With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

A 70-year-old female patient presented with fatigue and edema for 3 months and was found to have elevated serum creatinine for 3 weeks. During the course of the disease, she had fever and cough. Examinations revealed multiple ground-glass opacities in both lungs and positivity for myeloperoxidase-anti-neutrophil cytoplasmic antibodies (ANCA), leading to a diagnosis of ANCA-associated vasculitis. The patient′s condition initially improved after pulse glucocorticoid therapy combined with cyclophosphamide. During treatment, however, the patient developed hematochezia, and colonoscopy revealed multiple colonic ulcers. Immunohistochemistry of colonic mucosal biopsy confirmed cytomegalovirus (CMV) positivity, establishing a diagnosis of CMV colitis. The patient was found to have concurrent Clostridioidesdifficile and pulmonary infections. During the disease course, the patient also developed deep vein thrombosis and roxadustat-associated central hypothyroidism. Given the presence of multiple comorbidities, rituximab was subsequently used for vasculitis treatment, resulting in sustained remission. This case highlights the importance of highly individualized treatment strategies for older patients with vasculitis, requiring adjustment of immunosuppressive therapy intensity based on disease progression.

As a cheap and effective antibiotic,sulfonamides are often used in animal husbandry.However,their residues in animal-derived foodstuffs will threaten human health.Consequently,a high-performance liquid chromatography(HPLC)method integrated with supramolecular solvent microextraction was successfully established for simultaneous quantification of sulfonamide residues sulfachlorpyridazine,sulfamethoxazole,sulfamethoxypyridazine and sulfadimethoxine in milk matrices.This approach exhibited prominent characteristics of operational simplicity,environmental sustainability,and high extraction efficiency.The supramolecular solvents prepared by tributyl octylphosphine tetrafluoroborate and tetrahydrofuran were employed as extraction solvents.The analytes underwent isolation and concentration via dispersive liquid-liquid microextraction(DLLME)prior to quantitative determination using high-performance liquid chromatography(HPLC).The composition and microscopic morphology of the supramolecular solvent were characterized through a series of analytical techniques,including phase diagram,Fourier transform infrared spectroscopy,scanning electron microscopy,and inverted fluorescence microscopy and so on.The density and pH value of supramolecular solvents were determined.The extraction conditions were optimized through the one-factor experiments.The experimental results demonstrated that under the optimal extraction conditions,the four kinds of sulfonamide antibiotics exhibited excellent linearity within respective detection range(R2 ≥ 0.9998)and the limits of detection(LOD)were 0.67-1.45 μg/L.Compared with literature methods,this approach offered some advantages such as simplicity of operation and less reagent consumption,and could be used for analysis and detection of sulfonamide antibiotic residues in milk samples.The present method provided technical support for food safety regulation and paved a new way for the application of supramolecular solvents in the field of extraction and separation.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Background:To compare the efficacy and safety of monthly administrations of gonadotropin releasing hormone (GnRH) agonists LY01005 and Zoladex ? in Chinese patients with premenopausal breast cancer. Methods:From October 2020 to November 2021, 188 premenopausal breast cancer patients were enrolled in 34 hospitals and randomized 1:1 to receive either LY01005 or Zoladex ? every 28 days for a total of three injections. All patients concomitantly received oral tamoxifen (TAM). The primary efficacy endpoint was cumulative probability of maintaining menopausal level [oestradiol (E2) ≤30 pg/ml] from day 29 to day 85. The second efficacy endpoint included changes in E2, luteinizing hormone (LH), and follicle-stimulating hormone (FSH) compared with the baseline. Pharmacokinetics (PK), pharmacodynamics (PD), and safety were analyzed. The study also evaluated the pharmacokinetic and pharmacodynamic characteristics of LY01005. Results:A total of 188 patients were randomised and 187 patients received either LY01005 or Zoladex ?. Cumulative probabilities of maintaining menopausal level (E2≤30 pg/ml) from day 29 to day 85 were 93.1% for LY01005 and 86.3% for Zoladex ?. The between-group difference was 6.8% (95% CI: -2.3%, 15.9%) and primary efficacy in the LY01005 group was not inferior to that in the Zoladex ? group. Changes in E2, LH, and FSH levels compared with the baseline were equivalent between the two groups (E2: 89.34% to 90.23% vs. 82.11% to 85.02%; LH: 88.89% to 95.52% vs. 89.70% to 97.02%; FSH: 75.36% to 80.85% vs.73.07% to 80.24%, respectively). After three consecutive doses of LY01005, the LH and FSH levels of the subjects showed a transient increase after the first dose, reached a peak on the second day and then started to decrease. The LH and FSH reached a lower level and remained at or below that level until the 85th day. Both treatments were well-tolerated. Conclusion:LY01005 is as effective as Zoladex ? in suppressing E2 to menopausal levels in Chinese patients with premenopausal breast cancer, with a similar safety profile.

