Objective:To explore and establish an artificial neural network (ANN) model for predicting the efficacy of first-line FOLFOX chemotherapy for metastatic colorectal cancer.Methods:A set of FOLFOX chemotherapy data from a group of patients with metastatic colorectal cancer (mCRC) (GSE104645) was downloaded from the GEO database as a training set. According to the FOLFOX protocol, the efficacy was divided into two groups: the chemo-sensitive group (including complete response and partial response) and the chemo-resistant group (including stable disease and progressive disease), including 31 cases in the sensitive group and 23 in the resistant group. Then, chip data (accessible number: GSE69657) from Fujian Medical University Union Hospital were chosen as a test set. A total of 30 patients were enrolled in the study, including 13 in the sensitive group and 17 in the resistant group. The batch effect correction was performed on the expression values of the two sets of matrices using the R 3.5.1 software Combat package. The gene expression difference of sensitive and resistant group in GSE104645 was analyzed by the GEO2R platform. P<0.05 and the absolute value of log 2FC>0.33 (FC abbreviation of fold change) were used as the threshold value to screen the drug resistance and sensitive genes of the FOLFOX regimen. An ANN was constructed using the multi-layer perceptron (MLP) to perform the FOLFOX regimen on the GSE104645 dataset. The GSE69657 expression matrix and clinical efficacy parameters were then used for retrospective verification. Receiver operating characteristic(ROC) curves were used to evaluate the test results and predictive power. Results:A total of 2, 076 differentially expressed genes in GSE104645 were selected, of which 822 genes were up-regulated and 1, 254 genes were down-regulated in the chemo-resistance group. The down-regulated genes were sensitive genes. GO analysis of the biological processes in which the differentially expressed genes were involved, revealed that they were mainly involved in the regulation of substance metabolism. A total of 39 genes were included in the final model construction. This was a neural network model with two hidden layers. The accuracy of predicting training samples and test samples was 75.7% and 76.5%, respectively, and the area under the ROC curve was 0.875. The chip data set of our department (GSE69657) was set as the test set, and the area under the ROC curve was 0.778.Conclusions:In this study, an artificial neural network model is successfully constructed to predict the efficacy of first-line FOLFOX regimen for metastatic colorectal cancer based on the microarray, and an independent external verification is also conducted. The model has good stability and well prediction efficiency. Besides, the results of this study suggest that the gene functions related to oxaliplatin resistance are mainly enriched in the regulation process of substance metabolism.

Objective:To explore and establish an artificial neural network (ANN) model for predicting the efficacy of first-line FOLFOX chemotherapy for metastatic colorectal cancer.Methods:A set of FOLFOX chemotherapy data from a group of patients with metastatic colorectal cancer (mCRC) (GSE104645) was downloaded from the GEO database as a training set. According to the FOLFOX protocol, the efficacy was divided into two groups: the chemo-sensitive group (including complete response and partial response) and the chemo-resistant group (including stable disease and progressive disease), including 31 cases in the sensitive group and 23 in the resistant group. Then, chip data (accessible number: GSE69657) from Fujian Medical University Union Hospital were chosen as a test set. A total of 30 patients were enrolled in the study, including 13 in the sensitive group and 17 in the resistant group. The batch effect correction was performed on the expression values of the two sets of matrices using the R 3.5.1 software Combat package. The gene expression difference of sensitive and resistant group in GSE104645 was analyzed by the GEO2R platform. P<0.05 and the absolute value of log 2FC>0.33 (FC abbreviation of fold change) were used as the threshold value to screen the drug resistance and sensitive genes of the FOLFOX regimen. An ANN was constructed using the multi-layer perceptron (MLP) to perform the FOLFOX regimen on the GSE104645 dataset. The GSE69657 expression matrix and clinical efficacy parameters were then used for retrospective verification. Receiver operating characteristic(ROC) curves were used to evaluate the test results and predictive power. Results:A total of 2, 076 differentially expressed genes in GSE104645 were selected, of which 822 genes were up-regulated and 1, 254 genes were down-regulated in the chemo-resistance group. The down-regulated genes were sensitive genes. GO analysis of the biological processes in which the differentially expressed genes were involved, revealed that they were mainly involved in the regulation of substance metabolism. A total of 39 genes were included in the final model construction. This was a neural network model with two hidden layers. The accuracy of predicting training samples and test samples was 75.7% and 76.5%, respectively, and the area under the ROC curve was 0.875. The chip data set of our department (GSE69657) was set as the test set, and the area under the ROC curve was 0.778.Conclusions:In this study, an artificial neural network model is successfully constructed to predict the efficacy of first-line FOLFOX regimen for metastatic colorectal cancer based on the microarray, and an independent external verification is also conducted. The model has good stability and well prediction efficiency. Besides, the results of this study suggest that the gene functions related to oxaliplatin resistance are mainly enriched in the regulation process of substance metabolism.

