Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer

BACKGROUND Lymph node(LN)staging in rectal cancer(RC)affects treatment decisions and patient prognosis.For radiologists,the traditional preoperative assessment of LN metastasis(LNM)using magnetic resonance imaging(MRI)poses a challenge.AIM To explore the value of a nomogram model that combines Conventional MRI and radiomics features from the LNs of RC in assessing the preoperative metastasis of evaluable LNs.METHODS In this retrospective study,270 LNs(158 nonmetastatic,112 metastatic)were randomly split into training(n=189)and validation sets(n=81).LNs were classified based on pathology-MRI matching.Conventional MRI features[size,shape,margin,T2-weighted imaging(T2WI)appearance,and CE-T1-weighted imaging(T1WI)enhancement]were evaluated.Three radiomics models used 3D features from T1WI and T2WI images.Additionally,a nomogram model combining conventional MRI and radiomics features was developed.The model used univariate analysis and multivariable logistic regression.Evaluation employed the receiver operating characteristic curve,with DeLong test for comparing diagnostic performance.Nomogram performance was assessed using calibration and decision curve analysis.RESULTS The nomogram model outperformed conventional MRI and single radiomics models in evaluating LNM.In the training set,the nomogram model achieved an area under the curve(AUC)of 0.92,which was significantly higher than the AUCs of 0.82(P<0.001)and 0.89(P<0.001)of the conventional MRI and radiomics models,respectively.In the validation set,the nomogram model achieved an AUC of 0.91,significantly surpassing 0.80(P<0.001)and 0.86(P<0.001),respectively.CONCLUSION The nomogram model showed the best performance in predicting metastasis of evaluable LNs.

Predictive value of machine learning models for lymph node metastasis in gastric cancer: A two-center study

BACKGROUND Gastric cancer is one of the most common malignant tumors in the digestive system,ranking sixth in incidence and fourth in mortality worldwide.Since 42.5%of metastatic lymph nodes in gastric cancer belong to nodule type and peripheral type,the application of imaging diagnosis is restricted.AIM To establish models for predicting the risk of lymph node metastasis in gastric cancer patients using machine learning(ML)algorithms and to evaluate their pre-dictive performance in clinical practice.METHODS Data of a total of 369 patients who underwent radical gastrectomy at the Depart-ment of General Surgery of Affiliated Hospital of Xuzhou Medical University(Xuzhou,China)from March 2016 to November 2019 were collected and retro-spectively analyzed as the training group.In addition,data of 123 patients who underwent radical gastrectomy at the Department of General Surgery of Jining First People’s Hospital(Jining,China)were collected and analyzed as the verifi-cation group.Seven ML models,including decision tree,random forest,support vector machine(SVM),gradient boosting machine,naive Bayes,neural network,and logistic regression,were developed to evaluate the occurrence of lymph node metastasis in patients with gastric cancer.The ML models were established fo-llowing ten cross-validation iterations using the training dataset,and subsequently,each model was assessed using the test dataset.The models’performance was evaluated by comparing the area under the receiver operating characteristic curve of each model.RESULTS Among the seven ML models,except for SVM,the other ones exhibited higher accuracy and reliability,and the influences of various risk factors on the models are intuitive.CONCLUSION The ML models developed exhibit strong predictive capabilities for lymph node metastasis in gastric cancer,which can aid in personalized clinical diagnosis and treatment.

ScRNA-seq reveals the correlation between M2 phenotype of tumorassociated macrophages and lymph node metastasis of breast cancer

The process of lymphatic metastasis was proved to be associated with podoplanin-expressing macrophages in breast cancer(BC).This study aimed to investigate the role of the M2 phenotype of tumor-associated macrophages and mine the key M2 macrophages-related genes for lymph node metastasis in BC.We downloaded the GSE158399 dataset from the Gene Expression Omnibus(GEO)database,which includes transcriptomic profiles of individual cells from primary tumors,negative lymph nodes(NLNs),and positive lymph nodes(PLNs)of breast cancer patients.The cell subsets were identified by clustering analysis after quality control of the scRNA-seq using Seurat.The activation and migration capability of M2 macrophages were evaluated with R package“GSVA”.The key M2 macrophages-related genes were screened from the differential expressed genes(DEGs)and M2 macrophages activation and migration gene sets collected from MSigDB database.Our analysis identified three main cell types in primary tumors,NLNs,and PLNs:basal cells,luminal cells,and immune cell subsets.The further cell type classification of immune cell subsets indicated M2 macrophages accumulation in NLs and PLs.The GSVA enrichment scores for activation and migration capability were increased significantly in M2 macrophages from primary tumors than NLNs and PLNs(pvalue<0.001).Seven M2 macrophages activation-related and 15 M2 macrophages migration-related genes were significantly up-regulated in primary tumors than NLNs and PLNs.The proportion and GSVA enrichment scores for activation and migration of M2 macrophages may be potential markers for lymph node metastasis in breast cancer.Our study demonstrated that twenty-two up-regulated mRNA may be possible therapeutic targets for lymph node metastasis in breast cancer.