A 70-year-old female patient presented with fatigue and edema for 3 months and was found to have elevated serum creatinine for 3 weeks. During the course of the disease, she had fever and cough. Examinations revealed multiple ground-glass opacities in both lungs and positivity for myeloperoxidase-anti-neutrophil cytoplasmic antibodies (ANCA), leading to a diagnosis of ANCA-associated vasculitis. The patient′s condition initially improved after pulse glucocorticoid therapy combined with cyclophosphamide. During treatment, however, the patient developed hematochezia, and colonoscopy revealed multiple colonic ulcers. Immunohistochemistry of colonic mucosal biopsy confirmed cytomegalovirus (CMV) positivity, establishing a diagnosis of CMV colitis. The patient was found to have concurrent Clostridioidesdifficile and pulmonary infections. During the disease course, the patient also developed deep vein thrombosis and roxadustat-associated central hypothyroidism. Given the presence of multiple comorbidities, rituximab was subsequently used for vasculitis treatment, resulting in sustained remission. This case highlights the importance of highly individualized treatment strategies for older patients with vasculitis, requiring adjustment of immunosuppressive therapy intensity based on disease progression.

Objective:To explore the feasibility, practicality, and safety of the day surgery management model for the treatment of patent ductus arteriosus with Da Vinci robotic surgery in children.Methods:A non-randomized controlled study was conducted.The clinical data of children with patent ductus arteriosus who underwent Da Vinci robotic surgery at Children′s Hospital, Zhejiang University School of Medicine from August 2020 to December 2023 were collected and retrospectively analyzed.The patients were divided into day surgery group and non-day surgery group according to whether they had discharged within 24 hours. t-test and Chi-square tests were used to compare the differences in clinical features, perioperative complications and prognosis between the two groups of patients.In addition, the satisfaction of the treatment effect was surveyed. Results:A total of 276 children were included in this study, with an age ranging from 6 to 154 months with a median of 34 months.The weight ranged from 6.2 to 63.2 kilograms, with a median of 13.5 kilograms.The operation time ranged from 23 to 90 minutes, with a median of 45 minutes.One hundred and thirty-five patients underwent day surgery and 141 patients underwent non-day surgery.The average age and average weight of the patients in the day surgery and non-day surgery groups was (43.7±30.8) months vs.(42.4±30.2) months and (15.0±6.4) kg vs.(14.8±6.9) kg, respectively.There was no statistically significant difference in age and weight between the two groups (all P>0.05).There was no difference in perioperative data and incidence of perioperative complications between the two groups (all P>0.05).However, the length of hospital stay of the day surgery group was significantly shorter than that of the non-day surgery group[(1.0±0) days vs.(2.5±0.9) days, t=-20.993, P<0.001], and the hospitalization cost of the day surgery group was also significantly lower than that of the non-day surgery group[(50 800±1 100) yuan vs.(53 500±3 900) yuan, t=-10.040, P<0.001].Both families of the two groups were satisfied with the treatment results, and there was no difference in satisfaction between the two groups ( χ2=0.501, P=0.479). Conclusions:The day surgery management model of Da Vinci robotic surgery for the treatment of pediatric patent ductus arteriosus is safe and feasible.To a certain extent, it can reduce the length of hospital stay, treatment costs, and treatment burden.