Objective: To screen out the potential gene biomarkers to predict responses to neoadjuvant chemoradiotherapy (CRT) in patients with rectal cancer and to explore the main downstream pathways of resistance. Methods: The gene expression profiles (GSE35452) of locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy from 46 specimens (24 responders, TRG 0/1, and 22 non-responders, TRG 2/3) were downloaded from the GEO database. The differentially expressed genes were identified to screen out the potential biomarkers by use of the GCBI platform. GO and KEGG pathways enrichment analysis were performed to integrate enrichment results of differentially expressed genes. Signal-signal interaction network was constructed and analyzed to screen out potential main downstream pathways. Results: A total of 1079 differentially expressed genes were screened, including 657 up-regulated and 422 down-regulated ones. Among these genes, REG4 had the maximum fold change value of -6.029 491. In GO term, these differentially expressed genes were mainly enriched in molecule metabolic process, cell cycle, DNA-dependent transcription, signal transduction and apoptotic process. The KEGG pathways enrichment analysis showed that the differentially expressed genes were enriched in 65 KEGG pathways, including metabolic pathways, cell cycle and metabolism pathways. Signal-signal interaction network analysis showed that MAPK signaling pathway and cell cycle pathway might play a determinant role in the development of neoadjuvant chemoradiotherapy resistance. Further analysis showed that CDKN1B, CDKN2A, RBL1, TFDP1, CCND2, CCNE2, CDC6 and CDK6 in cell cycle might induce chemoradiotherapy resistance by blocking G1/S phase cell cycle arrest, decreasing the apoptosis of tumor cells and increasing S phase ratio of chemoradiotherapy resistance. Conclusion G1/S phase cell cycle arrest blocking plays an important role in the development of chemoradiotherapy resistance in patients with rectal cancer. Moreover, the key genes, such as REG4, may be useful in predicting responses to neoadjuvant chemoradiotherapy.

