Validation and quality assessment of hybrid fluorescence-mediated computed tomography in deep tissue regions

Fluorescence imaging is a well-established and widely used technology in many research areas. Fluorescence images can be acquired even in 3D by using confocal and 2-photon microscopy, but only in a very low depth of around 100 to 200 µm. An improvement in the field of fluorescence imaging was the invention of fluorescence-mediated tomography (FMT). FMT imaging enables a non-invasive, three-dimensional, and longitudinal assessment of the distribution of fluorescent molecules for example in the whole murine body. However, FMT imaging was practically restricted to superficial structures for a very long time, because the irregular mouse shape and heterogeneous absorption and scattering coefficients of biological chromophores such as hemoglobin, melanin, and fat, hamper a correct fluorescence signal reconstruction in deep regions. This obstacle was overcome by combining FMT with an additional imaging modality, computed tomography (CT), that provides anatomical information and promotes a more accurate organ segmentation. Nevertheless, the validation and quality assessment of hybrid fluorescence-mediated computed tomography was and is still challenging. For validation purposes, plastic-, agarose-, gelatin-based or 3D-printed phantoms are intensively used. However, they are not representative for in vivo experiments since the specific absorption and scattering coefficients of biological tissues depend on oxygenation state, are highly heterogeneous, difficult to measure, and thus, hard to be simulated with phantoms. Therefore, the aim of my thesis is to validate hybrid FMT-CT imaging especially in deep tissue regions and evidence its suitability for preclinical imaging studies. In my first publication, I established an in vivo protocol based on rectal insertions containing specific amounts of fluorescent dyes to assess the sensitivity and accuracy of 3D fluorescence imaging. Thereby, I demonstrate that the improved FMT-CT reconstruction algorithm allows an accurate detection of fluorescence signals in deep tissue regions even in a picomolar range. Thus, preclinical imaging studies can be performed to determine fluorescence intensities in the entire body. As part of these studies, a huge number of FMT-CT data are generated through multiple groups, animals, probes, and points in time. In order to assess these images, single organs or regions need to be segmented, e.g. by manual delineation. However, this is a time-consuming, error-prone, and user-dependent approach with a low reproducibility. To facilitate the development of more reliable automated segmentation algorithms for future FMT-CT studies, I introduce a CT database consisting of native and contrast-enhanced CT scans along with 3D organ segmentations in my second publication. By performing over 225 whole body organ segmentations and calculation of the Sørensen-Dice coefficient, I demonstrate high user-dependent errors due to manual analysis especially for liver and spleen. In summary, both publications together contribute towards establishment of FMT-CT imaging as an accurate, robust, and efficient tool for basic and applied science

A preclinical micro-computed tomography database including 3D whole body organ segmentations

The gold-standard of preclinical micro-computed tomography (μCT) data processing is still manual delineation of complete organs or regions by specialists. However, this method is time-consuming, error-prone, has limited reproducibility, and therefore is not suitable for large-scale data analysis. Unfortunately, robust and accurate automated whole body segmentation algorithms are still missing. In this publication, we introduce a database containing 225 murine 3D whole body μCT scans along with manual organ segmentation of most important organs including heart, liver, lung, trachea, spleen, kidneys, stomach, intestine, bladder, thigh muscle, bone, as well as subcutaneous tumors. The database includes native and contrast-enhanced, regarding spleen and liver, μCT data. All scans along with organ segmentation are freely accessible at the online repository Figshare. We encourage researchers to reuse the provided data to evaluate and improve methods and algorithms for accurate automated organ segmentation which may reduce manual segmentation effort, increase reproducibility, and even reduce the number of required laboratory animals by reducing a source of variability and having access to a reliable reference group

Mixing Matrix-corrected Whole-body Pharmacokinetic Modeling Using Longitudinal Micro-computed Tomography and Fluorescence-mediated Tomography

Purpose!#!Pharmacokinetic modeling can be applied to quantify the kinetics of fluorescently labeled compounds using longitudinal micro-computed tomography and fluorescence-mediated tomography (μCT-FMT). However, fluorescence blurring from neighboring organs or tissues and the vasculature within tissues impede the accuracy in the estimation of kinetic parameters. Contributions of elimination and retention activities of fluorescent probes inside the kidneys and liver can be hard to distinguish by a kinetic model. This study proposes a deconvolution approach using a mixing matrix to model fluorescence contributions to improve whole-body pharmacokinetic modeling.!##!Procedures!#!In the kinetic model, a mixing matrix was applied to unmix the fluorescence blurring from neighboring tissues and blood vessels and unmix the fluorescence contributions of elimination and retention in the kidney and liver compartments. Accordingly, the kinetic parameters of the hepatobiliary and renal elimination routes and five major retention sites (the kidneys, liver, bone, spleen, and lung) were investigated in simulations and in an in vivo study. In the latter, the pharmacokinetics of four fluorescently labeled compounds (indocyanine green (ICG), HITC-iodide-microbubbles (MB), Cy7-nanogels (NG), and OsteoSense 750 EX (OS)) were evaluated in BALB/c nude mice.!##!Results!#!In the simulations, the corrected modeling resulted in lower relative errors and stronger linear relationships (slopes close to 1) between the estimated and simulated parameters, compared to the uncorrected modeling. For the in vivo study, MB and NG showed significantly higher hepatic retention rates (P<0.05 and P<0.05, respectively), while OS had smaller renal and hepatic retention rates (P<0.01 and P<0.01, respectively). Additionally, the bone retention rate of OS was significantly higher (P<0.01).!##!Conclusions!#!The mixing matrix correction improves pharmacokinetic modeling and thus enables a more accurate assessment of the biodistribution of fluorescently labeled pharmaceuticals by μCT-FMT

