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

Singular value decomposition metrics show limitations of detector design in diffuse fluorescence tomography

The spatial resolution and recovered contrast of images reconstructed from diffuse fluorescence tomography data are limited by the high scattering properties of light propagation in biological tissue. As a result, the image reconstruction process can be exceedingly vulnerable to inaccurate prior knowledge of tissue optical properties and stochastic noise. In light of these limitations, the optimal source-detector geometry for a fluorescence tomography system is non-trivial, requiring analytical methods to guide design. Analysis of the singular value decomposition of the matrix to be inverted for image reconstruction is one potential approach, providing key quantitative metrics, such as singular image mode spatial resolution and singular data mode frequency as a function of singular mode. In the present study, these metrics are used to analyze the effects of different sources of noise and model errors as related to image quality in the form of spatial resolution and contrast recovery. The image quality is demonstrated to be inherently noise-limited even when detection geometries were increased in complexity to allow maximal tissue sampling, suggesting that detection noise characteristics outweigh detection geometry for achieving optimal reconstructions

Advanced tomographic image reconstruction algorithms for Diffuse Optical Imaging

Diffuse Optical Imaging is relatively new set of imaging modality that use infrared and near infrared light to characterize the optical properties of biological tissue. The technology used is less expensive than other imaging modalities such as X-ray mammography, it is portable and can be used to monitor brain activation and cancer diagnosis, besides to aid to other imaging modalities and therapy treatments in the characterization of diseased tissue, i. e. X-ray, Magnetic Resonance Imaging and Radio Frequency Ablation. Due the optical properties of biological tissue near-infrared light is highly scattered, as a consequence, a limited amount of light is propagated thus making the image reconstruction process very challenging. Typically, diffuse optical image reconstructions require from several minutes to hours to produce an accurate image from the interaction of the photons and the chormophores of the studied medium. To this day, this limitation is still under investigation and there are several approaches that are close to the real-time image reconstruction operation. Diffuse Optical Imaging includes a variety of techniques such as functional Near-Infrared Spectroscopy (fNIRS), Diffuse Optical Tomography (DOT), Fluorescence Diffuse Optical Tomography (FDOT) and Spatial Frequency Domain imaging (SFDI). These emerging image reconstruction modalities aim to become routine modalities for clinical applications. Each technique presents their own advantages and limitations, but they have been successfully used in clinical trials such as brain activation analysis and breast cancer diagnosis by mapping the response of the vascularity within the tissue through the use of models that relate the interaction between the tissue and the path followed by the photons. One way to perform the image reconstruction process is by separating it in two stages: the forward problem and the inverse problem; the former is used to describe light propagation inside a medium and the latter is related to the reconstruction of the spatio-temporal distribution of the photons through the tissue. Iterative methods are used to solve both problems but the intrinsic complexity of photon transport in biological tissue makes the problem time-consuming and computationally expensive. The aim of this research is to apply a fast-forward solver based on reduced order models to Fluorescence Diffuse Optical Tomography and Spatial Frequency Domain Imaging to contribute to these modalities in their application of clinical trials. Previous work showed the capabilities of the reduced order models for real-time reconstruction of the absorption parameters in the brain of mice. Results demonstrated insignificant loss of quantitative and qualitative accuracy and the reconstruction was performed in a fraction of the time normally required on this kind of studies. The forward models proposed in this work, offer the capability to run three-dimensional image reconstructions in CPU-based computational systems in a fraction of the time required by image reconstructions methods that use meshes generated using the Finite Element Method. In the case of SFMI, the proposed approach is fused with the approach of the virtual sensor for CCD cameras to reduce the computational burden and to generate a three-dimensional map of the distribution of tissue optical properties. In this work, the use case of FDOT focused on the thorax of a mouse model with tumors in the lungs as the medium under investigation. The mouse model was studied under two- and three- dimension conditions. The two-dimensional case is presented to explain the process of creating the Reduced-Order Models. In this case, there is not a significant improvement in the reconstruction considering NIRFAST as the reference. The proposed approach reduced the reconstruction time to a quarter of the time required by NIRFAST, but the last one performed it in a couple of seconds. In contrast, the three-dimensional case exploited the capabilities of the Reduced-Order Models by reducing the time of the reconstruction from a couple of hours to several seconds, thus allowing a closer real-time reconstruction of the fluorescent properties of the interrogated medium. In the case of Spatial Frequency Domain Imaging, the use case considered a three-dimensional section of a human head that is analysed using a CCD camera and a spatially modulated light source that illuminates the mentioned head section. Using the principle of the virtual sensor, different regions of the CCD camera are clustered and then Reduced Order Models are generated to perform the image reconstruction of the absorption distribution in a fraction of the time required by the algorithm implemented on NIRFAST. The ultimate goal of this research is to contribute to the field of Diffuse Optical Imaging and propose an alternative solution to be used in the reconstruction process to those models already used in three-dimensional reconstructions of Fluorescence Diffuse Optical Tomography and Spatial Frequency Domain Imaging, thus offering the possibility to continuously monitor tissue obtaining results in a matter of seconds

