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.

Objective:To compare the effects of different reference brain regions on the semi-quantitative SUV ratio (SUVR) of 18F-Florzolotau PET images of Alzheimer′s disease (AD). Methods:The 18F-Florzolotau PET images of 28 (13 males, 15 females, age (57.3±9.5) years) normal controls (NC), 19 patients (4 males, 15 females, age (73.3±7.3) years) with β-amyloid (Aβ)-positive mild cognitive impairment (MCI) and 40 patients (19 males, 21 females, age (61.9±9.1) years) with AD were collected from Huashan Hospital, Fudan University between November 2018 and July 2020. Six semi-quantitative reference brain regions were defined, including whole cerebellum (WC), cerebellar gray matter (GM), cerebellar white matter (WM), parametric estimation of reference signal intensity (PERSI), WC after partial volume correction (WC_pvc), cerebellar GM after partial volume correction (GM_pvc). SUVR was calculated for 14 ROIs, which included the whole brain defined by the automated anatomical labeling (AAL) template, fusiform, inferior temporal, lingual, middle temporal, occipital, parahippocampal, parietal, posterior cingulate, precuneus defined by the AAL template, and Meta ROI composed of the above brain regions, and braak_Ⅰ-Ⅱ, braak_Ⅲ-Ⅳ, braak_Ⅴ-Ⅵ defined by the Desikan Killiany template. AUC was used to evaluate the classification ability of SUVR, and the correlation between SUVR and clinical scale scores were assessed by Spearman rank correlation analysis. Results:The SUVRs of most brain regions showed a steady upward trend in the AD disease spectrum. In the classification task of NC and MCI, the overall performance of SUVR based on WC_pvc was relatively optimal (AUCs: 0.975-1.000). In the classification task of NC and AD, SUVRs of 10 ROIs based on the WC_pvc method showed the relatively best performance (AUCs: 0.976-1.000). The correlation between SUVR of fusiform based on cerebellar WM and mini-mental state examination (MMSE) score was the strongest ( rs=-0.72, P<0.001), and the SUVR of precuneus based on WC_pvc showed the strongest correlation with clinical dementia rating (CDR) score ( rs=0.78, P<0.001). Conclusion:The SUVR based on WC_pvc method performs well in classification and correlation tasks, and is recommended to be used in semi-quantification of 18F-Florzolotau PET images of AD.

Objective:To perform harmonization based on the ComBat method for PET brain imaging scanned by different types of scanners from the same manufacturer and explored its effect on center effect.Methods:The three-dimensional (3D) Hoffman brain model was scanned by two different PET/CT instruments (Siemens Biograph64 TruePoint and Biograph128 mCT). Fourteen healthy subjects (8 males, 6 females, age: (57.7±9.5) years) underwent 18F-FDG PET/CT on Siemens Biograph64 TruePoint and 12 healthy subjects (9 males, 3 females, age: (55.8±10.5) years) underwent 18F-FDG PET/CT on Siemens Biograph128 mCT (all from Huashan Hospital, Fudan University; from November 2020 to March 2023). The whole brain was divided into 116 brain regions based on the anatomical automatic labeling (AAL) brain template. The ComBat method was applied to harmonized the PET data from brain model and healthy subjects. Mann-Whitney U test was performed on the radioactive counts and SUV ratios (SUVR) before and after homogenization acquired by both PET/CT instruments. Voxel-based statistical parametric mapping (SPM) independent-sample t test was also performed on data of healthy subjects. Results:In 3D Hoffman brain model, radioactivity counts (5 590.33(4 961.67, 6 102.95) vs 6 116.03(5 420.97, 6 660.66); z=-9.35, P<0.001) and SUVR (1.35(1.19, 1.47) vs 1.37(1.21, 1.49); z=-3.63, P<0.001) were significantly different between the two PET/CT scanners before harmonization and not after harmonization (radioactivity counts: 5 845.95(5 192.68, 6 378.63) vs 5 859.17(5 193.84, 6 380.52); SUVR: 1.35(1.20, 1.48) vs 1.36(1.20, 1.49); both z=-0.68, both P=0.498). In the healthy subjects, radioactive counts in 19 brain regions (12 422.78(11 181.60, 13 424.28)-18 166.40(15 882.80, 18 666.27); z values: from -3.24 to -2.06, all P<0.05) and SUVR in 40 brain regions (1.46(1.41, 1.52)-2.28(2.16, 2.36); z values: from -3.65 to -1.70, all P<0.05) were significantly different between the two scanners before harmonization, while after homogenization there were no statistical differences for all 116 brain regions (radioactivity counts: 9 243.55(8 502.38, 9 854.87)-20 419.60(19 931.51, 21 179.43); z values: from -0.72 to 0, all P>0.05; SUVR: 1.04(1.01, 1.09)-2.32(2.24, 2.40); z values: from -0.82 to 0, all P>0.05). SPM showed that significant differences of glucose metabolism in the cerebral cortex, basal ganglia, midbrain and cerebellum were found in healthy subjects between the two PET/CT scanners before homogenization, and brain regions with obvious differences reduced after homogenization. Conclusion:ComBat harmonization method is efficient at removing the center effect among different types of PET/CT scanners from the same manufacturer and may provide a simple and easy-to-implement homogenization for multicenter brain imaging studies.