Nomogram established using risk factors of early gastric cancer for predicting the lymph node metastasis

BACKGROUND For the prognosis of patients with early gastric cancer(EGC),lymph node metastasis(LNM)plays a crucial role.A thorough and precise evaluation of the patient for LNM is now required.AIM To determine the factors influencing LNM and to construct a prediction model of LNM for EGC patients.METHODS Clinical information and pathology data of 2217 EGC patients downloaded from the Surveillance,Epidemiology,and End Results database were collected and analyzed.Based on a 7:3 ratio,1550 people were categorized into training sets and 667 people were assigned to testing sets,randomly.Based on the factors influencing LNM determined by the training sets,the nomogram was drawn and verified.RESULTS Based on multivariate analysis,age at diagnosis,histology type,grade,T-stage,and size were risk factors of LNM for EGC.Besides,nomogram was drawn to predict the risk of LNM for EGC patients.Among the categorical variables,the effect of grade(well,moderate,and poor)was the most significant prognosis factor.For training sets and testing sets,respectively,area under the receiver-operating characteristic curve of nomograms were 0.751[95%confidence interval(CI):0.721-0.782]and 0.786(95%CI:0.742-0.830).In addition,the calibration curves showed that the prediction model of LNM had good consistency.CONCLUSION Age at diagnosis,histology type,grade,T-stage,and tumor size were independent variables for LNM in EGC.Based on the above risk factors,prediction model may offer some guiding implications for the choice of subsequent therapeutic approaches for EGC.

Predicting lymph node metastasis in colorectal cancer:An analysis of influencing factors to develop a risk model

BACKGROUND Colorectal cancer(CRC)is a significant global health issue,and lymph node metastasis(LNM)is a crucial prognostic factor.Accurate prediction of LNM is essential for developing individualized treatment strategies for patients with CRC.However,the prediction of LNM is challenging and depends on various factors such as tumor histology,clinicopathological features,and molecular characteristics.The most reliable method to detect LNM is the histopathological examination of surgically resected specimens;however,this method is invasive,time-consuming,and subject to sampling errors and interobserver variability.AIM To analyze influencing factors and develop and validate a risk prediction model for LNM in CRC based on a large patient queue.METHODS This study retrospectively analyzed 300 patients who underwent CRC surgery at two Peking University Shenzhen hospitals between January and December 2021.A deep learning approach was used to extract features potentially associated with LNM from primary tumor histological images while a logistic regression model was employed to predict LNM in CRC using machine-learning-derived features and clinicopathological variables as predictors.RESULTS The prediction model constructed for LNM in CRC was based on a logistic regression framework that incorporated machine learning-extracted features and clinicopathological variables.The model achieved high accuracy(0.86),sensitivity(0.81),specificity(0.87),positive predictive value(0.66),negative predictive value(0.94),area under the curve for the receiver operating characteristic(0.91),and a low Brier score(0.10).The model showed good agreement between the observed and predicted probabilities of LNM across a range of risk thresholds,indicating good calibration and clinical utility.CONCLUSION The present study successfully developed and validated a potent and effective risk-prediction model for LNM in patients with CRC.This model utilizes machine-learning-derived features extracted from primary tumor histology and clinicopathological variables,demonstrating superior performance and clinical applicability compared to existing models.The study provides new insights into the potential of deep learning to extract valuable information from tumor histology,in turn,improving the prediction of LNM in CRC and facilitate risk stratification and decision-making in clinical practice.

