Objective:To evaluate the diagnostic value of micro flow imaging (MFI) supported by Image Pro Plus (IPP) software for BI-RADS classification of breast nodules and the correlation between its parameters and Ki-67 expression level.Methods:A total of 205 cases of breast solid nodules with ultrasound BI-RADS classification of 4 categories were enrolled in this study. BI-RADS classification, CDFI score, MFI score, CDFI-IPP score and MFI-IPP score by IPP software were performed for each nodule. Ki-67 immunohistochemical staining of invasive ductal carcinoma was performed to analyze the correlation between MFI-IPP-VI and Ki-67 expression levels.Results:The combined BI-RADS classification for diagnosis of malignant nodules had the largest area under the ROC curve, which was significantly higher than that of BI-RADS, MFI-IPP-VI, MFI score, CDFI-IPP-VI, and CDFI score (all P<0.05). The combined BI-RADS classification had the best diagnostic efficacy for the diagnosis of malignant nodules with a sensitivity of 96.4%, specificity of 65.6% and accuracy of 82.4%. In addition, the agreement between experienced and inexperienced sonographers applying MFI-IPP-VI was higher than MFI (Kappa=0.780 vs. Kappa=0.743). The mean value of Ki-67 in invasive ductal carcinoma was 21.93%±16.37%, and Spearman's correlation analysis showed a positive correlation between MFI-IPP-VI and Ki-67 expression level ( r=0.815, P<0.05). Conclusions:MFI-IPP can assist sonographers to classify breast nodules by BI-RADS, providing an effective basis for puncture biopsy. MFI-IPP-VI offers the possibility of noninvasively predicting the expression level of Ki-67 in invasive ductal carcinoma.

Objective To explore the establishment,implementation,and outcomes of an integrated physician-nurse team-based comprehensive management model for breast cancer chemotherapy outpatients,ai-ming to provide a reference for standardized patient care.Methods In January 2019,the Breast Surgery De-partment of Peking Union Medical College Hospital developed an integrated physician-nurse team and estab-lished a full-cycle management pathway covering the pre-chemotherapy,chemotherapy,and inter-cycle phases.This model featured appointment-based scheduling,time-segmented visits,and closed-loop patient management.Key performance indicators-including healthcare efficiency,chemotherapy safety,staffing ratios,and satisfaction levels among patients and healthcare providers-were compared between pre-implementation(2018)and post-imple-mentation(2019)periods.Results Before implementation,patient waited times ranged from 30 to 120(75.40±20.97)minutes,with an annual chemotherapy volume of 8 715 cases.Two ward nurses were routinely redeployed daily to support the chemotherapy clinic.Post-implementation,patients received timely chemotherapy per scheduled appointments without delays,annual chemotherapy volume in-creased to 10 101 cases,and staffing between two chemotherapy units became flexibly adjustable.Ward nurses transitioned from an on-call to a reserve role.Adverse events(chemotherapy-related,catheter-related,and nursing incidents)remained at 0,consistent with pre-implementation levels.Both patient and staff satisfaction scores significantly improved across all domains(all P＜0.05).Conclusions The integrated physician-nurse team-based chemotherapy management model enhances service efficiency,ensures treatment safety,optimizes workforce allocation,and improves satisfaction among patients and healthcare providers.

Objective To explore the establishment,implementation,and outcomes of an integrated physician-nurse team-based comprehensive management model for breast cancer chemotherapy outpatients,ai-ming to provide a reference for standardized patient care.Methods In January 2019,the Breast Surgery De-partment of Peking Union Medical College Hospital developed an integrated physician-nurse team and estab-lished a full-cycle management pathway covering the pre-chemotherapy,chemotherapy,and inter-cycle phases.This model featured appointment-based scheduling,time-segmented visits,and closed-loop patient management.Key performance indicators-including healthcare efficiency,chemotherapy safety,staffing ratios,and satisfaction levels among patients and healthcare providers-were compared between pre-implementation(2018)and post-imple-mentation(2019)periods.Results Before implementation,patient waited times ranged from 30 to 120(75.40±20.97)minutes,with an annual chemotherapy volume of 8 715 cases.Two ward nurses were routinely redeployed daily to support the chemotherapy clinic.Post-implementation,patients received timely chemotherapy per scheduled appointments without delays,annual chemotherapy volume in-creased to 10 101 cases,and staffing between two chemotherapy units became flexibly adjustable.Ward nurses transitioned from an on-call to a reserve role.Adverse events(chemotherapy-related,catheter-related,and nursing incidents)remained at 0,consistent with pre-implementation levels.Both patient and staff satisfaction scores significantly improved across all domains(all P＜0.05).Conclusions The integrated physician-nurse team-based chemotherapy management model enhances service efficiency,ensures treatment safety,optimizes workforce allocation,and improves satisfaction among patients and healthcare providers.

