Objective:To investigate the value of a deep learning radiomics (DLR) nomogram model based on intra-tumoral and peri-tumoral MRI features for differentiating IgG4-related ophthalmic disease (IgG4-ROD) from orbital mucosa-associated lymphoid tissue (MALT) lymphoma.Methods:This was a case-control study. The clinical and imaging data of 233 patients pathologically confirmed with either IgG4-ROD or orbital MALT lymphoma were retrospective collected between January 2020 and December 2024 from the Second Hospital of Jilin University (Center 1) and Beijing Tongren Hospital, Capital Medical University (Center 2). Patients from Center 1 ( n=158) were used as the training cohort, while those from Center 2 ( n=75) served as the validation cohort. Among the cases, 102 were IgG4-ROD (70 in training, 32 in validation) and 131 were orbital MALT lymphoma (88 in training, 43 in validation). Univariate and multivariate logistic regression analyses were used to identify independent clinical imaging predictors and build a clinical imaging model. Based on T 1WI, T 2WI, and diffusion weighted images, intra-tumoral regions were manually delineated, a 2 mm peri-tumoral margin was automatically generated, and both regions were combined as a single region of interest for radiomics feature extraction. Deep learning features were extracted using a ResNet-50 backbone, and after feature selection and dimensionality reduction, a DLR model was constructed. The clinical imaging features and DLR features were integrated to build a combined nomogram model. Model performance in differentiating IgG4-ROD from orbital MALT lymphoma was assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis. The area under the curve (AUC) were compared using the DeLong test. Results:Bilateral orbital involvement ( OR=1.983, 95% CI 1.166-2.843, P=0.046) and extraocular muscle involvement ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as independent predictors for distinguishing IgG4-ROD from orbital MALT lymphoma and were used to construct the clinical model. Fourteen features (9 radiomics and 5 deep learning features) were selected for the DLR model, and a nomogram was developed. In the training set, the AUCs for the clinical model, DLR model, and nomogram were 0.762 (95% CI 0.712-0.812), 0.865 (95% CI 0.822-0.908), and 0.943 (95% CI 0.909-0.953), respectively. In the validation set, the AUCs were 0.733 (95% CI 0.675-0.791), 0.823 (95% CI 0.762-0.884), and 0.924 (95% CI 0.902-0.958), respectively. The nomogram showed significantly higher AUCs than those of the clinical and DLR models alone (training set: Z=3.92, 2.87, P0.001, P=0.004; validation set: Z=3.25, 2.46, P=0.001, 0.014). Calibration curves indicated good agreement between predicted and actual IgG4-ROD incidence, and decision curve analysis demonstrated the highest net benefit for the nomogram. Conclusion:A nomogram that incorporates both intra-tumoral and peri-tumoral DLR features and clinical imaging characteristics demonstrates excellent performance in distinguishing IgG4-ROD from orbital MALT lymphoma.

Objective:To evaluate cerebrospinal fluid (CSF) flow dynamics and volume changes of pulsatile tinnitus (PT) patients induced by sigmoid sinus wall dehiscence (SSWD) using MRI.Methods:This was a cross-sectional study. Totally 55 SSWD-PT patients, and 35 age- and sex-matched healthy controls were prospectively enrolled at Beijing Tongren Hospital, Capital Medical University from October 2019 to September 2023. The CSF at the midbrain aqueduct level was analyzed based on phase-contrast MRI to obtain the flow dynamics information. Based on T 1-weighted turbo field echo sequence, the CSF was segmented and the volume of CSF was calculated using ITK-SNAP software. The Mann-Whitney U test was used to compare the differences of each parameter between the two groups. Binary logistic regression was used to analyze the parameters with statistically significant differences to obtain the independent influencing factors of SSWD-PT and establish the combined parameters. Receiver operating characteristic curve analysis was used to evaluate the efficacy of diagnosing SSWD-PT. Results:Compared with controls, the SSWD-PT group showed significantly decreased mean flux (MF), mean velocity, peak velocity( P<0.05), and significantly increased regurgitant fraction (RF), CSF volume ( P<0.05). No significant differences were observed in forward flow volume, backward flow volume, and stroke volume ( P>0.05). The logistic regression results showed that MF ( OR=0.497, 95% CI 0.305-0.808, P=0.005) and RF ( OR=1.809, 95% CI 1.040-3.147, P=0.036) were independent influencing factors of SSWD-PT. The area under the curve (AUC) of MF and RF for diagnosing SSWD-PT were 0.641 (95% CI 0.517-0.766) and 0.675 (95% CI 0.564-0.786), respectively. The AUC of the combination of MF and RF was 0.724 (95% CI 0.614-0.833). Conclusions:SSWD-PT patients have abnormal changes in CSF flow dynamics and volume. The MF and RF demonstrate moderate diagnostic value for diagnosing SSWD-PT.

