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Objectives: To investigate the ability of CT and endoscopic sonography (EUS) in predicting the malignant risk of 1–2-cm gastric gastrointestinal stromal tumors (gGISTs) and to clarify whether radiomics could be applied for risk stratification. Methods: A total of 151 pathologically confirmed 1–2-cm gGISTs from seven institutions were identified by contrast-enhanced CT scans between January 2010 and March 2021. A detailed description of EUS morphological features was available for 73 gGISTs. The association between EUS or CT high-risk features and pathological malignant potential was evaluated. gGISTs were randomly divided into three groups to build the radiomics model, including 74 in the training cohort, 37 in validation cohort, and 40 in testing cohort. The ROIs covering the whole tumor volume were delineated on the CT images of the portal venous phase. The Pearson test and least absolute shrinkage and selection operator (LASSO) algorithm were used for feature selection, and the ROC curves were used to evaluate the model performance. Results: The presence of EUS- and CT-based morphological high-risk features, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not differ between very-low and intermediate risk 1–2-cm gGISTs (p > 0.05). The radiomics model consisting of five radiomics features showed favorable performance in discrimination of malignant 1–2-cm gGISTs, with the AUC of the training, validation, and testing cohort as 0.866, 0.812, and 0.766, respectively. Conclusions: Instead of CT- and EUS-based morphological high-risk features, the CT radiomics model could potentially be applied for preoperative risk stratification of 1–2-cm gGISTs. Key Points: • The presence of EUS- and CT-based morphological high-risk factors, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not correlate with the pathological malignant potential of 1–2-cm gGISTs. • The CT radiomics model could potentially be applied for preoperative risk stratification of 1–2-cm gGISTs. [ABSTRACT FROM AUTHOR]

Purpose: To develop and evaluate a preoperative risk stratification model for predicting disease-free survival (DFS) based on contrast-enhanced multidetector computed tomography (ceMDCT) images in patients with gastric cancer (GC) undergoing radical surgery. Methods: We retrospectively enrolled patients with GC who underwent ceMDCT followed by radical surgery. A preoperative risk stratification model was constructed (including risk factor selection, risk status scoring, and risk level assignment) using Cox proportional hazard regression and log-rank analyses in the training cohort; the model was tested in the validation cohort. A nomogram was used to compare the preoperative risk stratification model with a postoperative DFS prediction model. Results: A total of 462 patients (training/validation: 271/191) were included. The ceMDCT features of T category (score of 0 or 2), N category (0, 1, 2, or 3), extramural vessel invasion (0 or 2), and tumor location (0 or 1) were selected to construct the preoperative risk stratification model, with 4 risk levels defined based on risk score. There were significant differences in DFS among the risk levels in both cohorts (p < 0.001). The predictive value of the preoperative model was similar to that of the postoperative model, with concordance indices of 0.791 (95% CI, 0.743–0.837) and 0.739 (95% CI, 0.666–0.812), respectively, in the training cohort and 0.762 (95% CI, 0.696–0.828) and 0.738 (95% CI, 0.684–0.792), respectively, in the validation cohort. Conclusion: A preoperative risk stratification model based on ceMDCT images could be used to predict DFS and thus classify GC cases into various risk levels. [ABSTRACT FROM AUTHOR]

Purpose: Preoperative and noninvasive prognosis evaluation remains challenging for gastric cancer. Novel preoperative prognostic biomarkers should be investigated. This study aimed to develop multidetector‐row computed tomography (MDCT)‐guided prognostic models to direct follow‐up strategy and improve prognosis. Methods: A retrospective dataset of 353 gastric cancer patients were enrolled from two centers and allocated to three cohorts: training cohort (n = 166), internal validation cohort (n = 83), and external validation cohort (n = 104). Quantitative radiomic features were extracted from MDCT images. The least absolute shrinkage and selection operator penalized Cox regression was adopted to construct a radiomic signature. A radiomic nomogram was established by integrating the radiomic signature and significant clinical risk factors. We also built a preoperative tumor‐node‐metastasis staging model for comparison. All models were evaluated considering the abilities of risk stratification, discrimination, calibration, and clinical use. Results: In the two validation cohorts, the established four‐feature radiomic signature showed robust risk stratification power (P = 0.0260 and 0.0003, log‐rank test). The radiomic nomogram incorporated radiomic signature, extramural vessel invasion, clinical T stage, and clinical N stage, outperforming all the other models (concordance index = 0.720 and 0.727) with good calibration and decision benefits. Also, the 2‐yr disease‐free survival (DFS) prediction was most effective (time‐dependent area under curve = 0.771 and 0.765). Moreover, subgroup analysis indicated that the radiomic signature was more sensitive in risk stratifying patients with advanced clinical T/N stage. Conclusions: The proposed MDCT‐guided radiomic signature was verified as a prognostic factor for gastric cancer. The radiomic nomogram was a noninvasive auxiliary model for preoperative individualized DFS prediction, holding potential in promoting treatment strategy and clinical prognosis. [ABSTRACT FROM AUTHOR]

