ArticleJournal of Korean medical science2023
Textural and Volumetric Changes of the Temporal Lobes in Semantic Variant Primary Progressive Aphasia and Alzheimer's Disease.
Article in Journal of Korean medical science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Effects of a 5-week heart rate biofeedback randomized intervention on texture in the Alzheimer's Disease signature cortical region.Research square · 2026Article
- Refining Western Dementia-Risk Paradigms: Evidence From a Decade of the Korean Longitudinal Study on Cognitive Aging and Dementia.Journal of Korean medical science · 2025Review
- Microstructural grey matter alterations in patients with behavioural variant frontotemporal dementia.Brain communications · 2025Article
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10 authors.
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Abstract
backgroundTexture analysis may capture subtle changes in the gray matter more sensitively than volumetric analysis. We aimed to investigate the patterns of neurodegeneration in semantic variant primary progressive aphasia (svPPA) and Alzheimer's disease (AD) by comparing the temporal gray matter texture and volume between cognitively normal controls and older adults with svPPA and AD.
methodsWe enrolled all participants from three university hospitals in Korea. We obtained T1-weighted magnetic resonance images and compared the gray matter texture and volume of regions of interest (ROIs) between the groups using analysis of variance with Bonferroni posthoc comparisons. We also developed models for classifying svPPA, AD and control groups using logistic regression analyses, and validated the models using receiver operator characteristics analysis.
resultsCompared to the AD group, the svPPA group showed lower volumes in five ROIs (bilateral temporal poles, and the left inferior, middle, and superior temporal cortices) and higher texture in these five ROIs and two additional ROIs (right inferior temporal and left entorhinal cortices). The performances of both texture- and volume-based models were good and comparable in classifying svPPA from normal cognition (mean area under the curve [AUC] = 0.914 for texture; mean AUC = 0.894 for volume). However, only the texture-based model achieved a good level of performance in classifying svPPA and AD (mean AUC = 0.775 for texture; mean AUC = 0.658 for volume).
conclusionTexture may be a useful neuroimaging marker for early detection of svPPA in older adults and its differentiation from AD.
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