The integration of TCM and Western medicine in imaging aims to enrich the sources of diagnostic information by utilizing medical imaging technologies,focusing on key elements such as TCM imaging,Western medical imaging,diseases and TCM syndrome types,thereby facilitating the complementary strengths of both systems.With the advancement of digital imaging and artificial intelligence technologies,various research models and methodologies have emerged.This article discussed the development and application of integrated imaging of traditional Chinese and Western medicine,and proposed three primary research paradigms in this field:Analyzing TCM images(e.g.,tongue and face)through manual or image processing techniques to assist in the diagnosis of Western medical diagnosis;Mapping Western medical imaging signs(e.g.,computed tomography,magnetic resonance imaging and ultrasound imaging)to TCM syndrome patterns for objective evidence in TCM diagnosis and treatment;Applying imaging omics to extract and integrate features from both TCM and Western medical images for comprehensive diagnosis.This study reviewed the three paradigms,explained relevant concepts and technologies,and proposed a specific research workflow of integrated imaging omics of traditional Chinese and Western medicine,aiming to provide a reference for innovative development in this field.

To summarize the nursing experience of a patient with relapsed/refractory diffuse large B-cell lymphoma who suffered from cytokine release syndrome after chimeric antigen receptor T-cell therapy.The main nursing experiences include:implementing emergency care for distributive shock caused by cytokine storm;carrying out the nursing of lung ventilation protection strategies;strengthening detailed skin care;prevention,control and care of hospital-acquired infections in an immunosuppressed state.After active treatment,the patient was transferred to the general ward 9 days later and discharged 27 days later.

Objective To explore the value of diffusion tensor imaging analysis index along the perivascular space(DTI-ALPS)for assessing age-related functional changes in glymphatic system(GS).Methods Totally 27 healthy subjects from Meizhou People's Hospital and 100 healthy subjects from neuroimaging informatics tools and resources collaborator database who underwent T1-weighted magnetization-prepared rapid gradient echo(T1-MPRAGE)and DTI scanning were retrospectively enrolled and divided into youth group(n=38),middle-aged group(n=57)and elderly group(n=32).Automated DTI-ALPS index analysis procedure was used to minimize manual errors and derive DTI-ALPS index.The general data,neuropsychological assessment results and DTI-ALPS indices were compared among groups.Spearman correlation analysis was performed to observe the relationships of DTI-ALPS index and age,gender,as well as neuropsychological scores.Results The average age in youth group,middle-aged group and elderly group was(28.5±5.8),(53.7±6.8)and(73.8±2.3)years,respectively.No significant difference of DTI-ALPS index was found between middle-aged group and elderly group(P＞0.05),which were both lower than that in youth group(both P＜0.05).DTI-ALPS index was weakly negatively correlated with age(rs=-0.340,P＜0.001),but not significantly correlated with gender nor neuropsychological assessment results(both P＞0.05).Conclusion DTI-ALPS index was negatively correlated with age in healthy individuals,hence having potential utility for assessing age-related functional changes in GS.

OBJECTIVE: This study aims to elucidate the therapeutic potential of osthole for the treatment of atopic dermatitis (AD), focusing on its ability to alleviate chronic pruritus (CP) and the underlying molecular mechanisms. METHODS: In this study, we investigated the anti-inflammatory effects of osthole in both a 2,4-dichloronitrobenzene (DNCB)-induced AD mouse model and tumor necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) stimulated huma immortalized epidermal (HaCaT) cells. The anti-itch effect of osthole was specifically assessed in the AD mouse model. Using methods such as hematoxylin and eosin (HE) staining, enzyme-linked immunosorbent assay (ELISA), western blot (WB), quantitative real-time PCR (qRT-PCR), and immunofluorescence staining. RESULTS: Osthole improved skin damage and clinical dermatitis scores, reduced scratching bouts, and decreased epidermal thickness AD-like mice. It also reduced the levels of interleukin (IL)-31 and IL-31 receptor A (IL-31 RA) in both skin tissues and HaCaT cells. Furthermore, Osthole suppressed the protein expression levels of phosphor-p65 (p-p65) and phosphor-inhibitor of nuclear factor kappa-Bα (p-IκBα). Meanwhile, it increased the protein expression levels of peroxisome proliferator-activated receptor α (PPARα) and PPARγ in HaCaT cells. CONCLUSION These findings indicated that osthole effectively inhibited CP in AD by activating PPARα, PPARγ, repressing the NF-κB signaling pathway, as well as the expression of IL-31 and IL-31 RA.