Prediction of lymph node metastasis in early esophageal cancer

BACKGROUND Given the poor prognosis of patients with lymph node metastasis,estimating the lymph node status in patients with early esophageal cancer is crucial.Indicators that could be used to predict lymph node metastasis in early esophageal cancer have been reported in many recent studies,but no recent studies have included a review of this subject.AIM To review indicators predicting lymph node metastasis in early esophageal squamous cell carcinoma(ESCC)and early esophageal adenocarcinoma(EAC).METHODS We searched PubMed with“[early esophageal cancer(Title/Abstract)]and[lymph node(Title/Abstract)]”or“[early esophageal carcinoma(Title/Abstract)]and[lymph node(Title/Abstract)]”or“[superficial esophageal cancer(Title/Abstract)]and[lymph node(Title/Abstract)].”A total of 29 studies were eligible for analysis.RESULTS Preoperative imaging(size),serum markers(microRNA-218),postoperative pathology and immunohistochemical analysis(depth of invasion,tumor size,differentiation grade,lymphovascular invasion,neural invasion,expression of PIM-1<30%)were predictive factors for lymph node metastasis in both early ESCC and EAC.Serum markers(thymidine kinase 1≥3.38 pmol/L;cytokeratin 19 fragment antigen 21-1>3.30 ng/mL;stathmin-1)and postoperative pathology and immunohistochemical analysis(overexpression of cortactin,mixed-lineage leukaemia 2,and stanniocalcin-1)were predictive for lymph node metastasis in early ESCC.Transcription of CD69,myeloid differentiation protein 88 and toll-like receptor 4 and low expression of olfactomedin 4 were predictive of lymph node metastasis in early EAC.A total of 6 comprehensive models for early ESCC,including logistic regression model,nomogram,and artificial neural network(ANN),were reviewed.The areas under the receiver operating characteristic curve of these models reached 0.789-0.938,and the ANN performed best.As all these models relied on postoperative pathology,further models focusing on serum markers,imaging and immunohistochemical indicators are still needed.CONCLUSION Various factors were predictive of lymph node metastasis in early esophageal cancer,and present comprehensive models predicting lymph node metastasis in early ESCC mainly relied on postoperative pathology.Further studies focusing on serum markers,imaging and immunohistochemical indicators are still in need.

Establishment of Risk Prediction Model and Nomogram for Lymph Node Metastasis of Cervical Cancer: Based on SEER Database

Objective: To predict the risk factors of lymph node metastasis in cervical cancer by using large sample clinical data, and to construct and verify the nomogram for predicting lymph node metastasis. Methods: A total of 5940 patients with cervical cancer from 2004 to 2015 in the National Cancer Institute Surveillance Epidemiology and End Results database were retrospectively screened and randomly assigned to training group (n = 4172) and validation group (n = 1768). Multivariate Logistic regression analysis was used, and the optimal model was selected according to AIC or BIC and likelihood ratio test, and a nomogram was drawn. The accuracy and robustness of the prediction model were evaluated in three aspects: discrimination, calibration and clinical net benefit. Results: The prediction model based on race, tumor tissue differentiation degree, tumor histopathological type, distant metastasis of tumor, tumor diameter and other risk factors was successfully established and a nomogram was constructed. The AUCs of training group and validation group were: 0.736 and 0.714, respectively. And the p-values of the Hosmer-Lemeshow test were 0.28 and 0.11, respectively. The calibration curve was in good agreement with the ideal curve. It had high accuracy and applicability after internal verification. Conclusion: A prediction model is constructed based on the risk factors of lymph node metastasis of cervical cancer. The nomogram has a good effective prediction and can provide a theoretical basis for clinicians to assess the disease quickly before surgery.

Assessment of programmed death-ligand 1 expression in primary tumors and paired lymph node metastases of gastric adenocarcinoma

