MRI-coupled fluorescence tomography quantifies EGFR activity in brain tumors

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences

Glioma, the most common primary brain tumor in adults, can be difficult to discern radiologically from other brain lesions, which affects surgical planning and follow-up treatment. Recent advances in MRI demonstrate that preoperative diagnosis of glioma has stepped into molecular and algorithm-assisted levels. Specifically, the histology-based glioma classification is composed of multiple different molecular subtypes with distinct behavior, prognosis, and response to therapy, and now each aspect can be assessed by corresponding emerging MR sequences like amide proton transfer-weighted MRI, inflow-based vascular-space-occupancy MRI, and radiomics algorithm. As a result of this novel progress, the clinical practice of glioma has been updated. Accurate diagnosis of glioma at the molecular level can be achieved ahead of the operation to formulate a thorough plan including surgery radical level, shortened length of stay, flexible follow-up plan, timely therapy response feedback, and eventually benefit patients individually.

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.

Fluorescence-Guided Surgery: A Review on Timing and Use in Brain Tumor Surgery

Fluorescence-guided surgery (FGS) allows surgeons to have improved visualization of tumor tissue in the operating room, enabling maximal safe resection of malignant brain tumors. Over the past two decades, multiple fluorescent agents have been studied for FGS, including 5-aminolevulinic acid (5-ALA), fluorescein sodium, and indocyanine green (ICG). Both non-targeted and targeted fluorescent agents are currently being used in clinical practice, as well as under investigation, for glioma visualization and resection. While the efficacy of intraoperative fluorescence in studied fluorophores has been well established in the literature, the effect of timing on fluorophore administration in glioma surgery has not been as well depicted. In the past year, recent studies of 5-ALA use have shown that intraoperative fluorescence may persist beyond the previously studied window used in prior multicenter trials. Additionally, the use of fluorophores for different brain tumor types is discussed in detail, including a discussion of choosing the right fluorophore based on tumor etiology. In the following review, the authors will describe the temporal nature of the various fluorophores used in glioma surgery, what remains uncertain in FGS, and provide a guide for using fluorescence as a surgical adjunct in brain tumor surgery.

Visualization of Diagnostic and Therapeutic Targets in Glioma With Molecular Imaging

Gliomas, particularly high-grade gliomas including glioblastoma (GBM), represent the most common and malignant types of primary brain cancer in adults, and carry a poor prognosis. GBM has been classified into distinct subgroups over the years based on cellular morphology, clinical characteristics, biomarkers, and neuroimaging findings. Based on these classifications, differences in therapeutic response and patient outcomes have been established. Recently, the identification of complex molecular signatures of GBM has led to the development of diverse targeted therapeutic regimens and translation into multiple clinical trials. Chemical-, peptide-, antibody-, and nanoparticle-based probes have been designed to target specific molecules in gliomas and then be visualized with multimodality molecular imaging (MI) techniques including positron emission tomography (PET), single-photon emission computed tomography (SPECT), near-infrared fluorescence (NIRF), bioluminescence imaging (BLI), and magnetic resonance imaging (MRI). Thus, multiple molecules of interest can now be noninvasively imaged to guide targeted therapies with a potential survival benefit. Here, we review developments in molecular-targeted diagnosis and therapy in glioma, MI of these targets, and MI monitoring of treatment response, with a focus on the biological mechanisms of these advanced molecular probes. MI probes have the potential to noninvasively demonstrate the pathophysiologic features of glioma for diagnostic, treatment, and response assessment considerations for various targeted therapies, including immunotherapy. However, most MI tracers are in preclinical development, with only integrin α_Vβ₃ and isocitrate dehydrogenase (IDH)-mutant MI tracers having been translated to patients. Expanded international collaborations would accelerate translational research in the field of glioma MI.

