Objective:To explore the risk factors of colostomy site incisional hernia associated with colorectal can-cer and to construct and validate a nomogram model.Methods:A retrospective case-control study was conducted to collect and analyze the clinical data of patients who underwent stoma reversal after colorectal cancer surgery in the Gen-eral Surgery Department of Linyi People's Hospital from January 2019 to January 2023.A total of 371 patients were en-rolled and divided into SSIH group and non-SSIH group according to whether SSIH occurred.SPSS 25.0 software was used to perform univariate analysis on 22 related factors of patients,and multivariate analysis was performed on statisti-cally significant risk factors to screen out the independent influencing factors of SSIH related to CRC surgery.According to the results of multivariate analysis,the R language version 4.3.1 was used to establish and verify the nomogram risk prediction model.Results:SSIH occurred in 52 of 371 patients(14.02％).The results of univariate analysis showed that BMI,coronary heart disease,incision infection,stoma location,parastomal hernia,and closure time were statistically sig-nificant(P＜0.05).Multivariate analysis showed that coronary heart disease,closure time and parastomal hernia were in-dependent risk factors for SSIH after CRC(P＜0.05).Based on the above results,the nomogram prediction model was successfully drawn and verified.Conclusions:Coronary heart disease,closure time and parastomal hernia are inde-pendent risk factors for SSIH after CRC surgery.The nomogram constructed based on these factors has a high predictive value for SSIH,which can provide a basis for clinicians to prevent and treat SSIH,and help reduce the incidence of SSIH.

Objective:To optimize the previously established Improved Membrane Filtration(ISET)method for de-tecting circulating tumor cells(CTCs)and to develop and validate a new,reliable CTC detection method by combining it with immunofluorescence techniques.Methods:The study involved optimizing the CTC detection system using mixed samples of gastric cancer 803 cell lines and peripheral blood(PB)from healthy volunteers to simulate the peripheral blood of cancer patients.The optimized system was validated using peripheral blood samples from 23 patients with ad-vanced(Ⅲ/Ⅳ)cancer,employing the ISET technique combined with immunocytochemistry(ICC)and paraffin block im-munohistochemistry(IHC)identification techniques.A cohort of 74 patients with various cancer types was used to com-pare the diagnostic performance of the membrane filtration combined with immunofluorescence(ISET-ICC)system against the CTC-Biopsy and CellSearchTM methods.Results:By adding a red blood cell lysis step and increasing the membrane pore size to 10 μm,the filtration time of the ISET method was reduced by threefold.The ISET-ICC detection method achieved a CTC positivity rate of 65.2％.The combination of the ISET-ICC system with the cell paraffin block-IHC method enhanced the reliability of identifying circulating tumor cells undergoing epithelial-mesenchymal transition(EMT-CTCs).The ISET-ICC technique demonstrated a significantly higher CTC positivity rate(17.6％;13/74)within the study cohort compared to the CellSearchTM method,which showed a CTC positivity rate of 12.2％(9/74;x2=10.21,P=0.007).The difference in positive detection rates among patients at different stages was statistically significant(x2=3.64,P=0.029),with a notably higher CTC detection rate in stage Ⅳ patients compared to those in stages Ⅰ-Ⅲ(x2=6.76,P=0.001).Conclusion:The improved ISET-ICC system effectively detects CTCs across various cancer types and dem-onstrates greater accuracy compared to the CellSearchTM system.

