AUTHOR=Gwo Chih-Ying , Zhu David C. , Zhang Rong 

TITLE=Brain white matter hyperintensity lesion characterization in 3D T2 fluid-attenuated inversion recovery magnetic resonance images: Shape, texture, and their correlations with potential growth

JOURNAL=Frontiers in Neuroscience

VOLUME=16

YEAR=2022

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2022.1028929

DOI=10.3389/fnins.2022.1028929

ISSN=1662-453X

ABSTRACT=<p>Analyses of age-related white matter hyperintensity (WMH) lesions manifested in T<sub>2</sub> fluid-attenuated inversion recovery (FLAIR) magnetic resonance images (MRI) have been mostly on understanding the size and location of the WMH lesions and rarely on the morphological characterization of the lesions. This work extends our prior analyses of the morphological characteristics and texture of WMH from 2D to 3D based on 3D T<sub>2</sub> FLAIR images. 3D Zernike transformation was used to characterize WMH shape; a fuzzy logic method was used to characterize the lesion texture. We then clustered 3D WMH lesions into groups based on their 3D shape and texture features. A potential growth index (PGI) to assess dynamic changes in WMH lesions was developed based on the image texture features of the WMH lesion penumbra. WMH lesions with various sizes were segmented from brain images of 32 cognitively normal older adults. The WMH lesions were divided into two groups based on their size. Analyses of Variance (ANOVAs) showed significant differences in PGI among WMH shape clusters (<italic>P</italic> = 1.57 × 10<sup>–3</sup> for small lesions; <italic>P</italic> = 3.14 × 10<sup>–2</sup> for large lesions). Significant differences in PGI were also found among WMH texture group clusters (<italic>P</italic> = 1.79 × 10<sup>–6</sup>). In conclusion, we presented a novel approach to characterize the morphology of 3D WMH lesions and explored the potential to assess the dynamic morphological changes of WMH lesions using PGI.</p>