Purpose Compression of the iliac vein between the iliac artery and lumbosacral vertebra can cause iliac vein compression syndrome (IVCS). The purpose of this study is to assess compression characteristics and establish a new sub-typing in asymptomatic IVCS individuals using contrast-enhanced CT. Methods A retrospective analysis of abdomen contrast-enhanced CT images from 195 asymptomatic subjects with iliac vein compressed was investigated. Patients had no history of venous pathology, and images were collected from June 2018 to January 2019. Qualitative and quantitative characteristics of compression were examined including the location, pattern, minor diameter, area, and the percentage compression on an orthogonal section by the post-processing of multiple planar reconstruction and volume rendering. Results There were 107 females and 88 males with age range 18–92 years. The most common site of iliac vein compression was localized to the left common iliac vein (LCIV) (178/195, 91.3%). Notably, four compression types (type I–IV) were established according to the compression location, with type II being the most common. The four compression types had differences in the upper limit and fluctuation range of compression. It was found that the average level of iliac vein compression was below 25%. The compression degree of the left common iliac vein in type II was relatively concentrated, and the upper limit of compression was close to 70%. Conclusion Asymptomatic iliac vein compression was categorized according to compression location. The proposal of four types might help clinicians to predict which IVCS patients would benefit from interventional therapy.

ObjectiveTo establish a diagnostic model by combining imaging features with enhanced CT texture analysis to differentiate pancreatic serous cystadenomas (SCNs) from pancreatic mucinous cystadenomas (MCNs).Materials and MethodsFifty-seven and 43 patients with pathology-confirmed SCNs and MCNs, respectively, from one center were analyzed and divided into a training cohort (n = 72) and an internal validation cohort (n = 28). An external validation cohort (n = 28) from another center was allocated. Demographic and radiological information were collected. The least absolute shrinkage and selection operator (LASSO) and recursive feature elimination linear support vector machine (RFE_LinearSVC) were implemented to select significant features. Multivariable logistic regression algorithms were conducted for model construction. Receiver operating characteristic (ROC) curves for the models were evaluated, and their prediction efficiency was quantified by the area under the curve (AUC), 95% confidence interval (95% CI), sensitivity and specificity.ResultsFollowing multivariable logistic regression analysis, the AUC was 0.932 and 0.887, the sensitivity was 87.5% and 90%, and the specificity was 82.4% and 84.6% with the training and validation cohorts, respectively, for the model combining radiological features and CT texture features. For the model based on radiological features alone, the AUC was 0.84 and 0.91, the sensitivity was 75% and 66.7%, and the specificity was 82.4% and 77% with the training and validation cohorts, respectively.ConclusionThis study showed that a logistic model combining radiological features and CT texture features is more effective in distinguishing SCNs from MCNs of the pancreas than a model based on radiological features alone.

AIM: To examine fibrinogen-like protein 2 (fgl2) expression during taurocholate-induced acute pancreatitis progression in rats and its correlation with pancreatic injury severity. METHODS: Forty-eight male Sprague-Dawley rats were randomly divided into the severe acute pancreatitis (SAP) group (n = 24) and the sham operation (SO) group (n = 24). Sodium taurocholate (4% at doses of 1 mL/kg body weight) was retrogradely injected into the biliopancreatic ducts of the rats to induce SAP. Pancreatic tissues were prepared immediately after sacrifice. At the time of sacrifice, blood was obtained for determination of serum amylase activity and isolation of peripheral blood mononuclear cells (PBMCs). Pancreatic tissue specimens were obtained for routine light microscopy including hematoxylin and eosin staining, and the severity of pancreatic injury was evaluated 1, 4 and 8 h after induction. Expression of fgl2 mRNA was measured in the pancreas and PBMCs using reverse transcription polymerase chain reaction. Expression of fgl2 protein was evaluated in pancreatic tissues using Western blotting and immunohistochemical staining. Masson staining was also performed to observe microthrombosis. RESULTS: At each time point, levels of fgl2 mRNAs in pancreatic tissues and PBMCs were higher (P < 0.05) in the SAP group than in the SO group. For pancreatic tissue in SAP vs SO, the levels were: after 1 h, 3.911 ± 1.277 vs 1.000 ± 0.673; after 4 h, 9.850 ± 3.095 vs 1.136 ± 0.609; and after 8 h, 12.870 ± 3.046 vs 1.177 ± 0.458. For PBMCs in SAP vs SO, the levels were: after 1 h, 2.678 ± 1.509 vs 1.000 ± 0.965; after 4 h, 6.922 ± 1.984 vs 1.051 ± 0.781; and after 8 h, 13.533 ± 6.575 vs 1.306 ± 1.179. Levels of fgl2 protein expression as determined by Western blotting and immunohistochemical staining were markedly up-regulated (P < 0.001) in the SAP group compared with those in the SO group. For Western blotting in SAP vs SO, the results were: after 1 h, 2.183 ± 0.115 vs 1.110 ± 0.158; after 4 h, 2.697 ± 0.090 vs 0.947 ± 0.361; and after 8 h, 3.258 ± 0.094 vs 1.208 ± 0.082. For immunohistochemical staining in SAP vs SO, the results were: after 1 h, 1.793 ± 0.463 vs 0.808 ± 0.252; after 4 h, 4.535 ± 0.550 vs 0.871 ± 0.318; and after 8 h, 6.071 ± 0.941 vs 1.020 ± 0.406. Moreover, we observed a positive correlation in the pancreas (r = 0.852, P < 0.001) and PBMCs (r = 0.735, P < 0.001) between fgl2 expression and the severity of pancreatic injury. Masson staining showed that microthrombosis (%) in rats with SAP was increased (P < 0.001) compared with that in the SO group and it was closely correlated with fgl2 expression in the pancreas (r = 0.842, P < 0.001). For Masson staining in SAP vs SO, the results were: after 1 h, 26.880 ± 9.031 vs 8.630 ± 3.739; after 4 h, 53.750 ± 19.039 vs 8.500 ± 4.472; and after 8 h, 80.250 ± 12.915 vs 10.630 ± 7.003. CONCLUSION: Microthrombosis due to fgl2 overexpre...