Objective assessment of image quality (OAIQ) in fluorescence-enhanced optical imaging

The statistical evaluation of molecular imaging approaches for detecting, diagnosing, and monitoring molecular response to treatment are required prior to their adoption. The assessment of fluorescence-enhanced optical imaging is particularly challenging since neither instrument nor agent has been established. Small animal imaging does not address the depth of penetration issues adequately and the risk of administering molecular optical imaging agents into patients remains unknown. Herein, we focus upon the development of a framework for OAIQ which includes a lumpy-object model to simulate natural anatomical tissue structure as well as the non-specific distribution of fluorescent contrast agents. This work is required for adoption of fluorescence-enhanced optical imaging in the clinic. Herein, the imaging system is simulated by the diffusion approximation of the time-dependent radiative transfer equation, which describes near infra-red light propagation through clinically relevant volumes. We predict the time-dependent light propagation within a 200 cc breast interrogated with 25 points of excitation illumination and 128 points of fluorescent light collection. We simulate the fluorescence generation from Cardio-Green at tissue target concentrations of 1, 0.5, and 0.25 µM with backgrounds containing 0.01 µM. The fluorescence boundary measurements for 1 cc spherical targets simulated within lumpy backgrounds of (i) endogenous optical properties (absorption and scattering), as well as (ii) exogenous fluorophore crosssection are generated with lump strength varying up to 100% of the average background. The imaging data are then used to validate a PMBF/CONTN tomographic reconstruction algorithm. Our results show that the image recovery is sensitive to the heterogeneous background structures. Further analysis on the imaging data by a Hotelling observer affirms that the detection capability of the imaging system is adversely affected by the presence of heterogeneous background structures. The above issue is also addressed using the human-observer studies wherein multiple cases of randomly located targets superimposed on random heterogeneous backgrounds are used in a “double-blind” situation. The results of this study show consistency with the outcome of above mentioned analyses. Finally, the Hotelling observer’s analysis is used to demonstrate (i) the inverse correlation between detectability and target depth, and (ii) the plateauing of detectability with improved excitation light rejection

Video-Rate Fluorescence Molecular Tomography for Hand-held and Multimodal Molecular Imaging