Use of Intraoperative Fluorophores

Fluorescence-guided surgery provides surgeons with improved visualization of tumor tissue in the operating room to allow for maximal safe resection of brain tumors. Multiple fluorescent agents have been studied for fluorescence-guided surgery. Both nontargeted and targeted fluorescent agents are currently being used for glioblastoma multiforme visualization and resection. Fluorescence detection in the visible light or near infrared spectrum is possible. Visualization device advancements have permitted greater detection of fluorescence down to the cellular level, which may provide even greater ability for the neurosurgeon to resect tumors.

Development of a Mobile Fluorescence Tomography-guided System for Pre-clinical Radiotherapy Research

We proposed to build a mobile fluorescence tomography (mFT) system as an image-guided platform for pre-clinical radiotherapy research. The mFT system is expected to localize functional target/tumor, guide irradiation, and provide longitudinal treatment assessment.

A Comparison of the Efficiency of Using a Deep CNN Approach with Other Common Regression Methods for the Prediction of EGFR Expression in Glioblastoma Patients

To estimate epithermal growth factor receptor (EGFR) expression level in glioblastoma (GBM) patients using radiogenomic analysis of magnetic resonance images (MRI). A comparative study using a deep convolutional neural network (CNN)-based regression, deep neural network, least absolute shrinkage and selection operator (LASSO) regression, elastic net regression, and linear regression with no regularization was carried out to estimate EGFR expression of 166 GBM patients. Except for the deep CNN case, overfitting was prevented by using feature selection, and loss values for each method were compared. The loss values in the training phase for deep CNN, deep neural network, Elastic net, LASSO, and the linear regression with no regularization were 2.90, 8.69, 7.13, 14.63, and 21.76, respectively, while in the test phase, the loss values were 5.94, 10.28, 13.61, 17.32, and 24.19 respectively. These results illustrate that the efficiency of the deep CNN approach is better than that of the other methods, including Lasso regression, which is a regression method known for its advantage in high-dimension cases. A comparison between deep CNN, deep neural network, and three other common regression methods was carried out, and the efficiency of the CNN deep learning approach, in comparison with other regression models, was demonstrated.

MRI features can predict EGFR expression in lower grade gliomas: A voxel-based radiomic analysis

OBJECTIVE

To identify the magnetic resonance imaging (MRI) features associated with epidermal growth factor (EGFR) expression level in lower grade gliomas using radiomic analysis.

METHODS

270 lower grade glioma patients with known EGFR expression status were randomly assigned into training (n=200) and validation (n=70) sets, and were subjected to feature extraction. Using a logistic regression model, a signature of MRI features was identified to be predictive of the EGFR expression level in lower grade gliomas in the training set, and the accuracy of prediction was assessed in the validation set.

RESULTS

A signature of 41 MRI features achieved accuracies of 82.5% (area under the curve [AUC] = 0.90) in the training set and 90.0% (AUC = 0.95) in the validation set. This radiomic signature consisted of 25 first-order statistics or related wavelet features (including range, standard deviation, uniformity, variance), one shape and size-based feature (spherical disproportion), and 15 textural features or related wavelet features (including sum variance, sum entropy, run percentage).

CONCLUSIONS

A radiomic signature allowing for the prediction of the EGFR expression level in patients with lower grade glioma was identified, suggesting that using tumour-derived radiological features for predicting genomic information is feasible.

KEY POINTS

• EGFR expression status is an important biomarker for gliomas. • EGFR in lower grade gliomas could be predicted using radiogenomic analysis. • A logistic regression model is an efficient approach for analysing radiomic features.

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.

Agents for fluorescence-guided glioma surgery: a systematic review of preclinical and clinical results

BACKGROUND

Fluorescence-guided surgery (FGS) is a technique used to enhance visualization of tumor margins in order to increase the extent of tumor resection in glioma surgery. In this paper, we systematically review all clinically tested fluorescent agents for application in FGS for glioma and all preclinically tested agents with the potential for FGS for glioma.

METHODS

We searched the PubMed and Embase databases for all potentially relevant studies through March 2016. We assessed fluorescent agents by the following outcomes: rate of gross total resection (GTR), overall and progression-free survival, sensitivity and specificity in discriminating tumor and healthy brain tissue, tumor-to-normal ratio of fluorescent signal, and incidence of adverse events.