Background: Neoadjuvant chemotherapy (NCT) was developed to improve the prognosis of patients with advanced gastric cancer (AGC). Some studies have confirmed the diagnostic and prognostic value of various serum tumor markers in gastric cancer. However, most of these studies were focused on the value of preoperative and postoperative tumor markers in patients undergoing surgery with or without adjuvant therapy, and only a few studies focused on AGC patients undergoing NCT. Methods:We retrospectively analyzed the data of consecutive patients with histologically confirmed AGC who received NCT prior to surgical resection at Zhejiang Cancer Hospital from January 2010 to September 2018. The prognostic impact of tumor markers before and after NCT, including Carcinoembryonic antigen (CEA), Carbohydrate antigen199 (CA199), Carbohydrate antigen125 (CA125), Alpha-FetoProtein (AFP), Carbohydrate antigen242 (CA242), and Carbohydrate antigen724 (CA724), were evaluated using Kaplan-Meier log-rank survival analysis. The association between tumor marker normalization during preoperative chemotherapy and clinicopathological characteristics was also investigated.Results: Four hundred and seventy-two patients were included in the study. The levels of CEA, CA199, CA125, CA242, and CA724 before NCT could predict prognosis, and the levels of CA199, CA125, CA242, and CA724 after NCT were correlated with prognosis. The overall survival (OS) rate decreased with an increasing number of positive tumor markers before and after preoperative chemotherapy. Tumor marker abnormalization after NCT was not related to chemotherapy, whereas patients with tumor marker normalization after NCT obtained survival benefits.Conclusions: Tumor markers before and after NCT, such as CA199, CA125, CA242, and CA724, have a discriminatory ability for patients with GC. The normalization of tumor markers after NCT was associated with better survival.

Background: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of locally advanced gastric cancer (LAGC). The aim of this study was to identify radio-clinical signatures from pretreatment oversampled computed tomography (CT) images to predict the response to NCT and prognosis of LAGC patients. Methods: LAGC patients were retrospectively recruited from six hospitals from January 2008 to December 2021. An SE-ResNet50-based chemotherapy response prediction system was developed from pretreatment CT images preprocessed with an imaging oversampling method (i.e. DeepSMOTE). Then, the deep learning (DL) signature and clinic-based features were fed into the deep learning radio-clinical signature (DLCS). The predictive performance of the model was evaluated based on discrimination, calibration, and clinical usefulness. An additional model was built to predict overall survival (OS) and explore the survival benefit of the proposed DL signature and clinicopathological characteristics. Results: A total of 1060 LAGC patients were recruited from six hospitals; the training cohort (TC) and internal validation cohort (IVC) patients were randomly selected from center I. An external validation cohort (EVC) of 265 patients from five other centers was also included. The DLCS exhibited excellent performance in predicting the response to NCT in the IVC [area under the curve (AUC), 0.86] and EVC (AUC, 0.82), with good calibration in all cohorts ( P >0.05). Moreover, the DLCS model outperformed the clinical model ( P <0.05). Additionally, we found that the DL signature could serve as an independent factor for prognosis [hazard ratio (HR), 0.828, P =0.004]. The concordance index (C-index), integrated area under the time-dependent ROC curve (iAUC), and integrated Brier score (IBS) for the OS model were 0.64, 1.24, and 0.71 in the test set. Conclusion: The authors proposed a DLCS model that combined imaging features with clinical risk factors to accurately predict tumor response and identify the risk of OS in LAGC patients prior to NCT, which can then be used to guide personalized treatment plans with the help of computerized tumor-level characterization.

