echemi logo
Product
  • Product
  • Supplier
  • Inquiry
    Home > Active Ingredient News > Study of Nervous System > Front Aging Neurosci︱Sun Tao's research group proposes a new protocol for 11C-PiB-PET imaging for early diagnosis of Alzheimer's disease

    Front Aging Neurosci︱Sun Tao's research group proposes a new protocol for 11C-PiB-PET imaging for early diagnosis of Alzheimer's disease

    • Last Update: 2022-05-31
    • Source: Internet
    • Author: User
    Search more information of high quality chemicals, good prices and reliable suppliers, visit www.echemi.com

    Written by ︱ Sun Tao edited ︱ Sizhen Wang The diagnosis of Alzheimer's disease (AD) is usually based on clinical symptoms, while some pathological biomarkers such as amyloid-beta plaque and neurofibrillary tangles Neurofibrillary tangles, which can help confirm the diagnosis and enable early detection of lesions
    .

    As a non-invasive imaging method, positron emission tomography (PET), can use radiotracers such as 11C-PiB to quantify the deposition and distribution of amyloid in the brain (Fig.
    1A)
    .

    Standardized uptake value (SUVR) and distribution volume ratio (DVR), as the most commonly used quantitative methods of PiB-PET, have been proved to be effective in distinguishing AD, MCI (mild cognitive impairment, mild cognitive impairment) and normal people [1]
    .

    However, these quantitative parameters need to be measured when the tracer is in a steady state.
    For example, SUVR needs to use data after 60 minutes after injection, and DVR needs to continuously collect data for more than 60 minutes after injection
    .

    Furthermore, these two quantitative indicators require the selection of reference brain regions without specific uptake, however optimal selection of reference brain regions is often challenging [2]
    .

    These data acquisition and processing problems are one of the obstacles preventing the popularization of amyloid PET imaging
    .

    Therefore, how to simplify the acquisition time process and at the same time ensure that sufficient clinical information is obtained is an important issue for further clinical popularization of PET imaging in AD applications
    .

     On April 5, 2022, Sun Tao's research group from Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences published an article entitled "identifying Mild Alzheimer's Disease With First 30-Min 11C-PiB PET Scan" in Frontiers in Aging Neuroscience, proposing a A simplified protocol for PiB-PET imaging
    .

    Shen Chushu is the first author, and Sun Tao is the corresponding author
    .

    In this study, the authors propose a method based on the first 30 minutes of PET data acquisition, without the need to select a reference brain region, successfully using a shorter acquisition time, and better than traditional measures to detect mild AD patients
    .

    11C-PiB reflects its deposition in the brain by specifically binding to amyloid
    .

    According to the kinetic characteristics of 11C-PiB, the time-dependent changes in the uptake activity of the drug in the brain can be divided into influx phase, peak phase and elimination phase [3]
    .

    The influx phase shows the influx rate of PiB from blood to tissue, which is determined by both vascular blood flow and permeability
    .

    The peak period describes the highest tissue uptake value, which is usually reached within four minutes of drug injection, and the clearance period describes the clearance rate of the drug from the tissue after the peak period, and can reflect the deposition and distribution of amyloid in the brain
    .

    Generally speaking, AD patients have lower drug clearance rates and higher retention levels in cerebral cortical regions such as the caudal anterior cingulate compared to normal individuals (Figure 1).
    B), however, due to lack of specific binding in the cerebellar cortex, AD patients and normal subjects have similar dynamic metabolic profiles (Fig.
    1C)
    .

    Therefore, this distinction of dynamic uptake changes in specific brain regions can distinguish AD patients from normal individuals
    .

     Accordingly, the researchers hypothesized that by combining the characteristics of drug clearance and drug deposition levels, AD patients and normal individuals, especially AD with early mild symptoms, could be more effectively distinguished than traditional assessment of drug deposition levels alone
    .

    Based on this assumption, the researchers proposed a quantitative method and named it amyloid-beta quantification index (AQI), which calculated the linear combination of the two slopes of the temporal activity curve of the lesioned brain region (Figure 2): The first slope reflects the scan The early drug clearance rate and the slope of the second segment reflect the drug deposition in the middle and later stages of the scan, so as to achieve the purpose of distinguishing mild AD patients from normal people on the image
    .

    Figure 1 Left panel A reflects quantitative images of amyloid deposition in AD patients and normal subjects, right panels B and C reflect the 11C-PiB metabolic kinetics in the anterior caudal cingulate and cerebellar cortex of typical AD and normal subjects, respectively
    .

    (Source: C Shen, et al.
    , Front Aging Neurosci, 2022) Figure 2 AQI combines the characteristics of drug clearance and drug deposition levels, and only needs to collect the first 30 minutes of data
    .

    (Image source: C Shen, et al.
    , Front Aging Neurosci, 2022) This work used the OASIS-3 dataset, including scan data of 60 subjects diagnosed with mild AD and 60 normal subjects [4]
    .