Background: Staging laparoscopy(SL) is a recommended technique for the staging of Gastric Cancer(GC) and provides the indication for a radical surgery. Considering the medical practice in China, the standardized and regular usage of SL is yet to be spread. However, existing guidelines vary and make an ambiguity of indication for SL. Besides, the specific indication for Chinese patients remains a niche. This study aims to the essential, missing information of Chinese patients and tries to normalize the indication of LS in medical practice in China.Methods: The study is a prospective, multicenter cohort study being conducted in China with a total of 450 patients, all diagnosed with locally advanced gastric cancer (cT2-4 N0-3 M0, no evidence of intra-abdominal dissemination) through Computed Tomography(CT) and/or Endoscopic Ultrasonography(EUS). Peritoneal lavage is regularly performed during the SL. Multivariate Cox regression model and receiver-operator characteristic(ROC) analysis will be used to analyze the significant risk factors of intra-abdominal metastasis(including peritoneal dissemination and a positive cytological result).Discussion: This confirmatory study will provide us with the specific positive rate of intraabdominal metastasis of GC in China, compared with empirical evidence of 20%. We expect this trial will contribute to our discovery of the specific risk factors of intra-abdominal metastasis of Chinese patients and to the stimulating and performing of minimally invasive surgical procedures.Trial Registration: ClinicalTrials.gov : registration number NCT02172690 . [ABSTRACT FROM AUTHOR]

Tumors arising from Meckel's diverticulum (MD) reported in the literature are mainly carcinoid and gastrointestinal stromal tumors. We herein report a rare case of adenocarcinoma arising from intestinal mucosa in an MD with multiple liver metastases at the onset of symptoms. A 57-year-old female complaining of bloody stool for 2 weeks was admitted to our hospital. Colonoscopy revealed massive bloody fluids but did not find any neoplasm. Computed tomography (CT) found a heterogeneous mass at the distal ileum and multiple liver metastases. A segmental ileal resection with local mesentery excision was performed to control the bleeding. During surgery, a tumor arising from a diverticulum in the antimesenteric border of ileum was observed. Histologic examination revealed moderate to poorly differentiated adenocarcinoma. Majority of the MD remain asymptomatic and are diagnosed incidentally during small bowel contrast study, laparoscopy or laparotomy done for unrelated conditions, or until complications arise from the diverticulum. Malignancies are reported to account for only 0.5%-3.2% of the complications. The occurrence of adenocarcinoma in an MD is exceedingly rare. In the few cases described so far, the prognosis of adenocarcinoma within an MD has been poor due to the advanced stage as seen at the time of surgery. Despite the availability of many publications, there is a little consensus concerning the management of an incidental finding of MD. Adenocarcinoma in an MD is extremely sporadic and prognosis has been reported as very poor. However, early diagnosis is challenging. When found incidentally during laparotomy, MD should be carefully examined and best treated with prophylactic resection. [ABSTRACT FROM AUTHOR]

