OBJECTIVES: To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application. Methods and. RESULTS: Recommendations were formulated based on literature review and expert group discussion, and consensus was reached following expert consultation. The consensus recommendations are comprehensive, covering the entire treatment procedures from preoperative assessment and preparation, surgical operation process, postoperative management and traditional Chinese medicine treatment to individualized treatment planning. The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain, reduced the use of opioid drugs, and significantly improved the quality of life and enhanced immune function of the patients. Postoperative follow-up suggested good treatment tolerance among the patients without serious complications. CONCLUSIONS The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy. The combined treatment has a high clinical value with a good safety profile for management of cancer pain.
Humans ; Medicine, Chinese Traditional ; Cancer Pain/therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Drug Delivery Systems ; Pain Management/methods* ; China

Bone and soft tissue tumors occur in the musculoskeletal system, and malignant bone tumors of bone and soft tissue account for 0.2% of all human malignant tumors, and if not diagnosed and treated in a timely manner, patients may be at risk of a poor prognosis. Image interpretation plays an increasingly important role in the diagnosis of bone and soft tissue tumors. Artificial intelligence (AI) can be applied in clinical treatment to integrate large amounts of multidimensional data, derive models, predict outcomes, and improve treatment decisions. Among these methods, deep learning is a widely employed technique in AI that predominantly utilizes convolutional neural networks (CNN). The network is implemented through repeated training of datasets and iterative parameter adjustments. Deep learning-based AI models have successfully been applied to various aspects of bone and soft tissue tumors, encompassing but not limiting in image segmentation, tumor detection, classification, grading and staging, chemotherapy effect evaluation, recurrence and prognosis prediction. This paper provides a comprehensive review of the principles and current state of AI in the medical image diagnosis and treatment of bone and soft tissue tumors. Additionally, it explores the present challenges and future prospects in this field.

[Abstract]Objective To explore the predictive value of plaque characteristic index based on coronary CT angiography(CCTA)for disease-specific myocardial ischemia in stable coronary artery disease(CAD).Methods 90 stable CAD patients admitted to Zhongshan Hospital,Fudan University from October 2020 to March 2022 were prospectively enrolled,including 135 target vessels with stenosis degree ranging from 30%to 90%.All participants sequentially underwent CCTA,ICA,and fractional flow reserve(FFR)measurement within 2 weeks.Based on the presence or absence of significant hemodynamic stenosis,all patients were divided into myocardial ischemic population(FFR≤0.8,n=30)and non ischemic population(FFR＞0.8,n= 60),135 target blood vessels were divided into a disease-specific myocardial ischemia group(FFR≤0.8,n=36)and a non disease-specific myocardial ischemia group(FFR＞0.8,n=99).Univariate and subsequent forward stepwise multivariate logistic regression analyses were used to assess independent predictors of myocardial ischemia,and CCTA-derived plaque characteristics index logistic regression model was created.Receiver operating characteristic(ROC)analysis was used to analyze the diagnostic performance of CCTA-derived plaque characteristics index on detecting myocardial ischemia.Results There were no significant differences in age,body mass index,gender,cardiovascular risk factors,and medication between myocardial ischemia population and non-ischemia population.Compared with the non-lesion-specific ischemia group,plaque length,plaque area,percent area stenosis,total atheroma volume,vessel volume and lipid rich volume,positive remodeling and napkin-ring signs were significantly higher in lesion-specific group,while minimum luminal area(MLA)was significantly lower.MLA(OR=0.303,95%CI 0.178-0.517,P＜0.001)and total atheroma volume(TAV,OR=1.006,95%CI 1.002-1.010,P=0.003)were found to be the significant independent predictors of myocardial ischemia.The regression equation of CCTA-derived plaque characteristic index for predicting probability was P=1/[1+e-(-1.194 41×MLA+0.006 058×TAV+0.600 912)].The area under the ROC curve(AUC)of CCTA-derived plaque characteristic index on detecting myocardial ischemia was 0.879(95%CI 0.811-0.928),and the overall diagnostic accuracy,sensitivity,specificity,PPV and NPV were 80.0%,83.3%,78.8%,58.8%,and 92.9%,respectively.Conclusions CCTA-derived plaque characteristic index performs well in diagnosing lesion-specific myocardial ischemia,showing its great clinical application prospect.