Objective:To investigate the predictive value of serum CC chemokine ligand 20(CCL20)and leucine-rich G protein-coupled receptor 4(LGR4)for recurrence and metastasis in patients with colon cancer after laparoscopic surgery.Methods:A total of 214 patients with colon cancer who underwent laparoscopic surgery for colon cancer from April 2019 to April 2022 were selected as the cancer group,and 214 patients with benign lesions of colon admitted dur-ing the same period were selected as the benign lesion group.According to the results of 2-year follow-up,the patients with colon cancer were divided into recurrent group(66 cases)and non-recurrent group(148 cases).The levels of serum CCL20 and LGR4 were detected by ELISA.ROC curve was used to analyze the predictive value of serum CCL20 and LGR4 for recurrence and metastasis of colon cancer patients after laparoscopic surgery.Multivariate Cox regression analysis of the factors affecting postoperative recurrence and metastasis.Results:The levels of serum CCL20 and LGR4 in the cancer group were significantly lower after operation,but still significantly higher than those in the benign le-sion group(P＜0.05).Serum levels of CCL20 and LGR4 in relapsed group were significantly increased compared with those in non-recurrent group(P＜0.05).There were significant differences in TNM stage,differentiation degree and infil-tration depth between relapse group and non-recurrence group(P＜0.05).Compared with the single prediction,the com-bined detection of serum CCL20(Z=2.733,P=0.006)and LGR4(Z=3.705,P＜0.00)levels significantly increased the AUC in predicting the recurrence and metastasis of colon cancer after laparoscopic surgery.Multivariate Cox regression analy-sis showed that TNM stage,differentiation degree,CCL20 and LGR4 levels were the factors affecting the recurrence and metastasis of colon cancer patients after laparoscopic surgery(P＜0.05).Conclusion:The serum levels of CCL20 and LGR4 increased in patients with colon cancer,and the changes of the levels were closely related to the recurrence and metastasis of colon cancer after laparoscopic surgery.

Objective:To investigate the clinical significance of constructing a nomogram based on a combined model of clinical-pathological-imaging data for predicting postoperative recurrence/metastasis of breast cancer.Meth-ods:A retrospective study was conducted on 194 breast cancer patients who were admitted to the department of breast and thyroid surgery from June 2019 to June 2022.unvariate and multivariate Logistic regression analyses were used to screen independent predictors of postoperative recurrence/metastasis of breast cancer,and a model was con-structed based on the independent predictors.Another 83 breast cancer patients from July 2022 to February 2023 were taken as the validation set to verify the model with the ratio of 7∶3(training set∶validation set).Results:The postopera-tive recurrence/metastasis rate of breast cancer was 29.90％.Ki-67 expression level ≥20％,tumor location in the inner upper quadrant and outer upper quadrant,lesion size ≥20 mm,multiple lesions,and BI-RADS grade of 5 were indepen-dent risk factors for postoperative recurrence/metastasis of breast cancer(P＜0.05).PR positive expression was an inde-pendent protective factor for postoperative recurrence/metastasis of breast cancer(P＜0.05).The diagnostic performance of the combined clinical-pathological-imaging model(AUC:0.900)was superior to that of the clinical-pathological pa-rameters(AUC:0.655)and the MRI parameter model(AUC:0.857).In its nomogram model constructed based on a com-bined clinical-pathological-imaging model to predict breast cancer recurrence/metastasis after surgery,the AUC in the training set was 0.900(95％CI:0.859～0.942)with good discrimination,the maximum Yoden value was 0.710,the sensi-tivity was 0.931,and the specificity was 0.779,and the AUC in the validation set was 0.820(95％C/:0.712～0.928),well differentiated,with a maximum Yoden value of 0.554,a sensitivity of 0.630,and a specificity of 0.914.The theoretical and actual values of the calibration curves of the two sets were in good agreement,and the decision curve indicated the net benefit of the breast cancer recurrence-metastasis prediction model after surgery,which showed good predictive ability.Conclusion:The nomogram constructed based on the combined model of clinical-pathological-imaging data has good predictive ability,accuracy,and clinical applicability,which is helpful for clinicians to evaluate the risk of postoperative re-currence/metastasis of breast cancer.

Objective:Analyze the influencing factors of postoperative recurrence of common bile duct stones in patients with gallstones and multiple common bile duct stones,and evaluate the application value of nomogram predic-tion models.Methods:Collected clinical data of 587 patients with gallstones and multiple common bile duct stones who underwent surgical treatment at Beijing Fengtai Hospital from January 2022 to January 2024.They were divided into a training cohort(n=410)and a validation cohort(n=177)according to a 7∶3 ratio.Analyzed the influencing factors of postoperative recurrence of common bile duct stones in patients with gallstones and multiple common bile duct stones,and constructed a nomogram prediction model based on this.Results:The recurrence rate of postoperative common bile duct stones in the training queue was 38.05％(156/410).Age,BMI,intrahepatic bile duct stones,initial course of dis-ease,duodenal diverticulum,biliary tract infection,history of biliary surgery,thickness of the common bile duct wall,num-ber of multiple stones in the common bile duct,diameter of the common bile duct,and dysfunction of the Oddis sphincter in the duodenal papilla during ERCP examination are independent risk factors for postoperative recurrence in patients with gallbladder stones combined with multiple stones in the common bile duct(P＜0.05).The AUC of the constructed nomo-gram prediction model in the training queue and validation queue were 0.854 and 0.889,respectively.The Hosmer Lem-eshow fitting test results showed that there was no statistically significant difference between the predicted probability and the actual probability of the prediction model(x2=3.952,P=0.865),indicating that this model has good predictive abil-ity.Conclusion:The nomogram prediction model based on various risk factors can effectively predict the risk of post-operative common bile duct stone recurrence in patients with gallstones and multiple common bile duct stones.

