargeted MRI-GBCA images. Receptor availability estimates between the two methods were compared.

Results

Receptor availability values using the cross-modality approach were highly correlated to the conventional, single-modality approach (r = 0.94; p < 0.00001).

Conclusion

These results suggest that cross-modality paired-agent imaging for quantifying receptor availability is feasible. Ultimately, cross-modality paired-agent imaging could facilitate rapid, noninvasive receptor availability quantification in humans using hybrid clinical imaging modalities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11307-021-01629-6.

A review of the application of machine learning in molecular imaging

Molecular imaging (MI) is a science that uses imaging methods to reflect the changes of molecular level in living state and conduct qualitative and quantitative studies on its biological behaviors in imaging. Optical molecular imaging (OMI) and nuclear medical imaging are two key research fields of MI. OMI technology refers to the optical information generated by the imaging target (such as tumors) due to drug intervention and other reasons. By collecting the optical information, researchers can track the motion trajectory of the imaging target at the molecular level. Owing to its high specificity and sensitivity, OMI has been widely used in preclinical research and clinical surgery. Nuclear medical imaging mainly detects ionizing radiation emitted by radioactive substances. It can provide molecular information for early diagnosis, effective treatment and basic research of diseases, which has become one of the frontiers and hot topics in the field of medicine in the world today. Both OMI and nuclear medical imaging technology require a lot of data processing and analysis. In recent years, artificial intelligence technology, especially neural network-based machine learning (ML) technology, has been widely used in MI because of its powerful data processing capability. It provides a feasible strategy to deal with large and complex data for the requirement of MI. In this review, we will focus on the applications of ML methods in OMI and nuclear medical imaging.

A hyperspectral approach for recovering agent excretion biodistributions using whole-body fluorescence cryo-imaging

Understanding the uptake and clearance kinetics of new drugs and contrast agents is an important aspect of drug development that typically involves a combination of imaging and analysis of harvested organs. Although these techniques are well-established and can be quantitative, they generally do not preserve high resolution biodistribution information. In this context, fluorescence whole-body cryo-imaging is a promising technique for recovering 3D drug/agent biodistributions at a high resolution throughout an entire study animal at specific time points. A common challenge associated with fluorescence imaging in tissue is that agent signal can be confounded by endogenous fluorescence signal which is often observed in the visible window. One method to address this issue is to acquire hyperspectral images and spectrally unmix agent signal from confounding autofluorescence signals using known spectral bases. Herein, we apply hyperspectral whole-body cryo-imaging and spectral unmixing to examine the distribution of multiple fluorescent agents in excretion organ regions.

Monitoring cancer cell surface receptor expression during anti-angiogenesis therapy in vivo

Concurrent administration of cancer therapeutics with tumor vasculature targeting treatment has been shown to improve overall survival in multiple human cancer types, as such combinations aim to destroy different compartments of tumors. Anti-angiogenesis therapeutics designed to inhibit tumor induced vessel sprouting have also been shown to re-model the tumor vasculature through a transient vessel normalization effect, which leads to improved perfusion of oxygen and drug in tumor. However, the effects that this normalized vasculature has on the availability of cancer receptor, such as EGFR, is unknown. Herein, we examined the use of MRI-PAFT to estimate cancer surface receptor availability in response to anti-angiogenesis therapy, using MRI-coupled paired agent fluorescence tomography. Bevacizumab treated tumors showed increase in RA compared to control tumors, but this was not statistically significant.

Noninvasive quantification of target availability during therapy using paired-agent fluorescence tomography

Immuno-oncological treatment strategies that target abnormal receptor profiles of tumors are an increasingly important feature of cancer therapy. Yet, assessing receptor availability (RA) and drug-target engagement, important determinants of therapeutic efficacy, is challenging with current imaging strategies, largely due to the complex nonspecific uptake behavior of imaging agents in tumors. Herein, we evaluate whether a quantitative noninvasive imaging approach designed to compensate for nonspecific uptake, MRI-coupled paired-agent fluorescence tomography (MRI-PAFT), is capable of rapidly assessing the availability of epidermal growth factor receptor (EGFR) in response to one dose of anti-EGFR antibody therapy in orthotopic brain tumor models.

Methods: Mice bearing orthotopic brain tumor xenografts with relatively high EGFR expression (U251) (N=10) or undetectable human EGFR (9L) (N=9) were considered in this study. For each tumor type, mice were either treated with one dose of cetuximab, or remained untreated. All animals were scanned using MRI-PAFT, which commenced immediately after paired-agent administration, and values of RA were recovered using a model-based approach, which uses the entire dynamic sequence of agent uptake, as well as a simplified “snapshot” approach which requires uptake measurements at only two time points. Recovered values of RA were evaluated between groups and techniques. Hematoxylin & eosin (H&E) and immunohistochemical (IHC) staining was performed on tumor specimens from every animal to confirm tumor presence and EGFR status.