Bone and soft tissue tumors occur in the musculoskeletal system, and malignant bone tumors of bone and soft tissue account for 0.2% of all human malignant tumors, and if not diagnosed and treated in a timely manner, patients may be at risk of a poor prognosis. Image interpretation plays an increasingly important role in the diagnosis of bone and soft tissue tumors. Artificial intelligence (AI) can be applied in clinical treatment to integrate large amounts of multidimensional data, derive models, predict outcomes, and improve treatment decisions. Among these methods, deep learning is a widely employed technique in AI that predominantly utilizes convolutional neural networks (CNN). The network is implemented through repeated training of datasets and iterative parameter adjustments. Deep learning-based AI models have successfully been applied to various aspects of bone and soft tissue tumors, encompassing but not limiting in image segmentation, tumor detection, classification, grading and staging, chemotherapy effect evaluation, recurrence and prognosis prediction. This paper provides a comprehensive review of the principles and current state of AI in the medical image diagnosis and treatment of bone and soft tissue tumors. Additionally, it explores the present challenges and future prospects in this field.

Objective:To investigate the correlation between the neoadjuvant rectal (NAR) score and long-term survival in patients with locally advanced rectal cancer who have undergone neoadjuvant chemoradiotherapy.Methods:Clinical and pathological data of 487 patients diagnosed with rectal adenocarcinoma from October 2004 to April 2014 at Sun Yat-sen University Cancer Center who had received neoadjuvant chemoradiotherapy were retrospectively analyzed and the impact of NAR score on prognosis studied. Disease-free-survival (DFS) was calculated by the Kaplan-Meier method and survivals compared using the log-rank test. Cox models were used for univariate and multivariate analyses. Receiver operating characteristic curves were utilized to evaluate the predictive capability of NAR and tumor regression grade scores for the risk of 10-year postoperative recurrence and metastasis. The Delong test was employed to compare the diagnostic performance of the two scores.Results:Of the 487 patients included in the study, 166 were men (34.1%). The median age was 56 years (interquartile range [IQR]: 46–63). All patients completed adequate preoperative chemoradiotherapy and underwent R0 resection.The median interval between the end of chemoradiotherapy and surgery was 51 days (IQR: 44–58). Post-chemoradiotherapy downstaging occurred in 329 patients (67.6%). Tumor regression grades (TRGs) were 1–2 in 246 patients (50.5%) and 3–4 in 241 patients (49.5%). A total of 394 patients (80.9%) received postoperative chemotherapy. NAR scores were <8 in 182 patients (37.4%), 8–16 in 180 (37.0%), and >16 in 125 (25.6%). The median follow-up time was 111.5 months (IQR: 70.7–133.7 months). One hundred and thirteen patients died of rectal cancer, among whom 13 patients developed local recurrence, 88 patients developed distant metastasis, and 12 patients had unknown recurrence patterns. The 10-year DFS and overall survival rate of f the whole group were 68.9% and 71.5% respectively. The 10-year DFS rates for patients with NAR scores <8, 8–16, and >16 were 85.1%, 80.5%, and 66.4%, respectively ( P<0.001). Multivariate analyses revealed that the Dixon operation (HR=0.606, 95%CI: 0.408–0.902, P=0.014), and >16 (HR=2.569, 95%CI: 1.559–4.233, P<0.001) were independent predictors of the 10-year DFS of patients with locally advanced rectal cancer ( P<0.05 for all). In the entire patient cohort, the AUC of the receiver operating characteristic curve for NAR score predicting 10-year recurrence and metastasis was 0.67 (95%CI: 0.62–0.72), whereas the AUC for TRG score was 0.54 (95%CI: 0.49–0.60). The two scores differed significantly in accuracy ( Z=-4.06, P<0.001), the NAR score being a significantly better predictor of risk of 10-year recurrence and metastasis than the TRG score. Conclusion:The NAR score is a reliable predictor of 10-year DFS in patients with locally advanced rectal cancer who have undergone neoadjuvant chemoradiotherapy followed by curative surgery.