RESULTS

The search strategy resulted in 2155 articles that were screened by titles and abstracts. After full-text screening, 105 articles fulfilled the inclusion criteria evaluating the following fluorescent agents: 5-aminolevulinic acid (5-ALA) (44 studies, including three randomized control trials), fluorescein (11), indocyanine green (five), hypericin (two), 5-aminofluorescein-human serum albumin (one), endogenous fluorophores (nine) and fluorescent agents in a pre-clinical testing phase (30). Three meta-analyses were also identified.

CONCLUSIONS

5-ALA is the only fluorescent agent that has been tested in a randomized controlled trial and results in an improvement of GTR and progression-free survival in high-grade gliomas. Observational cohort studies and case series suggest similar outcomes for FGS using fluorescein. Molecular targeting agents (e.g., fluorophore/nanoparticle labeled with anti-EGFR antibodies) are still in the pre-clinical phase, but offer promising results and may be valuable future alternatives.

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.

Monoclonal antibody-conjugated superparamagnetic iron oxide nanoparticles for imaging of epidermal growth factor receptor-targeted cells and gliomas

The objective of this study was to successfully synthesize epidermal growth factor receptor monoclonal antibody-conjugated superparamagnetic iron oxide nanoparticles (EGFRmAb-SPIONs) and explore their biocompatibility and potential applications as a targeted magnetic resonance imaging (MRI) contrast agent for the EGFR-specific detection of brain glioma in vivo. After conjugation of EGFRmAb with SPIONs, the magnetic characteristics of EGFRmAb-SPIONs were investigated. Thereafter, the targeting abilities of EGFRmAb-SPIONs with MRI were qualitatively and quantitatively assessed in EGFR-positive C6 glioma cells in vitro and in a Wistar rat model bearing C6 glioma in vivo. Furthermore, the preliminary biocompatibility and toxicity of EGFRmAb-SPIONs were evaluated in normal rats through hematology assays and histopathologic analyses. Statistical analysis was performed using one-way analysis of variance and Student t-test, with a significance level of p < .05. From the results of EGFRmAb-SPION characterizations, the average particle size was 10.21 nm and the hydrodynamic diameter was 161.5 ± 2.12 nm. The saturation magnetization was 55 emu/g·Fe, and T2 relaxivity was 92.73 s-1mM-1 in distilled water. The preferential accumulation of the EGFRmAb-SPIONs within glioma and subsequent MRI contrast enhancement were demonstrated both in vitro in C6 cells and in vivo in rats bearing C6 glioma. After intravenous administration of EGFRmAb-SPIONs, T2-weighted MRI of the rat model with brain glioma exhibited an apparent hypointense region within glioma from 2 to 48 hours. The maximal image contrast was reached at 24 hours, where the signal intensity decreased and the R2 value increased by 30% compared to baseline. However, T2-weighted imaging of the rat model administered with SPIONs showed no visible signal changes within the tumor over the same time period. Moreover, no evident toxicities in vitro and in vivo with EGFRmAb-SPIONs were clearly identified based on the laboratory examinations. EGFRmAb-SPIONs could potentially be employed as a targeted contrast agent in the molecule-specific diagnosis of brain glioma in MRI.

Advances in optical imaging for pharmacological studies

Imaging approaches are an essential tool for following up over time representative parameters of in vivo models, providing useful information in pharmacological studies. Main advantages of optical imaging approaches compared to other imaging methods are their safety, straight-forward use and cost-effectiveness. A main drawback, however, is having to deal with the presence of high scattering and high absorption in living tissues. Depending on how these issues are addressed, three different modalities can be differentiated: planar imaging (including fluorescence and bioluminescence in vivo imaging), optical tomography, and optoacoustic approaches. In this review we describe the latest advances in optical in vivo imaging with pharmacological applications, with special focus on the development of new optical imaging probes in order to overcome the strong absorption introduced by different tissue components, especially hemoglobin, and the development of multimodal imaging systems in order to overcome the resolution limitations imposed by scattering.

