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Multimodal MRI Accurately Identifies Amyloid Status in Unbalanced Cohorts in Alzheimer's Disease Continuum (2406.13305v2)

Published 19 Jun 2024 in cs.AI

Abstract: Amyloid-$\beta$ (A$\beta$) plaques in conjunction with hyperphosphorylated tau proteins in the form of neurofibrillary tangles are the two neuropathological haLLMarks of Alzheimer's disease. It is well-known that the identification of individuals with A$\beta$ positivity could enable early diagnosis. In this work, we aim at capturing the A$\beta$ positivity status in an unbalanced cohort enclosing subjects at different disease stages, exploiting the underlying structural and connectivity disease-induced modulations as revealed by structural, functional, and diffusion MRI. Of note, due to the unbalanced cohort, the outcomes may be guided by those factors rather than amyloid accumulation. The partial views provided by each modality are integrated in the model allowing to take full advantage of their complementarity in encoding the effects of the A$\beta$ accumulation, leading to an accuracy of $0.762\pm0.04$. The specificity of the information brought by each modality is assessed by \textit{post-hoc} explainability analysis (guided backpropagation), highlighting the underlying structural and functional changes. Noteworthy, well-established biomarker key regions related to A$\beta$ deposition could be identified by all modalities, including the hippocampus, thalamus, precuneus, and cingulate gyrus, witnessing in favor of the reliability of the method as well as its potential in shading light on modality-specific possibly unknown A$\beta$ deposition signatures.

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Authors (8)
  1. Giorgio Dolci (3 papers)
  2. Charles A. Ellis (3 papers)
  3. Federica Cruciani (2 papers)
  4. Lorenza Brusini (1 paper)
  5. Anees Abrol (10 papers)
  6. Ilaria Boscolo Galazzo (5 papers)
  7. Gloria Menegaz (8 papers)
  8. Vince D. Calhoun (61 papers)
Citations (1)

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