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利用主动学习分割管道研究阿尔茨海默病脉络丛和 tau 之间的关系。

Associations between the choroid plexus and tau in Alzheimer's disease using an active learning segmentation pipeline.

机构信息

College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.

Psychology, Beijing Normal University, Beijing, China.

出版信息

Fluids Barriers CNS. 2024 Jul 12;21(1):56. doi: 10.1186/s12987-024-00554-4.

Abstract

BACKGROUND

The cerebrospinal fluid (CSF), primarily generated by the choroid plexus (ChP), is the major carrier of the glymphatic system. The alternations of CSF production and the ChP can be associated with the Alzheimer's disease (AD). The present work investigated the roles of the ChP in the AD based on a proposed ChP image segmentation pipeline.

METHODS

A human-in-the-loop ChP image segmentation pipeline was implemented with intermediate and active learning datasets. The performance of the proposed pipeline was evaluated on manual contours by five radiologists, compared to the FreeSurfer and FastSurfer toolboxes. The ChP volume and blood flow were investigated among AD groups. The correlations between the ChP volume and AD CSF biomarkers including phosphorylated tau (p-tau), total tau (t-tau), amyloid-β42 (Aβ42), and amyloid-β40 (Aβ40) was investigated using three models (univariate, multiple variables, and stepwise regression) on two datasets with 806 and 320 subjects.

RESULTS

The proposed ChP segmentation pipeline achieved superior performance with a Dice coefficient of 0.620 on the test dataset, compared to the FreeSurfer (0.342) and FastSurfer (0.371). Significantly larger volumes (p < 0.001) and higher perfusion (p = 0.032) at the ChP were found in AD compared to CN groups. Significant correlations were found between the tau and the relative ChP volume (the ChP volume and ChP/parenchyma ratio) in each patient groups and in the univariate regression analysis (p < 0.001), the multiple regression model (p < 0.05 except for the t-tau in the LMCI), and in the step-wise regression model (p < 0.021). In addition, the correlation coefficients changed from - 0.32 to - 0.21 along with the AD progression in the multiple regression model. In contrast, the Aβ42 and Aβ40 shows consistent and significant associations with the lateral ventricle related measures in the step-wise regression model (p < 0.027).

CONCLUSIONS

The proposed pipeline provided accurate ChP segmentation which revealed the associations between the ChP and tau level in the AD. The proposed pipeline is available on GitHub ( https://github.com/princeleeee/ChP-Seg ).

摘要

背景

脑脊液(CSF)主要由脉络丛(ChP)产生,是胶状淋巴系统的主要载体。CSF 产生和 ChP 的改变可能与阿尔茨海默病(AD)有关。本研究基于提出的 ChP 图像分割管道,探讨了 ChP 在 AD 中的作用。

方法

采用人机交互 ChP 图像分割管道,结合中间和主动学习数据集。通过五位放射科医生对手动轮廓进行评估,比较了该管道与 FreeSurfer 和 FastSurfer 工具箱的性能。研究了 AD 组间 ChP 体积和血流。在两个包含 806 名和 320 名受试者的数据集上,使用三种模型(单变量、多变量和逐步回归),对 ChP 体积与 AD CSF 生物标志物(包括磷酸化 tau(p-tau)、总 tau(t-tau)、淀粉样β42(Aβ42)和淀粉样β40(Aβ40))之间的相关性进行了研究。

结果

与 FreeSurfer(0.342)和 FastSurfer(0.371)相比,提出的 ChP 分割管道在测试数据集上的 Dice 系数为 0.620,性能更优。与 CN 组相比,AD 组 ChP 体积较大(p<0.001),灌注较高(p=0.032)。在每位患者组和单变量回归分析中(p<0.001)、多变量回归模型(p<0.05,除了 LMCI 中的 t-tau 外)以及逐步回归模型(p<0.021)中,tau 与 ChP 相对体积(ChP 体积与 ChP/实质比)之间均存在显著相关性。此外,在多变量回归模型中,随着 AD 进展,相关系数从-0.32 变为-0.21。相比之下,Aβ42 和 Aβ40 在逐步回归模型中与侧脑室相关指标的相关性一致且显著(p<0.027)。

结论

所提出的管道提供了准确的 ChP 分割,揭示了 AD 中 ChP 与 tau 水平之间的关联。该管道可在 GitHub(https://github.com/princeleeee/ChP-Seg)上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2c2/11245807/0fab027d523a/12987_2024_554_Fig1_HTML.jpg

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