Texture Analyses of Electrical Conductivity Maps in the Insula of Alzheimer’s Disease Patients

• Published in: Journal of medical and biological engineering Vol. 44; no. 2; pp. 208 - 219
• Main Authors: Kwon, Oh-In, Jahng, Geon-Ho, Lee, Munbae
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2024; Springer Nature B.V
• Subjects: Alzheimer's disease; Biological Techniques; Biomarkers; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedical Engineering/Biotechnology; Biomedicine; Electrical conductivity; Electrical resistivity; Entropy; Frequency analysis; Hydrofluorocarbons; Image acquisition; Magnetic resonance imaging; Medical imaging; Neurodegenerative diseases; Original Article; Parameters; Regenerative Medicine/Tissue Engineering; Texture; Electrical conductivity at Larmor frequency; Texture analysis; Alzheimer’s disease; MRI
• ISSN: 1609-0985; 2199-4757
• DOI: 10.1007/s40846-024-00865-9

Purpose Previous studies have utilized texture analyses on T1-weighted images and quantitative susceptibility maps in Alzheimer’s disease (AD) patients. This study aims to evaluate 3D texture analyses of high-frequency conductivity (HFC) maps at Larmor frequency, acquired from a 3T MRI system, as a potential imaging biomarker for AD Methods HFC maps were generated for 18 AD patients, 25 individuals with amnestic mild cognitive impairment (MCI), and 21 cognitively normal (CN) elderly participants using a six-echo turbo spin-echo pulse sequence on a clinical 3T MRI. Differences among the three groups were assessed by comparing the first- and second-order texture parameters of HFC images in the insular region, using a one-way analysis of covariance with age as a covariate Results For the first-order analysis, the mean HFC was elevated in AD patients compared to the other groups. Significant differences were observed in the second-order texture parameters, including angular second moment, inverse difference moment, sum of squares, entropy, sum of entropy, difference of entropy, and sum of average, across the subject groups Conclusion The findings indicate that AD patients have more complex and diverse patterns in HFCs within the insula compared to the CN and MCI groups. Thus, texture analysis of HFC images can effectively differentiate AD from other conditions