Large bowel perforation is an acute abdominal emergency requiring rapid diagnosis for proper treatment. The high mortality rate associated with large bowel perforation underlines the importance of an accurate and timely diagnosis. Computed tomography is useful for diagnosis of ingested foreign bodies, and endoscopic repair using clips can be an effective treatment of colon perforations. We herein describe a 78-year-old man with sigmoid colon perforation caused by accidental swallowing of a jujube pit. The jujube pit had become stuck in the wall of the sigmoid colon and was successfully removed by colonoscopy, avoiding an aggressive surgery. As a result of developments in endoscopic techniques, endoscopic closure has become a feasible option for the management of intestinal perforation.

BACKGROUND Ulcerative colitis (UC) is defined as a chronic inflammatory bowel disease that can occur in any part of the large bowel. In addition, UC affects only the large bowel except for backwash ileitis and pouchitis, whereas Crohn's disease (CD) affects the entire digestive tract. Inflammatory bowel disease (IBD) patients tend to be diagnosed with CD or indeterminate colitis when combined with gastric lesion. However, in recent years, some UC patients are reported to have various degrees of lesions in gastroduodenum. Here, we report a case of gastroduodenitis associated with UC (GDUC). CASE SUMMARY A 25-year-old man with a history of Klippel-Trenaunay syndrome presented to the hospital with mucopurulent bloody stool and epigastric persistent colic pain for 2 wk. Continuous superficial ulcers and spontaneous bleeding were observed under colonoscopy. Subsequent gastroscopy revealed mucosa with diffuse edema, ulcers, errhysis, and granular and friable changes in the stomach and duodenal bulb, which were similar to the appearance of the rectum. After ruling out other possibilities according to a series of examinations, a diagnosis of GDUC was considered. The patient hesitated about intravenous corticosteroids, so he received a standardized treatment with pentasa of 3.2 g/d. After 0.5 mo of treatment, the patient’s symptoms achieved complete remission. Follow-up endoscopy and imaging findings showed no evidence of recurrence for 26 mo. CONCLUSION The occurrence of gastrointestinal involvement in UC is rare, which may open a new window for studying the etiology and pathogenesis of UC. Physicians should consider broad differential diagnosis by endoscopic biopsy and laboratory examinations.

BackgroundThe prognosis of advanced gastric cancer (AGC) patients has attracted much attention, but there is a lack of evaluation method. MRI‐based radiomics has the potential to evaluate AGC patients' prognosis.PurposeTo identify and validate the risk stratification and overall survival (OS) in AGC patients using MRI‐based radiomics.Study TypeRetrospective.SubjectsA total of 233 patients (168 males, 63.6 ± 11.1 years; 65 females, 59.7 ± 11.8 years) confirmed AGC were collected. The data were randomly divided into a training (164) and validation set (69).SequenceA 3.0 T, axial T2‐weighted, diffusion‐weighted imaging, and contrast‐enhanced T1‐weighted (CE‐T1WI).AssessmentRadiologist 1 segmented 233 patients and radiologist 2 segmented randomly 50 patients on CE‐T1WI. The risk score (RS) was summed by each sample based on the radiomics features and correlation coefficients. Patients were followed up for 7–67 months (median 41; 138 dead and 95 alive).Statistical TestsThe intraclass correlation coefficient (ICC) and Kappa value were calculated. Differences in survival analysis were assessed by Kaplan–Meier curves and log‐rank test. Cox‐regression analysis was performed to identify the radiomics features and clinical indicators associated with OS. The calibration curves were built to assess the model. A two‐tailed P value < 0.05 was considered statistically significant.ResultsIntegrated with age, lymphovascular invasion (LVI) and RS, a survival combined model was built. The area under the curve (AUC) for predicting 3‐year and 5‐year OS was 0.765 and 0.788 in the training set, 0.757 and 0.729 in the validation set. There was no significant difference between the radiomics model and survival combined model for 3‐year (0.690 vs. 0.757, P = 0.425) and 5‐year OS (0.687 vs. 729, P = 0.412) in the validation set. The calibration curves showed a high degree of fit for the survival combined model.Data ConclusionThis study established a survival combined model that might help AGC patients in future clinical decision‐making.Evidence Level33Technical EfficacyStage 5