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
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.
Proc. SPIE. 7963, Medical Imaging 2011: Computer-Aided Diagnosis
KEYWORDS: X-ray computed tomography, Tissues, Image segmentation, Fourier transforms, 3D modeling, Medical imaging, In vivo imaging, Expectation maximization algorithms, Mouse models, Animal model studies
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.