In the United States, cancer is the second leading cause of death following heart disease. Although, a variety of treatment regimens are available, cancer management is complicated by the complexity of the disease and the variability, between people, of disease progression and response to therapy. Therefore, advancements in the methods and technologies for cancer diagnosis, prognosis and therapeutic monitoring are critical to improving the treatment of cancer patients. The development of improved imaging methods for early diagnosis of cancer and of near real-time monitoring of tumor response to therapy may improve outcomes as well as the quality of life of cancer patients. In the last decade, imaging methods including ultrasound, computed tomography: CT), magnetic resonance imaging: MRI), single photon emission computed tomography: SPECT), and positron emission tomography: PET), have revolutionized oncology. More recently optical techniques, that have access to unique molecular reporting strategies and functional contrasts, show promise for oncologic imaging This dissertation focuses on the development and optimization of a fiber-based, video-rate fluorescence molecular tomography: FMT) instrument. Concurrent acquisition of fluorescence and reference signals allowed the efficient generation of ratio-metric data for 3D image reconstruction. Accurate depth localization and high sensitivity to fluorescent targets were established to depths of \u3e10 mm. In vivo accumulation of indocyanine green dye was imaged in the region of the sentinel lymph node: SLN) following intradermal injection into the forepaw of rats. These results suggest that video-rate FMT has potential as a clinical tool for noninvasive mapping of SLN. Spatial and temporal co-registration of nuclear and optical images can enable the fusion of the information from these complementary molecular imaging modalities. A critical challenge is in integrating the optical and nuclear imaging hardware. Flexible fiber-based FMT systems provide a viable solution. The various imaging bore sizes of small animal nuclear imaging systems can potentially accommodate the FMT fiber imaging arrays. In addition FMT imaging facilitates co-registering the nuclear and optical contrasts in time. In this dissertation, the feasibility of integrating the fiber-based, video-rate FMT system with a commercial preclinical NanoSPECT/CT platform was established. Feasibility of in vivo imaging is demonstrated by tracking a monomolecular multimodal-imaging agent: MOMIA) during transport from the forepaw to the axillary lymph nodes region of a rat. These co-registered FMT/SPECT/CT imaging results with MOMIAs may facilitate the development of the next generation preclinical and clinical multimodal optical-nuclear platforms for a broad array of imaging applications, and help elucidate the underlying biological processes relevant to cancer diagnosis and therapy monitoring. Finally, I demonstrated that video-rate FMT is sufficiently fast to enable imaging of cardiac, respiratory and pharmacokinetic induced dynamic fluorescent signals. From these measurements, the image-derived input function and the real-time uptake of injected agents can be deduced for pharmacokinetic analysis of fluorescing agents. In a study comparing normal mice against mice liver disease, we developed anatomically guided dynamic FMT in conjunction with tracer kinetic modeling to quantify uptake rates of fluorescing agents. This work establishes fiber-based, video-rate FMT system as a practical and powerful tool that is well suited to a broad array of potential imaging applications, ranging from early disease detection, quantifying physiology and monitoring progression of disease and therapies

Visual Quality Enhancement in Optoacoustic Tomography using Active Contour Segmentation Priors

Segmentation of biomedical images is essential for studying and characterizing anatomical structures, detection and evaluation of pathological tissues. Segmentation has been further shown to enhance the reconstruction performance in many tomographic imaging modalities by accounting for heterogeneities of the excitation field and tissue properties in the imaged region. This is particularly relevant in optoacoustic tomography, where discontinuities in the optical and acoustic tissue properties, if not properly accounted for, may result in deterioration of the imaging performance. Efficient segmentation of optoacoustic images is often hampered by the relatively low intrinsic contrast of large anatomical structures, which is further impaired by the limited angular coverage of some commonly employed tomographic imaging configurations. Herein, we analyze the performance of active contour models for boundary segmentation in cross-sectional optoacoustic tomography. The segmented mask is employed to construct a two compartment model for the acoustic and optical parameters of the imaged tissues, which is subsequently used to improve accuracy of the image reconstruction routines. The performance of the suggested segmentation and modeling approach are showcased in tissue-mimicking phantoms and small animal imaging experiments.Comment: Accepted for publication in IEEE Transactions on Medical Imagin

Experimental imaging of asthma progression and therapeutic response in mouse lung models