BACKGROUND Anti-programmed death-1/programmed death-ligand 1(PD-1/PD-L1)immuno-therapy has demonstrated promising results on gastric cancer(GC).However,PD-L1 can express differently between metastatic sites and primary tumors(PT).AIM To compare PD-L1 status in PT and matched lymph node metastases(LNM)of GC patients and to determine the correlation between the PD-L1 status and clinicopathological characteristics.METHODS We retrospectively reviewed 284 GC patients who underwent D2-gastrectomy.PD-L1 was evaluated by immunohistochemistry(clone SP142)using the com-bined positive score.All PD-L1+PT staged as pN+were also tested for PD-L1 expression in their LNM.PD-L1(-)GC with pN+served as the comparison group.RESULTS Among 284 GC patients included,45 had PD-L1+PT and 24 of them had pN+.For comparison,44 PD-L1(-)cases with pN+were included(sample loss of 4 cases).Of the PD-L1+PT,54.2%(13/24 cases)were also PD-L1+in the LNM.Regarding PD-L1(-)PT,9.1%(4/44)had PD-L1+in the LNM.The agreement between PT and LNM had a kappa value of 0.483.Larger tumor size and moderate/severe peritumoral inflammatory response were associated with PD-L1 positivity in both sites.There was no statistical difference in overall survival for PT and LNM according to the PD-L1 status(P=0.166 and P=0.837,respectively).CONCLUSION Intra-patient heterogeneity in PD-L1 expression was observed between the PT and matched LNM.This disagreement in PD-L1 status may emphasize the importance of considering different tumor sites for analyses to select patients for immunotherapy.

Nomogram based on multimodal magnetic resonance combined with B7-H3mRNA for preoperative lymph node prediction in esophagus cancer

Accurate preoperative prediction of lymph node metastasis(LNM)in esophageal cancer(EC)patients is of crucial clinical significance for treatment planning and prognosis.AIM To develop a clinical radiomics nomogram that can predict the preoperative lymph node(LN)status in EC patients.METHODS A total of 32 EC patients confirmed by clinical pathology(who underwent surgical treatment)were included.Real-time fluorescent quantitative reverse transcription-polymerase chain reaction was used to detect the expression of B7-H3 mRNA in EC tissue obtained during preoperative gastroscopy,and its correlation with LNM was analyzed.Radiomics features were extracted from multi-modal magnetic resonance imaging of EC using Pyradiomics in Python.Feature extraction,data dimensionality reduction,and feature selection were performed using XGBoost model and leave-one-out cross-validation.Multivariable logistic regression analysis was used to establish the prediction model,which included radiomics features,LN status from computed tomography(CT)reports,and B7-H3 mRNA expression,represented by a radiomics nomogram.Receiver operating characteristic area under the curve(AUC)and decision curve analysis(DCA)were used to evaluate the predictive performance and clinical application value of the model.RESULTS The relative expression of B7-H3 mRNA in EC patients with LNM was higher than in those without metastasis,and the difference was statistically significant(P<0.05).The AUC value in the receiver operating characteristic(ROC)curve was 0.718(95%CI:0.528-0.907),with a sensitivity of 0.733 and specificity of 0.706,indicating good diagnostic performance.The individualized clinical prediction nomogram included radiomics features,LN status from CT reports,and B7-H3 mRNA expression.The ROC curve demonstrated good diagnostic value,with an AUC value of 0.765(95%CI:0.598-0.931),sensitivity of 0.800,and specificity of 0.706.DCA indicated the practical value of the radiomics nomogram in clinical practice.CONCLUSION This study developed a radiomics nomogram that includes radiomics features,LN status from CT reports,and B7-H3 mRNA expression,enabling convenient preoperative individualized prediction of LNM in EC patients.

Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma:A real-world retrospective cohort study

BACKGROUND Signet-ring cell carcinoma(SRCC)was previously thought to have a worse prognosis than other differentiated gastric cancer(GC),however,recent studies have shown that the prognosis of SRCC is related to pathological type.We hypothesize that patients with SRCC and with different SRCC pathological components have different probability of lymph node metastasis(LNM).AIM To establish models to predict LNM in early GC(EGC),including early gastric SRCC.METHODS Clinical data from EGC patients who had undergone gastrectomy at the First Affiliated Hospital of Nanjing Medical University from January 2012 to March 2022 were reviewed.The patients were divided into three groups based on type:Pure SRCC,mixed SRCC,and non-signet ring cell carcinoma(NSRC).The risk factors were identified through statistical tests using SPSS 23.0,R,and EmpowerStats software.RESULTS A total of 1922 subjects with EGC were enrolled in this study,and included 249 SRCC patients and 1673 NSRC patients,while 278 of the patients(14.46%)presented with LNM.Multivariable analysis showed that gender,tumor size,depth of invasion,lymphovascular invasion,ulceration,and histological subtype were independent risk factors for LNM in EGC.Establishment and analysis using prediction models of EGC showed that the artificial neural network model was better than the logistic regression model in terms of sensitivity and accuracy(98.0%vs 58.1%,P=0.034;88.4%vs 86.8%,P<0.001,respectively).Among the 249 SRCC patients,LNM was more common in mixed(35.06%)rather than in pure SRCC(8.42%,P<0.001).The area under the ROC curve of the logistic regression model for LNM in SRCC was 0.760(95%CI:0.682-0.843),while the area under the operating characteristic curve of the internal validation set was 0.734(95%CI:0.643-0.826).The subgroups analysis of pure types showed that LNM was more common in patients with a tumor size>2 cm(OR=5.422,P=0.038).CONCLUSION A validated prediction model was developed to recognize the risk of LNM in EGC and early gastric SRCC,which can aid in pre-surgical decision making of the best method of treatment for patients.

