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通过首次30分钟的C-PiB正电子发射断层扫描识别轻度阿尔茨海默病。

Identifying Mild Alzheimer's Disease With First 30-Min C-PiB PET Scan.

作者信息

Shen Chushu, Wang Zhenguo, Chen Hongzhao, Bai Yan, Li Xiaochen, Liang Dong, Liu Xin, Zheng Hairong, Wang Meiyun, Yang Yongfeng, Wang Haifeng, Sun Tao

机构信息

Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China.

Henan Provincial People's Hospital and the People's Hospital of Zhengzhou, University of Zhengzhou, Zhengzhou, China.

出版信息

Front Aging Neurosci. 2022 Apr 5;14:785495. doi: 10.3389/fnagi.2022.785495. eCollection 2022.

DOI:10.3389/fnagi.2022.785495
PMID:35450057
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9016824/
Abstract

INTRODUCTION

C-labeled Pittsburgh compound B (C-PiB) PET imaging can provide information for the diagnosis of Alzheimer's disease (AD) by quantifying the binding of PiB to β-amyloid deposition in the brain. Quantification index, such as standardized uptake value ratio (SUVR) and distribution volume ratio (DVR), has been exploited to effectively distinguish between healthy and subjects with AD. However, these measures require a long wait/scan time, as well as the selection of an optimal reference region. In this study, we propose an alternate measure named amyloid quantification index (AQI), which can be obtained with the first 30-min scan without the selection of the reference region.

METHODS

C-labeled Pittsburgh compound B PET scan data were obtained from the public dataset "OASIS-3". A total of 60 mild subjects with AD and 60 healthy controls were included, with 50 used for training and 10 used for testing in each group. The proposed measure AQI combines information of clearance rate and mid-phase PIB retention in featured brain regions from the first 30-min scan. For each subject in the training set, AQI, SUVR, and DVR were calculated and used for classification by the logistic regression classifier. The receiver operating characteristic (ROC) analysis was performed to evaluate the performance of these measures. Accuracy, sensitivity, and specificity were reported. The Kruskal-Wallis test and effect size were also performed and evaluated for all measures. Then, the performance of three measures was further validated on the testing set using the same method. The correlations between these measures and clinical MMSE and CDR-SOB scores were analyzed.

RESULTS

The Kruskal-Wallis test suggested that AQI, SUVR, and DVR can all differentiate between the healthy and subjects with mild AD ( < 0.001). For the training set, ROC analysis showed that AQI achieved the best classification performance with an accuracy rate of 0.93, higher than 0.88 for SUVR and 0.89 for DVR. The effect size of AQI, SUVR, and DVR were 2.35, 2.12, and 2.06, respectively, indicating that AQI was the most effective among these measures. For the testing set, all three measures achieved less superior performance, while AQI still performed the best with the highest accuracy of 0.85. Some false-negative cases with below-threshold SUVR and DVR values were correctly identified using AQI. All three measures showed significant and comparable correlations with clinical scores ( < 0.01).

CONCLUSION

Amyloid quantification index combines early-phase kinetic information and a certain degree of β-amyloid deposition, and can provide a better differentiating performance using the data from the first 30-min dynamic scan. Moreover, it was shown that clinically indistinguishable AD cases regarding PiB retention potentially can be correctly identified.

摘要

引言

¹¹C 标记的匹兹堡化合物 B(¹¹C-PiB)PET 成像可通过量化 PiB 与大脑中β淀粉样蛋白沉积的结合情况,为阿尔茨海默病(AD)的诊断提供信息。已采用标准化摄取值比率(SUVR)和分布容积比率(DVR)等量化指标来有效区分健康人与 AD 患者。然而,这些测量方法需要较长的等待/扫描时间,并且需要选择最佳参考区域。在本研究中,我们提出了一种名为淀粉样蛋白量化指标(AQI)的替代测量方法,该方法可在前 30 分钟扫描中获得,无需选择参考区域。

方法

从公共数据集“OASIS-3”获取¹¹C 标记的匹兹堡化合物 B PET 扫描数据。共纳入 60 例轻度 AD 患者和 60 例健康对照,每组 50 例用于训练,10 例用于测试。所提出的 AQI 指标结合了前 30 分钟扫描中特定脑区的清除率和中期 PiB 滞留信息。对于训练集中的每个受试者,计算 AQI、SUVR 和 DVR,并通过逻辑回归分类器进行分类。进行受试者工作特征(ROC)分析以评估这些测量方法的性能。报告了准确性、敏感性和特异性。还对所有测量方法进行了 Kruskal-Wallis 检验和效应量评估。然后,使用相同方法在测试集上进一步验证这三种测量方法的性能。分析了这些测量方法与临床简易精神状态检查表(MMSE)和临床痴呆评定量表-总和量表(CDR-SOB)评分之间的相关性。

结果

Kruskal-Wallis 检验表明,AQI、SUVR 和 DVR 均可区分健康人与轻度 AD 患者(P < 0.001)。对于训练集,ROC 分析表明 AQI 实现了最佳分类性能,准确率为 0.93,高于 SUVR 的 0.88 和 DVR 的 0.89。AQI、SUVR 和 DVR 的效应量分别为 2.35、2.12 和 2.06,表明 AQI 在这些测量方法中最有效。对于测试集,所有三种测量方法的性能均稍逊一筹,而 AQI 仍然表现最佳,最高准确率为 0.85。一些 SUVR 和 DVR 值低于阈值的假阴性病例使用 AQI 被正确识别。所有三种测量方法与临床评分均显示出显著且相当的相关性(P < 0.01)。

结论

淀粉样蛋白量化指标结合了早期动力学信息和一定程度的β淀粉样蛋白沉积,并可利用前 30 分钟动态扫描的数据提供更好的区分性能。此外,研究表明,在 PiB 滞留方面临床上难以区分的 AD 病例可能被正确识别。

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