Objective:A voxel-level quantification method based on the tau IQ algorithm and Braak staging, excluding β-amyloid (Aβ) imaging, was developed to achieve specific tau quantification. Methods:This cross-sectional study included 92 subjects (35 males, 57 females; age (62.9±10.4) years) from the Nuclear Medicine/PET Center of Huashan Hospital, Fudan University between November 2018 and July 2020. The cohort comprised 28 cognitively normal (CN) individuals, 20 patients with mild cognitive impairment (MCI), and 44 patients with Alzheimer′s disease (AD). All participants underwent 18F-florzolotau PET imaging, Mini-Mental State Examination (MMSE), and Clinical Dementia Rating (CDR) scoring. A longitudinal tau dataset was constructed based on Braak staging. Voxel-level logistic regression fitting provided a baseline matrix, decomposed via least squares to yield the Tau load coefficient. One-way analysis of variance (with post hoc Tukey) was used to compare Tau load and SUV ratio (SUVR) among groups. ROC curve analysis was used to evaluate classification between CN, MCI and AD. Spearman rank correlation was used to assess the relationships between Tau load, SUVR, and MMSE scores or CDR scores. Results:The Tau load in the CN group was close to 0 and significantly lower than that in the MCI and AD groups ( F=55.03, P<0.001; post hoc tests all P<0.001). Significant differences were also observed in the SUVR across all ROIs ( F values: 36.46-55.38, all P<0.001). Compared to SUVR, Tau load demonstrated greater intergroup differences. In ROC curve analyses between each pair of CN, MCI, and AD groups, Tau load consistently achieved the highest AUC (0.754-1.000). Both Tau load and SUVR for each ROI were negatively correlated with MMSE scores ( rs values: from -0.698 to -0.583, all P<0.05) and positively correlated with CDR scores ( rs values: 0.648-0.783, all P<0.05), with Tau load showing the highest absolute correlation coefficients. Conclusion:Compared to the traditional semi-quantitative SUVR method, the Braak-tau IQ algorithm does not require a specific reference brain region to achieve specific tau quantification.

Purpose To investigate the characteristics of 18F-Florbetaben(18F-FBB)β-amyloid(Aβ)PET imaging in different brain regions of Alzheimer's disease(AD)patients with different degrees of cognitive impairment,and to explore the correlation between Aβ deposition and cognitive dysfunction.Materials and Methods A total of eighteen patients with a clinical diagnosis of probable AD from August 2022 to October 2023 were retrospectively included in Huashan Hospital.All patients had Aβ abnormal deposition in the brain as confirmed by 18F-FBB PET imaging.According to the severity of symptoms,they were divided into the AD-induced mild cognitive impairment(MCI)group(8 cases)and the dementia group(10 cases).In addition,12 healthy controls were included.First,the standardized uptake value ratio of abnormal Aβ deposition in the frontal lobe,lateral parietal lobe,lateral temporal lobe,anterior and posterior cingulate gyrus,and compound cortex was semi-quantitatively calculated and compared among the three groups based on the subjects'brain MRI and automated anatomical labeling template.The correlation between the degree of Aβ deposition in the brains of AD patients and cognitive scale scores(mini-mental state examination,Montreal cognitive assessment)was then further analyzed.Results The standardized uptake value ratio values of Aβabnormal deposition in the frontal lobe,lateral temporal lobe,lateral parietal lobe,anterior and posterior cingulate cortex and compound cortex in the AD-induced MCI and dementia groups were significantly higher than those in the healthy controls(t=7.442-9.151,all P＜0.05).However,there was no significant difference in the standardized uptake value ratio values of Aβ abnormal deposition in the above brain regions between the MCI and dementia groups(t=0.312-0.996,all P＞0.05).In addition,there was no significant correlation between the degree of Aβ deposition in the brain and the cognitive scale scores(mini-mental state examination,Montreal cognitive assessment)in the AD-induced MCI and dementia groups(r=-0.049-0.050,all P＞0.05).Conclusion Aβ deposition in the brains of AD-induced MCI and dementia is significantly higher than in the healthy controls.However,Aβ deposition cannot identify AD patients with different degrees of cognitive impairment,reflecting that Aβ deposition has certain limitations in assessing the severity of clinical symptoms of AD.

