CT-based transformer model for non-invasively predicting the Fuhrman nuclear grade of clear cell renal cell carcinoma.

Background: Clear cell Renal Cell Carcinoma (ccRCC) is the most common malignant tumor in the urinary system and the predominant subtype of malignant renal tumors with high mortality. Biopsy is the main examination to determine ccRCC grade, but it can lead to unavoidable complications and sampling bias. Therefore, non-invasive technology (e.g., CT examination) for ccRCC grading is attracting more and more attention. However, noise labels on CT images containing multiple grades but only one label make prediction difficult. However, noise labels exist in CT images, which contain multiple grades but only one label, making prediction difficult. Aim: We proposed a Transformer-based deep learning algorithm with CT images to improve the diagnostic accuracy of grading prediction and to improve the diagnostic accuracy of ccRCC grading. Methods: We integrate different training models to improve robustness and predict Fuhrman nuclear grade. Then, we conducted experiments on a collected ccRCC dataset containing 759 patients and used average classification accuracy, sensitivity, specificity, and AreaUnderCurve as indicators to evaluate the quality of research. In the comparative experiments, we further performed various current deep learning algorithms to show the advantages of the proposed method. We collected patients with pathologically proven ccRCC diagnosed from April 2010 to December 2018 as the training and internal test dataset, containing 759 patients. We propose a transformer-based network architecture that efficiently employs convolutional neural networks (CNNs) and self-attention mechanisms to extract a persuasive feature automatically. And then, a nonlinear classifier is applied to classify. We integrate different training models to improve the accuracy and robustness of the model. The average classification accuracy, sensitivity, specificity, and area under curve are used as indicators to evaluate the quality of a model. Results: The mean accuracy, sensitivity, specificity, and Area Under Curve achieved by CNN were 82.3%, 89.4%, 83.2%, and 85.7%, respectively. In contrast, the proposed Transformer-based model obtains a mean accuracy of 87.1% with a sensitivity of 91.3%, a specificity of 85.3%, and an Area Under Curve (AUC) of 90.3%. The integrated model acquires a better performance (86.5% ACC and an AUC of 91.2%). Conclusion: A transformer-based network performs better than traditional deep learning algorithms in terms of the accuracy of ccRCC prediction. Meanwhile, the transformer has a certain advantage in dealing with noise labels existing in CT images of ccRCC. This method is promising to be applied to other medical tasks (e.g., the grade of neurogliomas and meningiomas).

Multi-nuclear magnetic resonance spectroscopy: state of the art and future directions.

With the development of heteronuclear fluorine, sodium, phosphorus, and other probes and imaging technologies as well as the optimization of magnetic resonance imaging (MRI) equipment and sequences, multi-nuclear magnetic resonance (multi-NMR) has enabled localize molecular activities in vivo that are central to a variety of diseases, including cardiovascular disease, neurodegenerative pathologies, metabolic diseases, kidney, and tumor, to shift from the traditional morphological imaging to the molecular imaging, precision diagnosis, and treatment mode. However, due to the low natural abundance and low gyromagnetic ratios, the clinical application of multi-NMR has been hampered. Several techniques have been developed to amplify the NMR sensitivity such as the dynamic nuclear polarization, spin-exchange optical pumping, and brute-force polarization. Meanwhile, a wide range of nuclei can be hyperpolarized, such as 2H, 3He, 13C, 15 N, 31P, and 129Xe. The signal can be increased and allows real-time observation of biological perfusion, metabolite transport, and metabolic reactions in vivo, overcoming the disadvantages of conventional magnetic resonance of low sensitivity. HP-NMR imaging of different nuclear substrates provides a unique opportunity and invention to map the metabolic changes in various organs without invasive procedures. This review aims to focus on the recent applications of multi-NMR technology not only in a range of preliminary animal experiments but also in various disease spectrum in human. Furthermore, we will discuss the future challenges and opportunities of this multi-NMR from a clinical perspective, in the hope of truly bridging the gap between cutting-edge molecular biology and clinical applications.

Computed Tomography-Based Texture Features for the Risk Stratification of Portal Hypertension and Prediction of Survival in Patients With Cirrhosis: A Preliminary Study.

