Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To investigate human factors underlying radiotherapy planning safety incidents and quantitatively explore their interrelationships.Methods:A total of 1 619 safety incidents recorded in the automated plan checking system developed by West China Hospital of Sichuan University were utilized. Human factors were identified and statistically analyzed using the Human Factors Analysis and Classification System (HFACS). A Bayesian network model was developed and combined with sensitivity analysis for quantitative assessment.Results:Key contributing factors included organizational processes (12.89%), inadequate supervision (11.85%), and personnel factors (13.50%). Utilizing the established HFACS Bayesian network hybrid model in conjunction with sensitivity analysis, it has been found that the most significant influences on skill‐based errors and decision errors were condition of operators and environmental factors, with corresponding indices of 0.96 and 0.76. Additionally, personnel factors had the greatest impact on routine, with an index of 3.51.Conclusions:Key contributing factors span all HFACS levels, with organizational processes, supervision, personnel, and condition of operators each playing a significant role. Upstream factors — such as organizational climate, environment factors, and personnel factors — strongly influence downstream risks. These offer actionable insights for developing targeted safety protocols.

Objective:To explore the effectiveness of outcome-oriented TECK teaching in the standardized training of neurology resident physicians, and to evaluate its impact on clinical practice, clinical thinking, and self-learning abilities.Methods:A controlled study design was adopted, and 78 resident physicians who rotated through the Department of Neurology at Guangdong Provincial People's Hospital Affiliated to Southern Medical University between November 2022 and November 2024 were divided into a control group ( n=39) and an experimental group ( n=39) according to their admission order. The control group received the traditional "theoretical teaching, rotation training, exit assessment" mode. The experimental group received an outcome-oriented TECK teaching mode, which included four modules: theoretical class, experimental course/practice, case discussion, and knowledge reinforcement. The two groups of residents were evaluated for clinical practice ability, clinical thinking ability, and teaching satisfaction. SPSS 22.0 was used for t-test and chi-square test. Results:The experimental group outperformed the control group in all dimensions of clinical practice ability (except for doctor-patient communication ability) (all P<0.001), such as basic operational skills [(4.42±0.41) vs. (3.87±0.56)] and emergency management ability [(4.38±0.39) vs. (3.65±0.62)]. The clinical thinking ability scores of the experimental group were higher (all P<0.001), such as diagnostic logic [(4.43±0.38) vs. (3.92±0.51)] and decision-making basis [(4.45±0.42) vs. (3.78±0.63)]. In terms of self-learning ability, the experimental group showed significant improvements in literature search [(4.42±0.43) vs. (3.65±0.58)] and knowledge update [(4.38±0.39) vs. (3.42±0.61)] (both P<0.001). In terms of teaching satisfaction, the experimental group scored higher in dimensions such as course design [(4.42±0.41) vs. (3.89±0.58)] and clinical fit [(4.45±0.37) vs. (3.82±0.61)] (all P<0.001). Conclusions:The outcome-oriented TECK teaching mode can effectively enhance the clinical practice and thinking abilities of neurology residents in standardized training, and improve the effectiveness of self-learning, providing an innovative path for the training of specialized physicians. In the future, interdisciplinary integration and long-term tracking and evaluation need to be optimized.

Objective:To explore the effectiveness of outcome-oriented TECK teaching in the standardized training of neurology resident physicians, and to evaluate its impact on clinical practice, clinical thinking, and self-learning abilities.Methods:A controlled study design was adopted, and 78 resident physicians who rotated through the Department of Neurology at Guangdong Provincial People's Hospital Affiliated to Southern Medical University between November 2022 and November 2024 were divided into a control group ( n=39) and an experimental group ( n=39) according to their admission order. The control group received the traditional "theoretical teaching, rotation training, exit assessment" mode. The experimental group received an outcome-oriented TECK teaching mode, which included four modules: theoretical class, experimental course/practice, case discussion, and knowledge reinforcement. The two groups of residents were evaluated for clinical practice ability, clinical thinking ability, and teaching satisfaction. SPSS 22.0 was used for t-test and chi-square test. Results:The experimental group outperformed the control group in all dimensions of clinical practice ability (except for doctor-patient communication ability) (all P<0.001), such as basic operational skills [(4.42±0.41) vs. (3.87±0.56)] and emergency management ability [(4.38±0.39) vs. (3.65±0.62)]. The clinical thinking ability scores of the experimental group were higher (all P<0.001), such as diagnostic logic [(4.43±0.38) vs. (3.92±0.51)] and decision-making basis [(4.45±0.42) vs. (3.78±0.63)]. In terms of self-learning ability, the experimental group showed significant improvements in literature search [(4.42±0.43) vs. (3.65±0.58)] and knowledge update [(4.38±0.39) vs. (3.42±0.61)] (both P<0.001). In terms of teaching satisfaction, the experimental group scored higher in dimensions such as course design [(4.42±0.41) vs. (3.89±0.58)] and clinical fit [(4.45±0.37) vs. (3.82±0.61)] (all P<0.001). Conclusions:The outcome-oriented TECK teaching mode can effectively enhance the clinical practice and thinking abilities of neurology residents in standardized training, and improve the effectiveness of self-learning, providing an innovative path for the training of specialized physicians. In the future, interdisciplinary integration and long-term tracking and evaluation need to be optimized.