Objective To investigate the effects of the number of harvested lymph nodes in neoadjuvant chemoradiotherapy (nCRT) combined with surgery on prognosis of middle-low rectal cancer.Methods The retrospective case-control study was conducted.The clinicopathological data of 373 patients with middle-low rectal cancer who underwent nCRT combined with surgery in the Fujian Medical University Union Hospital from January 2009 to December 2013 were collected.There were 241 males and 132 females,aged from 26 to 81 years,with the age of (55 ± 11) years.Observation indicators:(1) treatment situations;(2) follow-up and survival;(3)influencing factors for the number of harvested lymph nodes;(4) prognostic analysis of the different number of harvested lymph nodes as cut-off for grouping;(5) stratified analysis.Follow-up using telephone interview and outpatient examination was performed to detect postoperative survival of patients once every three months within postoperative 2 years and once every 6 months during the postoperative third year up to March 2016.The endpoint of follow-up was tumor recurrence,retastasis or death.Measurement data with normal distribution were represented as Mean±SD,and comparison between groups was done using the independent sample t test.Measurement data with skewed distribution were represented as M (range),and comparison between groups was done using the Kruska1-Wallis H test.Count data was described as absolute numbers.Univariate and multivariate analyses were done by the multiple linear regression model.Survival rate was calculated by the Kaplan-Meier method,and Logrank test was used for survival analysis.Results (l) Treatment situations:373 patients underwent nCRT combined with surgery,including 329 combined with sphincter-sparing rectal resection and 44 combined with abdominoperineal rectal resection.The number of harvested lymph nodes was 12 ± 6 in 373 patients.There were 185 patients with the number of harvested lymph nodes ＜ 12 and 188 with the number of harvested lymph nodes ≥ 12.(2) Follow-up and survival:373 patients were followed up for 5-77 months,with a median follow-up time of 43 months.During the follow-up,the 1-,3-,5-year disease-free survival rates were respectively 90.4％,76.3％,and 67.5％ in the 373 patients.(3) Influencing factors for the number of harvested lymph nodes:univariate analysis showed that distance between the tumor and anal verge,tumor diameter,tumor pathological N staging,and regression grade of rectal cancer were associated factors for the number of harvested lymph nodes (t =3.156,2.992,x2=8.183,10.839,P＜0.05).Multivariate analysis showed that distance between the tumor and anal verge,regression grade of rectal cancer,and tumor pathological N staging were independent factors for the number of harvested lymph nodes (t=3.308,2.690,2.584,95％ confidence interval:0.808-3.180,0.446-2.873,0.332-2.448,P＜0.05).(4) Prognostic analysis of the different number of harvested lymph nodes as cut-off for grouping:with the number of harvested lymph nodes of 6,7,8,9,10,11,12,13,14,15,and 16 as cut-off for grouping,there was no significant difference in the 3-year disease-free survival rate,cumulative local recurrence rate,and cumulative distant metastasis rate between ＜6 group and ≥6 group,between ＜7 group and ≥7 group,between＜8 group and ≥8 group,between ＜9 group and ≥9 group,between ＜10 group and ≥ 10 group,between ＜11 group and ≥ll group,between ＜12 group and ≥12 group,between ＜13 group and ≥13 group,between ＜ 14 group and ≥ 14 group,between ＜ 15 group and ≥ 15 group,between ＜ 16 group and ≥ 16 group,respectively (P＞0.05).(5) Stratified analysis:with the number of harvested lymph nodes of 7,8,9,and 10 as cut-off for grouping in 45 of 373 patients with Ⅱ-Ⅲ regression grade of rectal cancer and negative lymph nodes (NO staging),there was no significant difference in the 3-year disease-free survival rate between ＜7 group and ≥ 7group,between ＜8 group and ≥8 group,between ＜9 group and ≥9 group,between＜10 group and ≥ 10 group,respetively (x2 =3.946,5.346,6.375,4.297,P＜0.05).Conclusions The number of lymph nodes as 12 is not the independent factor for prognosis of patients with middle-low rectal cancer after nCRT combined with surgery.The number of harvested lymph nodes as 7 to 10 is the important factor for evaluating the prognosis of middle-low rectal cancer patients with Ⅱ-Ⅲ regression grade of rectal cancer and negative lymph nodes after nCRT combined with surgery.

