Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective This study aims to develop and validate a dynamic web-based nomogram for predicting kinetophobia in patients following percutaneous coronary intervention(PCI).Methods A prospective design was employed to selectively enroll 330 PCI patients admitted to a hospital in Hangzhou from December 2022 to July 2023.Single-factor analysis and Lasso regression were utilized to identify independent risk factors for kinesophobia post-PCI.Logistic regression was performed using R software,and a nomogram was constructed.The model was assessed through the area under the receiver operating characteristic curve(AUC)and Hosmer-Lemeshow tests.Results There were 206 cases of kinesiophobia in 330 patients after PCI,and the incidence was 62.4％.Logistic regression analysis identified combined heart failure,emergency surgery,NYHA cardiac function grade,ADL level,sedentary behavior,Chinese version of PROMIS Physical Function Summary Table score,and Chinese version of Perceptive Social Support Scale score as independent influencing factors for kinesophobia after PCI(P＜0.05).The AUC value of the model was 0.821,with a sensitivity of 70.4％and specificity of 82.0％.The Hosmer-Lemeshow fit test yielded a non-significant result(x2=9.350,P=0.314).Calibration and decision curves demonstrated the model's favorable calibration and clinical practicability.The C-index of the nomogram prediction model was 0.778,0.774,and 0.800,respectively,by 5-fold cross-validation,10-fold cross-validation,and the Bootstrap method.Conclusion The dynamic nomogram model developed in this study effectively predicts kinesophobia in patients after PCI.It provides valuable references and support for clinical staff in early identification of high-risk patients,enabling the formulation of individualized health education strategies and exercise rehabilitation plans.

Objective　To explore the clinical characteristics and drug resistance of Elizabethkingia meningoseptica (EM) nosocomial infection, so as to provide evidence for prevention of EM nosocomial infection and guiding the rational use of antibiotics. Methods　A retrospective study was conducted of 67 patients with EM infection in a tertiary hospital from January 2021 to December 2022. The infective characteristics and drug resistance were analyzed. Results　The cohort of 67 EM-infected patients was predominantly males aged ≥60 years, with the most frequent source being the first district of the intensive care unit (ICU), followed by the respiratory medicine and emergency department (19.40%, 13/67). The specimens were mainly isolated from respiratory tract (86.57%, 58/67), of which sputum accounted for 49.25% (33/67), and alveolar lavage fluid accounted for 37.31% (25/67). The majority of EM infections occurred in patients with pre-existing respiratory conditions (49.25%, 33/67), who generally experienced prolonged hospital stays and underwent invasive procedures, such as mechanical ventilation 94.03% (63/67), urinary catheterization (95.52%, 64/67), and central venous catheterization (97.01%, 65/67). Post-treatment, the improved rate of the 67 patients was 40.30% (27/67). Susceptibility testing demonstrated a high resistance rate of EM to cefoperazone-sulbactam, 98.39% (61/62), contrasted by significant susceptibility to compound trimethoprim-sulfamethoxazole (TMP-SMX)/cotrimoxazole, doxycycline, minocycline, and piperacillin-tazobactam, with susceptibility rates exceeding 90%. Conclusions　The patients infected with EM were almost elderly men with certain underlying diseases, experienced prolonged hospital stays, and had a history of invasive operations. The specimens of EM were mainly from Intensive Care Unit and isolated from respiratory tract. The strain showed high resistance to cefoperazone-sulbactam, whereas it remained highly susceptible to cotrimoxazole, doxycycline, minocycline and piperacillin-tazobactam, which may be considered as first-line treatment options.

Objective To generate and identify the Itgbl1(integrin beta-like)promoter-driven Cre knock-in mouse line.Methods Itgbll-Cre knock-in mice were generated using clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated protein 9(Cas9)gene editing.The Itgbl1-Cre mice were crossed with the Cre reporter ROSALSL-tdTomato)mice to detect the expression profile of Cre activity.The tdTomato expression pattern across tissues and cell-specific markers were used to identify the cell types of Itgbl1-expressing cells and their progeny.Results and Conclusion tdTomato was specifically expressed in mucous acinar cells of the sublingual gland,pancreatic islet cells,and gastric endocrine cells.In addition,tdTomato expression was also found in some of the neurons of the retina and brain,as well as in a few cells in the serosal layer of the intestine,articular cartilage,periosteum,and bone marrow.The first Itgbl1-Cre recombinase transgenic mouse line was established,which can specifically label the mucous acinar cells of the sublingual gland.

Scientifically preparing technical requirement for medical equipment can ensure that the purchase results meet the actual needs of the hospital.This study introduces the platform guarantee model implemented by the First Affiliated Hospital of Sun Yat-sen University in the management of medical equipment,analyzes the advantages,disadvantages,opportunities,and challenges of technical requirement preparation based on this model management,and proposes optimization strategies based on the analysis results,aiming to provide reference for the technical requirement preparation in general hospitals.

Scientifically preparing technical requirement for medical equipment can ensure that the purchase results meet the actual needs of the hospital.This study introduces the platform guarantee model implemented by the First Affiliated Hospital of Sun Yat-sen University in the management of medical equipment,analyzes the advantages,disadvantages,opportunities,and challenges of technical requirement preparation based on this model management,and proposes optimization strategies based on the analysis results,aiming to provide reference for the technical requirement preparation in general hospitals.

Objective:To develop a new method to set up patients using optical surface monitoring system and to compare it with the conventional method in head radiotherapy.Methods:A total of 358 set-ups (130 with the conventional method and 228 with the new method ), which were from 99 head tumor patients in Beijing Cancer Hospital treated between May 2018 to April 2019, obtained by using Image Guided Radiotherapy were retrospectively analyzed. The distributions of set-up errors, the number of abnormal positions, and the set-up time were compared to evaluate the potential advantages of the new method .Results:The mean (± standard deviation) absolute values of setup errors of the new method were (0.07±0.07) , (0.08±0.06) and (0.06±0.06) cm for the vertical, lateral, and longitudinal, (0.53±0.41)°, (0.59±0.44)° and (0.59±0.46)° for the rotation, pitch and roll, respectively. In the new method , the setup accuracy was improved( t=3.24-6.10, P<0.001)and the number of abnormal positions was greatly reduced(χ 2=60.66, P<0.001). Compared with the conventional method, the patient setup time was slightly reduced by the new method , but the difference was not statistically significant ( P>0.05). Conclusions:The new high-precision method to set up patients using optical surface monitoring system improves the accuracy of patients′ position, decreases the corrections applied by 6DoF couch, reduces the probability of abnormal positions, and suggests the potential benefit in head radiotherapy.