Background and purpose:Diffuse large B-cell lymphoma(DLBCL)is subclassified into germinal center B-cell-like(GCB)and non-GCB subtypes,which differ in prognosis and treatment response.However,current distinction still relies on invasive pathological assays.This study developed radiomics and deep-learning models based on multiparametric magnetic resonance imaging(MRI)to non-invasively differentiate the two subtypes preoperatively,thereby reducing dependence on histopathological examination.Methods:This study retrospectively included patients with pathologically confirmed DLBCL diagnosed at Huashan Hospital,Fudan University,and other institutions between March 2013 and December 2024.Using multiparametric MRI data,we developed DLBCL-subtype classification models that combined 4 radiomics-based machine-learning algorithms:support vector machine(SVM),logistic regression(LR),Gaussian process(GP)and Naive Bayes(NB),with 3 deep-learning architectures[densely-connected convolutional networks 121(DenseNet121),residual network 101(ResNet101)and EfficientNet-b5].Additionally,two radiologists with different experience levels independently classified DLBCL on MRI in a blinded fashion.Model and radiologist performance were quantified using the area under the receiver operating characteristic curve(AUC),accuracy(ACC),and F1-score to evaluate their ability to distinguish GCB from non-GCB subtypes.This study was approved by the Ethics Committee of Huashan Hospital of Fudan University(No.KY2024-663),and all patients signed informed consents.Results:A total of 173 patients were enrolled(55 with GCB subtype and 118 with non-GCB subtype).Radiomics and deep learning methods effectively distinguished DLBCL subtypes.Among these,the GP radiomics model(based on T1-CE+T2-FLAIR+ADC sequences)and DenseNet121 deep learning model(based on T1-CE+T2-FLAIR+ADC sequences)demonstrated optimal performance.Both achieved excellent results on the internal validation set(GP:AUC=0.900,ACC=0.896,F1=0.840;DenseNet121:AUC=0.846,ACC=0.854,F1=0.774)and maintained robustness on the external validation set.Furthermore,the classification efficacy of the optimal AI model surpassed that of experienced radiologists(highest physician AUC=0.678).Conclusion:Radiomics and deep-learning models based on multiparametric MRI features can effectively differentiate GCB from non-GCB subtypes of DLBCL.Among them,GP and DenseNet121 exhibit outstanding performance,especially when integrating multi-sequence feature sets for classifying DLBCL subtypes on complex imaging data.

Background and purpose:Diffuse large B-cell lymphoma(DLBCL)is subclassified into germinal center B-cell-like(GCB)and non-GCB subtypes,which differ in prognosis and treatment response.However,current distinction still relies on invasive pathological assays.This study developed radiomics and deep-learning models based on multiparametric magnetic resonance imaging(MRI)to non-invasively differentiate the two subtypes preoperatively,thereby reducing dependence on histopathological examination.Methods:This study retrospectively included patients with pathologically confirmed DLBCL diagnosed at Huashan Hospital,Fudan University,and other institutions between March 2013 and December 2024.Using multiparametric MRI data,we developed DLBCL-subtype classification models that combined 4 radiomics-based machine-learning algorithms:support vector machine(SVM),logistic regression(LR),Gaussian process(GP)and Naive Bayes(NB),with 3 deep-learning architectures[densely-connected convolutional networks 121(DenseNet121),residual network 101(ResNet101)and EfficientNet-b5].Additionally,two radiologists with different experience levels independently classified DLBCL on MRI in a blinded fashion.Model and radiologist performance were quantified using the area under the receiver operating characteristic curve(AUC),accuracy(ACC),and F1-score to evaluate their ability to distinguish GCB from non-GCB subtypes.This study was approved by the Ethics Committee of Huashan Hospital of Fudan University(No.KY2024-663),and all patients signed informed consents.Results:A total of 173 patients were enrolled(55 with GCB subtype and 118 with non-GCB subtype).Radiomics and deep learning methods effectively distinguished DLBCL subtypes.Among these,the GP radiomics model(based on T1-CE+T2-FLAIR+ADC sequences)and DenseNet121 deep learning model(based on T1-CE+T2-FLAIR+ADC sequences)demonstrated optimal performance.Both achieved excellent results on the internal validation set(GP:AUC=0.900,ACC=0.896,F1=0.840;DenseNet121:AUC=0.846,ACC=0.854,F1=0.774)and maintained robustness on the external validation set.Furthermore,the classification efficacy of the optimal AI model surpassed that of experienced radiologists(highest physician AUC=0.678).Conclusion:Radiomics and deep-learning models based on multiparametric MRI features can effectively differentiate GCB from non-GCB subtypes of DLBCL.Among them,GP and DenseNet121 exhibit outstanding performance,especially when integrating multi-sequence feature sets for classifying DLBCL subtypes on complex imaging data.