OBJECTIVE: To explore the efficacy of radiotherapy combined with surgery for locally advanced rectal mucinous adenocarcinoma. METHODS: Clinical data of patients with locally advanced rectal mucinous adenocarcinoma (T3-4 and/or N+) diagnosed by postoperative pathology from 1992 to 2013 were retrieved from the US Surveillance, Epidemiology, and End Results (SEER) database. Patients with local excision only, tumor biopsy or combined organ excision and incomplete follow-up information were excluded. All the enrolled patients were divided into three groups according to different treatments, including surgery alone (SA) group, preoperative radiotherapy combined with surgery (RT+S) group and surgery combined with postoperative radiotherapy (S+RT) group. The extracted data included basic data of patients and tumor, treatment status, and follow-up results. The χ² test was used to compare the count data. Kaplan-Meier method was used to draw the survival curve and calculate the survival rate. The survival was analyzed and compared by Log-rank test. The R language 2.8.1 was used to match the patients as 1:1 pairing through the propensity score matching (PSM). The matching variables included gender, age at diagnosis, year at diagnosis, ethnicity, degree of tissue differentiation, TNM stage, depth of invasion, making the baseline data of subgroups comparable. The Cox proportional hazard model was used for multivariate analysis of prognostic factors. RESULTS: A total of 2 149 patients with locally advanced rectal mucinous adenocarcinoma were enrolled in the study, including 1 255 males (58.4%) and 894 females (41.6%). There were 706 patients (32.9%) in the SA group, 772 patients (35.9%) in the RT+S group and 671 patients (31.2%) in the S+RT group. In SA, RT+S and S+RT groups, the median overall survival time was 39, 85, and 74 months respectively; the 5-year overall survival (OS) rate was 38.7%, 56.5%, and 55.2% respectively; the median cancer-specific survival (CSS) time was 86, 127, and 111 months respectively, and the 5-year CSS rate was 53.7%, 62.2% and 60.7% respectively. In comparison among the 3 groups, the 5-year OS rate and CSS rate in the SA group were significantly lower than those in the RT+S group and S+RT group (all P<0.001); the 5-year OS rate and CSS rate between RT+S group and S+RT group were not significantly different (P=0.166 and 0.392,respectively). After the baseline data of subgroups were corrected through PSM, the 5-year OS rate and CSS rate in the SA group (n=375) were significantly lower than those in the RT+S group (n=375)(OS:40.1% vs. 54.5%, P<0.001; CSS:54.3% vs. 63.3%, P=0.023). The 5-year OS rate and CSS rate in the SA group (n=403) were also lower than those in the S+RT group (n=403) (OS:37.4% vs. 54.7%,P<0.001;CSS:51.6% vs. 61.0%,P=0.031). The 5-year OS rate and CSS rate between RT+S group (n=363) and S+RT group (n=363) were not significantly different (OS:51.7% vs. 55.5%, P=0.789; CSS:57.7% vs. 60.5%, P=0.484). Cox multivariate analysis showed that radiotherapy (HR=0.845, 95%CI: 0.790 to 0.903, P=0.001) was an independent prognostic factor for OS of locally advanced rectal mucinous adenocarcinoma; radiotherapy (HR=0.907, 95% CI: 0.835 to 0.985, P=0.021) was also an independent prognostic factor affecting CSS in patients with locally advanced rectal mucinous adenocarcinoma. CONCLUSION As compared with surgery alone, surgery combined with preoperative or postoperative radiotherapy is beneficial to the long-term survival of patients with locally advanced rectal mucinous adenocarcinoma.
Adenocarcinoma, Mucinous ; pathology ; radiotherapy ; surgery ; therapy ; Female ; Humans ; Male ; Neoplasm Staging ; Proctectomy ; Prognosis ; Radiotherapy, Adjuvant ; Rectal Neoplasms ; pathology ; radiotherapy ; surgery ; therapy ; Retrospective Studies ; SEER Program ; Survival Analysis ; Treatment Outcome

Objective To screen out the potential gene biomarkers to predict responses to neoadjuvant chemoradiotherapy (CRT) in patients with rectal cancer and to explore the main downstream pathways of resistance. Methods The gene expression profiles (GSE35452) of locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy from 46 specimens (24 responders, TRG 0/1, and 22 non?responders, TRG 2/3) were downloaded from the GEO database. The differentially expressed genes were identified to screen out the potential biomarkers by use of the GCBI platform. GO and KEGG pathways enrichment analysis were performed to integrate enrichment results of differentially expressed genes. Signal?signal interaction network was constructed and analyzed to screen out potential main downstream pathways. Results A total of 1079 differentially expressed genes were screened, including 657 up?regulated and 422 down?regulated ones. Among these genes, REG4 had the maximum fold change value of –6.029 491. In GO term, these differentially expressed genes were mainly enriched in molecule metabolic process, cell cycle, DNA?dependent transcription, signal transduction and apoptotic process. The KEGG pathways enrichment analysis showed that the differentially expressed genes were enriched in 65 KEGG pathways, including metabolic pathways, cell cycle and metabolism pathways. Signal?signal interaction network analysis showed that MAPK signaling pathway and cell cycle pathway might play a determinant role in the development of neoadjuvant chemoradiotherapy resistance. Further analysis showed that CDKN1B, CDKN2A, RBL1, TFDP1, CCND2, CCNE2, CDC6 and CDK6 in cell cycle might induce chemoradiotherapy resistance by blocking G1/S phase cell cycle arrest, decreasing the apoptosis of tumor cells and increasing S phase ratio of chemoradiotherapy resistance. Conclusion G1/S phase cell cycle arrest blocking plays an important role in the development of chemoradiotherapy resistance in patients with rectal cancer. Moreover, the key genes, such as REG4, may be useful in predicting responses to neoadjuvant chemoradiotherapy.

