Nomogram model predicting the overall survival for patients with primary gastric mucosa-associated lymphoid tissue lymphoma.

BACKGROUND: Increasingly extranodal marginal B-cell lymphoma of mucosa-associated lymphoid tissue, known as mucosa-associated lymphoid tissue (MALT) lymphoma, is a type of non-Hodgkin's lymphoma. The prognosis of primary gastric MALT (GML) patients can be affected by many factors. Clinical risk factors, including age, type of therapy, sex, stage and family hematologic malignancy history, also have significant effects on the development of the disease. The available data are mainly focused on epidemiology; in contrast, few studies have investigated the prognostic variables for overall survival (OS) in patients with primary GML. Based on the realities above, we searched a large amount of data on patients diagnosed with primary GML in the Surveillance, Epidemiology and End Results (SEER) database. The aim was to develop and verify a survival nomogram model that can predict the overall survival prognosis of primary GML by combining prognostic and determinant variables. AIM: To create an effective survival nomogram for patients with primary gastric GML. METHODS: All data of patients with primary GML from 2004 to 2015 were collected from the SEER database. The primary endpoint was OS. Based on the LASSO and COX regression, we created and further verified the accuracy and effectiveness of the survival nomogram model by the concordance index (C-index), calibration curve and time-dependent receiver operating characteristic (td-ROC) curves. RESULTS: A total of 2604 patients diagnosed with primary GML were selected for this study. A total of 1823 and 781 people were randomly distributed into the training and testing sets at a ratio of 7:3. The median follow-up of all patients was 71 mo, and the 3- and 5-year OS rates were 87.2% and 79.8%, respectively. Age, sex, race, Ann Arbor stage and radiation were independent risk factors for OS of primary GML (all P < 0.05). The C-index values of the nomogram were 0.751 (95%CI: 0.729-0.773) and 0.718 (95%CI: 0.680-0.757) in the training and testing cohorts, respectively, showing the good discrimination ability of the nomogram model. Td-ROC curves and calibration plots also indicated satisfactory predictive power and good agreement of the model. Overall, the nomogram shows favorable performance in discriminating and predicting the OS of patients with primary GML. CONCLUSION: A nomogram was developed and validated to have good survival predictive performance based on five clinical independent risk factors for OS for patients with primary GML. Nomograms are a low-cost and convenient clinical tool in assessing individualized prognosis and treatment for patients with primary GML.

Radiomics-based classification models for HBV-related cirrhotic patients with covert hepatic encephalopathy.

INTRODUCTION: The significant abnormalities of precuneus (PC), which are associated with brain dysfunction, have been identified in cirrhotic patients with covert hepatic encephalopathy (CHE). The present study aimed to apply radiomics analysis to identify the significant radiomic features in PC and their subregions, combine with clinical risk factors, then build and evaluate the classification models for CHE diagnosis. METHODS: 106 HBV-related cirrhotic patients (54 had current CHE and 52 had non-CHE) underwent the three-dimensional T1-weighted imaging. For each participant, PC and their subregions were segmented and extracted a large number of radiomic features and then identified the features with significant discriminative power as the radiomics signature. The logistic regression analysis was employed to develop and evaluate the classification models, which are constructed using the radiomics signature and clinical risk factors. RESULTS: The classification model (R-C model) achieved best diagnostic performance, which incorporated radiomics signature (4 radiomic features from right PC), venous blood ammonia, and the Child-Pugh stage. And the area under the receiver operating characteristic curve values (AUC), sensitivity, specificity, and accuracy values were 0.926, 1.000, 0.765, and 0.848, in the testing set. Application of the radiomics nomogram in the testing set still showed a good predictive accuracy. CONCLUSIONS: This study presented the radiomic features of the right PC, as a potential image marker of CHE. The radiomics nomogram that incorporates the radiomics signature and clinical risk factors may facilitate the individualized prediction of CHE.

In vivo and in vitro imaging tracing of dual-labeled bone mesenchymal stem cells transplanted into myocardium of F344 rats.

OBJECTIVE: To investigate the feasibility of in vitro and in vivo magnetic resonance imaging (MRI) and fluorescence imaging tracking of transplanted bone mesenchymal stem cells (BMSCs) dual-labeled with ultrasmall superparamagnetic iron oxide (USPIO) and red fluorescence protein (RFP). METHODS: BMSCs were incubated with culture medium containing USPIO for 24 hours. The Prussian-blue staining, transmission electron microscopy and trypan-blue staining were used to study the efficacy and safety of labeling. F344 rat model of acute myocardial infarction was established by ligating the left anterior descending coronary artery. The dual-labeled BMSCs were injected into the margin of the infraction myocardium. Then MRI and fluorescence imaging were performed to trace the cells both in vitro and in vivo. Postmortal study was carried out to observe the distribution of transplanted cells in myocardium. RESULTS: The percentage of dual-labeled BMSCs reached 99% after co-incubating with USPIO for 24 hours. USPIO particles were mainly located in lysosomes. As demonstrated by trypan-blue staining, there was no significant deference in viability between labeled and unlabeled groups (P>0.05). All dual-labeled transplanted BMSCs showed a significant decreasing signal on MRI, and the signal intensity changes had no significant difference over 4 weeks (P=0.66). In vitro cell tracing with fluorescence imaging of isolated heart from F344 rats was successful,while in vivo cell tracing with fluorescence imaging failed. Prussian blue staining showed that USPIO distributed near the infarcted myocardium, corresponding with the fluorescence imaging. CONCLUSION: MRI can be used to trace the dual-labeled BMSCs transplanted into F344 rat hearts in vivo, while fluorescence imaging and pathological fluorescence imaging can trace the transplanted cells in vitro.