Results: In animals bearing EGFR(+) tumors, a significant difference in RA values between treated and untreated animals was observed (RA = 0.24 ± 0.15 and 0.61 ± 0.18, respectively, p=0.027), with an area under the curve - receiver operating characteristic (AUC-ROC) value of 0.92. We did not observe a statistically significant difference in RA values between treated and untreated animals bearing EGFR(-) tumors (RA = 0.18 ± 0.19 and 0.27 ± 0.21, respectively; p = 0.89; AUC-ROC = 0.55), nor did we observe a difference between treated EGFR(+) tumors compared to treated and untreated EGFR(-) tumors. Notably, the snapshot paired-agent strategy quantified drug-receptor engagement within just 30 minutes of agent administration. Examination of the targeted agent alone showed no capacity to distinguish tumors either by treatment or receptor status, even 24h after agent administration.

Conclusions: This study demonstrated that a noninvasive imaging strategy enables rapid quantification of receptor availability in response to therapy, a capability that could be leveraged in preclinical drug development, patient stratification, and treatment monitoring.

Development of tomographic reconstruction for three-dimensional optical imaging: From the inversion of light propagation to artificial intelligence

Optical molecular tomography (OMT) is an imaging modality which uses an optical signal, especially near-infrared light, to reconstruct the three-dimensional information of the light source in biological tissue. With the advantages of being low-cost, noninvasive and having high sensitivity, OMT has been applied in preclinical and clinical research. However, due to its serious ill-posedness and ill-condition, the solution of OMT requires heavy data analysis and the reconstruction quality is limited. Recently, the artificial intelligence (commonly known as AI)-based methods have been proposed to provide a different tool to solve the OMT problem. In this paper, we review the progress on OMT algorithms, from conventional methods to AI-based methods, and we also give a prospective towards future developments in this domain.

Kinetic modeling and analysis of dynamic bioluminescence imaging of substrates administered by intraperitoneal injection

Background

Bioluminescence imaging (BLI) has been found to have diverse applications in the life sciences and medical research due to its ease of use and high sensitivity. From kinetics analysis, dynamic imaging studies have significant advantages for diagnosis when compared to traditional static imaging studies. This work focuses on modeling and quantitatively analyzing the dynamic data produced from the intraperitoneal (IP) injection of D-luciferin in longitudinal BLI, aiming to provide a powerful tool for monitoring the growth of tumors.

Methods

We constructed a three-compartment pharmacokinetic (PK) model and employed the standard Michaelis-Menten (M-M) kinetics to investigate the dynamic BLI data produced from the IP injection of D-luciferin. The 3 compartments were the plasma compartment, the non-specific compartment, and the specific compartment. The validity of this PK model was tested by the dynamic BLI data of MKN28M-luc xenograft mice, along with the published longitudinal dynamic BLI data of B16F10-luc xenograft mice.

Results

The R-squares between the simulated lines and the measurement were 1 and 0.99, respectively, for the mice data and the published data. In addition, the 2 kinetic macroparameters obtained reflected the rate of tumor growth in vivo. In particular, the values of macroparameters A showed a significant dependence on tumor surface area.

Conclusions

The proposed PK model may be an effective tool for use in drug development programs and for monitoring the response of tumors to treatment.

Estimating paired-agent uptake in altered tumor vasculature using MRI-coupled fluorescence tomography

Angiogenesis inhibiting cancer therapy has become a standard treatment for many cancer types. The ability to examine the effects of these drugs in tumors noninvasively could help assess efficacy early in the treatment course or identify optimal times to introduce other combinatorial treatments. Herein, we examine whether a paired agent MRI-coupled fluorescence tomography approach can be used to monitor the effects of anti-angiogenesis therapy. Using small animal models bearing orthotopic glioma xenografts, we demonstrate noninvasive quantification of paired-agent uptake in response to anti-angiogenesis therapy in vivo. The result provides insights on receptor targeted drug delivery in altered vasculature, a potential important development for treatment monitoring and combinatorial strategies.

Small-animal 360-deg fluorescence diffuse optical tomography using structural prior information from ultrasound imaging

We demonstrate dual modality of free-space fluorescence diffuse optical tomography (FDOT) and handheld ultrasound (US) imaging to reveal both functional and structural information in small animals. FDOT is a noninvasive method for examining the fluorophore inside an object from the light distribution of the surface. In FDOT, a 660-nm continuous wave diode laser was used as an excitation source and an electron-multiplying charge-coupled device (EMCCD) was used for fluorescence data acquisition. Both the laser and EMCCD were mounted on a 360-deg rotation gantry for the transmission optical data collection. The structural information is obtained from a 6- to 17-MHz handheld US linear transducer by single-side access and conducts in the reconstruction as soft priors. The rotation ranges from 0 deg to 360 deg; different rotation degrees, object positions, and parameters were determined for comparison. Both phantom and tissue phantom results demonstrate that fluorophore distribution can be recovered accurately and quantitatively using this imaging system. Finally, an animal study confirms that the system can extract a dual-modality image, validating its feasibility for further in vivo experiments. In all experiments, the error and standard deviation decrease as the rotation degree is increased and the error was reduced to 10% when the rotation degree was increased over 135 deg.

