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多模态磁共振成像准确识别阿尔茨海默病连续体中不平衡队列的淀粉样蛋白状态。

Multimodal MRI accurately identifies amyloid status in unbalanced cohorts in Alzheimer's disease continuum.

作者信息

Dolci Giorgio, Ellis Charles A, Cruciani Federica, Brusini Lorenza, Abrol Anees, Galazzo Ilaria Boscolo, Menegaz Gloria, Calhoun Vince D

机构信息

Department of Computer Science, University of Verona, Verona, Italy.

Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy.

出版信息

Netw Neurosci. 2025 Mar 20;9(1):259-279. doi: 10.1162/netn_a_00423. eCollection 2025.

Abstract

Amyloid- (A) 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 positivity could enable early diagnosis. In this work, we aim at capturing the A 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 accumulation, leading to an accuracy of 0.762 ± 0.04. The specificity of the information brought by each modality is assessed by post hoc explainability analysis (guided backpropagation), highlighting the underlying structural and functional changes. Noteworthy, well-established biomarker key regions related to A 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 shedding light on modality-specific possibly unknown A deposition signatures.

摘要

淀粉样蛋白β(Aβ)斑块与神经原纤维缠结形式的过度磷酸化tau蛋白是阿尔茨海默病的两个神经病理学特征。众所周知,识别Aβ阳性个体能够实现早期诊断。在这项工作中,我们旨在捕捉处于不同疾病阶段的不平衡队列中个体的Aβ阳性状态,利用结构、功能和扩散磁共振成像揭示的潜在结构和连接性疾病诱导的调制。值得注意的是,由于队列不平衡,结果可能由这些因素而非淀粉样蛋白积累所引导。每种模态提供的部分视图被整合到模型中,从而能够充分利用它们在编码Aβ积累效应方面的互补性,准确率达到0.762±0.04。通过事后可解释性分析(引导反向传播)评估每种模态所带来信息的特异性,突出潜在的结构和功能变化。值得注意的是,所有模态都能识别与Aβ沉积相关的成熟生物标志物关键区域,包括海马体、丘脑、楔前叶和扣带回,这证明了该方法的可靠性及其在揭示特定模态可能未知的Aβ沉积特征方面的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2a9/11949592/590dd85dc6e5/netn-9-1-259-g001.jpg

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