In this paper, novel methods were used to map the corpus callosum morphology of children with chromosome 22q11.2 deletion syndrome in order to further investigate changes to that structure and to examine their possible effects on cognitive function. The callosal profiles were extracted from the centermost MRI midsagittal slice by supervised thresholding and the structure's boundary and midline were computed automatically. Difference analysis was based on non-rigid registration, in which a template image is warped to conform to the shape of each corpus callosum in the sample. Boundaries and midlines were registered to a template and the results used to determine the average callosal shapes for children with the deletion and for controls. Point-wise registration also enabled the detailed evaluation of callosal curvature, width, area and length. Significant differences between the two groups were found in shape, size and bending angle. Results showed group differences that were concentrated in the anterior part of the structure, more specifically in the rostrum, which was larger and longer in the group with the syndrome. Correlation analyses showed that ventricular enlargement does not fully account for callosal morphology differences in children with the deletion. However, areal measurements did reveal important relationships between changes in callosal morphology and cognitive function. These novel findings reveal intricate relationships between genetic and disease-specific factors in the callosal anatomy and the potential impact of those changes on cognitive functions. KeywordsChildren; chromosome 22q11.2 deletion syndrome; cognition; corpus callosum; morphology; image registration 1) INTRODUCTIONChromosome 22q11.2 deletion syndrome (DS22q11.2) results from a 1.5 -3Mb microdeletion on the long (q) arm of chromosome 22 (Driscoll, 1992a(Driscoll, , 1992b and encompasses the phenotypes of DiGeorge (DiGeorge, 1965), Velocardiofacial (Shprintzen, 1978) and * Corresponding Author Av. Dom José Gaspar, 500, PPGEE, Belo Horizonte, MG, Brazil, 30535-610 Phone: +5531 33194305 Fax: +5531 33194225 e-mail: alexei@grasp.cis.upenn.edu Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptConotruncal Anomaly Face (Burn, 1993) syndromes, and some cases of Cayler Cardiofacial syndrome (Giannotti, 1994) and Opitz G/BBB syndrome (McDonald-McGinn, 1995). Prevalence is thought to be around 1 in 4000 to 1 in 7000 live births (Burn, 1996). Following characterization of a range of medical manifestations ...

In this work, we describe an automated approach to morphometry based on spatial normalizations of the data, and demonstrate its application to the analysis of gender differences in the human corpus callosum. The purpose is to describe a population by a reduced and representative set of variables, from which a prior model can be constructed. Our approach is rooted in the assumption that individual anatomies can be considered as quantitative variations on a common underlying qualitative plan. We can therefore imagine that a given individual's anatomy is a warped version of some referential anatomy, also known as an atlas. The spatial warps which transform a labeled atlas into anatomic alignment with a population yield immediate knowledge about organ size and shape in the group. Furthermore, variation within the set of spatial warps is directly related to the anatomic variation among the subjects. Specifically, the shape statistics-mean and variance of the mappings-for the population can be calculated in a special basis, and an eigendecomposition of the variance performed to identify the most significant modes of shape variation. The results obtained with the corpus callosum study confirm the existence of substantial anatomical differences between males and females, as reported in previous experimental work.

In this paper, we present a content-based image retrieval system designed to retrieve mammographies from large medical image database. The system is developed based on breast density, according to the four categories defined by the American College of Radiology, and is integrated to the database of the Image Retrieval in Medical Applications (IRMA) project, that provides images with classification ground truth. Two-dimensional principal component analysis is used in breast density texture characterization, in order to effectively represent texture and allow for dimensionality reduction. A support vector machine is used to perform the retrieval process. Average precision rates are in the range from 83% to 97% considering a data set of 5024 images. The results indicate the potential of the system as the first stage of a computer-aided diagnosis framework.

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