    Each subject underwent a 60-minute dynamic 11C-PiB PET scan, acquired immediately after injection, using a Siemens ECAT HR+ 96, Biograph 40 PET/CT or Biograph mMR PET/MR
    .

    Each set of 60-minute PET data was reconstructed into 26-frame images, including 12 frames of 10 s, 3 frames of 60 s, and 11 frames of 300 s in length
    .

    All reconstructed images are preprocessed by smoothing, motion correction, standard spatial normalization,
    etc.

    SUVR images were then obtained by adding image data from 30 to 60 minutes, and DVR images were obtained by analyzing 0-60 minutes of data by Logan graphical analysis [5] method based on reference brain regions
    .

     The researchers used Lasso regression to identify the significant brain regions for AQI quantification as the anterior cingulate cortex and the caudate, and calculated the AQI values ​​based on these two brain regions for each subject by linear combination
    .

    The AQI values ​​of 50 AD patients and 50 normal subjects were trained by the linear regression method, and the remaining 10 AD patients and 10 normal subjects were tested and validated
    .

    The trained Receiver operating characteristic (ROC) analysis showed that AQI could identify early mild AD patients better than SUVR and DVR (AQI:AUC=0.
    944, SUVR:AUC=0.
    9066, DVR:AUC=0.
    886) (Figure 3)
    .

    Similarly, applying the same classification threshold to the test set data yields similar results
    .

    In addition, the effective sample size of the overall population of AQI is 2.
    35, and the SUVR and DVR for comparison are 2.
    12 and 2.
    06, respectively, indicating that AQI may require a relatively small number of samples when conducting large-sample experiments
    .

    In addition, AQI was compared with Clinical Dementia Rating (CDR) and Mini-Mental State Exam (MMSE) scores used in clinical tests, AQI was directly proportional to CDR-SOB (P<0.
    01) and inversely proportional to MMSE (P<0.
    01) )
    .

    However, the correlation between AQI and clinical score was not significantly different from that of SUVR and DVR
    .

    Figure 3.
    Comparison of ROC curve and sample discrimination distribution between the proposed method AQI and the traditional method
    .

    (Source: C Shen, et al.
    , Front Aging Neurosci, 2022) Article Conclusions and Discussions, Inspirations and Prospects AQI (amyloid-beta quantification index) is a semi-quantitative parameter for PiB-PET imaging, through linear combination of drugs Information on removal rates and scanned deposition levels were calculated
    .

    In this work, the researchers demonstrate that by mining the early and mid-brain dynamics of tracer drugs, patients with mild Alzheimer's disease (AD) can be more effectively distinguished from normal subjects
    .

    In particular, early lesions can be reflected by the abnormality of drug outflow tissues, and some early AD patients with inconspicuous amyloid deposition can be correctly identified
    .

    In the acquisition process, only the first 30 minutes of data are collected, which greatly shortens the scanning or waiting time required by conventional imaging methods, avoids motion artifacts that may be caused by long-term scanning, improves scanning efficiency, and reduces large-scale The experimental cost of the sample
    .

    At the same time, since the proposed quantification method does not need to select the reference brain region, it avoids the problem of non-specific uptake when using the cerebellar cortex as the reference brain region, thus avoiding the resulting quantitative bias
    .

    It is worth noting that for samples that were successfully identified by AQI in the experiment, but failed by traditional SUVR and DVR, further in vitro experiments are still needed to confirm whether these samples are really free of amyloid deposition or not bound by PiB [6]
    .

    In addition, only single-center data was used in this work, and the use of multi-center data validation is a necessary step to further promote the proposed method to verify the necessity and possibility of changing the existing clinical acquisition process
    .

    For other tracers for amyloid imaging, such as 18F-Florbetapir, the researchers expect similar results to those produced in this work
    .

    Link to the original text: https:// The first author, Shen Chushu (left), and the corresponding author, Sun Tao (right)
    .