Non-invasive molecular imaging for preclinical cancer therapeutic development

Molecular and non-invasive imaging are rapidly emerging fields in preclinical cancer drug discovery. This is driven by the need to develop more efficacious and safer treatments, the advent of molecular-targeted therapeutics, and the requirements to reduce and refine current preclinical in vivo models. Such bioimaging strategies include MRI, PET, single positron emission computed tomography, ultrasound, and optical approaches such as bioluminescence and fluorescence imaging. These molecular imaging modalities have several advantages over traditional screening methods, not least the ability to quantitatively monitor pharmacodynamic changes at the cellular and molecular level in living animals non-invasively in real time. This review aims to provide an overview of non-invasive molecular imaging techniques, highlighting the strengths, limitations and versatility of these approaches in preclinical cancer drug discovery and development.

Sensitivity of MRI-guided near-infrared spectroscopy clinical breast exam data and its impact on diagnostic performance

In this study, data from breast MRI-guided near infrared spectroscopy (NIRS) exams delivered to 44 patients scheduled for surgical resection (ending in 16 benign and 28 malignant diagnoses) were analyzed using a spatial sensitivity metric to quantify the adequacy of the optical measurements for interrogating the tumor region of interest, as derived from the concurrent MRI scan. Along with positional sensitivity, the incorporation of spectral priors and the selection of an appropriate regularization parameter in the image reconstruction were considered, and found to influence the diagnostic accuracy of the recovered images. Once optimized, the MRI/NIRS data was able to differentiate the malignant from benign lesions through both total hemoglobin (p = 0.0037) and tissue optical index (p = 0.00019), but required the relative spatial sensitivity of the optical measurement data to each lesion to be above 1%. Spectral constraints implemented during the reconstruction were required to obtain statistically significant diagnostic information from images of H2O, lipids, and Tissue Optical Index (TOI). These results confirm the need for optical systems that have homogenous spatial coverage of the breast while still being able to accommodate the normal range of breast sizes.

FMT-PCCT: hybrid fluorescence molecular tomography-x-ray phase-contrast CT imaging of mouse models

The implementation of hybrid fluorescence molecular tomography (FMT) and X-ray computed tomography (CT) has been shown to be a necessary development, not only for combining anatomical with functional and molecular contrast, but also for generating optical images of high accuracy. FMT affords highly sensitive 3-D imaging of fluorescence bio-distribution, but in stand-alone form it offers images of low resolution. It was shown that FMT accuracy significantly improves by considering anatomical priors from CT. Conversely, CT generally suffers from low soft tissue contrast. Therefore utilization of CT data as prior information in FMT inversion is challenging when different internal organs are not clearly differentiated. Instead, we combined herein FMT with emerging X-ray phase-contrast CT (PCCT). PCCT relies on phase shift differences in tissue to achieve soft tissue contrast superior to conventional CT. We demonstrate for the first time FMT-PCCT imaging of different animal models, where FMT and PCCT scans were performed in vivo and ex vivo, respectively. The results show that FMT-PCCT expands the potential of FMT in imaging lesions with otherwise low or no CT contrast, while retaining the cost benefits of CT and simplicity of hybrid device realizations. The results point to the most accurate FMT performance to date.

Effective cellular internalization of silica-coated CdSe quantum dots for high contrast cancer imaging and labelling applications

The possibility of developing novel contrast imaging agents for cancer cellular labelling and fluorescence imaging applications were explored using silica-coated cadmium selenide (CdSe) quantum dots (QDs). The time dependent cellular internalization efficiency study was carried out using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) and Confocal Laser Scanning Microscopy (cLSM) after exposing QDs to stem cells and cancer cells. The strong fluorescence from the cytoplasm confirmed that the QDs were efficiently internalized by the cells. The internalization maxima were observed at the fourth hour of incubation in both stem and cancer cells. Further, the in vitro fluorescence imaging as well as localization study of QDs were performed in various cells. Moreover, high contrast in vivo tumor imaging efficiency of silica-coated CdSe QDs was performed in ultrathin sections of tumor mice, and the results confirmed its effective role in cellular imaging and labelling in cancer and other diseases.

Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for diffuse optical tomography

Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform.

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.

Dynamic dual-tracer MRI-guided fluorescence tomography to quantify receptor density in vivo

The up-regulation of cell surface receptors has become a central focus in personalized cancer treatment; however, because of the complex nature of contrast agent pharmacokinetics in tumor tissue, methods to quantify receptor binding in vivo remain elusive. Here, we present a dual-tracer optical technique for noninvasive estimation of specific receptor binding in cancer. A multispectral MRI-coupled fluorescence molecular tomography system was used to image the uptake kinetics of two fluorescent tracers injected simultaneously, one tracer targeted to the receptor of interest and the other tracer a nontargeted reference. These dynamic tracer data were then fit to a dual-tracer compartmental model to estimate the density of receptors available for binding in the tissue. Applying this approach to mice with deep-seated gliomas that overexpress the EGF receptor produced an estimate of available receptor density of 2.3 ± 0.5 nM (n = 5), consistent with values estimated in comparative invasive imaging and ex vivo studies.

Optical imaging of tumor microenvironment

Tumor microenvironment plays important roles in tumor development and metastasis. Features of the tumor microenvironment that are significantly different from normal tissues include acidity, hypoxia, overexpressed proteases and so on. Therefore, these features can serve as not only biomarkers for tumor diagnosis but also theraputic targets for tumor treatment. Imaging modalities such as optical, positron emission tomography (PET) and magnetic resonance imaging (MRI) have been intensively applied to investigate tumor microenvironment. Various imaging probes targeting pH, hypoxia and proteases in tumor microenvironment were thus well developed. In this review, we will focus on recent examples on fluorescent probes for optical imaging of tumor microenvironment. Construction of these fluorescent probes were based on characteristic feature of pH, hypoxia and proteases in tumor microenvironment. Strategies for development of these fluorescent probes and applications of these probes in optical imaging of tumor cells or tissues will be discussed in this review paper.

Imaging a photodynamic therapy photosensitizer in vivo with a time-gated fluorescence tomography system

We report the tomographic imaging of a photodynamic therapy (PDT) photosensitizer, 2-(1-hexyloxyethyl)-2-devinyl pyropheophorbide-a (HPPH) in vivo with time-domain fluorescence diffuse optical tomography (TD-FDOT). Simultaneous reconstruction of fluorescence yield and lifetime of HPPH was performed before and after PDT. The methodology was validated in phantom experiments, and depth-resolved in vivo imaging was achieved through simultaneous three-dimensional (3-D) mappings of fluorescence yield and lifetime contrasts. The tomographic images of a human head-and-neck xenograft in a mouse confirmed the preferential uptake and retention of HPPH by the tumor 24-h post-injection. HPPH-mediated PDT induced significant changes in fluorescence yield and lifetime. This pilot study demonstrates that TD-FDOT may be a good imaging modality for assessing photosensitizer distributions in deep tissue during PDT monitoring.

Protoporphyrin IX fluorescence contrast in invasive glioblastomas is linearly correlated with Gd enhanced magnetic resonance image contrast but has higher diagnostic accuracy

The sensitivity and specificity of in vivo magnetic resonance (MR) imaging is compared with production of protoporphyrin IX (PpIX), determined ex vivo, in a diffusely infiltrating glioma. A human glioma transfected with green fluorescent protein, displaying diffuse, infiltrative growth, was implanted intracranially in athymic nude mice. Image contrast from corresponding regions of interest (ROIs) in in vivo MR and ex vivo fluorescence images was quantified. It was found that all tumor groups had statistically significant PpIX fluorescence contrast and that PpIX contrast demonstrated the best predictive power for tumor presence. Contrast from gadolinium enhanced T1-weighted (T1W+Gd) and absolute T2 images positively predicted the presence of a tumor, confirmed by the GFP positive (GFP+) and hematoxylin and eosin positive (H&E+) ROIs. However, only the absolute T2 images had predictive power from controls in ROIs that were GFP+ but H&E negative. Additionally, PpIX fluorescence and T1W+Gd image contrast were linearly correlated in both the GFP+ (r = 0.79, p<1×10(-8)) and H&E+ (r = 0.74, p<0.003) ROIs. The trace diffusion images did not have predictive power or significance from controls. This study indicates that gadolinium contrast enhanced MR images can predict the presence of diffuse tumors, but PpIX fluorescence is a better predictor regardless of tumor vascularity.

