Bildgebende Charakterisierung und Quantifizierung der Angiogenese bei Arthritis mittels μCT im Mausmodell

Angiogenesis is a key pathophysiological process in chronic inflammatory reactions, especially in arthritis, the progression and course of the disease influences. For quantification of changes of bone blood flow in mice with rheumatoid arthritis (RA)a multi-level segmentation method was developed. The blood vessels in the area of ​​inflamed knee joint were segmented and then quantitative 3D histomorphometric parameters were calculated. Two groups of mice (WT and RA) were investigated in vitro and the results compared to each other.Angiogenese ist ein wesentlicher pathophysiologischer Prozess bei chronischen Entz¨undungsreaktionen, insbesondere bei Arthritis, der das Fortschreiten und den Verlauf der Krankheit beeinflusst. Bei der Suche nach m¨oglichen Arthritistherapien sind die therapeutischen Ans¨atze gegen Angiogenese von großem Interesse. Um die ¨Anderungen der Knochendurchblutung bei M¨ausen mit rheumatoider Arthritis (RA) zu quantifizieren, wurde ein mehrstufiges Segmentierungsverfahren entwickelt. Dabei wurden die Blutgef¨aße im Bereich des entz¨undetes Kniegelenks segmentiert und anschließend quantitative 3D histomorphometrische Parameter berechnet. Zwei Gruppen von M¨ause (RA und WT) wurden in-vitro untersucht und die Ergebnisse miteinander verglichen

Longitudinal Imaging of the Ageing Mouse

Several non-invasive imaging techniques are used to investigate the effect of pathologies and treatments over time in mouse models. Each preclinical in vivo technique provides longitudinal and quantitative measurements of changes in tissues and organs, which are fundamental for the evaluation of alterations in phenotype due to pathologies, interventions and treatments. However, it is still unclear how these imaging modalities can be used to study ageing with mice models. Almost all age related pathologies in mice such as osteoporosis, arthritis, diabetes, cancer, thrombi, dementia, to name a few, can be imaged in vivo by at least one longitudinal imaging modality. These measurements are the basis for quantification of treatment effects in the development phase of a novel treatment prior to its clinical testing. Furthermore, the non-invasive nature of such investigations allows the assessment of different tissue and organ phenotypes in the same animal and over time, providing the opportunity to study the dysfunction of multiple tissues associated with the ageing process. This review paper aims to provide an overview of the applications of the most commonly used in vivo imaging modalities used in mouse studies: micro-computed-tomography, preclinical magnetic-resonance-imaging, preclinical positron-emission-tomography, preclinical single photon emission computed tomography, ultrasound, intravital microscopy, and whole body optical imaging

Characterization and quantification of angiogenesis in rheumatoid arthritis in a mouse model using Micro-CT

Angiogenese ist ein wesentlicher pathophysiologischer Prozess bei chronischen Entz¨undungsreaktionen, insbesondere bei Arthritis, der das Fortschreiten und den Verlauf der Krankheit beeinflusst. Bei der Suche nach m¨oglichen Arthritistherapien sind die therapeutischen Ans¨atze gegen Angiogenese von großem Interesse. Um die ¨Anderungen der Knochendurchblutung bei M¨ausen mit rheumatoider Arthritis (RA) zu quantifizieren, wurde ein mehrstufiges Segmentierungsverfahren entwickelt. Dabei wurden die Blutgef¨aße im Bereich des entz¨undetes Kniegelenks segmentiert und anschließend quantitative 3D histomorphometrische Parameter berechnet. Zwei Gruppen von M¨ause (RA und WT) wurden in-vitro untersucht und die Ergebnisse miteinander verglichen.Angiogenesis is a key pathophysiological process in chronic inflammatory reactions, especially in arthritis, the progression and course of the disease influences. For quantification of changes of bone blood flow in mice with rheumatoid arthritis (RA)a multi-level segmentation method was developed. The blood vessels in the area of ​​inflamed knee joint were segmented and then quantitative 3D histomorphometric parameters were calculated. Two groups of mice (WT and RA) were investigated in vitro and the results compared to each other

Characterization and quantification of angiogenesis in rheumatoid arthritis in a mouse model using μCT

Background Angiogenesis is an important pathophysiological process of chronic inflammation, especially in inflammatory arthritis. Quantitative measurement of changes in vascularization may improve the diagnosis and monitoring of arthritis. The aim of this work is the development of a 3D imaging and analysis framework for quantification of vascularization in experimental arthritis. Methods High-resolution micro-computed tomography (μCT) was used to scan knee joints of arthritic human tumor necrosis factor transgenic (hTNFtg) mice and non-arthritic wild-type controls previously perfused with lead-containing contrast agent Microfil MV-122. Vessel segmentation was performed by combination of intensity-based (local adaptive thresholding) and form-based (multi-scale method) segmentation techniques. Four anatomically defined concentric spherical shells centered in the knee joint were used as analysis volumes of interest. Vessel density, density distribution as well as vessel thickness, surface, spacing and number were measured. Simulated digital vessel tree models were used for validation of the algorithms. Results High-resolution μCT allows the quantitative assessment of the vascular tree in the knee joint during arthritis. Segmentation and analysis were highly automated but occasionally required manual corrections of the vessel segmentation close to the bone surfaces. Vascularization was significantly increased in arthritic hTNFtg mice compared to wild type controls. Precision errors for the morphologic parameters were smaller than 3% and 6% for intra- and interoperator analysis, respectively. Accuracy errors for vessel thickness were around 20% for vessels larger than twice the resolution of the scanner. Conclusions Arthritis-induced changes of the vascular tree, including detailed and quantitative description of the number of vessel branches, length of vessel segments and the bifurcation angle, can be detected by contrast-enhanced high-resolution μCT

Automatic Determination of Fiber-Length Distribution in Composite Material Using 3D CT Data

<p/> <p>Determining fiber length distribution in fiber reinforced polymer components is a crucial step in quality assurance, since fiber length has a strong influence on overall strength, stiffness, and stability of the material. The approximate fiber length distribution is usually determined early in the development process, as conventional methods require a destruction of the sample component. In this paper, a novel, automatic, and nondestructive approach for the determination of fiber length distribution in fiber reinforced polymers is presented. For this purpose, high-resolution computed tomography is used as imaging method together with subsequent image analysis for evaluation. The image analysis consists of an iterative process where single fibers are detected automatically in each iteration step after having applied image enhancement algorithms. Subsequently, a model-based approach is used together with a priori information in order to guide a fiber tracing and segmentation process. Thereby, the length of the segmented fibers can be calculated and a length distribution can be deduced. The performance and the robustness of the segmentation method is demonstrated by applying it to artificially generated test data and selected real components.</p

Automatic Determination of Fiber-Length Distribution in Composite Material Using 3D CT Data

Determining fiber length distribution in fiber reinforced polymer components is a crucial step in quality assurance, since fiber length has a strong influence on overall strength, stiffness, and stability of the material. The approximate fiber length distribution is usually determined early in the development process, as conventional methods require a destruction of the sample component. In this paper, a novel, automatic, and nondestructive approach for the determination of fiber length distribution in fiber reinforced polymers is presented. For this purpose, high-resolution computed tomography is used as imaging method together with subsequent image analysis for evaluation. The image analysis consists of an iterative process where single fibers are detected automatically in each iteration step after having applied image enhancement algorithms. Subsequently, a model-based approach is used together with a priori information in order to guide a fiber tracing and segmentation process. Thereby, the length of the segmented fibers can be calculated and a length distribution can be deduced. The performance and the robustness of the segmentation method is demonstrated by applying it to artificially generated test data and selected real components