Developing a novel hyperspectral imaging cryomacrotome for whole body fluorescence imaging

The ability to directly measure whole-body fluorescence can enable tracking of labeled cells, metastatic spread, and drug bio-distribution. We describe the development of a new hyperspectral imaging whole body cryo-macrotome designed to acquire 3-D fluorescence volumes in large specimens (whole animals) at high resolution. The use of hyperspectral acquisition provides full spectra at every voxel, enabling spectral decoupling of multiple fluorohpores and autofluorescence. We present examples of tissue spectra and spectral fitting in a rodent glioma xenograft.

Estimating drug delivery using hybrid system for simultaneous dynamic MRI and fluorescence tomography

Optical tomography is often coupled with high resolution imaging modality like MRI to provide functional information associated with specific anatomical structure noninvasively. MRI-coupled paired agent fluorescence molecular tomography (MRI-PAFT) is a hybrid imaging modality capable of noninvasively quantifying drug-target engagement in vivo utilizing a targeted and an untargeted fluorescence agent. This study compares the uptake kinetics of MRI contrast agent and fluorescence agents in tumor and normal tissue, and demonstrates the potential of utilizing MRI contrast agent kinetic and targeted fluorescence agent kinetics to quantify targeted tumor receptor concentration in glioma tumor model.

A paired-agent fluorescent molecular imaging strategy for quantifying antibody drug target engagement in in vivo window chamber xenograft models

A paired-agent fluorescent molecular imaging strategy is presented as a method to measure drug target engagement in whole tumor imaging. The protocol involves dynamic imaging of a pair of targeted and control imaging agents prior to and following antibody therapy. Simulations demonstrated that antibody "drug target engagement" can be estimated within a 15%-error over a wide range of tumor physiology (blood flow, vascular permeability, target density) and antibody characteristics (affinity, binding rates). Experimental results demonstrated the first in vivo detection of binding site barrier, highlighting the potential for this methodology to provide novel insights in drug distribution/binding imaging.

Adaptive Gaussian Weighted Laplace Prior Regularization Enables Accurate Morphological Reconstruction in Fluorescence Molecular Tomography

Fluorescence molecular tomography (FMT), as a powerful imaging technique in preclinical research, can offer the three-dimensional distribution of biomarkers by detecting the fluorescently labelled probe noninvasively. However, because of the light scattering effect and the ill-pose of inverse problem, it is challenging to develop an efficient reconstruction method, which can provide accurate location and morphology of the fluorescence distribution. In this research, we proposed a novel adaptive Gaussian weighted Laplace prior (AGWLP) regularization method, which assumed the variance of fluorescence intensity between any two voxels had a non-linear correlation with their Gaussian distance. It utilized an adaptive Gaussian kernel parameter strategy to achieve accurate morphological reconstructions in FMT. To evaluate the performance of the AGWLP method, we conducted numerical simulation and in vivo experiments. The results were compared with fast iterative shrinkage (FIS) thresholding method, split Bregman-resolved TV (SBRTV) regularization method, and Gaussian weighted Laplace prior (GWLP) regularization method. We validated in vivo imaging results against planar fluorescence images of frozen sections. The results demonstrated that the AGWLP method achieved superior performance in both location and shape recovery of fluorescence distribution. This enabled FMT more suitable and practical for in vivo visualization of biomarkers.

Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography

OBJECTIVE

Bioluminescence tomography (BLT) is a non-invasive technique designed to enable three-dimensional (3D) visualization and quantification of viable tumor cells in living organisms. However, despite the excellent sensitivity and specificity of bioluminescence imaging (BLI), BLT is limited by the photon scattering effect and ill-posed inverse problem. If the complete structural information of a light source is considered when solving the inverse problem, reconstruction accuracy will be improved.

METHODS

This article proposed a block sparse Bayesian learning method based on K-nearest neighbor strategy (KNN-BSBL), which incorporated several types of a priori information including sparsity, spatial correlations among neighboring points, and anatomical information to balance over-sparsity and morphology preservation in BLT. Furthermore, we considered the Gaussian weighted distance prior in a light source and proposed a KNN-GBSBL method to further improve the performance of KNN-BSBL.

RESULTS

The results of numerical simulations and in vivo glioma-bearing mouse experiments demonstrated that KNN-BSBL and KNN-GBSBL achieved superior accuracy for tumor spatial positioning and morphology reconstruction.

CONCLUSION

The proposed method KNN-BSBL incorporated several types of a priori information is an efficient and robust reconstruction method for BLT.

Fluorescence Molecular Tomography Based on Group Sparsity Priori for Morphological Reconstruction of Glioma

OBJECTIVE

Fluorescence molecular tomography (FMT) is an important tool for life science, which can noninvasive real-time three-dimensional (3-D) visualization for fluorescence source location. FMT is widely used in tumor research due to its high-sensitive and low cost. However, the reconstruction of FMT is difficult. Although the reconstruction methods of FMT have developed rapidly in recent years, the morphological reconstruction of FMT is still a challenge problem. Thus, the purpose of this study is to realize the morphological reconstruction performance of FMT in glioma research.

METHODS

In this study, group sparsity was used as a new priori information for FMT. Besides sparsity, group sparsity also takes the group structure of the fluorescent sources, which can maintain the morphological information of the sources. Fused LASSO method (FLM) was proved it can efficiently model the group sparsity prior. Thus, we utilize FLM to reconstruct the morphological information of glioma. Furthermore, to reduce the influence of the high scattering of skull, we modified the FLM for improving the accuracy of morphological reconstruction.