Objective:To evaluate the diagnostic value of micro flow imaging (MFI) supported by Image Pro Plus (IPP) software for BI-RADS classification of breast nodules and the correlation between its parameters and Ki-67 expression level.Methods:A total of 205 cases of breast solid nodules with ultrasound BI-RADS classification of 4 categories were enrolled in this study. BI-RADS classification, CDFI score, MFI score, CDFI-IPP score and MFI-IPP score by IPP software were performed for each nodule. Ki-67 immunohistochemical staining of invasive ductal carcinoma was performed to analyze the correlation between MFI-IPP-VI and Ki-67 expression levels.Results:The combined BI-RADS classification for diagnosis of malignant nodules had the largest area under the ROC curve, which was significantly higher than that of BI-RADS, MFI-IPP-VI, MFI score, CDFI-IPP-VI, and CDFI score (all P<0.05). The combined BI-RADS classification had the best diagnostic efficacy for the diagnosis of malignant nodules with a sensitivity of 96.4%, specificity of 65.6% and accuracy of 82.4%. In addition, the agreement between experienced and inexperienced sonographers applying MFI-IPP-VI was higher than MFI (Kappa=0.780 vs. Kappa=0.743). The mean value of Ki-67 in invasive ductal carcinoma was 21.93%±16.37%, and Spearman's correlation analysis showed a positive correlation between MFI-IPP-VI and Ki-67 expression level ( r=0.815, P<0.05). Conclusions:MFI-IPP can assist sonographers to classify breast nodules by BI-RADS, providing an effective basis for puncture biopsy. MFI-IPP-VI offers the possibility of noninvasively predicting the expression level of Ki-67 in invasive ductal carcinoma.

ObjectiveThis study aimed to investigate the current status of biosafety management in laboratory animal institutions in Hunan Province, identify management shortcomings, and provide targeted recommendations for improvement. MethodsA questionnaire survey was conducted in July 2023 among 40 laboratory animal institutions in Hunan Province, covering topics such as the establishment of laboratory management system and its overall operation status, emergency management for incidents, medical waste disposal, animal transportation, personnel practitioner management, environmental disinfection, and equipment maintenance. The awareness of biosafety, animal bite incidents, and vaccination history was surveyed from at least one animal feeder or experimental operation practitioner from each institution, totaling 50 practitioners. Through literature review and comparative analysis, this paper analyzed the current status of biosafety management in production, transportation, and use of laboratory animals in Hunan Province from aspects such as biosafety management systems, personnel training, disinfection of environmental facilities and waste disposal, and provided recommendations. ResultsAmong the 40 laboratory animal institutions in Hunan Province,39 institutions (97.5%) had established laboratory management systems, 37 (92.5%) had emergency response plans for incidents of to transport laboratory animals, 15 (37.5%) had complete records of emergency drills for laboratory animal biosafety, and 39 (97.5%) had established protocols for carcass and waste management. Moreover, 26 institutions (65.0%) had laboratory biosafety risk assessment reports. 4 out of 8 (50.0%) production units had emergency plans for animal transportation, with 7 (87.5%) using special vehicles to transport laboratory animals. 2 (4.0%) of the 50 practitioners were unaware of emergency response plans, 6 participants (12.0%) did not consistently wear personal protective equipment, and 38 participants (76.0%) had been bitten or scratched by laboratory animals. The results of the survey showed that emergency management, transportation management and personnel management of laboratory animal incidents still need improvement in Hunan Province. Relevant functional departments should strengthen supervision and management efforts, establish local regulations for the transportation management of laboratory animals, ensure strict compliance with relevant documents, conduct emergency drills in all units, and strengthen training for practitioners. ConclusionWhile daily management practices in the 40 laboratory animal institutions in Hunan Province are generally satisfactory, there remains a need for further improvement in emergency management, transportation management, personnel management, etc. Gradually enhancing the level of laboratory animal safety management is essential to collectively safeguard public health safety.