Advantage of log odds of positive lymph nodes in prognostic evaluation of patients with early-onset colon cancer

BACKGROUND Colon cancer(CC)is one of the most common cancers of the digestive tract,the third most common cancer worldwide,and the second most common cause of cancer-related deaths.Previous studies have demonstrated a higher risk of lymph node metastasis(LNM)in young patients with CC.It might be reasonable to treat patients with early-onset locally advanced CC with extended lymph node dissection.However,few studies have focused on early-onset CC(ECC)patients with LNM.At present,the methods of predicting and evaluating the prognosis of ECC patients with LNM are controversial.From the data of patients with CC obtained from the Surveillance,Epidemiology,and End Results(SEER)database,data of young patients with ECC(≤50 years old)was screened.Patients with unknown data were excluded from the study,while the remaining patients were included.The patients were randomly divided into a training group(train)and a testing group(test)in the ratio of 7:3,while building the model.The model was constructed by the training group and verified by the testing group.Using multiple Cox regression models to compare the prediction efficiency of LNM indicators,nomograms were built based on the best model selected for overall survival(OS)and cause-specific survival(CSS).In the two groups,the performance of the nomogram was evaluated by constructing a calibration plot,time-dependent area under the curve(AUC),and decision curve analysis.Finally,the patients were grouped based on the risk score predicted by the prognosis model,and the survival curve was constructed after comparing the survival status of the high and low-risk groups.RESULTS Records of 26922 ECC patients were screened from the SEER database.N classification,positive lymph nodes(PLN),lymph node ratio(LNR)and log odds of PLN(LODDS)were considered to be independent predictors of OS and CSS.In addition,independent risk factors for OS included gender,race,marital status,primary site,histology,grade,T,and M classification,while the independent prognostic factors for CSS included race,marital status,primary site,grade,T,and M classification.The prediction model including LODDS is composed of minimal Akaike information criterion,maximal concordance indexes,and AUCs.Factors including gender,race,marital status,primary site,histology,grade,T,M classification,and LODDS were integrated into the OS nomogram,while race,marital status,primary site,grade,T,M classification,and LODDS were included into the CSS nomogram.The nomogram representing both cohorts had been successfully verified in terms of prediction accuracy and clinical practicability.CONCLUSION LODDS is superior to N-stage,PLN,and LNR of ECC.The nomogram containing LODDS might be helpful in tumor evaluation and clinical decision-making,since it provides an appropriate prediction of ECC.

Computed tomography and magnetic resonance imaging evaluation of lymph node metastasis in early colorectal cancer

AIM: To assess the role of computed tomography(CT) and magnetic resonance imaging(MRI) and establish imaging criteria of lymph node metastasis in early colorectal cancer.METHODS: One hundred and sixty patients with early colorectal cancer were evaluated for tumor location, clinical history of polypectomy, depth of tumor invasion, and lymph node metastasis. Two radiologists assessed preoperative CT and/or MRI for the primary tumor site detectability, the presence or absence of regional lymph node, and the size of the largest lymph node. Demographic, imaging, and pathologic findings were compared between the two groups of patients based on pathologic lymph node metastasis and optimal size criterion was obtained.RESULTS: The locations of tumor were ascending, transverse, descending, sigmoid colon, and rectum. One hundred and sixty early colorectal cancers were classified into 3 groups based on the pathological depth of tumor invasion; mucosa, submucosa, and depth unavailable. A total of 20(12.5%) cancers with submucosal invasion showed lymph node metastasis. Lymph nodes were detected on CT or MRI in 53 patients. The detection rate and size of lymph nodes were significantly higher(P = 0.000, P = 0.044, respectively) in patients with pathologic nodal metastasis than in patients without nodal metastasis. Receiver operating curve analysis showed that a cut-off value of 4.1 mm is optimal with a sensitivity of 78.6% and specificity of 75%.CONCLUSION: The short diameter size criterion of≥ 4.1 mm for metastatic lymph nodes was optimal for nodal staging in early colorectal cancer.