Objective:To analyze the expression of conductance calcium-activated potassium channel(IKCa1)protein in papillary thyroid carcinoma(PTC)tissues and its relationship with postoperative recovery of thyroid function.Methods:A total of 153 PTC patients who were treated from December 2020 to December 2023 were selected as the research objects.All patients were divided into a good recovery group(n=97)and a poor recovery group(n=56)according to whether they had hypothyroidism after surgery.The expression of IKCa1 protein in PTC tissues and adjacent normal tissues was compared.The relationship between the expression of IKCa1 protein in PTC tissues and the clinicopathologi-cal characteristics of the patients was analyzed.Hierarchical regression analysis was used to analyze the relationship be-tween clinicopathological features and IKCa1 mRNA level.Univariate analysis was used to analyze the influencing factors of postoperative thyroid function recovery.Spearman correlation was used to analyze the relationship between IKCa1 mRNA expression and thyroid function related factors[free triiodothyronine(FT3),free thyroxine(FT4),total triiodothyro-nine(TT3),total thyroxine(TT4)and thyroid stimulating hormone(TSH)].The independent correlation between IKCa1 mRNA expression in PTC tissues and postoperative thyroid dysfunction was analyzed.The dose on response between IKCa1 mRNA expression in PTC tissues and postoperative thyroid function was analyzed.And the relationship between IKCa1 protein expression in PTC tissues and prognosis of patients.Results:The high expression of IKCa1 protein in PTC tissues(102 cases,66.67％)was significantly higher than that in adjacent normal tissues(33 cases,21.57％),and the difference was statistically significant(P＜0.05).The expression of IKCa1 protein in PTC tissues was related to tumor diameter,lymph node metastasis,TNM stage and Ki-67(P＜0.05).Tumor diameter,lymph node metastasis,TNM stage and Ki-67 had a significant positive effect on IKCa1 mRNA level(P＜0.05).There were significant differences in lymph node metastasis,tumor diameter and IKCa1 mRNA expression between the good recovery group and the poor recovery group(P＜0.05).The results of Spearman analysis showed that the expressions of FT3,FT4,TT3,TT4 and TSH had sig-nificant effects on IKCa1 mRNA expression(P＜0.05).The expression level of IKCa1 mRNA in PTC tissues was indepen-dently correlated with postoperative thyroid function(All P＜0.05).RCS model analysis showed that with the increase of IKCa1 mRNA expression,postoperative thyroid function showed a non-linear downward trend.The overall survival of pa-tients with high expression of IKCa1 protein in PTC tissues was significantly shorter than that of patients with low ex-pression of IKCa1 protein(P＜0.05).Conclusion:IKCa1 protein is highly expressed in PTC tissues,and its expression level is closely related to postoperative thyroid function,which is a risk factor for postoperative hypothyroidism.

