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Updated: Sep 18, 2025
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Unraveling SNAP: distinct patterns of early neurodegeneration through MRI texture analysis
Min Jeong Kwon1, Jieun Park1, Sungman Jo2
1Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Republic of Korea.
Aim:
Suspected non-Alzheimer's disease pathophysiology (SNAP) is a condition characterized by neurodegeneration in the absence of amyloid beta (Aβ) deposition, posing challenges for early diagnosis. This study aimed to investigate the progression of neurodegeneration in SNAP through the analysis of brain MRI volume and texture.
Methods:
The study included 449 amyloid-negative participants categorized into three groups: cognitively normal without neurodegeneration (N-CN), cognitively normal with neurodegeneration (N + CN), and MCI with neurodegeneration (N + MCI). Volume and texture metrics were derived from T1-weighted MRI. Texture analysis quantified microstructural changes using grey level co-occurrence matrices, while volume metrics measured atrophy.
Results:
Texture changes were observed earlier and more widely than volume reductions. In N + CN, texture changes were present in the hippocampus, entorhinal cortex and orbitofrontal cortex. In N + MCI, texture changes extended to frontal and subcortical regions, including the thalamus and putamen, while volume reductions extended to the lateral temporal cortex and amygdala.
Conclusions:
Texture analysis is a sensitive tool for detecting early neurodegenerative changes in SNAP, capturing microstructural changes preceding volume loss. By integrating texture and volume metrics, this study highlights a distinct neurodegenerative trajectory in SNAP. Future research should validate these findings longitudinally and explore the clinical application of texture metrics.