Objective:To investigate human factors underlying radiotherapy planning safety incidents and quantitatively explore their interrelationships.Methods:A total of 1 619 safety incidents recorded in the automated plan checking system developed by West China Hospital of Sichuan University were utilized. Human factors were identified and statistically analyzed using the Human Factors Analysis and Classification System (HFACS). A Bayesian network model was developed and combined with sensitivity analysis for quantitative assessment.Results:Key contributing factors included organizational processes (12.89%), inadequate supervision (11.85%), and personnel factors (13.50%). Utilizing the established HFACS Bayesian network hybrid model in conjunction with sensitivity analysis, it has been found that the most significant influences on skill‐based errors and decision errors were condition of operators and environmental factors, with corresponding indices of 0.96 and 0.76. Additionally, personnel factors had the greatest impact on routine, with an index of 3.51.Conclusions:Key contributing factors span all HFACS levels, with organizational processes, supervision, personnel, and condition of operators each playing a significant role. Upstream factors — such as organizational climate, environment factors, and personnel factors — strongly influence downstream risks. These offer actionable insights for developing targeted safety protocols.

Objective To investigate the therapeutic effects of bone marrow mesenchymal stem cells (BMSCs) for radiation-induced lung injury (RILI) and the underlying mechanism. Methods Forty-five healthy adult male C57BL/6 mice were randomly divided into control, model, and BMSCs groups. The model and BMSCs groups received a single irradiation dose of 20 Gy to the chest, while the control group did not receive X-ray irradiation. For the BMSCs group, an injection of 1 × 10⁶ BMSCs cells was administered via the tail vein within 6 h after irradiation. In the 5th week, the lung tissue was taken to observe pathological changes with HE staining; examine the expression of the inflammatory factors interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) with immunohistochemical staining; observe the polarization of macrophages with immunofluorescence staining; and measure the expression of the epithelial-mesenchymal transition markers E-cadherin, N-cadherin, and vimentin proteins by Western blot. Results After radiation, the model group developed pulmonary vasodilation and congestion with septal thickening and inflammatory cell infiltration, and these changes were markedly reduced in the BMSCs group. The model group showed significantly down-regulated expression of IL-6 and TNF-α compared with significantly increased levels in the model group (P < 0.01, P < 0.05). Treatment with BMSCs significantly increased the polarization of lung macrophages towards the M2 type, while significantly decreasing the abnormally increased N-cadherin and vimentin levels in RILI mice (P < 0.05, P < 0.01). Conclusion BMSCs have therapeutic effects for RILI mice, which may be through promoting macrophage polarization from M1 to M2.

To revise GBZ 188 Technical Specification for Occupational Health Surveillance based on national laws, regulations, standards, specifications and legal documents of occupational disease, and combination with the actual situation in China. The main modifications are as follows: the occupational health surveillance for workers exposed to toluene (xylene may implement by reference), bromopropane, methyl iodide, ethylene oxide, chloroacetic acid, indium and its compounds, coal tar, coal tarasphalt, asphalt, β-naphthylamine, dust of metal and its compounds(tin, iron, antimony, barium and its compounds), hard metal dust, erionite dust, low temperature, laser, tick-borne encephalitis virus, Borrelia burgdorferi, and human immunodeficiency virus, for scraper or grind operators, and underground workers using squatting or kneeling position, crawling position, side-lying position, or shoulder position for a long period of time are included. The emergency health screening for workers exposed to arsenic, fluorine and its inorganic compounds, and acrylamide are included. The occupational medical examination (OME) for workers exposed to amino and nitro compounds of benzene, phosgene, monomethylamine, organic fluorine and dimethyl sulfate has been adjusted and made mandatory, with corresponding assessments required upon leaving the job. The special occupational health surveillance for workers exposed to mycobacterium tuberculosis and hepatitis virus is removed. The OME conclusion of reexamination is removed, and standardize recheck/additional inspection requirements. The optional items in OME performed before, during and after leaving post are removed, but the optional items in emergency medical examination are retained. Additional OME items are added. The Guideline for OME Summary Reports is added as informative appendix, and so on. The revised GBZ 188 Technical Specification for Occupational Health Surveillance is more scientific and practical.

Objective:To verify and discuss the consistency and applicability of the semi empirical formula and Monte Carlo simulation method in the radiation shielding calculation for high energy synchrotron radiation source.Methods:The semi empirical formula and Monte Carlo simulation were used to calculate the ambient dose equivalent outside of the shielding.Results:The ratio of Jenkins semi empirical formula result to Monte Carlo simulation result was 111%-153%. The ratio of Sakano semi empirical formula result to Monte Carlo simulation result was 201%.Conclusions:For a single shielding material, the semi empirical formula can be simple and conservative to complete the shielding calculation for high-energy electron accelerator. For a variety of shielding materials, Monte Carlo simulation method should be used.

Objective:To improve the precision and accuracy of gross radioactivity detection in water, and to improve the radiological health and environmental monitoring level of each laboratory, it is necessary to carry out method verification and quality control.Methods:The thick source method for gross α and the thin source method for gross β analysis were used to analyze the actual samples. After multiple tests, the precision of the detection was calculated. Through the spike recovery test and the comparison sample analysis of the national radiological health in 2019, the accuracy analysis of the method was performed.Results:In the precision experiment, the relative standard deviations of the gross α and gross β results were 23% and 13%, respectively. The three spike recoveries were 103.1%, 103.5%, and 105.8%, respectively. The relative errors of gross α and gross β compared with the reference value were 0.92% and 9.4%, respectively. All the result reflected the high accuracy of the method .Conclusions:The relative standard deviations, recoveries, and relative errors in the method validation and quality control were below the limits of the criterion. This work systematically discussed the major factors that may cause errors in the detection, which could further improve the level of radiological health and environmental monitoring.