Objective:To construct a predictive model for benign and malignant colorectal lesions based on modal ultrasound parameters and clinical indicators,and evaluate the effectiveness of the predictive model.Methods:Clinical data of 198 patients with colorectal lesions treated in Hebei Petro China Central Hospital from March 2020 to March 2024 were recorded.According to pathological diagnosis,they were grouped into a benign lesion group of 102 cases and a malignant lesion group of 96 cases.All patients underwent multimodal ultrasound examination.Multivariate Logistic re-gression analysis was applied to screen the influencing factors of colorectal cancer progression.R software package was applied to build a nomogram prediction model.Hosmer-Lemeshow test,calibration curve,ROC curve,and clinical deci-sion curve were used for validation.Results:There were statistically obvious differences in internal echo,morphology,blood flow signal,rise time(RT),contrast agent of"fast in and fast out",mean Young's modulus(Emean),age,positive fecal occult blood,and polyps between the benign and malignant lesion groups(P＜0.05).Uneven internal echoes,irregu-lar shapes,abundant blood flow signals,contrast agent of"fast in and fast out",age ≥ 60 years,positive fecal occult blood,and polyps ≥ 2 were independent risk factors for colorectal cancer(P＜0.05),while RT is a protective factor for colorectal cancer(P＜0.05).The internal validation results of the nomogram prediction model showed that the Hosmer-Lemeshow test showed x2=3.661 and P=0.886.The calibration curve showed that the actual probability was basically consistent with the predicted probability,and the AUC of the ROC curve was 0.802(95％CI:0.732-0.871),indicating that the calibration and discrimination of the column chart prediction model were good.Within the high-risk threshold range of 0.28-0.98,the decision curve was above the All line and None line,indicating a high net benefit and clinical practicality.Conclusion:Internal echo,morphology,blood flow signal,contrast agent of"fast in and fast out",age,positive fecal occult blood,polyps,and RT are influencing factors for the occurrence of colorectal cancer.The column chart prediction model constructed based on this has good predictive performance and provides reference for early inter-vention by clinical physicians.

The European Society for Medical Oncology Asia Congress 2024 was held in Singapore from December 6 to 8,2024.The conference unveiled several groundbreaking studies in the field of hepatobiliary and pancreatic tumors,covering clinical applications related to neoadjuvant and adjuvant therapies,translational treatments,later-line therapies,and tumor biomarkers.These studies provide new insights into the clinical diagnosis and treatment of hepatobiliary and pancreatic malignancies and drive the development of related fields.This article focuses on the key topics in hepatobiliary and pancreatic malignancies presented at the conference,aiming to interpret the latest advances in the field and explore the hot issues and future directions for development in this area.

With the rapid development of artificial intelligence(AI)technology,especially deep learning,AI is playing an increasingly important role in the diagnosis and treatment of liver cancer.AI has shown great potential in improving diagnostic accuracy,reducing the workload of physicians,and providing personalized treatment plans.In imaging diagnosis of liver cancer,AI technology has been widely applied to ultrasound,CT,and MRI data,enabling automatic recognition and segmentation of liver lesions and differentiation between benign and malignant lesions.In some cases,its diagnostic accuracy can match or even surpass that of professional radiologists.In pathological diagnosis,AI assists pathologists in differential diagnosis and classification by analyzing whole slide image,improving diagnostic efficiency and accuracy.For treatment decision support,AI analyzes clinical,imaging,and pathological data to predict postoperative recurrence risk,evaluate the effectiveness of specific treatments,and identify biomarkers,providing new perspectives for precision medicine and assisting clinicians in designing personalized treatment plans.With the advancement of multimodal AI models that integrate imaging,pathology,and clinical data,it is possible to achieve a more comprehensive understanding of the biological behavior of liver cancer,thereby offering more precise diagnoses and treatments for patients.Despite its immense potential,AI in liver cancer diagnosis and treatment faces challenges such as data standardization,security,and privacy protection.The clinical translation of AI models requires further validation and refinement.With technological advancements and data accumulation,AI is expected to provide more precise and personalized medical services for liver cancer patients in the future.This article focuses on summarizing significant research advances in AI for liver cancer diagnosis and treatment,and briefly discusses its limitations and future directions.

In the 2010s,laparoscopic hepatectomy(LH)rapidly gained popularity in Japan as a minimally invasive approach for liver resections.It offers significant advantages,such as reduced postoperative pain and faster recovery.The Glissonean pedicle approach,employed during LH,enables precise anatomical resection,particularly for hepatocellular carcinoma and metastatic liver tumors.Innovations in training,including the use of animal models and the Japan Society for Endoscopic Surgery certification program,have been instrumental in improving surgical expertise.However,complex hepatectomies involving vascular or biliary reconstruction pose substantial technical challenges.Robot-assisted hepatectomy(RAH)has shown great potential for improved precision and visualization,though its high costs and uncertain long-term benefits limit its widespread adoption.Further technological advancements,enhanced training programs,and large-scale comparative trials are necessary to evaluate the long-term efficacy of both LH and RAH.