    (Photo provided by: Sun Tao's research group, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences) Talent recruitment [1] "Logical Neuroscience" is looking for an associate editor/editor/operation position (online office) Selected articles from previous issues [1] Front Aging Neurosci Review︱The role of astrocytes in the neurovascular unit after cerebral ischemia[2]HBM︱Region-based spatial standardization of brain MRI images to achieve accurate registration of brain regions[3]J Neuroinflammation︱ Ying Peng's group reveals the regulatory role of microglia mitophagy in morphine-induced central nervous system inflammatory inhibition [4] Curr Biol︱ Novelty detection and the relationship between surprise and recency in the primate brain [5] Neurosci Bull︱Qian Lingjia's research group reveals that homocysteine ​​affects cognitive function by regulating DNA methylation during chronic stress [6] Front Aging Neurosci︱Ma Tao's team reveals that traditional Chinese medicine compound improves multi-channel and multi-target improvement The mechanism of energy metabolism in Alzheimer's disease【7】Aging Cell︱Gao Xu's team found that good sleep quality can delay the accelerated aging caused by air pollution【8】Autophagy︱Shen Hanming's research group revealed that autophagy-related protein WIPI2 regulates mitochondrial outer membrane New Mechanisms of Protein Degradation and Mitophagy【9】Neuron’s Heavy Review︱Zheng Sheng’s Team Focuses on the Important Role of Axonal Mitochondria Maintenance and Energy Supply in Neurodegenerative Diseases and Repair after Neurological Injury【10】Cell Death Dis︱ Kong Hui et al revealed the role of the P2X7/NLRP3 inflammasome pathway in early diabetic retinopathy Recommended for high-quality scientific research training courses [1] Symposium on Patch Clamp and Optogenetics and Calcium Imaging Technology May 14-15 Tencent Conference [2] Research Skills︱The 4th NIR Brain Function Data Analysis Class (Online: 2022.
    4.
    18~4.
    30) References (swipe up and down to read) 1, Lowe, VJ, Kemp, BJ, Jack, CR, Senjem, M.
    , Weigand , S.
    , Shiung, M.
    , Smith, G.
    , Knopman, D.
    , Boeve, B.
    , Mullan, B.
    , and Petersen, RC (2009).
    Comparison of 18F-FDG and PiB PET in cognitive impairment.
    Journal of Nuclear Medicine 50, 878-886.
    2, Price, JC, Klunk, WE, Lopresti, BJ, Lu, X.
    , Hoge, JA, Ziolko, SK, Holt, DP , Meltzer, CC, Dekosky, ST, and Mathis, CA (2005).
    Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B.
    J Cereb Blood Flow Metab 25, 1528-1547.
    3, Rodell, A.
    , Aanerud , J.
    , Braendgaard, H.
    , and Gjedde, A.
    (2013).
    Washout allometric reference method (WARM) for parametric analysis of [11C]PIB in human brains.
    Frontiers in Aging Neuroscience 5:45.
    4, Lamontagne, PJ, Benzinger , TL, Morris, JC, Keefe, S.
    , Hornbeck, R.
    , Xiong, C.
    , Grant, E.
    , Hassenstab, J.
    , Moulder, K.
    , Vlassenko, AG, Raichle, ME, Cruchaga, C.
    , and Marcus, D.
    (2019).
    OASIS-3: Longitudinal Neuroimaging, Clinical,and Cognitive Dataset for Normal Aging and Alzheimer Disease.
    medRxiv.
    19014902.
    5, Bacskai, BJ, Frosch, MP, Freeman, SH, Raymond, SB, Augustinack, JC, Johnson, KA, Irizarry, MC, Klunk, WE, Mathis, CA, Dekosky, ST, Greenberg, SM, Hyman, BT, and Growdon, JH (2007).
    Molecular Imaging With Pittsburgh Compound B Confirmed at Autopsy: A Case Report.
    Archives of Neurology 64, 431-434.
    6, Logan J.
    , Fowler JS, Volkow ND, Wang GJ, Ding YS, Alexoff DL(1996).
    Distribution volume ratios without blood sampling from graphical analysis of PET data.
    J Cereb Blood Flow Metab.
    16: 834-840.
    and Growdon, JH (2007).
    Molecular Imaging With Pittsburgh Compound B Confirmed at Autopsy: A Case Report.
    Archives of Neurology 64, 431-434.
    6, Logan J.
    , Fowler JS, Volkow ND, Wang GJ, Ding YS, Alexoff DL ( 1996).
    Distribution volume ratios without blood sampling from graphical analysis of PET data.
    J Cereb Blood Flow Metab.
    16: 834-840.
    Plate making︱Sizhen Wang End of this paperand Growdon, JH (2007).
    Molecular Imaging With Pittsburgh Compound B Confirmed at Autopsy: A Case Report.
    Archives of Neurology 64, 431-434.
    6, Logan J.
    , Fowler JS, Volkow ND, Wang GJ, Ding YS, Alexoff DL ( 1996).
    Distribution volume ratios without blood sampling from graphical analysis of PET data.
    J Cereb Blood Flow Metab.
    16: 834-840.
    Plate making︱Sizhen Wang End of this paper
    This article is an English version of an article which is originally in the Chinese language on echemi.com and is provided for information purposes only. This website makes no representation or warranty of any kind, either expressed or implied, as to the accuracy, completeness ownership or reliability of the article or any translations thereof. If you have any concerns or complaints relating to the article, please send an email, providing a detailed description of the concern or complaint, to service@echemi.com. A staff member will contact you within 5 working days. Once verified, infringing content will be removed immediately.

    Contact Us

    The source of this page with content of products and services is from Internet, which doesn't represent ECHEMI's opinion. If you have any queries, please write to service@echemi.com. It will be replied within 5 days.

    Moreover, if you find any instances of plagiarism from the page, please send email to service@echemi.com with relevant evidence.