Objective:To assess the β-amyloid (Aβ) deposition of voxel-based PET imaging in Alzheimer′s disease (AD) and its relationships with blood biomarkers (Aβ).Methods:From January 2015 to December 2018, a total of 23 AD patients (9 males, 14 females, age (68.5±9.0) years; duration: (40.9±23.3) months; 8 mild patients, 15 moderate or severe patients) who underwent Aβ PET and with positive imaging results in Daping Hospital, Army Medical University were retrospectively enrolled. The information of Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) were collected. Blood level of Aβ42, Aβ40 were measured. Differences of those metrics including Aβ42/Aβ40 between mild and moderate or severe patients were compared. For all 11C-Pittsburgh compound B (PIB) PET images, voxel-based one-sample independent t test analyses were performed. Voxel-based two-sample independent t test analyses were also performed between mild and moderate or severe patients. The voxel-based Pearson correlation analyses were run to assess the associations between blood metrics and Aβ deposition of 11C-PIB PET. Results:Comparing with mild patients, moderate or severe patients had lower MMSE (9.67±4.37 vs 17.13±2.80; t=4.349, P<0.001) and longer duration ((48.8±23.8) vs (26.0±13.5) months; t=-2.489, P<0.05). On voxel-wise analysis, amyloid PET illustrated brain Aβ deposition in bilateral frontal, right temporal, right occipital and posterior cingulate regions ( t values: 0.44-0.67, all P<0.001). Within AD, Aβ42/Aβ40 ( r values: from -0.62 to -0.41, 0.41-0.66, all P<0.05) were associated with amyloid PET, but not associated with Aβ42 ( r values: from -0.33 to 0, all P>0.05) or Aβ40 ( r values: from -0.41 to 0, all P>0.05). Conclusions:Based on voxel-wise analysis, 11C-PIB PET has comparable value for brain Aβ deposition. Aβ42/Aβ40 has the potential to predict brain Aβ deposition.

Purpose To explore the application value of combining 18F-FDG PET images with interpretable deep learning radiomics(IDLR)models in the differential diagnosis of primary Parkinson's disease(IPD)and atypical Parkinson's syndrome.Materials and Methods This cross-sectional study was conducted using the Parkinson's Disease PET Imaging Benchmark Database from Huashan Hospital,Fudan University from March 2015 to February 2023.A total of 330 Parkinson's disease patients underwent 18F-FDG PET imaging,both 18F-FDG PET imaging and clinical scale information were collected for all subjects.The study included two cohorts,a training group(n=270)and a testing group(n=60),with a total of 211 cases in the IPD group,59 cases in the progressive supranuclear palsy(PSP)group,and a group of 60 patients with multiple system atrophy(MSA).The clinical information between different groups were compared.An IDLR model was developed to extract feature indicators.Under the supervision of radiomics features,IDLR features were selected from the features collected by neural network extractors,and a binary support vector machine model was constructed for the selected features in images of in testing group.The constructed IDLR model,traditional radiomics model and standard uptake ratio model were separately used to calculate the performance metrics and area under curve values of deep learning models for pairwise classification between IPD/PSP/MSA groups.The study conducted independent classification and testing in two cohorts using 100 10-fold cross-validation tests.Brain-related regions of interest were displayed through feature mapping,using gradient weighted class activation maps to highlight and visualize the most relevant information in the brain.The output heatmaps of different disease groups were examined and compared with clinical diagnostic locations.Results The IDLR model showed promising results for differentiating between Parkinson's syndrome patients.It achieved the best classification performance and had the highest area under the curve values compared to other comparative models such as the standard uptake ratio model(Z=1.22-3.23,all P<0.05),and radiomics model(Z=1.31-2.96,all P<0.05).The area under the curve values for the IDLR model in differentiating MSA and IPD were 0.935 7,for MSA and PSP were 0.975 4,for IPD and PSP were 0.982 5 in the test set.The IDLR model also showed consistency between its filtered feature maps and the visualization of gradient-weighted class activation mapping slice thermal maps in the radiomics regions of interest.Conclusion The IDLR model has the potential for differential diagnosis between IPD and atypical Parkinson's syndrome in 18F-FDG PET images.

Presynaptic dopaminergic PET imaging is a useful method for the diagnosis of parkinsonism. Based on the expert consensus on operation and clinical application of dopamine transporter brain PET imaging technology published in 2020, this paper further recommends the relevant elements of result interpretation of presynaptic dopaminergic PET imaging.

BACKGROUND: Insufficient cerebral perfusion is suggested to play a role in the development of Alzheimer disease (AD). However, there is a lack of direct evidence indicating whether hypoperfusion causes or aggravates AD pathology. We investigated the effect of chronic cerebral hypoperfusion on AD-related pathology in humans. METHODS: We enrolled a group of cognitively normal patients (median age: 64 years) with unilateral chronic cerebral hypoperfusion. Regions of interest with the most pronounced hypoperfusion changes were chosen in the hypoperfused region and were then mirrored in the contralateral hemisphere to create a control region with normal perfusion. 11C-Pittsburgh compound-positron emission tomography standard uptake ratios and brain atrophy indices were calculated from the computed tomography images of each patient. RESULTS: The median age of the 10 participants, consisting of 4 males and 6 females, was 64 years (47-76 years). We found that there were no differences in standard uptake ratios of the cortex (volume of interest [VOI]: P = 0.721, region of interest [ROI]: P = 0.241) and grey/white ratio (VOI: P = 0.333, ROI: P = 0.445) and brain atrophy indices (Bicaudate, Bifrontal, Evans, Cella, Cella media, and Ventricular index, P > 0.05) between the hypoperfused regions and contralateral normally perfused regions in patients with unilateral chronic cerebral hypoperfusion. CONCLUSION Our findings suggest that chronic hypoperfusion due to large vessel stenosis may not directly induce cerebral β-amyloid deposition and neurodegeneration in humans.
Aged ; Alzheimer Disease/pathology* ; Amyloid beta-Peptides/metabolism* ; Arteries ; Atrophy ; Brain/metabolism* ; Cerebral Cortex/metabolism* ; Cerebrovascular Circulation ; Constriction, Pathologic/pathology* ; Female ; Humans ; Magnetic Resonance Imaging/methods* ; Male ; Middle Aged ; Positron-Emission Tomography/methods*