RESULTS

Glioma numerical simulation model and in vivo glioma model were established to evaluate the performance of morphological reconstruction of the proposed method. The results demonstrated that the proposed method was efficient to reconstruct the morphological information of glioma.

CONCLUSION

Group sparsity priori can effectively improve the morphological accuracy of FMT reconstruction.

SIGNIFICANCE

Group sparsity can maintain the morphological information of fluorescent sources effectively, which has great application potential in FMT. The group sparsity based methods can realize the morphological reconstruction, which is of great practical significance in tumor research.

Simultaneous extracellular and intracellular quantification of EGFR using paired-agent imaging in an in ovo tumor model

Quantification of protein concentrations is often a static and tissue destructive technique. Paired-agent imaging (PAI) using matched targeted and untargeted agents has been established as a dynamic method for quantifying the extracellular domain of epidermal growth factor receptor (EGFR) in vivo in a variety of tumor lines. Here we extend the PAI model to simultaneously quantify the extracellular and intracellular regions of EGFR using novel cell membrane permeable fluorescent small molecules, TRITC-erlotinib (targeted) and BODIPY-N-erlotinib (non-binding control isoform) synthesized in house. An EGFR overexpressing squamous cell carcinoma cell xenograft tumor, A431, was implanted on the chorioallantoic membrane (CAM) of the embryonated chicken egg. In total six fluorescent molecules were administered and monitored over 1 h using multi-spectral imaging. EGFR concentrations were determined using both extracellular and intracellular PAI methods. The fluorescent molecules used for extracellular PAI were ABY-029, an anti-EGFR Affibody molecule conjugated to IRDye 800CW, and a Control Imaging Agent Affibody molecule conjugated to IRDye 680RD. The intracellular PAI (iPAI) fluorescent molecules were cell membrane penetrating TRITC-erlotinib, BODIPY-N-erlotinb, and BODIPY TR carboxylate, as well as cell membrane impermeant control agent, Alexa Fluor 647 carboxylate. Results from simultaneous imaging of both the extracellular and intracellular binding domains of EGFR indicate that concentrations of intracellular EGFR are higher than extracellular. This is anticipated as EGFR exists in two distinct populations in cells, cell membrane bound and internalized, activated protein. iPAI is a promising new method for quantifying intracellular proteins in a rapid tumor model on the chicken CAM.

Paired-agent imaging for detection of head and neck cancers

Head and neck cancers overwhelmingly overexpress epidermal growth factor receptor (EGFR). This overexpression has been utilized for head and neck cancers using molecular targeted agents for therapy and cancer cell detection. Significant progress has been made in using EGFR-targeted fluorescent antibody and Affibody molecule agents for fluorescent guided surgery in head and neck cancers. Although success in achieving tumor-to-background ratio of 3-5 have been achieved, the field is limited by the non-specific fluorescence in normal tissues as well as EGFR specific fluorescence in the oral cavity. We propose that paired-agent imaging (PAI) could improve the contrast between tumor and normal tissue by removing the fluorescent signal arising from non-specific binding. Here, ABY-029 - an anti-EGFR Affibody molecule labeled with IRDye 800CW - and IRDye 680RD conjugated to Affibody Control Imaging Agent molecule (IR680-Aff_ctrl) are used as targeted and untargeted control agents, respectively, in a panel of head and neck squamous cell carcinomas (HNSCC) to test the ability of PAI to increase tumor detection. Initial results demonstrate that binding potential, a value proportional to receptor concentration, correlates well to EGFR expression but experimental limitations prevented pixel-by-pixel analysis that was desired. Although promising, a more rigorous and well-defined experimental protocol is required to align ex vivo EGFR immunohistochemistry with in vivo binding potential and fluorescence intensity. Additionally, a new set of paired-agents, ABY-029 and IRDye 700DX, are successfully tested in naïve mice and will be carried forward for clinical translation.

Noninvasive imaging of dual-agent uptake in glioma and normal tissue using MRI-coupled fluorescence tomography

As the role of immuno-oncological therapeutics expands, the capacity to noninvasively quantify molecular targets and drug-target engagement is increasingly critical to drug development efforts and treatment monitoring. Previously, we showed that MRI-coupled dual-agent fluorescence tomography (FMT) is capable of estimating the concentration of epidermal growth factor receptor (EGFR) in orthotopic glioma models noninvasively. This approach uses the dynamic information of two fluorescent agents (a targeted agent and untargeted isotype) to estimate tumor receptor concentration in vivo. This approach generally relies on the two tracers having similar kinetics in normal tissues, which may not always be the case. Herein, we describe an additional channel added to the MRI-FMT system which measures the uptake of both agents in the normal muscle, data which can be used to compensate for differing kinetic behavior.