Objective:To investigate the predictive efficacy of Delta radiomics for the patholo-gical complete remission (pCR) of pancreatic cancer after total neoadjuvant therapy (TNT).Methods:The retrospective cohort study was conducted. The clinicopathological data of 263 patients with pancreatic cancer who were admitted to Henan Provincial People′s Hospital (Zhengzhou University People's Hspital) from January 2019 to September 2024 were collected. There were 166 males and 97 females, aged (56±12)years. All patients underwent TNT. The 263 patients were randomly divided into a training set of 184 cases and a test set of 79 cases using a 7∶3 random seed count. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) postoperative and follow-up condi-tions; (2) imaging feature selection and model construction; (3) evaluation of predictive efficacy of different radiomic models. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. The Kaplan-Meier method was used to calculate the survival rate and draw survival curve. The Log-rank test was used for survival analysis. The perfor-mance of the prediction model for pCR after TNT was evaluated using the receiver operator charac-teristic (ROC) curve, precision-recall (P-R) curve and Bootstrap method, along with the calculation of area under the curve (AUC), precision rate, recall rate, F1-score. Results:(1) Postoperative and follow-up conditions. All 263 patients underwent surgery after TNT, with pathological examination revealing 124 cases of pCR (86 cases in the training set, 38 cases in the test set) and 139 cases of non-pCR (98 cases in the training set, 41 cases in the test set), respectively. All 263 patients were followed up for 6(range, 3-12) months after surgery, of which 15 cases (4 cases of pCR and 11 cases of non-pCR) were lost to follow-up or died due to non-tumor reasons within 6 months after surgery. The postoperative 6-month recurrence-free survival rate of 124 pCR patients and 139 non-pCR patients were 80% and 50%, respectively, showing a significant difference between the two groups of patients ( χ2=22.84, P<0.05). (2) Imaging feature selection and model construction. Construction of the traditional radiology model: based on the response evaluation criteria in solid tumors 1.1, the Logistic regression model was constructed using the relative shrinkage (D%) as a predictive variable. The AUC of traditional radiology model was 0.72 [95% confidence interval ( CI) as 0.63?0.81] in the training set and 0.75 (95% CI as 0.66?0.84) in the test set, respectively. Construction of the Delta radiomics model: 10 non-zero coefficient features were selected. The Delta radiomics models were constructed by using the regularized Logistic regression, random forest, gradient boosting machine, and support vector machine algorithms through using selected features as input variables. (3) Evaluation of predictive efficacy of different radiomic models. The AUC of Delta radiomics model constructed by regularized Logistic regression algorithm in the test set for predicting pCR in pancreatic cancer after TNT was 0.90, higher than that of the random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm (AUC as 0.81, 0.81, 0.83), and higher than that of the traditional radiology model (AUC as 0.72). Results of Bootstrap method revealed significant differences in the predictive efficacy of Delta radiomics model constructed by regularized Logistic regression algorithm compared to the Delta radiomics model constructed by random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm and the tradi-tional radiology model (95% CI as 0.03?0.16, 0.03?0.16, 0.03?0.13, 0.08?0.29, P<0.05). The regularized Logistic regression algorithm within the Delta radiomics model demonstrated the best overall performance among the above models evaluated. Conclusion:Compared to the traditional radiology model, the Delta radiomics model offers superior efficacy in predicting pCR of pancreatic cancer after TNT, in which the regularized Logistic regression algorithm demonstrates the best overall performance metrics.

