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Differential effect of dementia etiology on cortical stiffness as assessed by MR elastography
BACKGROUND: Aging and dementia involve the disruption of brain molecular pathways leading to the alterations in tissue composition and gross morphology of the brain. Phenotypic and biomarker overlap between various etiologies of dementia supports a need for new modes of information to more accuratel...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879983/ https://www.ncbi.nlm.nih.gov/pubmed/36696808 http://dx.doi.org/10.1016/j.nicl.2023.103328 |
Sumario: | BACKGROUND: Aging and dementia involve the disruption of brain molecular pathways leading to the alterations in tissue composition and gross morphology of the brain. Phenotypic and biomarker overlap between various etiologies of dementia supports a need for new modes of information to more accurately distinguish these disorders. Brain mechanical properties, which can be measured noninvasively by MR elastography, represent one understudied feature that are sensitive to neurodegenerative processes. In this study, we used two stiffness estimation schemes to test the hypothesis that different etiologies of dementia are associated with unique patterns of mechanical alterations across the cerebral cortex. METHODS: MR elastography data were acquired for six clinical groups including amyloid-negative cognitively unimpaired (CU), amyloid-positive cognitively unimpaired (A + CU), amyloid-positive participants with mild cognitive impairment (A + MCI), amyloid-positive participants with Alzheimer’s clinical syndrome (A + ACS), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). Stiffness maps were computed using two neural network inversions with the objective to at least partially separate the parenchyma-specific and morphological effects of neurodegeneration on mechanical property estimates. A tissue-confined inversion algorithm was designed to obtain the best estimate of stiffness in the brain parenchyma itself, while a regionally-aware inversion algorithm was used to measure the tissue stiffness along with the surroundings. Mean stiffness of 15 bilateral gray matter cortical regions were considered for statistical analysis. First, we tested the hypothesis that cortical stiffness changes in the aging brain. Next, we tested the overall study hypothesis by first comparing stiffness in each clinical group to the CU group, and then comparing the clinical groups against one another. Finally, we assessed the spatial and statistical overlap between atrophy and stiffness changes for both inversions. RESULTS: Cortical brain regions become softer with age for both inversions with larger effects observed using regionally-aware stiffness. Stiffness decreases in the range 0.010–0.027 kPa per year were observed. Pairwise comparisons of each clinical group with cognitively unimpaired participants demonstrated 5 statistically significant differences in stiffness for tissue-confined measurements and 19 statistically different stiffness changes for the regionally-aware stiffness measurements. Pairwise comparisons between clinical groups further demonstrated unique patterns of stiffness differences. Analysis of the atrophy-versus-stiffness relationship showed that regionally-aware stiffness measurements exhibit higher sensitivity to neurodegeneration with findings that are not fully explained by partial volume effects or atrophy. CONCLUSIONS: Both tissue-confined and regionally-aware stiffness estimates exhibited unique and complementary stiffness differences in various etiologies of dementia. Our results suggest that mechanical alterations measured by MRE reflect both tissue-specific differences as well as environmental effects. Multi-inversion schemes in MRE may provide new insights into the relationships between neuropathology and brain biomechanics. |
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