A thermo-sensitive fluorescent agent based method for excitation light leakage rejection for fluorescence molecular tomography

Fluorescence molecular tomography (FMT) is widely used in preclinical oncology research. FMT is the only imaging technique able to provide 3D distribution of fluorescent probes within thick highly scattering media. However, its integration into clinical medicine has been hampered by its low spatial resolution caused by the undetermined and ill-posed nature of its reconstruction algorithm. Another major factor degrading the quality of FMT images is the large backscattered excitation light component leaking through the rejection filters and coinciding with the weak fluorescent signal arising from a low tissue fluorescence concentration. In this paper, we present a new method based on the use of a novel thermo-sensitive fluorescence probe. In fact, the excitation light leakage is accurately estimated from a set of measurements performed at different temperatures and then is corrected for in the tomographic data. The obtained results show a considerable improvement in both spatial resolution and quantitative accuracy of FMT images due to the proper correction of fluorescent signals.

Quantitative imaging of receptor-ligand engagement in intact live animals

Maintaining an intact tumor environment is critical for quantitation of receptor-ligand engagement in a targeted drug development pipeline. However, measuring receptor-ligand engagement in vivo and non-invasively in preclinical settings is extremely challenging. We found that quantitation of intracellular receptor-ligand binding can be achieved using whole-body macroscopic lifetime-based Förster Resonance Energy Transfer (FRET) imaging in intact, live animals bearing tumor xenografts. We determined that FRET levels report on ligand binding to transferrin receptors conversely to raw fluorescence intensity. FRET levels in heterogeneous tumors correlate with intracellular ligand binding but strikingly, not with ubiquitously used ex vivo receptor expression assessment. Hence, MFLI-FRET provides a direct measurement of systemic delivery, target availability and intracellular drug delivery in preclinical studies. Here, we have used MFLI to measure FRET longitudinally in intact and live animals. MFLI-FRET is well-suited for guiding the development of targeted drug therapy in heterogeneous tumors in intact, live small animals.

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.

Signal-to-noise ratio analysis and improvement for fluorescence tomography imaging

CCD-based fluorescence tomography is widely used for small animal whole-body imaging. In this report, systematic signal-to-noise ratio (SNR) analyses of a fluorescence tomography imaging (FTI) system were performed, resulting in an easy-to-follow strategy to optimize hardware configurations and operational conditions for acquiring high-quality imaging data and for improving the overall system performance. Phantom experiments were conducted to demonstrate the performance improvement by these optimizations. The improved performance was further verified by imaging a tumor-bearing mouse in vivo. This report provides general and practical guidelines for setting up a high-performance electron multiplying charge coupled device based FTI system to achieve an optimized SNR, which can be useful for future FTI technology development.

Correcting for targeted and control agent signal differences in paired-agent molecular imaging of cancer cell-surface receptors

Paired-agent kinetic modeling protocols provide one means of estimating cancer cell-surface receptors with in vivo molecular imaging. The protocols employ the coadministration of a control imaging agent with one or more targeted imaging agent to account for the nonspecific uptake and retention of the targeted agent. These methods require the targeted and control agent data be converted to equivalent units of concentration, typically requiring specialized equipment and calibration, and/or complex algorithms that raise the barrier to adoption. This work evaluates a kinetic model capable of correcting for targeted and control agent signal differences. This approach was compared with an existing simplified paired-agent model (SPAM), and modified SPAM that accounts for signal differences by early time point normalization of targeted and control signals (SPAMPN). The scaling factor model (SPAMSF) outperformed both SPAM and SPAMPN in terms of accuracy and precision when the scale differences between targeted and imaging agent signals (α) were not equal to 1, and it matched the performance of SPAM for α  =  1. This model could have wide-reaching implications for quantitative cancer receptor imaging using any imaging modalities, or combinations of imaging modalities, capable of concurrent detection of at least two distinct imaging agents (e.g., SPECT, optical, and PET/MR).

Multimodality Molecular Imaging-Guided Tumor Border Delineation and Photothermal Therapy Analysis Based on Graphene Oxide-Conjugated Gold Nanoparticles Chelated with Gd

Tumor cell complete extinction is a crucial measure to evaluate antitumor efficacy. The difficulties in defining tumor margins and finding satellite metastases are the reason for tumor recurrence. A synergistic method based on multimodality molecular imaging needs to be developed so as to achieve the complete extinction of the tumor cells. In this study, graphene oxide conjugated with gold nanostars and chelated with Gd through 1,4,7,10-tetraazacyclododecane-N,N′,N,N′-tetraacetic acid (DOTA) (GO-AuNS-DOTA-Gd) were prepared to target HCC-LM3-fLuc cells and used for therapy. For subcutaneous tumor, multimodality molecular imaging including photoacoustic imaging (PAI) and magnetic resonance imaging (MRI) and the related processing techniques were used to monitor the pharmacokinetics process of GO-AuNS-DOTA-Gd in order to determine the optimal time for treatment. For orthotopic tumor, MRI was used to delineate the tumor location and margin in vivo before treatment. Then handheld photoacoustic imaging system was used to determine the tumor location during the surgery and guided the photothermal therapy. The experiment result based on orthotopic tumor demonstrated that this synergistic method could effectively reduce tumor residual and satellite metastases by 85.71% compared with the routine photothermal method without handheld PAI guidance. These results indicate that this multimodality molecular imaging-guided photothermal therapy method is promising with a good prospect in clinical application.