Objective To explore the value of diffusion tensor imaging analysis index along the perivascular space(DTI-ALPS)for assessing age-related functional changes in glymphatic system(GS).Methods Totally 27 healthy subjects from Meizhou People's Hospital and 100 healthy subjects from neuroimaging informatics tools and resources collaborator database who underwent T1-weighted magnetization-prepared rapid gradient echo(T1-MPRAGE)and DTI scanning were retrospectively enrolled and divided into youth group(n=38),middle-aged group(n=57)and elderly group(n=32).Automated DTI-ALPS index analysis procedure was used to minimize manual errors and derive DTI-ALPS index.The general data,neuropsychological assessment results and DTI-ALPS indices were compared among groups.Spearman correlation analysis was performed to observe the relationships of DTI-ALPS index and age,gender,as well as neuropsychological scores.Results The average age in youth group,middle-aged group and elderly group was(28.5±5.8),(53.7±6.8)and(73.8±2.3)years,respectively.No significant difference of DTI-ALPS index was found between middle-aged group and elderly group(P＞0.05),which were both lower than that in youth group(both P＜0.05).DTI-ALPS index was weakly negatively correlated with age(rs=-0.340,P＜0.001),but not significantly correlated with gender nor neuropsychological assessment results(both P＞0.05).Conclusion DTI-ALPS index was negatively correlated with age in healthy individuals,hence having potential utility for assessing age-related functional changes in GS.

The integration of TCM and Western medicine in imaging aims to enrich the sources of diagnostic information by utilizing medical imaging technologies,focusing on key elements such as TCM imaging,Western medical imaging,diseases and TCM syndrome types,thereby facilitating the complementary strengths of both systems.With the advancement of digital imaging and artificial intelligence technologies,various research models and methodologies have emerged.This article discussed the development and application of integrated imaging of traditional Chinese and Western medicine,and proposed three primary research paradigms in this field:Analyzing TCM images(e.g.,tongue and face)through manual or image processing techniques to assist in the diagnosis of Western medical diagnosis;Mapping Western medical imaging signs(e.g.,computed tomography,magnetic resonance imaging and ultrasound imaging)to TCM syndrome patterns for objective evidence in TCM diagnosis and treatment;Applying imaging omics to extract and integrate features from both TCM and Western medical images for comprehensive diagnosis.This study reviewed the three paradigms,explained relevant concepts and technologies,and proposed a specific research workflow of integrated imaging omics of traditional Chinese and Western medicine,aiming to provide a reference for innovative development in this field.

To summarize the nursing experience of a patient with relapsed/refractory diffuse large B-cell lymphoma who suffered from cytokine release syndrome after chimeric antigen receptor T-cell therapy.The main nursing experiences include:implementing emergency care for distributive shock caused by cytokine storm;carrying out the nursing of lung ventilation protection strategies;strengthening detailed skin care;prevention,control and care of hospital-acquired infections in an immunosuppressed state.After active treatment,the patient was transferred to the general ward 9 days later and discharged 27 days later.

As an emerging discipline that combines traditional diagnostic methods with modern scientific technology,micro syndrome differentiation has good prospects for development,but there are some controversies in the research process.Based on ancient and modern literature,this article reviewed the origin and flow of research on micro syndrome differentiation,and summarized the problems to be improved in the process of research on micro syndrome differentiation from three aspects:application of disease type,guiding ideology and micro indicators.Based on this,the article further expounded the new thinking on"near-micro"syndrome differentiation from three aspects:connotation,scope of application,and links to traditional identification and micro-identification,and pointed out that the modern medical detection basis should be incorporated into the field of TCM syndrome differentiation,and at the same time,it should be based on the overall thinking mode of TCM,which would provide a new idea for the development of modern TCM diagnosis technology.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.