DBP2:MIND:Roadmap

Back to NA-MIC Internal Collaborations, MIND DBP 2

Brain Lesion Analysis in Neuropsychiatric Systemic Lupus Erythematosus

Objective

We would like to create an end-to-end application entirely within NA-MIC Kit allowing individual analysis of white matter lesions. Such a workflow applied to lupus patients is one of goals of the MIND DBP. This page describes the technology roadmap for lesion analysis in the NA-MIC Kit. The basic components necessary for this application are:

• Registration: co-registration of T1-weighted, T2-weighted, and FLAIR images
• Tissue segmentation: Should be multi-modality, correcting for intensity inhomogeneity and work on non-skull-stripped data.
• Lesion Localization: Each unique lesion should be detected and anatomical location summarized
• Lesion Load Measurement: Measure volume of each lesion, summarize lesion load by regions
• Time Series Analysis of white matter lesions:
• Multi-scale Analysis of white matter lesions:
• Tutorial: Documentation will be written for a tutorial and sample data sets will be provided

Roadmap

We will obtain gray matter, white matter, CSF, and lesion maps for each subject based on T1-weighted, T2-weighted, and FLAIR images. Ultimately, the NA-MIC Kit will provide a workflow for individual and group analysis of lesions. 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.

The current status of the main modules to be used are:

Registration

• ITK has mutual information registration
• T1/T2/Flair co-registration implemented into EM-segment module

Lesion segmentation

Five algorithms (all within NA-MIC kit) for fully or semi-automated lesion analysis will be evaluated. These include:

• Slicer3 EM-segment Module (Sandy Wells)
• ITK stand-alone itkEMS Compare Lesion Analysis Tools (Prastawa/Gerig)
• ITK stand-alone white matter lesion segmentation (Magnotta)
• ITK K Nearest Neighbor classification based on the work of Anabeek, et al
• ITK stand-alone segmentation combining elements of Boosting, Artificial Immune Systems, and Bayesian Classification. (Scully)

Manual tracing will serve as a bronze-standard:

• Slicer3 Manual tracing by clinically trained rater (Gasparovic/Bockholt)

Lesion Localization

• Slicer3 has tools for labeling white matter lesions and summarizing their anatomical location

Lesion Load Measurement

• Slicer3 has tools for measurement of labelled lesions

Performance characterization and validation

• Data will be collected at both 1.5 and 3T. Data at 1.5T will be obtained with the protocol utilized for the current project on lupus at UNM.
• Data at 3T will be obtained with sequences optimized for segmentation by the group at Utah.
• Comparisons will be based on the approach developed by Martin-Fernandez et al.
• The algorithm with the best performance will be incorporated into the NA-MIC kit.

Tutorial

• 10 Externally sharable T1,T2,Flair,Lesion Map data-sets (NIFTI format) will be made available to the scientific community
  • 5 subjects with lupus and 5 healthy normal volunteers
• A tutorial will be created that will guide end-users through each step needed to complete a lesion analysis in the NA-MIC kit
  • A step-by-step guide will be produced for one example lupus cases within the tutorial and one example healthy normal volunteer
  • Measurements for all 10 subjects will also be provided so that users may compare their results with those of the tutorial

Schedule

• Sequence Optimization and Data Collection

• 10/15/2007 T1, T2, FLAIR optimized sequences for Siemens 3T Trio Tim scanner (Jeremy, Bruce, Chuck)
  • We will work with Bruce Fischl on using MEMPR, Mugler, and FLAIR sequences that have been optimized for maximum constrast and minimal geometric distortion across sequences
  • DONE
• 3/31/2008 collection of 5 lupus subjects on clinical sequence and optimized 3T sequence (Chuck)
  • collected 2 patients and 3 controls so far
    • as of 3/10/2008 there are 3-4 additional patients scheduled, since january 1, we have had 4 patients not able to complete the protocol so far

