Keywords: Aging, Segmentation, Neurodegeneration, AI/ML Software, Data Analysis
Motivation: FLAIR imaging is sensitive for detecting white matter hyperintensities (WMHs) but sometimes unavailable due to lengthy acquisition times.
Goal(s): To assess 2D T2w TSE sequences as an alternative to 3D FLAIR for the automated estimation of WMH volumes.
Approach: WMHs were segmented from FLAIR images, and the images were registered to TSE images. Two neural networks were trained for skull stripping and WMH segmentation on TSE images. Separate test sets with paired FLAIR/TSE were used to evaluate the method.
Results: TSE-based segmentation correlated strongly with FLAIR (TIV: 0.98, WMH: 0.95), demonstrating suitability of TSE for estimating total WMH volume.
Impact: Using 2D T2w Turbo Spin Echo (TSE) sequences for white matter hyperintensity (WMH) volume estimation provides a dependable alternative to 3D FLAIR, particularly when quick scan protocols are necessary, but WMH estimation is still needed.
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