As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

Objective:To develop a deep learning-based segmentation model MT-UNet to automatically segment bone metastases and benign bone lesions in bone scintigraphy with SPECT/CT.Methods:A total of 93 patients (48 males and 45 females, age 28-84 years) who underwent bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from June 2023 to December 2023 were enrolled retrospectively in this study, with a total of 184 bone lesions (94 benign lesions and 90 metastatic tumors). The MT-UNet was employed to segment bone lesions in SPECT, CT and SPECT/CT images respectively. Comparative analysis with 8 segmentation models was performed. The training set and validation set were divided by using 5-fold cross-validation and transfer learning was introduced to further enhance the robustness of the model. An additional cohort of 22 patients (15 males and 7 females, age 37-87 years) who received bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from April 2023 to May 2023 were included, comprising 40 bone lesions (22 benign lesions and 18 metastatic tumors) as the test set of MT-UNet. Segmentation performance of different models was assessed using accuracy, sensitivity, specificity, AUC, intersection over union and Dice similarity coefficient (DSC). Delong test was used to compare the segmentation efficacy among different models in the test set.Results:In the validation set, MT-UNet demonstrated DSC of 0.940, 0.962, and 0.963 for SPECT, CT, and SPECT/CT bone lesion segmentation, respectively, which were outperformed other models. Following transfer learning implementation, the SPECT/CT model′s DSC was improved to 0.984. In the test set, MT-UNet maintained comparable segmentation performance to the validation set, with significant AUC differences among the three models ( Z values: from -15.42 to -9.27, all P<0.01). Compared with conventional image interpretation, MT-UNet-based segmentation reduced physician interpretation time from 164min to 102min. Conclusion:MT-UNet has shown good performance in automatic segmentation of bone metastases and benign bone lesions, and is expected to become an important part of SPECT/CT image intelligent diagnosis system for bone metastases.

Objective To establish an optimized diagnostic model for hepatocellular carcinoma(HCC),designated as G-GADA,in chronic hepatitis B(CHB)patients based on the parameters of age,sex,alpha-fetoprotein(AFP),des-γ-carboxy prothrombin(DCP),and Golgi protein 73(GP73),to address the problems of low sensitivity and specificity in the early diagnosis of hepatitis B virus(HBV)-related liver cancer,and to assess the value of this model in the diagnosis of HCC.Methods A retrospective analysis was performed for 201 CHB patients(CHB group),137 patients with HBV-related liver cirrhosis(LC group),and 111 treatment-na?ve patients with newly diagnosed HCC(HCC group)who were admitted to Mengchao Hepatobiliary Hospital of Fujian Medical University from June 2015 to June 2020.Serological markers(AFP,DCP,alpha-fetoprotein L3%[AFP-L3%],and GP73)were compared between groups and were analyzed in terms of their differences from the clinical and tumor characteristics of HCC patients,and the Spearman correlation analysis was used to assess the correlation between different markers.A Logistic regression analysis was used to establish a diagnostic model for liver cancer,and the receiver operating characteristic(ROC)curve was used to assess the diagnostic performance of each marker.Results Comparison of clinical features between CHB,LC,and HCC patients showed that HCC patients had significantly higher age,proportion of male patients,and serum levels of DCP,AFP,GP73,and AFP-L3%(all P<0.05).In HCC patients,DCP levels are associated with tumor size and microvascular invasion;AFP levels are related to patient age,tumor size,tumor number,distant metastasis,and microvascular invasion;AFP-L3%levels are associated with patient age,tumor size,tumor number,distant metastasis,Milan staging,and microvascular invasion;GP73 levels are linked to tumor number,distant metastasis,and microvascular invasion(all P<0.05).The correlation analysis of the serum markers showed a strong positive correlation between AFP and AFP-L3%(r=0.71,P<0.05)and a moderate positive correlation between AFP and GP73(r=0.33,P<0.05)and between AFP-L3%and GP73(r=0.41,P<0.05).Based on the features of age,sex,DCP,AFP,and GP73,the multivariate Logistic regression analysis was used to establish a G-GADA diagnostic model for HCC,and for all patients,the G-GADA model had an area under the ROC curve(AUC)of 0.915(95%confidence interval[CI]:0.875-0.945)in the derivation cohort and 0.913(95%CI:0.862-0.950)in the validation cohort for the diagnosis of HCC.In the AFP-negative patients,the G-GADA model achieved an AUC of 0.884(95%CI:0.833-0.924)in the derivation cohort and 0.851(95%CI:0.779-0.907)in the validation cohort,and in the patients with liver cirrhosis,the G-GADA model achieved an AUC of 0.901(95%CI:0.841-0.944)in the derivation cohort and 0.885(95%CI:0.806-0.940)in the validation cohort.Conclusion The G-GADA diagnostic model based on multiple variables significantly improves the detection rate of HCC,and demonstrates superior diagnostic performance in patients with low AFP expression and those with liver cirrhosis.The G-GADA model has a better clinical application value in the noninvasive diagnosis of HCC.

