DBP2:MIND:Roadmap

Brain Lesion Analysis in Neuropsychiatric Systemic Lupus Erythematosus

Objective

We would like to create an end-to-end application within NA-MIC Kit allowing individual and group analysis of white matter lesions. Such a workflow applied to lupus patients is one goal of the MIND DBP. This page describes the technology roadmap for lesion analysis in the NA-MIC Kit. The basic components necessary for this end-to-end 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 detacted and anatomical location summarized
• Lesion Load Measurement: Measure volume of each lesion, summarize lesion load by regions
• Statistical analysis/Hypothesis testing: Lesion Measurements need to be compared and tested locally incorporating multiple-comparison correction, correlative analysis would be necessary too.

Roadmap

Compare Lesion Analysis Tools

A number of algorithms for fully or semi-automated lesion analysis will be evaluated on brain images from subjects in a study on lupus erythematosis. These include:

1) The tools developed by the UNC group (marcel)

2) The tools developed by the BWH group (EM-segment with lesion segmentation)

3) Tools within Medx (automated lesion classification package)

4) BRAINS2 (automated lesion classification package)

5) manual tracing

Data will be collected at both 1.5 and 3T. Data at 1.5T will be obtained with the protocol utilized for 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.

Incorporation into NA-MIC Kit

The algorithm with the best performance will be incorporated in Slicer3.

Tutorial Documentation will be written for a tutorial and sample data sets will be provided

Hypothesis Testing

Performance characterization and validation

Schedule