Purpose To explore the value of the new generation tau PET tracer 18F-Florzolotau in Alzheimer's disease(AD)at different stages.Materials and Methods Twenty-five MCI patients and sixty-one AD patients with positive β-amyloid status in Huashan Hospital,Fudan University from February 2020 to January 2022 were retrospectively enrolled with 18F-Florzolotau PET imaging and demographic and clinical data.The pre-processed PET images were analyzed by SPM two-sample t-test between MCI and AD groups,and the standardized uptake value ratios(SUVR)were extracted from the region of interest defined by SPM analysis(P＜0.001);scaled subprofile model/principal component analysis was used to construct the different tau related patterns(MCItauRP,ADtauRP)and calculate the corresponding expression values.The classification efficiency of SUVR and MCItauRP,ADtauRP expression values was evaluated by receiver operating characteristic curve.Results Compared with MCI patients,tau protein deposition of AD patients was increased mainly in the bilateral temporal,occipital lobe(P＜0.001),and the SUVR of these brain region in the AD group was higher than that in the MCI group(Z=-3.164,P＜0.00l);the expression values of MCItauRP and ADtauRP were significantly different between the AD group and MCI group(t=3.72,Z=-3.51;both P＜0.001),and these expression values of AD patients were higher than those in the MCI group;the accuracy of tauRP expression values and SUVR for the differentiation between the AD and MCI group were 61.63％,65.12％and 65.12％,respectively;the sensitivity was 88.00％,96.00％and 100.00％,respectively;the specificity was 50.82％,52.46％and 50.82％,respectively.Conclusion The new tau PET can identify and distinguish the differences in tau protein deposition between AD and MCI patients.However,the classification and diagnosis efficiency is not high.In the future,it is necessary to find a more ideal analysis method.

Objective:To establish standard spatial brain template and ROIs template of 11C-methyl- N-2β-carbomethoxy-3β-(4-fluorophenyl)tropane (CFT) PET images for automated quantitative analysis of dopamine transporter (DAT) distribution. Methods:From May 2014 to December 2015, 11C-CFT PET and MRI T 1 brain images of 16 healthy volunteers (3 males, 13 females; age (63.3±6.9) years) from Huashan Hospital, Fudan University were co-registered and smoothed using statistical parametric mapping(SPM)5 software based on MATLAB to create a standard spatial brain template. The ROIs template was established by ScAnVp procedures. These templates were clinically verified by using 11C-CFT PET images of 37 healthy volunteers (23 males, 14 females; age (61.7±7.1) years), 32 Parkinson′s disease (PD) patients (20 males, 12 females; age (61.1±5.4) years), 10 multiple system atrophy with predominant parkinsonism (MSA-P) patients (7 males, 3 females; age (60.8±7.1) years) and 10 progressive supranuclear palsy (PSP) patients (5 males, 5 females; age (58.4±6.1) years) from Huashan Hospital, Fudan University between January 2014 and March 2019. One-way analysis of variance was used to analyze data. Results:Based on the 11C-CFT PET images and MRI T 1 images of healthy volunteers, a standard spatial brain template for normalization of 11C-CFT PET images was created. The ROIs template was established including seven regions: bilateral caudate, anterior putamen, posterior putamen (along the long axis) and the occipital cortex. The ROIs template was accurately aligned in each verification group. The normal reference values of semi-quantitative DAT distribution in caudate, anterior putamen and posterior putamen were obtained (1.84±0.13, 2.18±0.16, 1.77±0.11). The semi-quantitative values of 11C-CFT uptake in each ROI in patients were significantly lower than those in healthy volunteers ( F values: 49.79-283.83, all P<0.05). Conclusion:The established brain templates with accurate spatial alignment for 11C-CFT image analysis can provide foundational tools for the application of 11C-CFT PET imaging in clinical practice and scientific research.

