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.

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.

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.

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 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.

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.