Objective:To investigate the potential value of cerebral glucose metabolism characteristics in anti-leucine-rich glioma-inactivated protein 1 (LGI1) antibody-related encephalitic patients during acute phase as the clinical indicator of disease outcomes.Methods:From October 2019 to December 2023, 28 patients (18 males, 10 females; age (56.6±11.9) year) with anti-LGI1 antibody-related encephalitis diagnosed at Huashan Hospital, Fudan University were prospectively enrolled. All patients received baseline brain 18F-FDG PET imaging and were divided into different subgroups according to the prognosis (good prognosis and poor prognosis groups) and recurrence (recurrence and non-recurrence groups) after follow-up. The difference of Montreal Cognitive Assessment (MoCA) score between the two groups was compared by Mann-Whitney U test. Statistical parametric mapping (SPM) analysis was used to analyze the PET images of different groups by independent-sample t test, and the characteristics of cerebral glucose metabolism of patients with different outcomes were obtained. Results:MoCA scores between the recurrence group ( n=6) and the non-recurrence group ( n=22; 14.0(9.8, 20.5) vs 22.0(18.0, 24.0); Z=2.17, P=0.030), and between the poor prognosis group ( n=13) and the good prognosis group ( n=15; 14.0(10.0, 22.0) vs 22.0(19.8, 25.3); Z=2.47, P=0.013) were significantly different. Compared with the good prognosis group, the cerebral glucose metabolism in the poor prognosis group was decreased in the bilateral frontal lobe, lateral temporal lobe, inferior parietal lobule and cingulate gyrus, but increased in the brainstem, bilateral lentiform nucleus and bilateral paracentral lobule/postcentral gyrus (all t=1.71, all P<0.05). Compared with the non-recurrence group, the metabolism of bilateral medial frontal gyrus, anterior cingulate gyrus, bilateral insula, superior temporal gyrus and thalamus decreased in the recurrence group, while the metabolism of bilateral precentral gyrus, inferior frontal gyrus and bilateral lentiform nucleus increased (all t=1.71, all P<0.05). Conclusion:18F-FDG PET imaging reveals the differences in brain metabolism of anti-LGI1 antibody-related encephalitic patients at baseline with different outcomes (prognosis, recurrence or not), which can provide a new perspective for the clinical evaluation of the disease at baseline.

Purpose To investigate the cortical thickness features in Parkinson's disease(PD)patients at various stages and their association with dopamine transporter(DAT)levels in the putamen.Materials and Methods We retrospectively enrolled 30 PD patients and 15 healthy subject who underwent 11C-CFT PET and T1 MRI scans at the Department of Nuclear Medicine/PET Center of Huashan Hospital from August 2016 to October 2020.DAT average radioactivity in the anterior and posterior putamen was analysis using SPM12 software,with the occipital lobe as the reference region.Cortical segmentation and reconstruction were performed on T1 images using Freesurfer v7.2.The differences in cortical thinning between the groups were compared using a general linear model.Additionally,the relationship between cortical thickness in various brain regions and DAT uptake in the putamen were assessed.Results Compared to healthy subjects,significant cortical thinning was observed in the left inferior parietal lobule and the right and left inferior middle frontal gyrus of PD patients(all P<0.05).There was a significant positive correlation between the cortical thickness of the left inferior parietal lobule and right inferior middle frontal gyrus and DAT uptake in the corresponding anterior/posterior parts of the putamen(r=0.30-0.47,all P<0.05).Furthermore,the DAT uptake in the right precentral gyrus was positively correlated with the ipsilateral posterior putamen,exhibiting a stronger correlation than on the contralateral side(r=0.32,P=0.029).Conclusion The results show that the thickness of the thinning cortex area in the PD patients correlates significantly positively with DAT levels in the putamen,highlighting the importance of the basal ganglia cortical circuit and providing a basis for further research into the neural mechanisms of PD.

Purpose To investigate the cortical thickness features in Parkinson's disease(PD)patients at various stages and their association with dopamine transporter(DAT)levels in the putamen.Materials and Methods We retrospectively enrolled 30 PD patients and 15 healthy subject who underwent 11C-CFT PET and T1 MRI scans at the Department of Nuclear Medicine/PET Center of Huashan Hospital from August 2016 to October 2020.DAT average radioactivity in the anterior and posterior putamen was analysis using SPM12 software,with the occipital lobe as the reference region.Cortical segmentation and reconstruction were performed on T1 images using Freesurfer v7.2.The differences in cortical thinning between the groups were compared using a general linear model.Additionally,the relationship between cortical thickness in various brain regions and DAT uptake in the putamen were assessed.Results Compared to healthy subjects,significant cortical thinning was observed in the left inferior parietal lobule and the right and left inferior middle frontal gyrus of PD patients(all P<0.05).There was a significant positive correlation between the cortical thickness of the left inferior parietal lobule and right inferior middle frontal gyrus and DAT uptake in the corresponding anterior/posterior parts of the putamen(r=0.30-0.47,all P<0.05).Furthermore,the DAT uptake in the right precentral gyrus was positively correlated with the ipsilateral posterior putamen,exhibiting a stronger correlation than on the contralateral side(r=0.32,P=0.029).Conclusion The results show that the thickness of the thinning cortex area in the PD patients correlates significantly positively with DAT levels in the putamen,highlighting the importance of the basal ganglia cortical circuit and providing a basis for further research into the neural mechanisms of PD.