Objective:To investigate the value of a deep learning radiomics (DLR) nomogram model based on intra-tumoral and peri-tumoral MRI features for differentiating IgG4-related ophthalmic disease (IgG4-ROD) from orbital mucosa-associated lymphoid tissue (MALT) lymphoma.Methods:This was a case-control study. The clinical and imaging data of 233 patients pathologically confirmed with either IgG4-ROD or orbital MALT lymphoma were retrospective collected between January 2020 and December 2024 from the Second Hospital of Jilin University (Center 1) and Beijing Tongren Hospital, Capital Medical University (Center 2). Patients from Center 1 ( n=158) were used as the training cohort, while those from Center 2 ( n=75) served as the validation cohort. Among the cases, 102 were IgG4-ROD (70 in training, 32 in validation) and 131 were orbital MALT lymphoma (88 in training, 43 in validation). Univariate and multivariate logistic regression analyses were used to identify independent clinical imaging predictors and build a clinical imaging model. Based on T 1WI, T 2WI, and diffusion weighted images, intra-tumoral regions were manually delineated, a 2 mm peri-tumoral margin was automatically generated, and both regions were combined as a single region of interest for radiomics feature extraction. Deep learning features were extracted using a ResNet-50 backbone, and after feature selection and dimensionality reduction, a DLR model was constructed. The clinical imaging features and DLR features were integrated to build a combined nomogram model. Model performance in differentiating IgG4-ROD from orbital MALT lymphoma was assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis. The area under the curve (AUC) were compared using the DeLong test. Results:Bilateral orbital involvement ( OR=1.983, 95% CI 1.166-2.843, P=0.046) and extraocular muscle involvement ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as independent predictors for distinguishing IgG4-ROD from orbital MALT lymphoma and were used to construct the clinical model. Fourteen features (9 radiomics and 5 deep learning features) were selected for the DLR model, and a nomogram was developed. In the training set, the AUCs for the clinical model, DLR model, and nomogram were 0.762 (95% CI 0.712-0.812), 0.865 (95% CI 0.822-0.908), and 0.943 (95% CI 0.909-0.953), respectively. In the validation set, the AUCs were 0.733 (95% CI 0.675-0.791), 0.823 (95% CI 0.762-0.884), and 0.924 (95% CI 0.902-0.958), respectively. The nomogram showed significantly higher AUCs than those of the clinical and DLR models alone (training set: Z=3.92, 2.87, P0.001, P=0.004; validation set: Z=3.25, 2.46, P=0.001, 0.014). Calibration curves indicated good agreement between predicted and actual IgG4-ROD incidence, and decision curve analysis demonstrated the highest net benefit for the nomogram. Conclusion:A nomogram that incorporates both intra-tumoral and peri-tumoral DLR features and clinical imaging characteristics demonstrates excellent performance in distinguishing IgG4-ROD from orbital MALT lymphoma.