Objective: : This study aims to investigate the relationship between aneurysm wall enhancement and clinical rupture risks based on the magnetic resonance vessel wall imaging (MR-VWI) quantitative methods. Methods: : One hundred and eight patients with 127 unruptured aneurysms were prospectively enrolled from Feburary 2016 to October 2017. Aneurysms were divided into high risk (≥10) and intermediate-low risk group (<10) according to the PHASES (Population, Hypertension, Age, Size of aneurysm, Earlier SAH history from another aneurysm, Site of aneurysm) scores. Clinical risk factors, aneurysm morphology, and wall enhancement index (WEI) calculated using 3D MR-VWI were analyzed and compared. Results: : In comparison of high-risk and intermediated-low risk groups, univariate analysis showed that neck width (4.5±3.3 mm vs. 3.4±1.7 mm, p=0.002), the presence of wall enhancement (100.0% vs. 62.9%, p<0.001), and WEI (1.6±0.6 vs. 0.8±0.8, p<0.001) were significantly associated with high rupture risk. Multivariate regression analysis revealed that WEI was the most important factor in predicting high rupture risk (odds ratio, 2.6; 95% confidence interval, 1.4–4.9; p=0.002). The receiver operating characteristic (ROC) curve analysis can efficiently differentiate higher risk aneurysms (area under the curve, 0.780; p<0.001) which have a reliable WEI cutoff value (1.04; sensitivity, 0.833; specificity, 0.67) predictive of high rupture risk. Conclusion : Aneurysms with higher rupture risk based on PHASES score demonstrate increased neck width, wall enhancement, and the enhancement intensity. Higher WEI in unruptured aneurysms has a predictive value for increased rupture risk.

Objective To investigate the life quality changes and influencing factors of acute coronary syn -drome after stent implantation .Methods 100 cases with acute coronary syndrome received stent implantation were selected .SF-36 life quality questionnaire was used to survey the patients′life quality before operation and 6 months af-ter operation,and the life quality changes and influence factors were analyzed .Results 6 months after operation,the physical activity ,mental health ,social activities ,physical pain ,physical function ,physical role ,energy and health score of the patients were higher than before operation (P<0.05).According to Logistic regression analysis ,female,type 2 diabetes,underwent percutaneous coronary intervention ,ST-T segment elevation myocardial infarction were the im-portant factors affecting patients′recovery(P<0.05).Conclusion 6 months after stent implantation,the life quality of the patients with acute coronary syndrome were improved obviously;the female and underwent percutaneous coro-nary intervention have positive influence on patients′recovery,while type 2 diabetes,ST-T segment elevation myocar-dial infarction affect patients′recovery in negative way .

Objective To assess the clinical features and associated factors of interstitial lung disease (ILD) in patients with dermatomyositis (DM).Methods Clinical data were retrospectively analyzed on 206 patients with DM collected at the Department of Dermatology,Huashan Hospital,Fudan University in the past 6 years.Chi-square test and t test were performed for statistical analysis.Results The prevalence of ILD was 49.03％ in the 206 patients with DM.Heliotrope rash on the upper eyelids,Gottron's sign (papules),arthralgia,and cough were correlated with the incidence of ILD in DM patients (all P ＜ 0.05),and of these factors,the prevalence of artharalgia and cough were positively correlated with the incidence of ILD,while the presence of Gottron's papules was negatively correlated.The patients with DM and ILD showed a higher prevalence of abnormal serum levels of lactate dehydrogenase (LDH),hydroxybutyrate dehydrogenase (HBDH) and anti-Jo-1 antibodies,as well as with a poorer pulmonary function,compared with those suffering from DM only (all P ＜0.05).Characteristic imaging findings on computed tomography (CT) scan in patients with DM and ILD included linear opacity (57.4％),high-density patchy opacity (31.7％),reticular opacity (16.8％) and even ground glass-like opacity (13.8％),usually at the bottom or apex of the lungs.Conclusions In patients with DM,the prevalence of artharalgia and cough is positively correlated,whereas the presence of Gottron's papules is negatively correlated,with the incidence of ILD.Characteristic imaging findings on CT scan in patients with DM and ILD are linear opacity,high-density patchy opacity,reticular opacity and ground glass-like opacity at the bottom and apex of lungs.