A 78-year-old male patient presented with significant dilation of the non-coronary sinus of the aorta,which compressed the right atrium and formed a local low-voltage area,resulting in frequent polymorphic atrial premature beats(24-hour load 40.9%).Through dual-chamber combined activation mapping,the target point(right atrial appendage-tricuspid valve annulus junction)was locked.After radiofrequency ablation,atrial premature beats disappeared,and there was no recurrence during the follow-up period of six months.Currently,there are many causes of atrial arrhythmias related to atrial compression,but it is extremely rare for the right atrium to be involved and cause isolated frequent atrial premature beats.Treatment should be individualized,choosing either interventional or surgical methods,and emphasizing the interpretation of anatomical-electrical correlations using multimodal imaging(ultrasound,CT angiography,three-dimensional electroanatomical system).

A 78-year-old male patient presented with significant dilation of the non-coronary sinus of the aorta,which compressed the right atrium and formed a local low-voltage area,resulting in frequent polymorphic atrial premature beats(24-hour load 40.9%).Through dual-chamber combined activation mapping,the target point(right atrial appendage-tricuspid valve annulus junction)was locked.After radiofrequency ablation,atrial premature beats disappeared,and there was no recurrence during the follow-up period of six months.Currently,there are many causes of atrial arrhythmias related to atrial compression,but it is extremely rare for the right atrium to be involved and cause isolated frequent atrial premature beats.Treatment should be individualized,choosing either interventional or surgical methods,and emphasizing the interpretation of anatomical-electrical correlations using multimodal imaging(ultrasound,CT angiography,three-dimensional electroanatomical system).

Objective To establish an optimized diagnostic model for hepatocellular carcinoma(HCC),designated as G-GADA,in chronic hepatitis B(CHB)patients based on the parameters of age,sex,alpha-fetoprotein(AFP),des-γ-carboxy prothrombin(DCP),and Golgi protein 73(GP73),to address the problems of low sensitivity and specificity in the early diagnosis of hepatitis B virus(HBV)-related liver cancer,and to assess the value of this model in the diagnosis of HCC.Methods A retrospective analysis was performed for 201 CHB patients(CHB group),137 patients with HBV-related liver cirrhosis(LC group),and 111 treatment-na?ve patients with newly diagnosed HCC(HCC group)who were admitted to Mengchao Hepatobiliary Hospital of Fujian Medical University from June 2015 to June 2020.Serological markers(AFP,DCP,alpha-fetoprotein L3%[AFP-L3%],and GP73)were compared between groups and were analyzed in terms of their differences from the clinical and tumor characteristics of HCC patients,and the Spearman correlation analysis was used to assess the correlation between different markers.A Logistic regression analysis was used to establish a diagnostic model for liver cancer,and the receiver operating characteristic(ROC)curve was used to assess the diagnostic performance of each marker.Results Comparison of clinical features between CHB,LC,and HCC patients showed that HCC patients had significantly higher age,proportion of male patients,and serum levels of DCP,AFP,GP73,and AFP-L3%(all P<0.05).In HCC patients,DCP levels are associated with tumor size and microvascular invasion;AFP levels are related to patient age,tumor size,tumor number,distant metastasis,and microvascular invasion;AFP-L3%levels are associated with patient age,tumor size,tumor number,distant metastasis,Milan staging,and microvascular invasion;GP73 levels are linked to tumor number,distant metastasis,and microvascular invasion(all P<0.05).The correlation analysis of the serum markers showed a strong positive correlation between AFP and AFP-L3%(r=0.71,P<0.05)and a moderate positive correlation between AFP and GP73(r=0.33,P<0.05)and between AFP-L3%and GP73(r=0.41,P<0.05).Based on the features of age,sex,DCP,AFP,and GP73,the multivariate Logistic regression analysis was used to establish a G-GADA diagnostic model for HCC,and for all patients,the G-GADA model had an area under the ROC curve(AUC)of 0.915(95%confidence interval[CI]:0.875-0.945)in the derivation cohort and 0.913(95%CI:0.862-0.950)in the validation cohort for the diagnosis of HCC.In the AFP-negative patients,the G-GADA model achieved an AUC of 0.884(95%CI:0.833-0.924)in the derivation cohort and 0.851(95%CI:0.779-0.907)in the validation cohort,and in the patients with liver cirrhosis,the G-GADA model achieved an AUC of 0.901(95%CI:0.841-0.944)in the derivation cohort and 0.885(95%CI:0.806-0.940)in the validation cohort.Conclusion The G-GADA diagnostic model based on multiple variables significantly improves the detection rate of HCC,and demonstrates superior diagnostic performance in patients with low AFP expression and those with liver cirrhosis.The G-GADA model has a better clinical application value in the noninvasive diagnosis of HCC.