Progress in the Study of Lymph Node Metastasis in Early-stage Cervical Cancer

Spread into regional lymph node is the major route of metastasis in cervical cancer. Although lymph node status is not involved in the International Federation of Gynecology and Obstetrics staging system of uterine cervical cancer, the presence or absence of lymph node metastasis provides important information for prognosis and treatment. In this review, we have attempted to focus on the incidence and patterns of lymph node metastasis, and the issues surrounding surgical assessment of lymph nodes. In addition, the preoperative prediction of lymph node status, as well as the intraoperative assessment by sentinel nodes will be reviewed. Finally, lymph node micrometastasis also will be discussed.

Feasibility of endoscopic treatment and predictors of lymph node metastasis in early gastric cancer

BACKGROUND Endoscopic submucosal dissection (ESD) has been routinely performed in applicable early gastric cancer (EGC) patients as an alternative to conventional surgical operations that involve lymph node dissection. The indications for ESD have been recently expanded to include larger, ulcerated, and undifferentiated mucosal lesions, and differentiated lesions with slight submucosal invasion. The risk of lymph node metastasis (LNM) is the most important consideration when deciding on a treatment strategy for EGC. Despite the advantages over surgical procedures, lymph nodes cannot be removed by ESD. In addition, whether patients who meet the expanded indications for ESD can be managed safely remains controversial. AIM To determine whether the ESD indications are applicable to Chinese patients and to investigate the predictors of LNM in EGC. METHODS We retrospectively analyzed 12552 patients who underwent surgery for gastric cancer between June 2007 and December 2018 at the Affiliated Hospital of Qingdao University. A total of 1262 (10.1%) EGC patients were eligible for inclusion in this study. Data on the patients’ clinical, endoscopic, and histopathological characteristics were collected. The absolute and expanded indications for ESD were validated by regrouping the enrolled patients and determining the positive LNM results in each subgroup. Predictors of LNM in patients were evaluated by univariate and multivariate analyses. RESULTS LNM was observed in 182 (14.4%) patients. No LNM was detected in the patients who met the absolute indications (0/90). LNM occurred in 4/311 (1.3%) patients who met the expanded indications. According to univariate analysis, LNM was significantly associated with positive tumor marker status, medium (20-30 mm) and large (>30 mm) lesion sizes, excavated macroscopic-type tumors, ulcer presence, submucosal invasion (SM1 and SM2), poor differentiation, lymphovascular invasion (LVI), perineural invasion, and diffuse and mixed Lauren’s types. Multivariate analysis demonstrated SM1 invasion (odds ration [OR]= 2.285, P = 0.03), SM2 invasion (OR = 3.230, P < 0.001), LVI (OR = 15.702, P < 0.001), mucinous adenocarcinoma (OR = 2.823, P = 0.015), and large lesion size (OR = 1.900, P = 0.006) to be independent risk factors. CONCLUSION The absolute indications for ESD are reasonable, and the feasibility of expanding the indications for ESD requires further investigation. The predictors of LNM include invasion depth, LVI, mucinous adenocarcinoma, and lesion size.

Prediction of lymph node metastasis and sentinel node navigation surgery for patients with early-stage gastric cancer

Accurate prediction of lymph node(LN) status is crucially important for appropriate treatment planning in patients with early gastric cancer(EGC). However,consensus on patient and tumor characteristics associated with LN metastasis are yet to be reached. Through systematic search,we identified several independent variables associated with LN metastasis in EGC,which should be included in future research to assess which of these variables remain as significant predictors of LN metastasis. On the other hand,even if we use these promising parameters,we should realize the limitation and the difficulty of predicting LN metastasis accurately. The sentinel LN(SLN) is defined as first possible site to receive cancer cells along the route of lymphatic drainage from the primary tumor. The absence of metastasis in SLN is believed to correlate with the absence of metastasis in downstream LNs. In this review,we have attempted to focus on several independent parameters which have close relationship between tumor and LN metastasis in EGC. In addition,we evaluated the history of sentinel node navigation surgery and the usefulness for EGC.