Objective:To evaluate cerebrospinal fluid (CSF) flow dynamics and volume changes of pulsatile tinnitus (PT) patients induced by sigmoid sinus wall dehiscence (SSWD) using MRI.Methods:This was a cross-sectional study. Totally 55 SSWD-PT patients, and 35 age- and sex-matched healthy controls were prospectively enrolled at Beijing Tongren Hospital, Capital Medical University from October 2019 to September 2023. The CSF at the midbrain aqueduct level was analyzed based on phase-contrast MRI to obtain the flow dynamics information. Based on T 1-weighted turbo field echo sequence, the CSF was segmented and the volume of CSF was calculated using ITK-SNAP software. The Mann-Whitney U test was used to compare the differences of each parameter between the two groups. Binary logistic regression was used to analyze the parameters with statistically significant differences to obtain the independent influencing factors of SSWD-PT and establish the combined parameters. Receiver operating characteristic curve analysis was used to evaluate the efficacy of diagnosing SSWD-PT. Results:Compared with controls, the SSWD-PT group showed significantly decreased mean flux (MF), mean velocity, peak velocity( P<0.05), and significantly increased regurgitant fraction (RF), CSF volume ( P<0.05). No significant differences were observed in forward flow volume, backward flow volume, and stroke volume ( P>0.05). The logistic regression results showed that MF ( OR=0.497, 95% CI 0.305-0.808, P=0.005) and RF ( OR=1.809, 95% CI 1.040-3.147, P=0.036) were independent influencing factors of SSWD-PT. The area under the curve (AUC) of MF and RF for diagnosing SSWD-PT were 0.641 (95% CI 0.517-0.766) and 0.675 (95% CI 0.564-0.786), respectively. The AUC of the combination of MF and RF was 0.724 (95% CI 0.614-0.833). Conclusions:SSWD-PT patients have abnormal changes in CSF flow dynamics and volume. The MF and RF demonstrate moderate diagnostic value for diagnosing SSWD-PT.

With the widespread application of information technology in the field of Traditional Chinese Medicine(TCM),the data in the TCM domain is becoming increasingly rich.The emergence of data-driven research in TCM has utilized knowledge graphs for the management,analysis,and presentation of TCM data,becoming a crucial method for the inheritance and innovation of Traditional Chinese Medicine.Therefore,reasoning based on TCM knowledge graphs has become a hot topic in contemporary TCM research.In order to better utilize knowledge graph reasoning technology to promote innovation and development in TCM,this article,after providing an overview of TCM knowledge graph reasoning,focuses on the development of knowledge graph reasoning in TCM and its applications from three perspectives:logic rule-based,distributed representation,and neural network-based methods.Finally,the article summarizes the advantages and disadvantages of knowledge reasoning methods and provides prospects for research and applications in TCM knowledge graph reasoning,including studies on interpretability,temporal knowledge graphs,and the fusion of multimodal information.

Objective:To investigate the status and diagnostic reference levels (DRLs) of adult CT radiation dose based on survey result from some hospitals in Beijing.Methods:From September to December 2023, the survey results for 50 hospitals were collected in Beijing, including 47 tertiary hospitals and 3 second grade general hospitals. The CT data sets in total of 20 items including head (sequential scanning), head (spiral scanning), head perfusion, sinus, neck, chest, chest (low dose scanning), abdomen, pelvis, abdomen-pelvis, chest-abdomen-pelvis, lumbar spine, CT urography, coronary CTA (retrospective), coronary CTA (prospective), head CTA, neck CTA, aorta CTA, leg CTA and knee were collected on clinical commonly used CT scanners with annual qualified state inspection. For each item, radiation dose data was collected continuously and randomly for up to 50 cases for every CT scanner. Using the volume CT dose index (CTDI vol) and dose length product (DLP) as dose parameters, the median value of each item in each hospital was obtained. The median CTDI vol and DLP values of all hospitals were arranged, and the local DRL of each item was set as the 75th percentile of the median values. The obtained DRLs were compared with the DRLs issued by domestic and international radiological protection organizations. Results:A total of 26 031 dose values of adult patients were collected and 25 996 dose values were left while 35 invalid values removed.For different CT users, CTDl vol, DLP and scanning phases were different for the same item. The five items with the highest CTDI were head perfusion, head sequential scanning, head spiral scanning, coronary CTA (retrospective mode), and sinus. The five items with the highest DLP were CTU, head perfusion, leg CTA, chest-abdomen-pelvis and aortic CTA. The CTDI vol of CTU was only 16.9 mGy (75th percentile), while the DLP was as high as 2 394.9 mGy·cm (75th percentile). The survey showed that the DRLs of most items in Beijing was lower than the national DRLs of domestic and foreign standards, and the DRLs of a small number of items were slightly higher. Conclusion:The current CT dose level in Beijing is not consistent with national DRLs released at home and abroad, so it is necessary to establish local DRLs according to the clinical status in Beijing.