Development and evaluation of a connective tissue phantom model for subsurface visualization of cancers requiring wide local excision

Wide local excision (WLE) of tumors with negative margins remains a challenge because surgeons cannot directly visualize the mass. Fluorescence-guided surgery (FGS) may improve surgical accuracy; however, conventional methods with direct surface tumor visualization are not immediately applicable, and properties of tissues surrounding the cancer must be considered. We developed a phantom model for sarcoma resection with the near-infrared fluorophore IRDye 800CW and used it to iteratively define the properties of connective tissues that typically surround sarcoma tumors. We then tested the ability of a blinded surgeon to resect fluorescent tumor-simulating inclusions with ∼1-cm margins using predetermined target fluorescence intensities and a Solaris open-air fluorescence imaging system. In connective tissue-simulating phantoms, fluorescence intensity decreased with increasing blood concentration and increased with increasing intralipid concentrations. Fluorescent inclusions could be resolved at ≥1-cm depth in all inclusion concentrations and sizes tested. When inclusion depth was held constant, fluorescence intensity decreased with decreasing volume. Using targeted fluorescence intensities, a blinded surgeon was able to successfully excise inclusions with ∼1-cm margins from fat- and muscle-simulating phantoms with inclusion-to-background contrast ratios as low as 2∶1. Indirect, subsurface FGS is a promising tool for surgical resection of cancers requiring WLE.

Bioluminescence Tomography Based on Gaussian Weighted Laplace Prior Regularization for In Vivo Morphological Imaging of Glioma

Bioluminescence tomography (BLT) is a powerful non-invasive molecular imaging tool for in vivo studies of glioma in mice. However, because of the light scattering and resulted ill-posed problems, it is challenging to develop a sufficient reconstruction method, which can accurately locate the tumor and define the tumor morphology in three-dimension. In this paper, we proposed a novel Gaussian weighted Laplace prior (GWLP) regularization method. It considered the variance of the bioluminescence energy between any two voxels inside an organ had a non-linear inverse relationship with their Gaussian distance to solve the over-smoothed tumor morphology in BLT reconstruction. We compared the GWLP with conventional Tikhonov and Laplace regularization methods through various numerical simulations and in vivo orthotopic glioma mouse model experiments. The in vivo magnetic resonance imaging and ex vivo green fluorescent protein images and hematoxylin-eosin stained images of whole head cryoslicing specimens were utilized as gold standards. The results demonstrated that GWLP achieved the highest accuracy in tumor localization and tumor morphology preservation. To the best of our knowledge, this is the first study that achieved such accurate BLT morphological reconstruction of orthotopic glioma without using any segmented tumor structure from any other structural imaging modalities as the prior for reconstruction guidance. This enabled BLT more suitable and practical for in vivo imaging of orthotopic glioma mouse models.

Self-prior strategy for organ reconstruction in fluorescence molecular tomography

The purpose of this study is to propose a strategy for organ reconstruction in fluorescence molecular tomography (FMT) without prior information from other imaging modalities, and to overcome the high cost and ionizing radiation caused by the traditional structural prior strategy. The proposed strategy is designed as an iterative architecture to solve the inverse problem of FMT. In each iteration, a short time Fourier transform (STFT) based algorithm is used to extract the self-prior information in the space-frequency energy spectrum with the assumption that the regions with higher fluorescence concentration have larger energy intensity, then the cost function of the inverse problem is modified by the self-prior information, and lastly an iterative Laplacian regularization algorithm is conducted to solve the updated inverse problem and obtains the reconstruction results. Simulations and in vivo experiments on liver reconstruction are carried out to test the performance of the self-prior strategy on organ reconstruction. The organ reconstruction results obtained by the proposed self-prior strategy are closer to the ground truth than those obtained by the iterative Tikhonov regularization (ITKR) method (traditional non-prior strategy). Significant improvements are shown in the evaluation indexes of relative locational error (RLE), relative error (RE) and contrast-to-noise ratio (CNR). The self-prior strategy improves the organ reconstruction results compared with the non-prior strategy and also overcomes the shortcomings of the traditional structural prior strategy. Various applications such as metabolic imaging and pharmacokinetic study can be aided by this strategy.

Activatable clinical fluorophore-quencher antibody pairs as dual molecular probes for the enhanced specificity of image-guided surgery

The emergence of fluorescently labeled therapeutic antibodies has given rise to molecular probes for image-guided surgery. However, the extraneous interstitial presence of an unbound and nonspecifically accumulated probe gives rise to false-positive detection of tumor tissue and margins. Thus, the concept of tumor-cell activation of smart probes provides a potentially superior mechanism of delineating tumor margins as well as small tumor deposits. The combination of molecular targeting with intracellular activation circumvents the presence of extracellular, nonspecific signals of targeted probe accumulation. Here, we present a demonstration of the clinical antibodies cetuximab (cet, anti-EGFR mAb) and trastuzumab (trast, anti-HER-2 mAb) conjugated to Alexa Fluor molecules and IRDye QC-1 quencher optimized at the ratio of 1∶2∶6 to provide the greatest degree of proteolytic fluorescence activation, synonymous with intracellular lysosomal degradation. The cet-AF-Q-C1 conjugate (1∶2∶6) provides up to 9.8-fold proteolytic fluorescence activation. By preparing a spectrally distinct, irrelevant sham IgG-AF-QC-1 conjugate, a dual-activatable probe approach is shown to enhance the specificity of imaging within an orthotopic AsPC-1 pancreatic cancer xenograft model. The dual-activatable approach warrants expedited clinical translation to improve the specificity of image-guided surgery by spectrally decomposing specific from nonspecific probe accumulation, binding, and internalization.

Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method

Fluorescence molecular tomography (FMT) is an important in vivo imaging modality to visualize physiological and pathological processes in small animals. However, FMT reconstruction is ill-posed and ill-conditioned due to strong optical scattering in deep tissues, which results in poor spatial resolution. It is well known that FMT image quality can be improved substantially by applying the structural guidance in the FMT reconstruction. An approach to introducing anatomical information into the FMT reconstruction is presented using the kernel method. In contrast to conventional methods that incorporate anatomical information with a Laplacian-type regularization matrix, the proposed method introduces the anatomical guidance into the projection model of FMT. The primary advantage of the proposed method is that it does not require segmentation of targets in the anatomical images. Numerical simulations and phantom experiments have been performed to demonstrate the proposed approach’s feasibility. Numerical simulation results indicate that the proposed kernel method can separate two FMT targets with an edge-to-edge distance of 1 mm and is robust to false-positive guidance and inhomogeneity in the anatomical image. For the phantom experiments with two FMT targets, the kernel method has reconstructed both targets successfully, which further validates the proposed kernel method.

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).

Dynamic Measurement of Tumor Vascular Permeability and Perfusion using a Hybrid System for Simultaneous Magnetic Resonance and Fluorescence Imaging

PURPOSE

Assessing tumor vascular features including permeability and perfusion is essential for diagnostic and therapeutic purposes. The aim of this study was to compare fluorescence and magnetic resonance imaging (MRI)-based vascular readouts in subcutaneously implanted tumors in mice by simultaneous dynamic measurement of tracer uptake using a hybrid fluorescence molecular tomography (FMT)/MRI system.

PROCEDURE

Vascular permeability was measured using a mixture of extravascular imaging agents, GdDOTA and the dye Cy5.5, and perfusion using a mixture of intravascular agents, Endorem and a fluorescent probe (Angiosense). Dynamic fluorescence reflectance imaging (dFRI) was integrated into the hybrid system for high temporal resolution.

RESULTS

Excellent correspondence between uptake curves of Cy5.5/GdDOTA and Endorem/Angiosense has been found with correlation coefficients R > 0.98. The two modalities revealed good agreement regarding permeability coefficients and centers-of-gravity of the imaging agent distribution.

CONCLUSION

The FMT/dFRI protocol presented is able to accurately map physiological processes and poses an attractive alternative to MRI for characterizing tumor neoangiogenesis.

Investigation of injection dose and camera integration time on quantifying pharmacokinetics of a Cy5.5-GX1 probe with dynamic fluorescence imaging in vivo

The aim of this article is to investigate the influence of a tracer injection dose (ID) and camera integration time (IT) on quantifying pharmacokinetics of Cy5.5-GX1 in gastric cancer BGC-823 cell xenografted mice. Based on three factors, including whether or not to inject free GX1, the ID of Cy5.5-GX1, and the camera IT, 32 mice were randomly divided into eight groups and received 60-min dynamic fluorescence imaging. Gurfinkel exponential model (GEXPM) and Lammertsma simplified reference tissue model (SRTM) combined with a singular value decomposition analysis were used to quantitatively analyze the acquired dynamic fluorescent images. The binding potential (Bp) and the sum of the pharmacokinetic rate constants (SKRC) of Cy5.5-GX1 were determined by the SRTM and EXPM, respectively. In the tumor region, the SKRC value exhibited an obvious trend with change in the tracer ID, but the Bp value was not sensitive to it. Both the Bp and SKRC values were independent of the camera IT. In addition, the ratio of the tumor-to-muscle region was correlated with the camera IT but was independent of the tracer ID. Dynamic fluorescence imaging in conjunction with a kinetic analysis may provide more quantitative information than static fluorescence imaging, especially for a priori information on the optimal ID of targeted probes for individual therapy.

Light sheet luminescence imaging with Cherenkov excitation in thick scattering media

Light scattering leads to a severe loss of axial and transverse resolution with depth into tissue, limiting accuracy and value of biomedical luminescence imaging techniques. High-resolution imaging beyond a few-millimeter depth is prohibited because diffusive transport dominates beyond a few scattering distances. In this study, light sheet imaging through scattering media is demonstrated using a radiotherapy linear accelerator to deliver well-defined thin scanned sheets of x-rays. These sheets produce Cherenkov light within the medium, which in turn excites luminescence of an optical probe across the sheet plane. This luminescence can then be imaged by an intensified camera positioned perpendicular to the sheet plane. The precise knowledge of the light sheet position within the medium allowed for efficient attenuation correction of the signal with depth as well as spatial deconvolution of the excitation light. Together these methods allowed for the first time, to the best of our knowledge, high-resolution imaging of tissue-equivalent phantoms up to 3 cm thick, yielding the precise position and shape of luminescent lesions located deep in tissue without the need for nonlinear image reconstruction.