Significance and prognostic value of increased serum direct bilirubin level for lymph node metastasis in Chinese rectal cancer patients

AIM: To determine the significance of increased serum direct bilirubin level for lymph node metastasis(LNM) in Chinese rectal cancer patients, after those with known hepatobiliary and pancreatic diseases were excluded.METHODS: A cohort of 469 patients, who were treated at the China-Japan Friendship Hospital, Ministry of Health(Beijing, China), in the period from January 2003 to June 2011, and with a pathological diagnosis of rectal adenocarcinoma, were recruited. They included 231 patients with LNM(49.3%) and 238 patients without LNM. Follow-up for these patients was taken through to December 31, 2012.RESULTS: The baseline serum direct bilirubin concentration was(median/inter-quartile range) 2.30/1.60-3.42 μmol/L. Univariate analysis showed that compared with patients without LNM, the patients with LNM had an increased level of direct bilirubin(2.50/1.70-3.42 vs 2.10/1.40-3.42, P = 0.025). Multivariate analysis showed that direct bilirubin wasindependently associated with LNM(OR = 1.602; 95%CI: 1.098-2.338, P = 0.015). Moreover, we found that:(1) serum direct bilirubin differs between male and female patients; a higher concentration was associated with poor tumor classification;(2) as the baseline serum direct bilirubin concentration increased, the percentage of patients with LNM increased; and(3) serum direct bilirubin was associated with the prognosis of rectal cancer patients and higher values indicated poor prognosis.CONCLUSION: Higher serum direct bilirubin concentration was associated with the increased risk of LNM and poor prognosis in our rectal cancers.

Construction and external validation of a nomogram that predicts lymph node metastasis in early gastric cancer patients using preoperative parameters

Objective: To create a nomogram to predict the incidence of lymph node metastasis(LNM) in early gastric cancer(EGC) patients and to externally validate the nomogram.Methods: To construct the nomogram,we retrospectively analyzed a primary cohort of 272 EGC patients.Univariate analysis and a binary logistic regression were performed.A nomogram predicting the incidence of LNM in EGC patients was created.The discrimination ability of the nomogram was measured using the concordance index(c-index),and the nomogram was also calibrated.Then,another prospective cohort of 81 patients was analyzed to validate the nomogram.Results: In the primary cohort,LNM was pathologically confirmed in 37(13.6%) patients.In multivariate analysis,the presence of an ulcer,the maximum lesion diameter observed via gastroscopy,the thickness of the lesion observed via endoscopic ultrasonography,and the presence of enlarged lymph nodes on computed tomography(CT) were independent risk factors for LNM.A nomogram was then created based on the regression model with the c-index of 0.905,and the calibration curve of the nomogram fell approximately on the ideal 45-degree line.The cut-off score of the nomogram was 110,and the sensitivity,specificity,positive predictive and negative predictive values of the nomogram in the primary cohort were 81.1%,86.0%,47.6% and 96.7%,respectively,and in the prospective validation cohort were 75.0%,91.0%,60.0% and 95.5%,respectively.The calibration curve of the external validation cohort was almost on the 45-degree line.Conclusions: We developed an effective nomogram predicting the incidence of LNM for EGC patients.

Prognostic value of lymph node metastasis in patients with T1-stage colorectal cancer from multiple centers in China