Asthma ist eine Erkrankung die das komplette Immunsystems involviert, ein System so komplex, dass es sich nur unzureichend in-vitro studieren lässt. Daher haben sich Mausmodelle als ein unverzichtbares Werkzeug in der präklinischen Asthmaforschung etabliert. Da es sich weiterhin bei Asthma um eine Erkrankung handelt, die durch eine schnelle Änderung der Symptome gekennzeichnet ist, wäre longitudinale vorzugsweise nicht-invasive Bildgebung, insbesondere bei der Entwicklung und Bewertung neuer Therapiekonzepte von großem Interesse. Nachteilig hingegen ist, dass die Darstellung der Mauslunge in der Praxis auf Grund der Größe des Organs und, im Falle einer in vivo Bildgebung, durch die Bewegung des Brustkorbes sich als äußerst schwierig herausstellt. Die Vielzahl der Luft-Gewebe-Grenzflächen erzeugt starke Streuung in der optischen Bildgebung, der große Hohlraum der Lunge verursacht Suszeptibilitätsartefakte bei der MRT und die Rippen erschweren eine Ultraschallbildgebung. Aus diesen Gründen besteht ein großer Bedarf an neuen Bildgebungsverfahren, um die durch Asthma verursachten anatomischen, funktionalen und molekularen Veränderungen darstellen zu können. Um die Schwierigkeiten in der Lungenbildgebung bei Mäusen zu umgehen, habe ich mich auf drei wesentliche Bildgebungsstrategien fokussiert: A) anatomische Bildgebung durch “inline free propagation phase contrast computed tomography”, B) direkte Messung der Lungenfunktion durch “low dose planar cinematic x-ray imaging” und C) funktionale Bildgebung mit Hilfe der „near infrared fluorescence imaging“ in Kombination mit Antikörpern, die mit einem Fluoreszenzfarbstoff markiert wurden, oder “smart probes”, die in Gegenwart von Entzündungen aktiviert werden. Durch die Anwendung von “phase contrast computed tomography” für die anatomische Bildgebung war ich in der Lage morphologische Veränderung des Lungengewebes zu quantifizieren, indem ich lokal das Verhältnis zwischen Weichgewebe und Luft, das Zusammenziehen der Luftwege sowie das Anschwellen der Bronchialwände im asthmatischen Lungengewebe ausgewertet habe. Diese Parameter erlaubten es zwischen Mäusen von Asthmamodellen unterschiedlicher Schweregrade, therapierten und gesunden Mäusen zu unterscheiden. Zusätzlich ermöglichte diese Technik die Darstellung intra-tracheal applizierter Bariumsulfat markierter Makrophagen im Lungengewebe. Dies stellt meines Wissens die erste Kombination einer funktionalisierten Kontrastierung und hochauflösender Lungenbildgebung mittels CT unter in vivo ähnlichen Bedingungen dar. Um diese Ergebnisse mit dem Grad der asthmabedingten Kurzatmigkeit zu korrelieren, habe ich eine einfache und verlässige Methode entwickelt die es, basierend auf 2D Röntgen-videos niedriger Röntgendosis (~6,5mGy) erlaubt, in narkotisierten Mäusen die Lungenfunktion zu bewerten. Mit Hilfe dieser neuen Methode gelang es mir charakteristische Unterschiede in der Lungenfunktion von asthmatischen, therapierten und gesunden Mäusen in vivo über die Zeit nachzuweisen, und diese Resultate mit den Ergebnissen von CT und Histologie zu korrelieren. Das Verfahren wird derzeit von mir für die Anwendung an frei beweglichen und nicht narkotisierten Mäusen weiterentwickelt. Dies sollte zu einer deutlichen Stressreduktion für die Maus bei der Untersuchung führen und somit, vor allem in Asthma, im Gegensatz zu etablierten Verfahren wie Plethysmographie, die Erhebung validerer Messdaten erlauben. Mit Hilfe von „near infrared fluorescence imaging“ konnten wir in vivo und longitudinal erfolgreich verschiedene durch Asthma ausgelöste molekulare Veränderungen in der Mauslunge verfolgen. Erstens erlaubte die Verwendung einer neuen Polyglyzerol Probe mit dendritischer Struktur (MN2012) die spezifisch an Selektine bindet, die Darstellung der durch Asthma verursachten Entzündung der Lunge. Im Zuge dessen konnten wir nachweisen, dass sich MN2012  zur Darstellung von Enzymkinetiken bei Entzündungsreaktionen durch eine schnellere Kinetik und höher Spezifität als kommerziell erhältliche Proben auszeichnet. Zweitens haben wir gezeigt, dass in Kombination mit einem Fluoreszenz markiertem Antikörper gegen SiglecF, einem Antigen das hauptsächlich auf Eosinophilen exprimiert ist, Eosinophilie in asthmatischen Mäusen verfolgt und der Effekt einer Dexamethason Behandlung  ebenso dargestellt werden kann. Drittens konnten wir den Verbleib inhalierter fluoreszierender Nanopartikel in der Lunge der Maus in vivo untersuchen und dabei nachweisen, dass diese hauptsächlich von endogenen Makrophagen im Lungengewebe aufgenommen werden. Alle diese Techniken wurden gegeneinander und mittels histologischer Analyse und Fluoreszenzmikroskopie korreliert und validiert.  Zusammenfassend bilden die in meiner Dissertation entwickelten Lungenbildgebungsstrategien für Asthmamausmodelle eine Bildgebungsplattform, um sowohl spezifische Effekte in asthmatischen Mäusen unterschiedlichen Schweregrades als auch die Auswirkungen neuer Therapien abzubilden und im Detail zu untersuchen