Objective This study investigated feasible cases and their significance in promoting the"generalized"development of inspection through digital-intelligent equipment.Methods A qualitative research approach was used,involving interviews conducted between February 2025 and March 2025 with experts in traditional Chinese medicine diagnostics,clinical research methodology,medical engineering integration,and related disciplines,using both online and offline methods.In accordance with the Consolidated Criteria for Reporting Qualitative Research,feasible cases involving the specific application of digital equipment in various parts of observation were collected through item enrichment.The significance of extending observation capabilities via these cases was analyzed,along with the overall implications of integrating digital technologies with traditional inspection method.Results Interviews were completed with 11 experts from domestic universities and research institutes in the fields of traditional Chinese medicine diagnosis,medical engineering integration,and related disciplines.A total of 78 feasible cases of digital-intelligent inspection were identified,along with 69 insights regarding the significance of enhancing the inspection capabilities.These insights were synthesized into two dimensions and 23 holistic meanings.The first dimension is to expand the scope of inspection,including obtaining internal environmental characteristics,observing external environmental characteristics,expanding thermodynamic characteristic data,and crossing time and space.The second dimension is to improve the quality of observation and diagnosis information collection and analysis,including 19 specific meanings,such as standardized collection environment,objective quantification,and refined observation.Conclusion Digital-intelligent equipment plays a significant role in expanding the scope of inspection content and achieving high-quality acquisition and analysis of extensive inspection information.These advancements extend and enrich the capabilities of traditional inspection method in traditional Chinese medicine.

Objective To investigate and compare the epidemiological characteristics of common respiratory viruses among influenza-like illness(ILI)and severe acute respiratory infection(SARI)cases in Huzhou,Zhejiang Province before and after the COVID-19 pandemic,so as to provide a basis for formulating and adjusting the prevention and control strategies for viral respiratory infectious diseases.Methods ILI and SARI cases at two influenza surveillance sentinel hospitals in Huzhou and had throat swab samples collected during Nov 2017 to Feb 2020(pre-COVID-19 pandemic period)and Dec 2022 to Apr 2024(post-COVID-19 mitigation phase)were selected as the participants.Seven common viral respiratory pathogens were tested,including influenza A virus(H1N1 and H3N2 subtypes),influenza B virus(Victoria lineage,FluB),respiratory syncytial virus(RSV),rhinovirus(HRV),adenovirus(ADV),and severe acute respiratory syndrome coronavirus-2(SARS-CoV-2).The positive rates of respiratory pathogens before and after the COVID-19 pandemic were compared across different age groups and different time.Results A total of 7 948 ILI samples and 2 294 SARI samples were included.The overall positive rate of ILI samples increased from 33.6%to 47.1%,primarily due to the increase in influenza and COVID-19 infections;the overall positive rate of SARI samples decreased from 31.4%to 24.8%,mainly due to the reduction in HRV and ADV infections.During the post-COVID-19 mitigation phase,SARS-CoV-2(22.1%),H3N2(12.7%),and FluB(6.0%)were the primary pathogens in ILI samples,while RSV(7.1%),H3N2(5.3%),and HRV(4.5%)dominated in SARI samples.During the post-COVID-19 mitigation phase,the influenza virus circulation period was shortened.Before the COVID-19 pandemic,RSV was mainly detected in autumn and winter,while during the post-COVID-19 mitigation phase,out-of-season RSV epidemics were observed in spring and summer.Co-infection rate in ILI cases increased significantly in the post-COVID-19 mitigation phase,predominantly consisting of co-infections of COVID-19 and influenza A virus,while co-infection rate in SARI cases showed a decline.Conclusion We found important epidemiological changes in respiratory viruses in Huzhou during the post-COVID-19 mitigation phase compared to pre-COVID-19 period,including increased positive rates of influenza and COVID-19,and disruptions to the seasonal patterns of influenza and RSV.The prevention and control strategies should be adjusted in a timely manner based on the monitoring data.