Purpose: To determine the 1-year progression-free survival (PFS) of extramural venous invasion (EMVI), detected with contrast-enhanced multiple-row detector computed tomography (ceMDCT), in patients with stage III gastric cancer. Methods: Between January 2009 and December 2013, 117 patients with pathological-proved stage III gastric cancer based on the criteria of the AJCC 7th were included in this retrospective study. All patients underwent adjuvant chemotherapy postoperatively and had been monitored with the follow-up chest/abdomen/pelvis ceMDCT on 3, 6, and 12 months post-operation. Two radiologists reviewed preoperative images regarding the presence of EMVI, categories of tumor and categories of lymph node. Conventional prognostic histological factors including pathological T/N status, tumor location/growth pattern, histological type/tumor differentiation, and tumor size were also recorded. Disease progression was defined as the presence of radiological or/and pathology-confirmed metachronous metastases, local recurrence, or gastric cancer-related death. The 1-year PFS for both EMVI-positive and EMVI-negative was calculated using the Kaplan-Meier product limit. Hazard ratios for 1-year PFS were generated using a Cox proportional hazard regression on ceMDCT tumor characteristics. Results: The prevalence of EMVI detected with ceMDCT was 43.6% (51/117) in patients with stage III gastric cancer. The EMVI-positive patients had significantly lower 1-year PFS rates (45.1%), than the EMVI-negative patients (75.8%), (Log-rank test, P = 0.0008). In a Cox proportional hazards regression analysis, EMVI and tumor location/growth pattern were identified as independent prognostic factors of 1-year PFS with hazard ratio of 2.272 (95% CI 1.133-4.556, P = 0.021) and 1.982 (95% CI 1.040-3.780, P = 0.039), respectively. Conclusion: EMVI status, detected with ceMDCT, could be used to counsel patients regarding ongoing risks of metastatic disease, implications for surveillance, and systemic chemotherapy. [ABSTRACT FROM AUTHOR]

Objective: To investigate the capability of a radiomics model, which was designed to identify histopathologic growth pattern (HGP) of colorectal liver metastases (CRLMs) based on contrast-enhanced multidetector computed tomography (ceMDCT), to predict early response and 1-year progression free survival (PFS) in patients treated with bevacizumab-containing chemotherapy.Methods: Patients with unresectable CRLMs who were treated with bevacizumab-containing chemotherapy were included in this multicenter retrospective study. For each target lesion, the radiomics-diagnosed HGP (RAD_HGP) of desmoplastic (D) pattern or replacement (R) pattern was determined. Logistic regression and receiver operating characteristic (ROC) curves were used to assess lesion- and patient-based responses according to morphologic response criteria. One-year PFS was calculated using Kaplan-Meier curves. Hazard ratios for 1-year PFS were obtained through Cox proportional hazard regression analysis.Results: Among 119 study patients, 206 D pattern and 140 R pattern lesions were identified. In patients with multiple lesions, 52 had D pattern, 31 had R pattern, and 36 had mixed (D + R) pattern. The area under the curve value for RAD_HGP in predicting early response was 0.707 for lesion-based analysis and 0.720 for patient-based analysis. Patients with D pattern had a significantly longer PFS than patients with R pattern or mixed pattern (P < 0.001). RAD_HGP was the only independent predictor of 1-year PFS.Conclusions: HGP diagnosed using a radiomics model could be used as an effective predictor of PFS for patients with CRLMs treated with bevacizumab-containing chemotherapy. [ABSTRACT FROM AUTHOR]

Purpose: To develop a radiomic nomogram to predict disease-free survival (DFS) in patients with colon cancer.Methods: We retrospectively identified 302 patients with stage III colon cancer and 269 patients with stage II colon cancer who had undergone multidetector computed tomography (MDCT) and radical resection between January 2009 and December 2015. Patients were divided into a training cohort (n = 322) and an external validation cohort (n = 249). Radiomic features were extracted from MDCT images, and a radiomic signature was built as to predict DFS. A radiomic nomogram integrating the radiomic signature and clinicopathologic characteristics was developed using multivariable logistic regression. The nomogram was evaluated with regard to calibration, discrimination, and clinical utility.Results: The radiomic signature was an independent prognostic factor for DFS in the training cohort (HR = 1.102; 95 % CI: 1.052-1.156; P < 0.001) and the external validation cohort (HR = 1.157; 95 % CI: 1.030-1.301; P = 0.014). The radiomic signature-based nomogram was more effective at predicting DFS than either the TNM staging system or a clinicopathologic nomogram. The C-indices of the radiomic nomogram and TNM staging system were 0.780 (95 % CI: 0.734-0.847) and 0.738 (0.687-0.784) respectively. The radiomic signature-based nomogram demonstrated good fitness (shown by calibration curves) and clinical usefulness (shown by decision curve analysis).Conclusion: A radiomic signature derived from MDCT images can effectively predict DFS in patients with stage II and III colon cancer and could be used as a supplement for risk stratification. [ABSTRACT FROM AUTHOR]