An Anatomical Thermal 3D Model in Preclinical Research: Combining CT and Thermal Images

Even though animal trials are a controversial topic, they provide knowledge about diseases and the course of infections in a medical context. To refine the detection of abnormalities that can cause pain and stress to the animal as early as possible, new processes must be developed. Due to its noninvasive nature, thermal imaging is increasingly used for severity assessment in animal-based research. Within a multimodal approach, thermal images combined with anatomical information could be used to simulate the inner temperature profile, thereby allowing the detection of deep-seated infections. This paper presents the generation of anatomical thermal 3D models, forming the underlying multimodal model in this simulation. These models combine anatomical 3D information based on computed tomography (CT) data with a registered thermal shell measured with infrared thermography. The process of generating these models consists of data acquisition (both thermal images and CT), camera calibration, image processing methods, and structure from motion (SfM), among others. Anatomical thermal 3D models were successfully generated using three anesthetized mice. Due to the image processing improvement, the process was also realized for areas with few features, which increases the transferability of the process. The result of this multimodal registration in 3D space can be viewed and analyzed within a visualization tool. Individual CT slices can be analyzed axially, sagittally, and coronally with the corresponding superficial skin temperature distribution. This is an important and successfully implemented milestone on the way to simulating the internal temperature profile. Using this temperature profile, deep-seated infections and inflammation can be detected in order to reduce animal suffering

Bone regeneration using composite non-demineralized xenogenic dentin with beta-tricalcium phosphate in experimental alveolar cleft repair in a rabbit model

Abstract Background Alveolar cleft repair is performed via bone grafting procedure to restore the dental arch continuity. A suitable bone substitute materials should possess osteoinductive and osteoconductive properties, to promote new bone formation, along with a slowly resorbable scaffold that is subsequently replaced with functionally viable bone. Calcium phosphate biomaterials have long proved their efficacy as bone replacement materials. Dentin in several forms has also demonstrated its possibility to be used as bone graft replacement material in several studies. The purpose of this study was to evaluate bone regeneration pattern and quantify bone formation after grafting pre-established experimental alveolar clefts defects model in rabbits using composite xenogenic dentin and β-TCP in comparison to β-TCP alone. Methods Unilateral alveolar cleft defects were created in 16 New Zealand rabbits according to previously described methodology. Alveolar clefts were allowed 8 weeks healing period. 8 defects were filled with β-TCP, whereas 8 defects filled with composite xenogenic dentin with β-TCP. Bone regeneration of the healed defects was compared at the 8 weeks after intervention. Quantification of bone formation was analyzed using micro-computed tomography (µCT) and histomorphometric analysis. Results µCT and histomorphometric analysis revealed that defects filled with composite dentin/β-TCP showed statistically higher bone volume fraction, bone mineral density and percentage residual graft volume when compared to β-TCP alone. An improved surgical handling of the composite dentin/β-TCP graft was also noted. Conclusions Composite xenogenic dentin/β-TCP putty expresses enhanced bone regeneration compared to β-TCP alone in the reconstruction of rabbit alveolar clefts defects

Data Curation for Preclinical and Clinical Multimodal Imaging Studies

Purpose: In biomedical research, imaging modalities help discover pathological mechanisms to develop and evaluate novel diagnostic and theranostic approaches. However, while standards for data storage in the clinical medical imaging field exist, data curation standards for biomedical research are yet to be established. This work aimed at developing a free secure file format for multimodal imaging studies, supporting common in vivo imaging modalities up to five dimensions as a step towards establishing data curation standards for biomedical research. Procedures: Images are compressed using lossless compression algorithm. Cryptographic hashes are computed on the compressed image slices. The hashes and compressions are computed in parallel, speeding up computations depending on the number of available cores. Then, the hashed images with digitally signed timestamps are cryptographically written to file. Fields in the structure, compressed slices, hashes, and timestamps are serialized for writing and reading from files. The C++ implementation is tested on multimodal data from six imaging sites, well-documented, and integrated into a preclinical image analysis software. Results: The format has been tested with several imaging modalities including fluorescence molecular tomography/x-ray computed tomography (CT), positron emission tomography (PET)/CT, single-photon emission computed tomography/CT, and PET/magnetic resonance imaging. To assess performance, we measured the compression rate, ratio, and time spent in compression. Additionally, the time and rate of writing and reading on a network drive were measured. Our findings demonstrate that we achieve close to 50 % reduction in storage space for μCT data. The parallelization speeds up the hash computations by a factor of 4. We achieve a compression rate of 137 MB/s for file of size 354 MB. Conclusions: The development of this file format is a step to abstract and curate common processes involved in preclinical and clinical multimodal imaging studies in a standardized way. This work also defines better interface between multimodal imaging modalities and analysis software.RST/Biomedical Imagin