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

TITLE=Identifying Mild Alzheimer's Disease With First 30-Min 11C-PiB PET Scan

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=Volume 14 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2022.785495

DOI=10.3389/fnagi.2022.785495

ISSN=1663-4365

ABSTRACT=Introduction: 11C-PiB PET imaging can provide information for the diagnosis of Alzheimer’s diseases (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 healthy and AD subjects. However, these measures require 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 reference region.
Methods: 11C-PiB PET scan data were obtained from the public dataset “OASIS-3”. 60 mild AD subjects 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 training set, AQI, SUVR and DVR were calculated and used for classification by logistic regression classifier. The Receiver Operating Characteristic (ROC) analysis was performed to evaluate the performance of these measures. Accuracy, sensitivity and specificity were reported. Kruskal-Wallis test and effect size were also performed and evaluated for all measures. Then the performance of three measures were further validated on the testing set using the same method. 
Results: Kruskal-Wallis test suggested that AQI, SUVR and DVR can all differentiate the healthy and AD subjects (p<0.001). For the training set, ROC analysis showed that AQI achieved the best classification performance with an accuracy rate of 0.93,. 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. 
Conclusion: AQI combines early-phase kinetic information and mid-phase β-amyloid deposition and can provide a better diagnostic performance using the data from the first 30-min dynamic scan. Moreover, it was shown that indistinguishable AD cases regarding PiB retention potentially can be correctly identified.