Mr. Arnaud Marchadier Profile

Arnaud Marchadier

at Univ d'Orléans

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Publications (2)

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Proceedings Article | 9 March 2011 Paper

3D visualization and quantification of bone and teeth mineralization for the study of osteo/dentinogenesis in mice models

A. Marchadier, C. Vidal, S. Ordureau, R. Lédée, C. Léger, M. Young, M. Goldberg

Proceedings Volume 7965, 79650J (2011) https://doi.org/10.1117/12.878251

KEYWORDS: Bone, Teeth, Visualization, Volume rendering, Microscopy, 3D visualizations, Mouse models, 3D image processing, Animal model studies, Image resolution

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Research on bone and teeth mineralization in animal models is critical for understanding human pathologies. Genetically modified mice represent highly valuable models for the study of osteo/dentinogenesis defects and osteoporosis. Current investigations on mice dental and skeletal phenotype use destructive and time consuming methods such as histology and scanning microscopy. Micro-CT imaging is quicker and provides high resolution qualitative phenotypic description. However reliable quantification of mineralization processes in mouse bone and teeth are still lacking. We have established novel CT imaging-based software for accurate qualitative and quantitative analysis of mouse mandibular bone and molars. Data were obtained from mandibles of mice lacking the Fibromodulin gene which is involved in mineralization processes. Mandibles were imaged with a micro-CT originally devoted to industrial applications (Viscom, X8060 NDT). 3D advanced visualization was performed using the VoxBox software (UsefulProgress) with ray casting algorithms. Comparison between control and defective mice mandibles was made by applying the same transfer function for each 3D data, thus allowing to detect shape, colour and density discrepencies. The 2D images of transverse slices of mandible and teeth were similar and even more accurate than those obtained with scanning electron microscopy. Image processing of the molars allowed the 3D reconstruction of the pulp chamber, providing a unique tool for the quantitative evaluation of dentinogenesis. This new method is highly powerful for the study of oro-facial mineralizations defects in mice models, complementary and even competitive to current histological and scanning microscopy appoaches.

Proceedings Article | 9 March 2011 Paper

Quantitative CT imaging for adipose tissue analysis in mouse model of obesity

A. Marchadier, C. Vidal, J.-P. Tafani, S. Ordureau, R. Lédée, C. Léger

Proceedings Volume 7963, 79632O (2011) https://doi.org/10.1117/12.878144

KEYWORDS: Tissues, X-ray computed tomography, Image segmentation, Fourier transforms, Mouse models, Animal model studies, Expectation maximization algorithms, 3D modeling, In vivo imaging, Medical imaging

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In obese humans CT imaging is a validated method for follow up studies of adipose tissue distribution and quantification of visceral and subcutaneous fat. Equivalent methods in murine models of obesity are still lacking. Current small animal micro-CT involves long-term X-ray exposure precluding longitudinal studies. We have overcome this limitation by using a human medical CT which allows very fast 3D imaging (2 sec) and minimal radiation exposure. This work presents novel methods fitted to in vivo investigations of mice model of obesity, allowing (i) automated detection of adipose tissue in abdominal regions of interest, (ii) quantification of visceral and subcutaneous fat. For each mouse, 1000 slices (100μm thickness, 160 μm resolution) were acquired in 2 sec using a Toshiba medical CT (135 kV, 400mAs). A Gaussian mixture model of the Hounsfield curve of 2D slices was computed with the Expectation Maximization algorithm. Identification of each Gaussian part allowed the automatic classification of adipose tissue voxels. The abdominal region of interest (umbilical) was automatically detected as the slice showing the highest ratio of the Gaussian proportion between adipose and lean tissues. Segmentation of visceral and subcutaneous fat compartments was achieved with 2D 1/2 level set methods. Our results show that the application of human clinical CT to mice is a promising approach for the study of obesity, allowing valuable comparison between species using the same imaging materials and software analysis.

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