Objective To assess the influence of community and hospital comprehensive Health management on quality of life in aged patients with coronary artery disease (CAD) after PCI.Methods 147 patients with CAD after PCI were divided into experimental group(72 cases) and control group (75 cases) accordance with their residential community.In control group,community health education was introduced.While in experimental group,hospital and community comprehensive healthy education lasted for one year.Before and after invention,major adverse cardiac events (MACE) was recorded and generic quality of life inventory (CQOLI-74),self-rating anxiety scale (SAS),and self-rating depression scale (SDS) were carried out on the basis of giving unite guiding words.Results The observation items of the SAS(34±6 vs41 ±7,t =2.714,P ＜0.01)and SDS(35 ±7 vs 41 ±8,t =2.572,P ＜0.05)scores in experimental group were lower than those in control group.Meanwhile the body health dimension(63 ± 12 vs 59 ±11,t =5.935,P ＜0.01 ),psychological health dimension(64 ± 14 vs 58 ± 13,t =6.116,P ＜0.01 ),social function dimension(64 ± 11 vs 58 ± 10,t =6.157,P ＜0.01 ) were higher than those in control group,but the difference of the material life dimension and the MACE rate were not statistically significant( P ＞0.05).Conclusions Community and Hospital comprehensive health management is a practical and valuable strategy for palliating the depression and anxiety and improving quality of life after PCI in aged patients.

Among 172 patients with coronary artery disease (CAD),94 received community and hospital joint management (joint group) after percutaneous coronary intervention (PCI) for Ⅰ year and 78 received community-based health education only (control group) after PCI.The compliance of medication,readmission rate,times of hospitalization,medical costs,major adverse cardiac events (MACE),and general quality of life inventory (CQOLI-74),self-rating anxiety scale (SAS) and self-rating depression scale (SDS) scores were compared between two groups.The rate of readmission,times of hospitalization,medical costs,the sores of SAS and SDS in joint group were lower than those in control group(P ＜ 0.01 or 0.05).The compliance of medication,body health dimension,psychological health dimension and social function dimension in joint group were better than those in control group,but there were no differences in material life dimension and the MACE rate between two groups(P ＞ 0.05).Community and hospital joint management can reduce the readmission rate and medical burden,and improve quality of life for elderly CAD patients after PCI.

Objective To explore the relationship between structure and function in the diseases of posterior visual pathways as well as the anatomic mechanism of the abnormal visual responses.Methods Eleven cases of diseases of posterior visual pathways(3 gliomas,4 meningiomas,3 metastasis,1 stroke) involving either cortical or subcortical visual pathways were investigated by combining fMRI and DTI.fMRI was performed by using flashing checkerboard at 8 Hz.For imaging processing,fMRI analysis was performed with SPM99,and DTI and tractography with DTVⅡ.Fractional anisotropy(FA) of optic radiations and activated volume(VOXELs) of primary visual cortices(V1 and V2) were measured and analyzed at the affected side and the contralateral side.Relative FA(rFA) and relative activated volume(rVOXELs) were also calculated.3D tractography of optic radiations was performed successfully in 11 patients.Results In the patients with brain tumors,FA values in the affected side of optic radiations were significantly different with the contralateral side(P

Objective To study and establish the GC fingerprint of Rhizoma Ligustici from Suichuan to guide the standardization of planting Rhizoma Ligustici. MethodsTen batches of volatile oils were extracted by steam distillation, then separated by capillary gas chromatography and determined by GC/MS. ResultsThe similarity of ten batches of Rhizoma Ligustici from Suichuan is higher, all samples contain derivatives of phthalides and allyl-benzene. ConclusionThe method is reliable, accurate and can be used to evaluate the quality of Suichuan Rhizoma Ligustici and guide the planting.