Objective To analyze the factors affecting the risk of hepatocellular carcinoma(HCC)in patients with chronic hepatitis B-associated cirrhosis(CHB-Cir)complicated by essential hypertension(EH)and explore the impact of EH on HCC risk in patients with CHB-Cir.Methods This study was conducted among the patients with CHB-Cir with or without EH received antiviral therapy in the Infectious Disease Department,Third Affiliated Hospital of Xinxiang Medical University from January,2017 to January,2024.The cases with insufficient follow-up time or missing data were excluded.The patients were subjected to propensity score matching in a 1:1 ratio to form an EH group and a non-EH group.The Kaplan-Meier method was used to compare the cumulative incidence of HCC between the two groups,and the Cox proportional hazards regression model was used to analyze the risk of HCC and the factors affecting HCC risk.Results A total of 390 CHB-Cir patients(274 male and 116 female patients)were enrolled in this study,including 195 with EH and 195 without EH.In these patients,EH was significantly correlated with the occurrence of HCC(HR=1.69,P=0.002).Multivariate analysis suggested that the male gender(HR=1.73,P=0.005),a family history of liver cancer(HR=2.23,P<0.001),elevated alpha-fetoprotein(HR=2.83,P=0.001),elevated glutathione reductase(HR=1.53,P=0.046),reduced high-density lipoprotein(HR=1.46,P=0.027),and elevated low-density lipoprotein(HR=2.29,P=0.003)were all significantly correlated with HCC occurrence,while elevated triglycerides(HR=0.37,P<0.001)was a protective factor against HCC.In the EH group,treatment with non-RASIs drugs(HR=2.77,P=0.021)and no treatment/diuretic treatment(HR=7.18,P<0.001)were significantly correlated with HCC occurrence.Conclusion Hypertension increases the risk of HCC in patients with CHB-Cir,suggesting the importance of controlling hypertension in these patients.

Objective To analyze the factors affecting the risk of hepatocellular carcinoma(HCC)in patients with chronic hepatitis B-associated cirrhosis(CHB-Cir)complicated by essential hypertension(EH)and explore the impact of EH on HCC risk in patients with CHB-Cir.Methods This study was conducted among the patients with CHB-Cir with or without EH received antiviral therapy in the Infectious Disease Department,Third Affiliated Hospital of Xinxiang Medical University from January,2017 to January,2024.The cases with insufficient follow-up time or missing data were excluded.The patients were subjected to propensity score matching in a 1:1 ratio to form an EH group and a non-EH group.The Kaplan-Meier method was used to compare the cumulative incidence of HCC between the two groups,and the Cox proportional hazards regression model was used to analyze the risk of HCC and the factors affecting HCC risk.Results A total of 390 CHB-Cir patients(274 male and 116 female patients)were enrolled in this study,including 195 with EH and 195 without EH.In these patients,EH was significantly correlated with the occurrence of HCC(HR=1.69,P=0.002).Multivariate analysis suggested that the male gender(HR=1.73,P=0.005),a family history of liver cancer(HR=2.23,P<0.001),elevated alpha-fetoprotein(HR=2.83,P=0.001),elevated glutathione reductase(HR=1.53,P=0.046),reduced high-density lipoprotein(HR=1.46,P=0.027),and elevated low-density lipoprotein(HR=2.29,P=0.003)were all significantly correlated with HCC occurrence,while elevated triglycerides(HR=0.37,P<0.001)was a protective factor against HCC.In the EH group,treatment with non-RASIs drugs(HR=2.77,P=0.021)and no treatment/diuretic treatment(HR=7.18,P<0.001)were significantly correlated with HCC occurrence.Conclusion Hypertension increases the risk of HCC in patients with CHB-Cir,suggesting the importance of controlling hypertension in these patients.