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.

Objective:To investigate whether the presynaptic dopamine neuronal depletion in different striatal subregions predicts future development of wearing-off (WO) in Parkinson′s disease (PD) patients.Methods:A retrospective longitudinal study included 57 PD patients who were referred to the Department of Neurology of Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2019 to September 2020, and completed 11C-2β-carbomethoxy-3β-(4-fluorophenyl) tropane dopamine transporter (DAT) positron emission tomography scans at the initial evaluation and received dopaminergic drugs for at least 12 months during follow-up. The time of starting dopaminergic drug treatment and the occurrence of WO were recorded. After adjusting for clinical related factors, the predictive value of DAT uptake and related parameters in striatal subregions for WO was evaluated by Cox proportional hazards model. Results:During a median follow-up period of 23 months, 10 patients (18.18%) developed WO. Patients with WO exhibited less DAT uptake in the caudate nucleus and anterior putamen nucleus (0.66±0.52 vs 1.08±0.42, t=2.76, P=0.008 and 0.66±0.20 vs 0.87±0.28, t=2.27, P=0.027 respectively), especially in these subregions contralateral to the less-affected side of the body, compared to those without WO. Cox proportional hazard models revealed that after adjusting for gender, age, course of disease, baseline Unified Parkinson′s Disease Rating Scale Ⅲ score and increment of levodopa equivalent dosage, the lower the DAT uptake of the caudate ipsilateral to the less-affected side of the body ( HR=0.20, 95% CI 0.07-0.63, P=0.006), as well as the lower the DAT uptake of the caudate nucleus and posterior putamen nucleus ( HR=0.28, 95% CI 0.11-0.69, P=0.006 and HR=0.08, 95% CI 0.01-0.64, P=0.018 respectively) and the higher the ratio of putamen/caudate contralateral to the less-affected side of the body ( HR=2.33, 95% CI 1.02-5.33, P=0.045), the higher the risk of WO. Conclusion:The presynaptic dopamine neuronal loss, particularly bilateral caudate nucleus dopaminergic depletion at the early stage, has predictive value of development of WO in PD.

Objective:To investigate the clinical, neuropsychological, and neuroimage characteristics in patients with corticobasal syndrome (CBS), and to elucidate the exact diagnosis of CBS patients.Methods:Twelve CBS cases admitted to the Department of Neurology, Huashan Hosiptal,Fudan University from April 2019 to July 2021 were retrospectively enrolled in this study. Those data, including clinical features (demographic data and clinical characteristics of cortical dysfunction and movement disorder), neuropsychological assessment [Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scales score], brain magnetic resonance imaging (MRI) and multi-mode positron emission tomography (PET)/CT, were collected and carefully reviewed. Exact diagnosis of these patients was given according to the disease diagnosis criteria.Results:Cortical dysfunction and asymmetrical movement disorders were found in all cases, with poor response to levodopa. Patients suffered from cognitive impairment (MMSE score 16.16±9.82, MoCA score 13.44±7.35). The cranial MRI demonstrated significant asymmetric atrophy of frontal and parietal lobes, especially in the pre- and post-central gyrus. Fluorodeoxyglucose PET of 12 patients showed asymmetric frontal lobe and basal ganglia (especially caudate and putamen) hypometabolism (obviously on the contralateral side of the affected limb). Tau PET was implemented in 11 patients and displayed that abnormal tau protein deposition was positive in the cortex and/or subcortex in all patients. Of the 4 cases, who completed amyloid PET, amyloid protein deposition was positive in the cortex of 2 patients. As a result, 6 patients were diagnosed as progressive supranuclear palsy, 1 patient was diagnosed as corticobasal degeneration, and 5 patients were diagnosed as Alzheimer′s disease.Conclusions:The etiology of CBS is heterogeneous. The combination of clinical manifestation, cranial MRI and multi-mode PET/CT helps the differential diagnosis of CBS.