AIM To explore the features and prognostic value of lymph node metastasis in patients with T1-stage colorectal cancer(CRC).METHODS In all,321 cases of T1-stage CRC were selected from 10132 patients with CRC who received surgical therapy in six large-scale hospitals in China and were retrospectively analyzed. Univariate and multivariate analyses were performed to analyze the risk factors for lymphatic metastasis. A survival analysis was then performed to analyze the prognostic value of lymph node metastasis.RESULTS The occurrence rate of T1 stage was 3.17%(321/10132);of these patients,the lymph node metastasis rate was 8.41%(27/321),and the non-lymph node metastasis rate was 91.59%(294/321). Univariate analysis showed that preoperative serum CEA,preoperative serum CA199,preoperative serum CA724,vascular invasion,and degree of differentiation were associated with lymph node metastasis in T1-stage CRC(P < 0.05 for all). Multivariate analysis indicated that preoperative serum CA724,vascular invasion,and degree of differentiation were closely related to lymph node metastasis(P < 0.05 for all). Log-rank survival analysis showed that age,preoperative serum CEA,preoperative serum CA199,vascular invasion,degree of differentiation,and lymph node metastasis(χ2 = 24.180,P < 0.001) were predictors of 5-year overall survival(OS)(P < 0.05 for all). COX regression analysis demonstrated that preoperative serum CA199 and lymph node metastasis(HR = 5.117;P < 0.05;95%CI: 0.058-0.815) were independent prognostic indicators of 5-year OS in patients with T1-stage CRC(P < 0.05 for both). CONCLUSION The morbidity of T1-stage CRC was 3.17% for all CRC cases. Preoperative serum CA724,vascular invasion,and degree of differentiation are independent risk factors for lymph node metastasis. Lymph node metastasis is an independent prognostic factor for OS in patients with T1-stage CRC.

Comparison of DWI and PET/CT in evaluation of lymph node metastasis in uterine cancer

AIM: To investigate diffusion-weighted imaging (DWI) and positron emission tomography and computed tomography (PET/CT) with Ⅳ contrast for the preoperative evaluation of pelvic lymph node (LN) metastasis in uterine cancer. METHODS: Twenty-five patients with endometrial or cervical cancer who underwent both DWI and PET/CT before pelvic lymphadenectomy were included in this study. For area specific analysis, LNs were divided into eight regions: both common iliac, external iliac, internal iliac areas, and obturator areas. The classification for malignancy on DWI was a focally abnormal signal intensity in a location that corresponded to the LN chains on the T1WI and T2WI. The criterion for malignancy on PET/CT images was increased tracer uptake by the LN.RESULTS: A total of 36 pathologically positive LN areas were found in 9 patients. With DWI, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy for detecting metastatic LNs on an LN area-by-area analysis were 83.3%, 51.2%, 27.3%, 93.3% and 57.0%, respectively, while the corresponding values for PET/CT were 38.9%, 96.3%, 70.0%, 87.8% and 86.0%. Differences in sensitivity, specificity and accuracy were significant (P < 0.0005). CONCLUSION: DWI showed higher sensitivity and lower specificity than PET/CT. Neither DWI nor PET/CT were sufficiently accurate to replace lymphadenectomy.

Risk of lymph node metastasis in mixed-type early gastric cancer determined by the extent of the poorly differentiated component

AIM: To predict the rate of lymph node(LN) metastasis in diffuse- and mixed-type early gastric cancers(EGC) for guidelines of the treatment.METHODS: We reviewed 550 cases of EGC withdiffuse- and mixed-type histology. We investigated the clinicopathological factors and histopathological components that influence the probability of LN metastasis, including sex, age, site, gross type, presence of ulceration, tumour size, depth of invasion, perineural invasion, lymphovascular invasion, and LN metastasis status. We reviewed all slides and estimated the proportions of each tumour component; pure diffuse type, mixed-predominantly diffuse type(diffuse > intestinal type), mixed-predominantly intestinal type(intestinal > diffuse type), and mixed diffuse = intestinal type. We calculated the extents of the respective components.RESULTS: LN metastasis was observed in 12.9%(71/550) of early gastric cancers cases [15/288 mucosal EGCs(5.2%) and 56/262 submucosal EGCs(21.4%)]. Of 550 cases, 302 were diffuse-type and 248 were mixed-type EGCs. Of 248 mixed-type EGCs, 163 were mixed-predominantly diffuse type, 82 were mixed-predominantly intestinal type, and 3 were mixed diffuse = intestinal type. Mixed-type cases with predominantly diffuse type histology showed a higher frequency of LN metastasis(20.2%) than cases of pure diffuse type(9.3%) and predominantly intestinal type(12.2%) histology. We measured the dimensions of each component(intestinal and diffuse type) to determine the association of the extent of each component with LN metastasis in mixed-type gastric carcinoma. The total tumour size and the extent of poorly differentiated components was associated with LN metastasis, while that of signet ring cell components was not.CONCLUSION: We recommend careful identification and quantitative evaluation of mixed-type early gastric cancer components after endoscopic resection to determine the intensity of the treatment.