Objective:To develop a deep learning-based segmentation model MT-UNet to automatically segment bone metastases and benign bone lesions in bone scintigraphy with SPECT/CT.Methods:A total of 93 patients (48 males and 45 females, age 28-84 years) who underwent bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from June 2023 to December 2023 were enrolled retrospectively in this study, with a total of 184 bone lesions (94 benign lesions and 90 metastatic tumors). The MT-UNet was employed to segment bone lesions in SPECT, CT and SPECT/CT images respectively. Comparative analysis with 8 segmentation models was performed. The training set and validation set were divided by using 5-fold cross-validation and transfer learning was introduced to further enhance the robustness of the model. An additional cohort of 22 patients (15 males and 7 females, age 37-87 years) who received bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from April 2023 to May 2023 were included, comprising 40 bone lesions (22 benign lesions and 18 metastatic tumors) as the test set of MT-UNet. Segmentation performance of different models was assessed using accuracy, sensitivity, specificity, AUC, intersection over union and Dice similarity coefficient (DSC). Delong test was used to compare the segmentation efficacy among different models in the test set.Results:In the validation set, MT-UNet demonstrated DSC of 0.940, 0.962, and 0.963 for SPECT, CT, and SPECT/CT bone lesion segmentation, respectively, which were outperformed other models. Following transfer learning implementation, the SPECT/CT model′s DSC was improved to 0.984. In the test set, MT-UNet maintained comparable segmentation performance to the validation set, with significant AUC differences among the three models ( Z values: from -15.42 to -9.27, all P<0.01). Compared with conventional image interpretation, MT-UNet-based segmentation reduced physician interpretation time from 164min to 102min. Conclusion:MT-UNet has shown good performance in automatic segmentation of bone metastases and benign bone lesions, and is expected to become an important part of SPECT/CT image intelligent diagnosis system for bone metastases.

ObjectiveThe natural history of chronic HBV infection often involves a histologically defined immune tolerance state， and once such immune tolerance state is broken， antiviral therapy should be initiated immediately. This study aims to investigate the correlation between immune-mediated liver injury and virological indicators for HBV and precisely identify the patients with a histologically defined immune tolerance state. MethodsThis study was conducted among 577 HBeAg-positive chronic hepatitis B （CHB） patients with HBV DNA >2×10⁶ IU/mL who did not receive antiviral therapy in The Fifth Medical Center of PLA General Hospital， Tianjin Second People’s Hospital， Shanghai Ruijin Hospital， and Taizhou Hospital of Zhejiang Province from January 2010 to December 2022. Liver biopsy was performed to determine the extent of liver injury， and the serum levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， and virological indicators were measured. The proportion of patients with a histologically defined immune tolerance state was analyzed based on the cut-off values of noninvasive indicators recommended in various guidelines， especially HBV load. In addition， a diagnostic model was established for the histologically defined immune tolerance state based on serum HBV DNA at the time when its correlation with liver immunopathological injury disappeared as the new threshold in combination with multiple indicators. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. The Spearman method was used for correlation analysis. The binary Logistic regression analysis was used to establish a multivariate diagnostic model； the area under the receiver operating characteristic curve （AUC） was used to investigate the diagnostic efficiency of different models， and the Z test was used for comparison of AUC. ResultsAmong the patients with an immune tolerance state defined by the noninvasive indicators in the Chinese guidelines （2022 edition）， the EASL guidelines （2017 edition）， the AASLD guidelines （2018 edition）， and the APASL guidelines （2015 edition） for the prevention and treatment of CHB， the patients with a histologically defined immune tolerance state who met the definition in this article （HBV DNA>2×10⁶ IU/mL） accounted for 47.0%， 38.5%， 36.0%， and 44.6%， respectively， which did not exceed 50%. When the threshold of serum HBV DNA increased to >2×10⁸ IU/mL， although the correlation between immune-mediated liver injury and HBV DNA disappeared （r=-0.029， P=0.704）， the patients with a histologically defined immune tolerance state reached only 52.0%. In the cohort of 251 HBeAg-positive patients with serum HBV DNA >1×10⁸ IU/mL， there were significant differences in the levels of HBsAg， HBeAg， HBV DNA， ALT， and AST between the significant liver injury group with 140 children and the non-significant liver injury group with 111 patients （all P<0.05）， and the multivariate binary Logistic regression analysis showed that AST， HBV DNA， and HBeAg were influencing factors for histologically defined immune tolerance state in patients （all P<0.05）. Based on the above indicators and related clinical data， a predictive model was established as logit（P）=1.424－0.028×AST， with an AUC of 0.730， an optimal cut-off value of 30.5 U/L， a sensitivity of 52.8%， and a specificity of 84.1%. A total of 238 adult patients with chronic HBV infection who underwent liver biopsy in Taizhou Hospital of Zhejiang Province were enrolled as the validation cohort， and the analysis showed that the predictive model established in this study had a better efficiency than AST/ALT， FIB-4， and APRI， with an AUC of 0.698， 0.555， 0.518， and 0.373， respectively （all P<0.05）. ConclusionFor HBeAg-positive patients with chronic HBV infection and HBV DNA>2×10⁸ IU/mL， an AST level of >30.5 U/L might indicate the “breakdown” of histologically defined immune tolerance state.