Rational chemical design of the next generation of molecular imaging probes based on physics and biology: mixing modalities, colors and signals

In recent years, numerous in vivo molecular imaging probes have been developed. As a consequence, much has been published on the design and synthesis of molecular imaging probes focusing on each modality, each type of material, or each target disease. More recently, second generation molecular imaging probes with unique, multi-functional, or multiplexed characteristics have been designed. This critical review focuses on (i) molecular imaging using combinations of modalities and signals that employ the full range of the electromagnetic spectra, (ii) optimized chemical design of molecular imaging probes for in vivo kinetics based on biology and physiology across a range of physical sizes, (iii) practical examples of second generation molecular imaging probes designed to extract complementary data from targets using multiple modalities, color, and comprehensive signals (277 references).

Sparsity-driven reconstruction for FDOT with anatomical priors

In this paper we propose a method based on (2, 1)-mixed-norm penalization for incorporating a structural prior in FDOT image reconstruction. The effect of (2, 1)-mixed-norm penalization is twofold: first, a sparsifying effect which isolates few anatomical regions where the fluorescent probe has accumulated, and second, a regularization effect inside the selected anatomical regions. After formulating the reconstruction in a variational framework, we analyze the resulting optimization problem and derive a practical numerical method tailored to (2, 1)-mixed-norm regularization. The proposed method includes as particular cases other sparsity promoting regularization methods such as l(1)-norm penalization and total variation penalization. Results on synthetic and experimental data are presented.

Fluorescence molecular tomography: principles and potential for pharmaceutical research

Fluorescence microscopic imaging is widely used in biomedical research to study molecular and cellular processes in cell culture or tissue samples. This is motivated by the high inherent sensitivity of fluorescence techniques, the spatial resolution that compares favorably with cellular dimensions, the stability of the fluorescent labels used and the sophisticated labeling strategies that have been developed for selectively labeling target molecules. More recently, two and three-dimensional optical imaging methods have also been applied to monitor biological processes in intact biological organisms such as animals or even humans. These whole body optical imaging approaches have to cope with the fact that biological tissue is a highly scattering and absorbing medium. As a consequence, light propagation in tissue is well described by a diffusion approximation and accurate reconstruction of spatial information is demanding. While in vivo optical imaging is a highly sensitive method, the signal is strongly surface weighted, i.e., the signal detected from the same light source will become weaker the deeper it is embedded in tissue, and strongly depends on the optical properties of the surrounding tissue. Derivation of quantitative information, therefore, requires tomographic techniques such as fluorescence molecular tomography (FMT), which maps the three-dimensional distribution of a fluorescent probe or protein concentration. The combination of FMT with a structural imaging method such as X-ray computed tomography (CT) or Magnetic Resonance Imaging (MRI) will allow mapping molecular information on a high definition anatomical reference and enable the use of prior information on tissue's optical properties to enhance both resolution and sensitivity. Today many of the fluorescent assays originally developed for studies in cellular systems have been successfully translated for experimental studies in animals. The opportunity of monitoring molecular processes non-invasively in the intact organism is highly attractive from a diagnostic point of view but even more so for the drug developer, who can use the techniques for proof-of-mechanism and proof-of-efficacy studies. This review shall elucidate the current status and potential of fluorescence tomography including recent advances in multimodality imaging approaches for preclinical and clinical drug development.

