# Presentation: 884265

## Statistical Brain Structure Analysis

- This work was supported by the National Institutes of Health, Roadmap Initiative for Bioinformatics and Computational Biology under grant ID 1-U54-EB005149. For more information, see _[http://www.](http://www.bisti.nih.gov/ncbc)__[bisti](http://www.bisti.nih.gov/ncbc)__[.](http://www.bisti.nih.gov/ncbc)__[nih](http://www.bisti.nih.gov/ncbc)__[.gov/ncbc](http://www.bisti.nih.gov/ncbc)_

**Wavelets/Particle Shape **
- Two additional novel shape representations complement SPHARM-PDM. Our spherical wavelet based representation allows a hierarchical decomposition and an increased sensitivity of the statistical analysis through a reduction of the number of shape features (see above Figure for an example of an hierarchical analysis). Further, our particle-system based representation allows the analysis of non-spherical topology structures, such as the cranium, and is insensitive to noise-induced topological variations.

- http://wiki.na-mic.org

- http://www.na-mic.org

**Statistical Brain Structure Analysis**

- Martin Styner*1*,Oguz Ipek*1*, Guido Gerig*1*, Delphine Nain*2*, Allen Tannenbaum*2*,
- Martha Shenton*3*, James J Levitt*3*, Sylvain Bouix*3*, Marc Niethammer*3*, Polina Golland*4*,
-  Tom Fletcher*5*, Ross Whitaker*5*

*1**University of North Carolina, Chapel Hill, NC,** **2**Georgia Tech, Atlanta, GA** *
*3**Brigham and Women’s Hospital, Harvard Medical School, Boston, MA*
*4**MIT **CSAIL**, Cambridge, MA, **5**University of Utah, Salt Lake City, UT *

**Statistical Testing**
- New methods for the computation of group discrimination and group mean difference testing have been developed. Three levels of statistical shape analysis are in the testing framework (from optimistic raw values to conservatively corrected values), These correction methods are crucial in enhancing the sensitivity and the power of the analysis.
- The results of the three statistical levels are shown in the Figure below on the NA-MIC male SPD study.

**Overview**
- Routine quantitative morphologic assessment based on volumetric measurements capture global atrophy or dilation due to illness. Changes at specific locations are though not sufficiently reflected. Shape analysis has thus become of increasing relevance to the neuroimaging community due to its potential to precisely locate morphological changes between healthy and pathological structures.
- Within the NA-MIC network, all key problems in structural shape analysis are being tackled in a joint effort. A coherent framework and set of tools have been implemented, disseminated to several groups, as well as applied to clinical data. Selected projects are presented in this poster.

- Binary Segmentation

- Volumetric analysis

- Shape Description
- Correspondence

- Statistics
- Testing

- Shape Analysis

- Raw

- FDR

- Perms

- Medial View

- Lateral View

- p > 0.05

- p = 0.05

- p = 0

**SPHARM-PDM**
- We have developed a toolset for the computation of the statistical shape analysis on triangulated meshes using correspondence defined by spherical harmonics (SPHARM). The tools have been disseminated and are in use in several NA-MIC sites, as well as major international research labs. Its application to two schizo-typal personality disorder (SPD) studies on caudates are currently being written up (see Figure below for the mean difference between male controls and male SPD).
- Intermediate results of this tool set are used as input to other types of shape analysis, e.g., based on spherical wavelets.