Objective To investigate the effect of ventilation with different tidal volumes on respiratory mechanics and haemodynamics in children with severe pneumonia.Methods A total of 104 children with severe pneumonia were divided into the control group and the observation group using a random number table method,with 52 cases in each group.Both groups underwent mechanical ventilation treatment.The control group was treated with conventional tidal volume of 10-12 mL/kg,while the observation group was given a low tidal volume of 6-8 mL/kg.The respiratory mechanics indicators,hemodynamic indicators and inflammatory factor indicators before and after treatment were compared between the two groups.Results After treatment,the airway resistance(AR)and airway closing pressure(AOP)were lower in the observation group than those of the control group(P＜0.05),and pulmonary dynamic compliance(Cdyn)was higher in the observation group than that of the control group(P＜0.05).There were no significant differences in heart rate(HR),mean arterial pressure(MAP)and central venous pressure(CVP)after treatment between the two groups(P＜0.05).After treatment,the levels of interleukin(IL)-6,IL-8 and tumor necrosis factor-α(TNF-α)were all lower in the observation group than those in the control group(P＜0.05).Conclusion Small tidal volume mechanical ventilation is effective in improving the respiratory mechanics of children with severe pneumonia without causing large fluctuations in their hemodynamics.At the same time,it can reduce the level of inflammatory factors in the organism.

Objective To investigate the effect of the rs3765467 polymorphism of glucagon-like peptide-1 receptor(GLP-1R)gene on the efficacy of Liraglutide(Lir)in patients with type 2 diabetes mellitus(T2DM)and metabolic associated fatty liver disease(MAFLD).Methods A total of 281 patients with T2DM from May 2022 to May 2023 were selected,including 125 patients with simple T2DM(T2DM group)and 156 patients with T2DM combined with MAFLD(T2DM+MAFLD group).120 healthy individuals during the same period were selected as the control(NC)group.The related indexes of glucose and lipid metabolism were detected.The polymorphism of GLP-1R gene rs3765467 was detected.Results BMI,FPG,HbA1c,HOMA-IR and TG in each group increased in turn(P<0.05),while the distribution frequency of genotype GG and allele G decreased in turn(P<0.05).TC and LDL-C in T2DM and T2DM+MAFLD groups were higher than those in NC group(P<0.05).TC and TG levels in genotype GA/AA patients were significantly higher than those in genotype GG patients(P<0.05).Compared with before treatment,the levels of BMI,FPG,HbA1c,HOMA-IR,TC,TG and LDL-C in T2DM patients with MAFLD were significantly decreased after Lir treatment(P<0.05).There was no significant difference in BMI and related indexes of glucose and lipid metabolism in GG and GA/AA patients before and after Lir treatment(P>0.05).Conclusions The distribution frequency of GG and G allele at rs3765467 of GLP-1R gene is reduced in T2DM patients with MAFLD.The carrying of allele A was associated with increased TC and TG levels,but did not affect the efficacy of Lir in reducing weight and improving glycolipid metabolism.

Objective To investigate the effect of ventilation with different tidal volumes on respiratory mechanics and haemodynamics in children with severe pneumonia.Methods A total of 104 children with severe pneumonia were divided into the control group and the observation group using a random number table method,with 52 cases in each group.Both groups underwent mechanical ventilation treatment.The control group was treated with conventional tidal volume of 10-12 mL/kg,while the observation group was given a low tidal volume of 6-8 mL/kg.The respiratory mechanics indicators,hemodynamic indicators and inflammatory factor indicators before and after treatment were compared between the two groups.Results After treatment,the airway resistance(AR)and airway closing pressure(AOP)were lower in the observation group than those of the control group(P＜0.05),and pulmonary dynamic compliance(Cdyn)was higher in the observation group than that of the control group(P＜0.05).There were no significant differences in heart rate(HR),mean arterial pressure(MAP)and central venous pressure(CVP)after treatment between the two groups(P＜0.05).After treatment,the levels of interleukin(IL)-6,IL-8 and tumor necrosis factor-α(TNF-α)were all lower in the observation group than those in the control group(P＜0.05).Conclusion Small tidal volume mechanical ventilation is effective in improving the respiratory mechanics of children with severe pneumonia without causing large fluctuations in their hemodynamics.At the same time,it can reduce the level of inflammatory factors in the organism.