Combined PET/MRI: one step further in multimodality imaging

Given the need for sophisticated in vivo detection techniques to better characterize the cellular and subcellular processes in animals and humans, molecular imaging has become an important discipline. Techniques in molecular imaging have developed from stand alone modalities to multimodality methods. Among these, the combination of positron emission tomography (PET) and computed tomography (CT) is a successful imaging method and has become an important tool in clinical practice. Technological approaches that combine magnetic resonance imaging (MRI) with diffuse optical tomography (DOT), fluorescence tomography (FT) and PET have now been introduced. PET/MRI and the resulting combination of molecular, morphological and functional information will pave the way for a better understanding of physiological and disease mechanisms in preclinical and clinical settings.

Comparing implementations of magnetic-resonance-guided fluorescence molecular tomography for diagnostic classification of brain tumors

Fluorescence molecular tomography (FMT) systems coupled to conventional imaging modalities such as magnetic resonance imaging (MRI) and computed tomography provide unique opportunities to combine data sets and improve image quality and content. Yet, the ideal approach to combine these complementary data is still not obvious. This preclinical study compares several methods for incorporating MRI spatial prior information into FMT imaging algorithms in the context of in vivo tissue diagnosis. Populations of mice inoculated with brain tumors that expressed either high or low levels of epidermal growth factor receptor (EGFR) were imaged using an EGF-bound near-infrared dye and a spectrometer-based MRI-FMT scanner. All data were spectrally unmixed to extract the dye fluorescence from the tissue autofluorescence. Methods to combine the two data sets were compared using student's t-tests and receiver operating characteristic analysis. Bulk fluorescence measurements that made up the optical imaging data set were also considered in the comparison. While most techniques were able to distinguish EGFR(+) tumors from EGFR(-) tumors and control animals, with area-under-the-curve values=1, only a handful were able to distinguish EGFR(-) tumors from controls. Bulk fluorescence spectroscopy techniques performed as well as most imaging techniques, suggesting that complex imaging algorithms may be unnecessary to diagnose EGFR status in these tissue volumes.

A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging

Three dimensional image reconstruction for multi-modality optical spectroscopy systems needs computationally efficient forward solvers with minimum meshing complexity, while allowing the flexibility to apply spatial constraints. Existing models based on the finite element method (FEM) require full 3D volume meshing to incorporate constraints related to anatomical structure via techniques such as regularization. Alternate approaches such as the boundary element method (BEM) require only surface discretization but assume homogeneous or piece-wise constant domains that can be limiting. Here, a coupled finite element-boundary element method (coupled FE-BEM) approach is demonstrated for modeling light diffusion in 3D, which uses surfaces to model exterior tissues with BEM and a small number of volume nodes to model interior tissues with FEM. Such a coupled FE-BEM technique combines strengths of FEM and BEM by assuming homogeneous outer tissue regions and heterogeneous inner tissue regions. Results with FE-BEM show agreement with existing numerical models, having RMS differences of less than 0.5 for the logarithm of intensity and 2.5 degrees for phase of frequency domain boundary data. The coupled FE-BEM approach can model heterogeneity using a fraction of the volume nodes (4-22%) required by conventional FEM techniques. Comparisons of computational times showed that the coupled FE-BEM was faster than stand-alone FEM when the ratio of the number of surface to volume nodes in the mesh (N(s)/N(v)) was less than 20% and was comparable to stand-alone BEM ( ± 10%).

Development and applications of photo-triggered theranostic agents

Theranostics, the fusion of therapy and diagnostics for optimizing efficacy and safety of therapeutic regimes, is a growing field that is paving the way towards the goal of personalized medicine for the benefit of patients. The use of light as a remote-activation mechanism for drug delivery has received increased attention due to its advantages in highly specific spatial and temporal control of compound release. Photo-triggered theranostic constructs could facilitate an entirely new category of clinical solutions which permit early recognition of the disease by enhancing contrast in various imaging modalities followed by the tailored guidance of therapy. Finally, such theranostic agents could aid imaging modalities in monitoring response to therapy. This article reviews recent developments in the use of light-triggered theranostic agents for simultaneous imaging and photoactivation of therapeutic agents. Specifically, we discuss recent developments in the use of theranostic agents for photodynamic-, photothermal- or photo-triggered chemotherapy for several diseases.