Objective To observe the correlation between cortical thickness and pathological deposition of β-amyloid(Aβ)in patients with Alzheimer disease(AD)induced mild cognitive impairment(MCI)or dementia.Methods Totally 22 AD patients were prospectively enrolled and divided into dementia group(n=12)and MCI group(n=10)based on the degree of cognitive impairment,while 17 healthy individuals without cognitive impairment were recruited as control group.MR examination and 18F-florbutaben(18F-FBB)PET imaging were performed,the cortical thickness and Aβ deposition value(Centiloid[CL]value)were calculated and compared among 3 groups and between each 2 groups,then the correlation between the above two indexes was analyzed.Results The cortical thickness in dementia group,MCI group and control group was(2.18±0.14),(2.35±0.08)and(2.36±0.09)mm,respectively,with significant difference among 3 groups(P＜0.05).The cortical thickness in dementia group was significantly thinner than that in MCI group and control group(both P＜0.05).CL value in dementia group,MCI group and control group was 77.97(63.07,95.55),65.51(54.54,90.50)and-1.17(-9.66,4.88),respectively,with significant difference among 3 groups(P＜0.05).CL value in dementia group and MCI group were significantly higher than in control group(both P＜0.05).The cortical thickness was moderately negatively correlated with CL value in MCI group(r=-0.580,P=0.048)but not in the other 2 groups(both P＞0.05).Conclusion The cortical thickness was moderately negatively correlated with abnormal deposition of Aβ in patients with AD induced MCI,but was not during dementia.

Objective To observe the correlation between cortical thickness and pathological deposition of β-amyloid(Aβ)in patients with Alzheimer disease(AD)induced mild cognitive impairment(MCI)or dementia.Methods Totally 22 AD patients were prospectively enrolled and divided into dementia group(n=12)and MCI group(n=10)based on the degree of cognitive impairment,while 17 healthy individuals without cognitive impairment were recruited as control group.MR examination and 18F-florbutaben(18F-FBB)PET imaging were performed,the cortical thickness and Aβ deposition value(Centiloid[CL]value)were calculated and compared among 3 groups and between each 2 groups,then the correlation between the above two indexes was analyzed.Results The cortical thickness in dementia group,MCI group and control group was(2.18±0.14),(2.35±0.08)and(2.36±0.09)mm,respectively,with significant difference among 3 groups(P＜0.05).The cortical thickness in dementia group was significantly thinner than that in MCI group and control group(both P＜0.05).CL value in dementia group,MCI group and control group was 77.97(63.07,95.55),65.51(54.54,90.50)and-1.17(-9.66,4.88),respectively,with significant difference among 3 groups(P＜0.05).CL value in dementia group and MCI group were significantly higher than in control group(both P＜0.05).The cortical thickness was moderately negatively correlated with CL value in MCI group(r=-0.580,P=0.048)but not in the other 2 groups(both P＞0.05).Conclusion The cortical thickness was moderately negatively correlated with abnormal deposition of Aβ in patients with AD induced MCI,but was not during dementia.

Objective:To investigate the potential value of cerebral glucose metabolism characteristics in anti-leucine-rich glioma-inactivated protein 1 (LGI1) antibody-related encephalitic patients during acute phase as the clinical indicator of disease outcomes.Methods:From October 2019 to December 2023, 28 patients (18 males, 10 females; age (56.6±11.9) year) with anti-LGI1 antibody-related encephalitis diagnosed at Huashan Hospital, Fudan University were prospectively enrolled. All patients received baseline brain 18F-FDG PET imaging and were divided into different subgroups according to the prognosis (good prognosis and poor prognosis groups) and recurrence (recurrence and non-recurrence groups) after follow-up. The difference of Montreal Cognitive Assessment (MoCA) score between the two groups was compared by Mann-Whitney U test. Statistical parametric mapping (SPM) analysis was used to analyze the PET images of different groups by independent-sample t test, and the characteristics of cerebral glucose metabolism of patients with different outcomes were obtained. Results:MoCA scores between the recurrence group ( n=6) and the non-recurrence group ( n=22; 14.0(9.8, 20.5) vs 22.0(18.0, 24.0); Z=2.17, P=0.030), and between the poor prognosis group ( n=13) and the good prognosis group ( n=15; 14.0(10.0, 22.0) vs 22.0(19.8, 25.3); Z=2.47, P=0.013) were significantly different. Compared with the good prognosis group, the cerebral glucose metabolism in the poor prognosis group was decreased in the bilateral frontal lobe, lateral temporal lobe, inferior parietal lobule and cingulate gyrus, but increased in the brainstem, bilateral lentiform nucleus and bilateral paracentral lobule/postcentral gyrus (all t=1.71, all P<0.05). Compared with the non-recurrence group, the metabolism of bilateral medial frontal gyrus, anterior cingulate gyrus, bilateral insula, superior temporal gyrus and thalamus decreased in the recurrence group, while the metabolism of bilateral precentral gyrus, inferior frontal gyrus and bilateral lentiform nucleus increased (all t=1.71, all P<0.05). Conclusion:18F-FDG PET imaging reveals the differences in brain metabolism of anti-LGI1 antibody-related encephalitic patients at baseline with different outcomes (prognosis, recurrence or not), which can provide a new perspective for the clinical evaluation of the disease at baseline.

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.

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: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.