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.

Large language models (LLMs), represented by ChatGPT, have garnered significant attention due to their powerful capabilities in understanding and generating human language. Research on the application of LLMs across various medical tasks has shown a vigorous development trend. This review aims to outline the development and clinical applications of LLMs, with a focus on the primary tasks of medical intelligent assistants, including their associated opportunities and challenges. At the technical level, we provide a detailed explanation of the architecture and training processes of existing medical LLMs, and summarize the general technical steps for adapting large models to the healthcare domain. At the application level, we introduce the main tasks of medical intelligent assistants from both healthcare provider- and patient-oriented perspectives, andcompare the performance of different LLMs across various medical tasks to illustrate their unique advantages and limitations in medical applications.

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.

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.