Background::Thoracic aortic aneurysm (TAA) is a fatal cardiovascular disease, the pathogenesis of which has not yet been clarified. This study aimed to identify and validate the diagnostic markers of TAA to provide a strong theoretical basis for developing new methods to prevent and treat this disease.Methods::Gene expression profiles of the GSE9106, GSE26155, and GSE155468 datasets were acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the "limma" package in R. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), random forest, and binary logistic regression analyses were used to screen the diagnostic marker genes. Single-sample gene set enrichment analysis (ssGSEA) was used to estimate immune cell infiltration in TAA.Results::A total of 16 DEGs were identified. The enrichment and functional correlation analyses showed that DEGs were mainly associated with inflammatory response pathways and collagen-related diseases. Collagen type I alpha 1 chain ( COL1A1) and synaptotagmin like 2 ( SYTL2) were identified as diagnostic marker genes with a high diagnostic value for TAA. The expression of COL1A1 and SYTL2 was considerably higher in TAA vascular wall tissues than in the corresponding normal tissues, and there were significant differences in the infiltration of immune cells between TAA and normal vascular wall tissues. Additionally, COL1A1 and SYTL2 expression were associated with the infiltration of immune cells in the vascular wall tissue. Single-cell analysis showed that COL1A1 in TAA was mainly derived from fibroblasts and SYTL2 mainly from cluster of differentiation (CD)8 + T cells. In addition, single-cell analysis indicated that fibroblasts and CD8 + T cells in TAA were significantly higher than those in normal arterial wall tissue. Conclusions::COL1A1 and SYTL2 may serve as diagnostic marker genes for TAA. The upregulation of SYTL2 and COL1A1 may be involved in the inflammatory infiltration of the vessel wall and poor extracellular matrix remodeling, promoting the progression of TAA.

Objective:To explore and think about the project management model of investigator-initiated trial (IIT), and the project management of industry sponsored trial (IST), we should standardize the management process of clinical research projects initiated by researchers, improve the management system of clinical research in medical institutions, improve the quality management level of clinical research, and protect the rights and interests of research participants.Methods:By taking the clinical research management of a medical and health institution in Hainan province as an example, one of the first pilot areas for the standardized management of clinical research by the National Health Commission, the difficulties in the management of clinical research initiated by researchers were sorted out, to analyze and standardize the management of clinical research project initiated by researchers.Results:Discussion Project management was the primary link and basic guarantee of standardized management of clinical research, and scientific and feasible project management was a powerful hand to carry out deep and high-quality IIT.Conclusions:It can be manifested in a Hainan provincial public medical institution that a feasible project management was the basement in carrying out the profound and high quality IIT. It is advicable to make full use of policy advantages and clinical resources to produce high-quality research results as well as build a high-level research hospital.

ObjectiveTo realize the automatic recognition of the slicing angles of Fritillariae Thunbergii Bulbus （FTB） based on the improved YOLOv7-tiny algorithm. MethodFirstly， a diverse dataset of FTB images， totaling 16 000 pictures， with various angles was constructed. Furthermore， improvements were made to YOLOv7-tiny by replacing standard convolutions with ghost convolution （GhostConv）， incorporating the coordinate attention （CA） mechanism as a preferred addition， substituting some activation functions with HardSwish function for decreasing the floating point operations. Additionally， a penalty term for angle recognition error was integrated into the loss function， and modifications were made to the non-maximum suppression （NMS） strategy to address cases where multiple detection results were associated with the same target. In order to verify the effectiveness of different improvement points on the optimization of the algorithm model， ablation experiments were carried out on all the improvement points， and the effectiveness of the improvement points was proved by comparing the prediction results before and after the addition of a certain improvement point on the basis of the original model or the model with the addition of an improvement point that has been verified to be effective， in order to evaluate the improvement of the indexes. ResultThe number of parameters required for the improved slicing angle recognition algorithm of FTB was about 55.4% of the original algorithm， and the amount of computation was about 59.4% of the original algorithm. The mAP@0.5［mean average precision at an intersection over union（IoU） of 0.5］ increased by 12.2%， the mean absolute error（MAE） of the recognized angle was 5.02°， representing a reduction of 4.58° compared to the original algorithm. In the experimental environment of this paper， the average recognition time per image was as low as 8.7 ms， significantly faster than the average human reaction time. ConclusionThis study， by utilizing the improved YOLOv7-tiny algorithm， achieves effective slicing angle recognition of FTB with high accuracy and more lightweight， which provides a novel approach for stable and precise automated slicing of FTB， thereby providing valuable insights into the automation of processing other traditional Chinese medicines.