Small-Animal Imaging Using Diffuse Fluorescence Tomography

Diffuse fluorescence tomography (DFT) has been developed to image the spatial distribution of fluorescence-tagged tracers in living tissue. This capability facilitates the recovery of any number of functional parameters, including enzymatic activity, receptor density, blood flow, and gene expression. However, deploying DFT effectively is complex and often requires years of know-how, especially for newer mutlimodal systems that combine DFT with conventional imaging systems. In this chapter, we step through the process of using MRI-DFT imaging of a receptor-targeted tracer in small animals.

In vivo quantifying molecular specificity of Cy5.5-labeled cyclic 9-mer peptide probe with dynamic fluorescence imaging

We quantified molecular specificity of Cy5.5-GX1 in vivo with dynamic fluorescence imaging to better understand its kinetic properties. According to whether or not free GX1 was injected and when it was injected, twelve of BGC-823 xenografted mice were randomly divided into three groups and underwent a 60 minute dynamic fluorescence scanning. Combined with a principal-component analysis, the binding potential (Bp) of the probe was determined by both Logan graphical analysis with reference tissue model (GARTM) and Lammertsma simplified reference tissue model (SRTM). The sum of the pharmacokinetic rate constants (SKRC) was quantified by the Gurfinkel exponential model (GEXPM). Cy5.5-GX1 specifically targeted tumor both in vitro and in vivo. We obtained similar quantification results of Bp (GARTM Bp = 0.582 ± 0.2655, SRTM Bp = 0.618 ± 0.2923), and obtained a good linear relation between the Bp value and the SKRC value. Our results indicate that the SKRC value is more suitable for an early-stage kinetic data analysis, and the Bp value depicts kinetic characteristics under the equilibrium state. Dynamic fluorescence imaging in conjunction with various kinetic models are optimal tools to quantify molecular specificity of the Cy5.5-GX1 probe in vivo.

An Inversion Scheme for Hybrid Fluorescence Molecular Tomography Using a Fuzzy Inference System

The imaging performance of fluorescence molecular tomography (FMT) improves when information from the underlying anatomy is incorporated into the inversion scheme, in the form of priors. The requirement for incorporation of priors has recently driven the development of hybrid FMT systems coupled to other modalities, such as X-ray CT and MRI. A critical methodological aspect in this modality relates to the particular method selected to incorporate prior information obtained from the anatomical imaging modality into the FMT inversion. We propose herein a new approach for utilizing prior information, which preferentially minimizes residual errors associated with measurements that better describe the anatomical segments considered. This preferential minimization was realized using a weighted least square (WLS) approach, where the weights were optimized using a Mamdani-type fuzzy inference system. The method of priors introduced herein was deployed as a two-step structured regularization approach and was verified with experimental measurements from phantoms as well as ex vivo and in vivo animal studies. The results demonstrate accurate performance and minimization of reconstruction bias, without requiring user input for setting the regularization parameters. As such, the proposed method offers significant progress in incorporation of anatomical priors in FMT and, as a result, in realization of the full potential of hybrid FMT.

Multimodal iron oxide (Fe3O4)-saturated lactoferrin nanocapsules as nanotheranostics for real-time imaging and breast cancer therapy of claudin-low, triple-negative (ER-/PR-/HER2-)

Aim: To unravel the multimodal nanotheranostic ability of Fe3O4-saturated bovine lactoferrin nanocapsules (FebLf NCs) in claudin-low, triple-negative breast cancer model. Materials & methods: Xenograft study was performed to examine biocompatibility, antitumor efficacy and multimodal nanotheranostic action in combination with near-infrared live mice imaging. Results: FebLf NCs exhibited a size range of 80 nm ± 5 nm with observed superparamagnetism. FebLf NCs successfully internalized into breast cancer cells through receptor-mediated endocytosis and induced apoptosis through the downregulation of inhibitor of apoptosis survivin and livin proteins. Investigations revealed a remarkable biocompatibility, anticancer efficacy of the FebLf NCs. Near-infrared imaging observations confirmed selective localization of multimodal FebLf NCs at the tumor site and lead to time-dependent reduction of tumor growth. Conclusion: FebLf NCs can be safe, biocompatible nanotheranostic approach for real-time imaging and monitoring the effect of drugs in real time and have potentials in future clinical trials.

Accelerating fDOT image reconstruction based on path-history fluorescence Monte Carlo model by using three-level parallel architecture

The excessive time required by fluorescence diffuse optical tomography (fDOT) image reconstruction based on path-history fluorescence Monte Carlo model is its primary limiting factor. Herein, we present a method that accelerates fDOT image reconstruction. We employ three-level parallel architecture including multiple nodes in cluster, multiple cores in central processing unit (CPU), and multiple streaming multiprocessors in graphics processing unit (GPU). Different GPU memories are selectively used, the data-writing time is effectively eliminated, and the data transport per iteration is minimized. Simulation experiments demonstrated that this method can utilize general-purpose computing platforms to efficiently implement and accelerate fDOT image reconstruction, thus providing a practical means of using path-history-based fluorescence Monte Carlo model for fDOT imaging.