Objective To screen out the potential gene biomarkers to predict responses to neoadjuvant chemoradiotherapy (CRT) in patients with rectal cancer and to explore the main downstream pathways of resistance. Methods The gene expression profiles (GSE35452) of locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy from 46 specimens (24 responders, TRG 0/1, and 22 non?responders, TRG 2/3) were downloaded from the GEO database. The differentially expressed genes were identified to screen out the potential biomarkers by use of the GCBI platform. GO and KEGG pathways enrichment analysis were performed to integrate enrichment results of differentially expressed genes. Signal?signal interaction network was constructed and analyzed to screen out potential main downstream pathways. Results A total of 1079 differentially expressed genes were screened, including 657 up?regulated and 422 down?regulated ones. Among these genes, REG4 had the maximum fold change value of –6.029 491. In GO term, these differentially expressed genes were mainly enriched in molecule metabolic process, cell cycle, DNA?dependent transcription, signal transduction and apoptotic process. The KEGG pathways enrichment analysis showed that the differentially expressed genes were enriched in 65 KEGG pathways, including metabolic pathways, cell cycle and metabolism pathways. Signal?signal interaction network analysis showed that MAPK signaling pathway and cell cycle pathway might play a determinant role in the development of neoadjuvant chemoradiotherapy resistance. Further analysis showed that CDKN1B, CDKN2A, RBL1, TFDP1, CCND2, CCNE2, CDC6 and CDK6 in cell cycle might induce chemoradiotherapy resistance by blocking G1/S phase cell cycle arrest, decreasing the apoptosis of tumor cells and increasing S phase ratio of chemoradiotherapy resistance. Conclusion G1/S phase cell cycle arrest blocking plays an important role in the development of chemoradiotherapy resistance in patients with rectal cancer. Moreover, the key genes, such as REG4, may be useful in predicting responses to neoadjuvant chemoradiotherapy.

Objective To screen out the potential gene to predict regional lymph node metastasis after neoadjuvant chemoradiotherapy (CRT) for locally advanced rectal cancer (LARC) and develop a 6-gene model using an artificial neural network (ANN).Methods The gene expression profiles (GSE46862) of locally advanced rectal cancer undergoing preoperative chemoradiotherapy from 64 specimens (21 with ypN-and 43 with ypN+) were downloaded from the gene expression omnibus (GEO) database.The differentially expressed genes were identified to screen out the potential biomarkers through the Gene-Cloud of Biotechnology Information (GCBI) platform.The top 6 genes were screened out for building model.An ANN model was trained and validated using the SPSS Modeler software.The study samples were allocated randomly into the training sample group and testing sample group with a 7∶3 ratio.The training samples and testing samples were respectively used for building an ANN model and independent back-substitution test.Observation indicators:(1) screening results of differentially expressed genes;(2) analysis results of ANN model.The receiver operating characteristic (ROC) curve was drawn and the area under the curve (AUC) was calculated to evaluate the predictive abilities of ANN and each biomarker.Results (1) Screening results of differentially expressed genes:A total of 50 genes were screened.Six top genes included IL6,AKR1B1,AREG,SELE,ROBO1 and CD274.(2) Analysis results of ANN model:Six top genes were selected to construct a three-layer ANN model with a 7-5-2 structure.The IL6 made the greatest effect on the ANN model,followed by ROBO1,AKR1B1,AREG,CD274 and SELE.The AUC was 0.929.The sensitivity and specificity of ANN model were 96.7％ and 85.7％,and accuracy of training samples was 93.2％.In the independent back-substitution test,sensitivity and specificity were 92.3％ and 85.7％,and accuracy of testing samples was 90.0％.Conclusion The prediction ANN model based on multiple molecular markers (IL6,ROBO1,AKR1B1,AREG,CD274 and SELE) for regional lymph node metastases in LARC patients after CRT would be beneficial in selecting potential candidates for rectum-preserving surgery following CRT for LARC.

OBJECTIVETo establish a nomogram to predict long-term survival in non-metastatic colorectal cancer patients.

METHODSA retrospective analysis was conducted in patients with non-metastatic colorectal cancer who underwent radical surgery in the Department of Colorectal Surgery of Affiliated Union Hospital of Fujian Medical University between January 2000 and December 2014. Univariate and multivariate analyses on disease-free survival (DFS) were performed using the Cox proportional regression model. Based on the multivariate analysis results, a prognostic nomogram was formulated to predict the probability for DFS. Concordance index was applied in predictive evaluation of the nomogram and calibration curves were drawn to test the nomogram's prediction and actual observation of the 5-year DFS rate. The predictive ability of nomogram was compared with AJCC-7 staging system.