• Co-Registration and Atlas Registration

• 1/31/2008 optimized mutual information registration for clinical sequences and optimized 3T sequences (Jeremy)
  • we have tried the registration tools built-in to Slicer 3 EM-segment module so far
  • DONE Brad has implemented this successfully into the EM-segment module

• Lesion segmentation

• 3/17/2008 complete lesion segmentation methods for Slicer3 EM-segment, ITK itkEMS, ITK lesion segmentation, and Slicer3 manual tracing (Jeremy, Chuck, Vince Magnotta, Kilian/Brad, Marcel)
  • Slicer3 EM-segment Module
    • (Resolved) Currently has a bug that does not permit 3 channel segmentation Mantis ID#0000205
      • (Resolved) Only using 2 channels such as T1/T2 or T1/FLAIR does not produce sensible/usable results
    • (Resolved) Does not properly allow user to edit or change weighting of channels, this is crucial for hierarchical lesion classification. Mantis ID#0000204
    • EMSegment has been run against collected lupus cases. Segmentations have improved but are still unusable as of 08/14/2008.
      • Currently working with Killian on optimizing parameters in EMSegment to improve the lesion segmentation.
      • Testing parameters and resulting segmentation on collected lupus cases.
  • ITK itkEMS stand-alone package
    • Marcel and Mark are in active collaboration with getting this method to work on-site, we have encountered compilation and memory problems with the package on mac and linux environments so far
    • 3/17/2008 update, marcel built a 64-bit linux version that appears to run successfully, current results are are shown here
  • ITK lesion classification stand-alone package
    • Vince Magnotta has develop an ITK-based 2 stage lesion segmentation method
      • stage one uses k-means tissue classification into grey, white, or csf of co-registered T1/T2
      • stage two use bayesian classifier into normal tissue or lesion using results of stage one and co-reigstered Flair
        • current results of this method as of 3/17/2008 are shown here
        • This method has been run against all cases as of 05/01/08. Currently working with Vince Magnotta to improve the performance.
        • As of 08/14/2008, currently running a modified version of Vince's classifier that has been improved by replacing intensity thresholding with joint histogram feature vector occurrence thresholding.
  • ITK K Nearest Neighbor Classifier
    • Mark Scully is currently implementing a K-NN lesion classifier using ITK.
      • This approach allows for on the fly additions to the classification model.
      • The same segmentation approach is applicable to multiple lesion types.
      • The resulting label map contains the percent likelihood that a given voxel is a lesion. This allows the clinician to adjust the thresholding to match their preference.
    • On hold as of 1/12/2008 due to incomplete ITK algorithmic support
  • ITK Custom Classifier
    • Mark Scully is currently implementing a combined approach classifier using ITK.
      • This approach allows for on the fly additions to the classification model.
      • The same segmentation approach is applicable to multiple lesion types.
      • This approach takes advantage of multiple approaches and advancements in the literature, including feature generation, Gentle Boosting based feature reduction, Artificial Immune System based filtering, and Bayesian classification.
    • As of 1/01/2009 this method is functional and built into the lesion segmentation slicer3 applications.
    • 
    • 

• • Slicer3 Manual Tracing
    • Gasparovic has manually traced all tutorial cases with lesions using T2/Flair images following tracing guidelines and a qualitative neuroradiological review report
      • 4/1/2008 create manual tracing guidelines documentation and share here

• Lesion Localization

• 4/15/2008 complete lesion localizations and maps for Slicer3 EM-segment, ITK itkEMS, ITK lesion segmentation, and Slicer3 manual tracing (Jeremy, Chuck, Vince Magnotta, Steve)

• Lesion Measurement

• 4/20/2008 complete lesion measurements and regional lesion load summaries for Slicer3 EM-segment, ITK itkEMS, ITK lesion segmentation, and Slicer3 manual tracing (Jeremy, Chuck, Vince Magnotta, Steve)