The emergency management of biosafety for laboratory animals in Hunan Province is an essential component of the province's implementation of the national biosafety strategy.To strengthen the prevention and control of biosafety risks in laboratory animals and to ensure a quick and effective response to laboratory animal biosafety emergencies,Hunan Province has formulated the"Emergency Response Plan for Laboratory Animal Biosafety Emergencies in Hunan Province".This plan aims to minimize damages caused to practitioners,public health,and laboratory animal industry,protect lives and property,and safeguard public safety and social stability.This paper analyzes the necessity,guiding ideology,principles,and basis for formulating the plan.It details the main contents of the plan,which includes scope of application,incident classification,organizational structure and responsibilities,monitoring and early warning mechanisms,emergency reporting and response,post-incident assessment,and safeguard measures.Moreover,this paper provides a summary and outlook on the emergency management of biosafety laboratory animals in Hunan Province in recent years.

Due to the low contrast of CT images,irregular shape of the liver,and blurred boundaries with adjacent organs,the existing methods based on convolutional neural network underperform in liver segmentation tasks,especially for boundary recognition and small object detection.A novel liver segmentation method is proposed based on multi-scale feature fusion and attention,namely MFFA UNet.Multi-scale feature fusion is firstly employed to acquire abundant segmentation details,while spatial and channel attention mechanisms are utilized to capture global spatial and inter-channel relationships.Additionally,a deep supervision module fully leverages the output of intermediate hidden layers,enhancing the learning capability of the network,which in turn accelerates the network's convergence speed.Moreover,a hybrid loss function is adopted to address the issue of class imbalance,further boosting the model's segmentation efficacy.Experimental results demonstrate that the proposed MFFA UNet outperforms the prevailing segmentation networks on the public LITS dataset,producing results that are closer to the ground truth.

Objective:To explore the predictive value of ultrasound-based radiomics for liver metastasis in pancreatic neuroendocrine tumors (pNEN).Methods:A retrospective analysis was conducted on clinical, pathological, and ultrasound data of 269 pNEN patients confirmed by pathology at Tianjin Medical University Cancer Institute and Hospital from January 2012 to June 2022, including 94 patients with liver metastasis and 175 without liver metastasis. The regions of interest (ROI) were delineated on the maximum diameter section of the tumor using ITKSNAP software, and radiomics features were extracted using Pyradiomics. Radiomics features with an intra-group correlation coefficient greater than 0.90 were retained, and the optimal features were selected using the maximum relevance minimum redundancy (MRMR) algorithm. The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3, and the random forest algorithm (Rfs) was used to predict pNEN liver metastasis. Three models were constructed, including the clinical ultrasound model, the radiomics model, and the comprehensive model that combined clinical ultrasound and radiomics features. The predictive performance of different models for pNEN liver metastasis was analyzed using the ROC curve, and the predictive performance of different models was compared using the Delong test.Results:A total of 874 features were extracted from the ROI, and 12 highly robust radiomics features were retained for model construction based on inter- and intra-observer correlation grading and feature selection. The area under curve(AUC), sensitivity, specificity, and accuracy of the radiomics model, the clinical ultrasound model, and the comprehensive model for predicting liver metastasis in pNEN patients were 0.800, 0.574, 0.789, 0.714; 0.780, 0.596, 0.874, 0.777; and 0.890, 0.694, 0.874, 0.810, respectively. The Delong test showed that the comprehensive model had the best predictive performance, with an AUC superior to that of radiomics model ( Z=3.845, P=0.000 12) and clinical ultrasound model ( Z=3.506, P=0.000 45). Conclusions:The radiomics model based on ultrasound has good performance in predicting liver metastasis in pNEN, and the comprehensive model that combines clinical ultrasound and radiomics features can further improve the predictive performance of the model.

Primary central nervous system lymphoma (PCNSL) is a rare and aggressive non-Hodgkin’s lymphoma that affects the brain, eyes, cerebrospinal fluid, or spinal cord without systemic involvement. The outcome of patients with PCNSL is worse compared to patients with systemic diffuse large B-cell lymphoma. Given potential mortality associated with severe immune effector cell-associated neurotoxicity syndrome (ICANS), patients with PCNSL have been excluded from most clinical trials involving chimeric antigen receptor T-cell (CAR-T) therapy initially. Here, we report for the first time to apply decitabine-primed tandem CD19/CD22 dual-targeted CAR-T therapy with programmed cell death-1 (PD-1) and Bruton’s tyrosine kinase (BTK) inhibitors maintenance in one patient with multiline-resistant refractory PCNSL and the patient has maintained complete remission (CR) for a 35-month follow-up period. This case represents the first successful treatment of multiline resistant refractory PCNSL with long-term CR and without inducing ICANS under tandem CD19/CD22 bispecific CAR-T therapy followed by maintenance therapy with PD-1 and BTK inhibitors. This study shows tremendous potential in the treatment of PCNSL and offers a look toward ongoing clinical studies.