论文标题
使用海马表面多元形态计量学统计数据和稀疏编码，改善了β-淀粉样蛋白和TAU负担的预测
Improved Prediction of Beta-Amyloid and Tau Burden Using Hippocampal Surface Multivariate Morphometry Statistics and Sparse Coding
论文作者
论文摘要
背景：大脑中的β-淀粉样蛋白（$β$）斑块和tau蛋白缠结是阿尔茨海默氏病（AD）的定义“ A”和“ T”标志，以及在脑磁共振成像（MRI）扫描（MRI）上可检测到的结构性萎缩，作为神经脱发的一种生物群体，是ADNE'S''''''''''''''''''）。当前检测$β$/tau病理学的方法包括脑脊液（CSF；侵入性），正电子发射断层扫描（PET；昂贵且不可广泛可用）以及基于血液的生物标志物（BBBM；有希望的，主要仍在开发中）。 目的：开发非侵入性且可广泛可用的基于结构的MRI框架，以定量预测淀粉样蛋白和TAU测量值。 方法：利用基于MRI的海马多元形态统计（MMS）特征，我们将基于斑块分析的表面correntropropy诱导的稀疏编码和最大形式（PASCS-MP）方法与Ridge回归模型结合到单个淀粉样蛋白/TAU测量。 结果：我们评估了来自阿尔茨海默氏病神经成像计划（ADNI）的淀粉样蛋白PET/MRI和TAU PET/MRI数据集的框架。每个受试者都有一对由PET图像和MRI扫描组成的，大约在同一时间收集。实验结果表明，使用我们的PASCP-MP表示预测的淀粉样蛋白/TAU测量值比从其他方法中得出的测量（例如海马表面积，体积和基于球形谐音的形状形态特征（SPHARM））更接近实际值。 结论：基于MMS的PASCP-MP是一种有效的工具，可以用淀粉样蛋白和TAU病理桥接海马萎缩，从而有助于评估疾病负担，进展和治疗效果。
Background: Beta-amyloid (A$β$) plaques and tau protein tangles in the brain are the defining 'A' and 'T' hallmarks of Alzheimer's disease (AD), and together with structural atrophy detectable on brain magnetic resonance imaging (MRI) scans as one of the neurodegenerative ('N') biomarkers comprise the ''ATN framework'' of AD. Current methods to detect A$β$/tau pathology include cerebrospinal fluid (CSF; invasive), positron emission tomography (PET; costly and not widely available), and blood-based biomarkers (BBBM; promising but mainly still in development). Objective: To develop a non-invasive and widely available structural MRI-based framework to quantitatively predict the amyloid and tau measurements. Methods: With MRI-based hippocampal multivariate morphometry statistics (MMS) features, we apply our Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP) method combined with the ridge regression model to individual amyloid/tau measure prediction. Results: We evaluate our framework on amyloid PET/MRI and tau PET/MRI datasets from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject has one pair consisting of a PET image and MRI scan, collected at about the same time. Experimental results suggest that amyloid/tau measurements predicted with our PASCP-MP representations are closer to the real values than the measures derived from other approaches, such as hippocampal surface area, volume, and shape morphometry features based on spherical harmonics (SPHARM). Conclusion: The MMS-based PASCP-MP is an efficient tool that can bridge hippocampal atrophy with amyloid and tau pathology and thus help assess disease burden, progression, and treatment effects.
