DBP2:UNC:Cortical Thickness Roadmap
Contents
Objective
We would like to create an end-to-end application within Slicer3 allowing individual and group analysis of regional and local cortical thickness. Such a workflow applied to the young brain (2-4 years old) is one goal of the UNC DBP. This page describes the technology roadmap for cortical thickness analysis in the NA-MIC Kit. The basic components necessary for this end-to-end application are:
- Tissue segmentation: Should be multi-modality, correcting for intensity inhomogeneity and work on non-skull-stripped data.
- Cortical thickness measurement: Local cortical thickness needs measurements at every location of the white-gray matter boundary, as well as at the gray-csf boundary. Regional analysis does not need such a dense measurement.
- Cortical correspondence: Local analysis needs a full correspondence on both white-gray boundary and gray-csf boundary.
- Statistical analysis/Hypothesis testing: Measurements need to be compared and tested localy incorporating multiple-comparison correction, correlative analysis would be necessary too.
Roadmap
Starting with several MRI images (weighted-T1, weighted-T2...) we want to obtain cortical thickness maps for each subject, compute cortical correspondences between subjects, and analyze the cortical thickness at these corresponding locations. Ultimately, the NA-MIC Kit will provide a workflow for individual and group analysis of cortical thickness. It will be implemented as a set of Slicer3 modules that can be used interactively within the Slicer3 application as well as in batch on a computing cluster using BatchMake.
Next we discuss the main modules and details of current status and development work:
White matter/gray matter segmentation
- UNC has a open source segmentation tool called itkEMS (binary download) implemented in an ITK framework for segmenting white matter and gray matter in the young brain. This technique will be converted into a Slicer3 command line module
- Since this segmentation technique exists in an ITK framework, the integration into Slicer3 is low risk and should be completed over the next couple of months (mid fall)
- UNC will also investigate adapting the Slicer3 EM Segment module to their young brain studies. Here, UNC will adapt the UNC atlas of the 2 year old brain to provide priors for the EM Segment module
- This will be a good test case for applying the Slicer3 EM Segment module to a slightly different application. UNC should work through the training material on the Slicer3 EM Segment module and then refer to Brad Davis and Kilian Pohl as needed.
- This also should be completed before the AHM.
- UNC has a open source segmentation tool called itkEMS (binary download) implemented in an ITK framework for segmenting white matter and gray matter in the young brain. This technique will be converted into a Slicer3 command line module
Local cortical thickness measurement
- UNC has an algorithm to measure a local cortical thickness given a labeling of white matter and gray matter. This technique will be converted into a Slicer3 command line module
- This technique is non-symmetric and sparse (only computing distances where they can be computed reliably).
- This module is well suited for regional analysis, but additional work to interpolate dense measurements along the boundaries from the sparse ones would be necessary for a local analysis.
- It is expected that this module should be available before the AHM (for the current, sparse measurements).
- Marc Niethammer developed a technique at a previous project week that would be symmetric. This could be used for the local cortical thickness analysis, if our comparison studies show appropriate results.
- UNC has an algorithm to measure a local cortical thickness given a labeling of white matter and gray matter. This technique will be converted into a Slicer3 command line module
Local correspondence
- Regional as well as local subject comparisons are needed
- Regional analysis will require precise deformable registration to a young brain atlas
- NA-MIC toolkit can be applied here, Slicer 3 has a b-spline based MI registration which needs to be tested
- Parcellation atlas for regional analysis is the current atlas used by the DBP
- Local analysis requires techniques which are not currently in the NA-MIC Kit
- Freesurfer can be used for the local analysis (but it is not in the NA-MIC Kit)
- Ipek Oguz is developing local analysis tools and should be available in Fall 2008. The tool necessitates the following steps (also performed within Freesurfer)
- 1) spherical topology of white matter: Marc Niethammer has Slicer module for this step, testing will be necessary to ensure appropriateness in the cortical case
- 2) inflation of cortical surface: A Slicer module exists for this step, but likely not with the properties. Tests and possible additional implementation will need to be done.
- 3) computation of correspondence on inflated surface using particle system: No module exists, first prototype programs are in development in collaboration with Utah (I Oguz, J Cates)
Hypothesis testing
Regional testing can be done with standard statistical tools as there are a limited, relatively small number of regions.
For local analysis, such standard statistical tools are not applicable. Currently there is no local hypothesis testing framework with multiple comparison and generalized linear model computation in Slicer 3. Freesurfer has such a framework readily available. The UNC shape analysis testing framework and extensions of it should be applicable here.
- Freesurfer can compute group difference and correlative analysis on local cortical thickness
- UNC shape analysis testing framework allows local hypothesis testing with mulitple comparison correction, but no General Linear Model. An extenstion in this regard is currently in development (M Styner). A Slicer 3 module alloing for direct group differences will be available by AHM.
- An alternative possible testing framework is also being developed at UNC (outside of NAMIC) as an open source tool
Performance characterization and validation
- Characterize response based on signal noise, patient motion, etc.
- Comparison to other tools (FreeSurfer, itkEMS, UNC cortical thickness)
To do
- Assign owners to tasks
- Define schedule
Schedule
- Tissue segmentation
- 15/10/2007 - White matter/gray matter segmentation of the young brain using itkEMS as a Slicer3 module (C Vachet) - at AHM
- 01/12/2007 - White matter/gray matter segmentation of the young brain using the Slicer3 EM Segment module (C Vachet) - at AHM
- 15/12/2007 - Comparison study itEMS vs EM Segment in Slicer 3 (C Vachet) - at AHM
- Cortical thickness
- 23/12/2007 - UNC Cortical thickness measurement as a Slicer3 module (C Vachet) - at AHM
- 23/12/2007 - Niethammer's Laplacian Cortical thickness measurement module code working at UNC as a Slicer3 module (C Vachet) - at AHM
- 01/03/2008 - Regional comparison between UNC and Laplacian cortical thickness (C Vachet)
- Cortical correspondence
- 15/12/2007 - Slicer 3 Deformable registration of young brain regional atlas (C Vachet) - at AHM
- 01/04/2008 - Regional analysis of cortical thickness as a Slicer3 module (C Vachet), develoment work is necessary
- 01/11/2007 - Niethammer Spherical topology tool tested on cortical data (I Oguz)
- 01/12/2007 - Inflation/Unfolding Slicer module testd on cortical data (I Oguz)
- 01/06/2008 - Slicer 3 module for cortical correspondence on inflated surface (I Oguz)
- 01/08/2008 - Fully ealuation of cortical computation on autism DBP datasets (C Vachet)
- Statistical analysis and Hypothesis testing
- 01/12/2007 - Slicer 3 Statistical Shape Analysis module (C Vachet)
- 01/04/2008 - Slicer 3 Statistical Cortical Thickness Analysis module (C Vachet)
- 01/06/2008 - GLM model for UNC statistical shape analysis (M Styner)
- Workflow/cohesive tools
- 01/06/2008 - Groupwise regional analysis of cortical thickness as a NA-MIC Workflow (C Vachet)
- 01/02/2009 - Groupwise local analysis of cortical thickness as a NA-MIC Workflow (C Vachet)
Team and Institute
- Co-PI: Heather Cody Hazlett, PhD, (heather_cody at med.unc.edu, Ph: 919-966-4099)
- Co-PI: Joseph Piven, MD
- NA-MIC Engineering Contact: Jim Miller, GE Research
- NA-MIC Algorithms Contact: Martin Styner, UNC