RESULTSA total of 2 641 patients were identified. The median age was 59.3 years old, and 60.3% of cases were men. The number of patients with TNM stage 0, I(, II( and III( was 96, 505, 923 and 1043, respectively. The most common tumor site was the rectum, accounting for 43.2%. A total of 413 (15.6%) patients underwent neoadjuvant treatment. The most common gross type of tumor was ulcerative type, accounting for 79.5%. The 3- and 5-year DFS rate was 85.8% and 79.8%, respectively. Based on the Cox proportional regression model, the following six factors were independently associated with reduced DFS rate and were selected for the nomogram: older age, higher pathologic T stage, higher pathologic N stage, higher preoperative serum CEA level, infiltrative gross type and perineural invasion. The results of the nomogram showed that the score of T0, T1, T2, T3 and T4 stage was 0, 2.2, 3.9, 4.1 and 6, respectively, and the score of N0, N1 and N2 was 0, 3.8 and 9.3, respectively. For gross type, the score of expanding type, ulcerative type and infiltrative type was 6, 9 and 10, respectively. The score of perineural invasion was 5.2. Higher scores were added to older age and higher CEA level. The total scores were calculated by taking the sum of the points from all predictors. Higher total score was associated with poor DFS. The prognostic nomogram differentiated well and showed a concordance index of 0.718, which was better than AJCC-7 staging system (concordance index=0.683). Also, the calibration of nomogram predictions was good.

CONCLUSIONSA nomogram based on 6 independently prognostic factors to predict long-term survival in non-metastatic colorectal cancer patients is established successfully. The nomogram can be conveniently used to facilitate the accurate individualized prediction of DFS rates in patients with non-metastatic colorectal cancer.

OBJECTIVETo establish a nomogram model to predict the peritoneal metastasis in colon cancer patients without distant metastasis by preoperative imaging examination.

METHODSClinicopathological data of colon cancer patients without distant metastasis by preoperative imaging examination who underwent surgery in our department between January 2000 and December 2014 were retrospectively analyzed. Predictors of peritoneal carcinomatosis were analyzed by univariate and Logistic multivariate analyses. Base on the independent predictors by multivariable analysis results, a nomogram model was formulated with further use of R software. The total score was calculated by the addition of each predictor score, indicating the corresponding risk of peritoneal metastasis. The score was greater in the nomogram, and the risk was higher in peritoneal implantation metastasis. A receiver operating characteristic(ROC) curve was then constructed to evaluate the predictive abilities of the various preoperative factors and nomogram.

RESULTSA total of 1 417 patients were defined as above and enrolled in the study. The median age was (60.5±13.3) years, 835 cases (58.9%) were male, and 132 cases (9.3%, 132/1417) were diagnosed with synchronous peritoneal carcinomatosis during operation. Univariate analysis showed that peritoneal metastasis was associated with age, incidence of abdominal pain, incidence of mucous bloody stool, CEA level, traversible rate, tumor diameter, ratio of infiltrating type cancer, differentiation, histological type, cT staging and cN staging (all P<0.05). Logistic multivariate analysis revealed that younger age (OR:0.974, 95%CI: 0.958 to 0.990, P=0.001), later clinical T stage (OR: 2.949, 95%CI: 1.588 to 5.476, P=0.001), lesion not traversible(OR: 0.519, 95%CI: 0.314 to 0.858, P=0.011), infiltrative gross type (OR: 1.812, 95%CI: 1.099 to 2.987, P=0.020), larger tumor (OR: 1.044, 95%CI: 0.998 to 1.093, P=0.061), higher preoperative serum CEA level(OR:1.004,95%CI: 1.001 to 1.007, P=0.007) and histopathologic type of mucinous or signet ring cell adenocarcinoma (OR:1.642, 95%CI: 1.009 to 2.673, P=0.046) were independent risk factors. The nomogram model was further established based on above 7 independent risk factors, whose total score was 350 and area under the ROC curve was 0.753(P=0.000).

CONCLUSIONThe nomogram model can be helpful to screen the colon cancer patients with high risk of peritoneal metastasis and to avoid unnecessary laparotomy for colon cancer patients without distant metastasis by preoperative imaging examination.