• Performance characterization and validation

• 1/6/2008 report to 2008 NA-MIC AHM on progress for performance and validation of lesion segmentation methods for EM-segment, BRAINS2, manual, UNC packages (Jeremy)
  • DONE
• 5/15/2008 submit abstract on reliability and summary of novel NA-MIC kit lesion analysis method (Jeremy, Chuck, Mark Scully, Brad, Kilian, others)
  • plan is to submit SFN abstract and manuscript closely after
• 5/20/2008 analyze NIH study clinical sample using NA-MIC kit lesion analysis method (Jeremy, Chuck, Mark Scully)
• 7/1/2008 submit manuscript on clinical application of NA-MIC kit lesion analysis method (Jeremy, Chuck, Mark Scully, Carlos Roldan, Bill Sibbitt)
• 8/14/2008 submit manuscript on the lesion segmentation methods as applied to MS lesions for MICCAI 2008. (Mark, Jeremy, Chuck, Vince Magnotta)
• 1/11/2009 submit abstract on the new lesion segmentation methods as applied to Lupus lesions for HBM 2009.
• 3/08/2009 submit manuscript on the new lesion segmentation methods as applied to Lupus lesions for MICCAI 2009.

• Incorporation of approach into NA-MIC kit

• 1/6/2008 Slicer3 Lesion Analysis Module that handles co-registration of T1, T2, and Flair (Mark Scully, Steve)
  • DONE Brad completed this
• 5/1/2008 extend Slicer3 Lesion Analysis Module to handle lesion localization and measurement ('Mark Scully, Steve)
  • 08/01/2008 currently locates all independent lesion clusters and identifies the anatomical regions, provided by a registered atlas, that the lesions overlap.
• 6/1/2008 extend Slicer3 Lesion Analysis Module to implement the ITK-based lesion analysis algorithm/method (EM-segment, ITK itkEMS, ITK lesion segmentation) with the best performance (Mark Scully, Steve)
  • a demonstration will be given at the 2008 NA-MIC AHM--we would consider this version a prototype and would be testing, refining the module through the clinical application phase (Jeremy, Mark Scully)
• 6/15/2008 functioning prototype version of lesion analysis Slicer3 Module complete (Mark Scully, Steve)
• 8/14/2008 in the process of creating a module that "chains" together all of the steps in the lesion segmentation analysis pipeline.
• 1/03/2009 Newly developed lesion segmentation method with significantly increased performance incorporated into Slicer3 module.

• Tutorial and Data-sharing

• 6/20/2008 present tutorial to 2008 NA-MIC programming week (Mark Scully, Jeremy, Sonja)
  • A logical project for programming week for Jeremy and Sonja to finish public version of tutorial
• 7/1/2008 make data sets and tutorial available to the scientific community (Mark Scully, Jeremy, Sonja)
  • If we submit SFN abstract, we can advertise the availability during SFN Conference in November 2008
    • We could think about advertising the roadmaps at the BIRN booth at SFN this year?
• 10/15/2008 In the process of making the tutorial data available using XNAT.

Compare view of baseline and followup with color-coded lesion differences: http://www.na-mic.org/Wiki/index.php/File:CompareViewFlairLesionDiffWholeBrain.png

Diffusion tracts intersecting a lesion volume: http://www.na-mic.org/Wiki/index.php/File:LesionTractsNear.png

Axial slice with % predicted chance, thresholded predicted % chance, and manual tracing: http://www.na-mic.org/Wiki/index.php/File:Scully_Figure3.jpg

Team and Institute

• Co-PI: H Jeremy Bockholt (jbockholt at mrn.org)
• Co-PI: Charles Gasparovic (chuck at unm.edu)
• Software Engineer: Mark Scully (mscully at mrn.org)
• NA-MIC Engineering Contact: Steve Pieper, Isomics
• NA-MIC Algorithms Contact: Ross Whitaker, Utah
• Host Institues: The Mind Research Network and The University of New Mexico