Objective: Clinical evidence suggests that the risk stratification of portal hypertension (PH) plays a vital role in disease progression and patient outcomes. However, the gold standard for stratifying PH [portal vein pressure (PVP) measurement] is invasive and therefore not suitable for routine clinical practice. This study is aimed to stratify PH and predict patient outcomes using liver or spleen texture features based on computed tomography (CT) images non-invasively. Methods: A total of 114 patients with PH were included in this retrospective study and divided into high-risk PH (PVP ≥ 20 mm Hg, n = 57) or low-risk PH (PVP < 20 mm Hg, n = 57), a progression-free survival (PFS) group (n = 14), or a non-PFS group (n = 51) based on patients with rebleeding or death after the transjugular intrahepatic portosystemic shunt (TIPS) procedure. All patients underwent contrast-enhanced CT, and the laboratory data were recorded. Texture features of the liver or spleen were obtained by a manual drawing of the region of interest (ROI) and were performed in the portal venous phase. Logistic regression analysis was applied to select the significant features related to high-risk PH, and PFS-related features were determined by the Cox proportional hazards model and Kaplan-Meier analysis. Receiver operating characteristic (ROC) curves were used to test the diagnostic capacity of each feature. Results: Five texture features (one first-order feature from the liver and four wavelet features from the spleen) and the international normalized ratio (INR) were identified as statistically significant for stratifying PH (p < 0.05). The best performance was achieved by the spleen-derived feature of wavelet.LLH_ngtdm_Busyness, with an AUC of 0.72. The only log.sigma.3.0.mm.3D_firstorder_RobustMeanAbsoluteDeviation feature from the liver was associated with PFS with a C-index of 0.72 (95% CI 0.566-0.885), which could stratify patients with PH into high- or low-risk groups. The 1-, 2-, and 3-year survival probabilities were 66.7, 50, and 33.3% for the high-risk group and 93.2, 91.5, and 84.4% for the low-risk group, respectively (p < 0.05). Conclusion: CT-based texture features from the liver or spleen may have the potential to stratify PH and predict patient survival.

New Liver MR Imaging Hallmarks for Small Hepatocellular Carcinoma Screening and Diagnosing in High-Risk Patients.

Objective: Early detection and diagnosis of hepatocellular carcinoma (HCC) is essential for prognosis; however, the imaging hallmarks for tumor detection and diagnosis has remained the same for years despite the use of many new immerging imaging methods. This study aimed to evaluate the detection performance of hepatic nodules in high risk patients using either hepatobiliary specific contrast (HBSC) agent or extracellular contrast agent (ECA), and further to compare the diagnostic performances for hepatocellular carcinoma (HCC) using different diagnostic criteria with the histopathological results as reference standard. Methods: This prospective study included 247 nodules in 222 patients (mean age, 53.32 ± 10.84 years; range, 22-79 years). The detection performance and imaging features of each nodule were evaluated in all MR sequences by three experienced abdominal radiologists. The detection performance of each nodule on all MR sequences were compared and further the diagnostic performance of various diagnostic criteria were evaluated. Results: For those patients who underwent ECA-MRI, the conventional imaging hallmark of "AP + PVP and/or DP" was recommended, as 60.19% diagnostic sensitivity, 80.95% specificity and 100% lesion detection rate. Additionally, for those patients who underwent HBSC-MRI, the diagnostic criteria of "DWI + HBP" was recommended. This diagnostic criteria demonstrated, both in all tumor size and for nodules ≤2 cm, higher sensitivity (93.07 and 90.16%, all p <0.05, respectively) and slightly lower specificity (64.71 and 87.50%, all p >0.05, respectively) than that of the European Association for the Study of the Liver (EASL) criteria. Conclusions: Different abbreviated MR protocols were recommended for patients using either ECA or HBSC. These provided imaging settings demonstrated high lesion detection rate and diagnostic performance for HCC.

Quantitative measurements of esophageal varices using computed tomography for prediction of severe varices and the risk of bleeding: a preliminary study.

BACKGROUND: We aimed to assess whether the quantitative parameters of esophageal varices (EV) based on computed tomography (CT) can noninvasively predict severe EV and the risk of esophageal variceal bleeding (EVB). METHODS: A total of 136 endoscopically confirmed EV patients were included in this retrospective study and were divided into a non-conspicuous (mild-to-moderate EV, n = 30) and a conspicuous EV group (severe EV, n = 106), a bleeding (n = 89) and a non-bleeding group (n = 47). EV grade (EVG), EV diameter (EVD), cross-sectional surface area (CSA), EV volume (EVV), spleen volume (SV), splenic vein (SNV), portal vein (PV), diameter of left gastric vein (DLGV), and the opening type of LGV were measured independently using 3D-slicer. Univariate and multivariate logistic analysis were used to determine the independent factors and the receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic performance. RESULTS: The difference of EVG, EVD, CSA, EVV, DLGV, SNV between the conspicuous and non-conspicuous EV group were statistically significant (p < 0.05), area under the curves (AUCs) of them for predicting severe EV were 0.72, 0.772, 0.704, 0.768, 0.707, 0.65, with corresponding sensitivities of 70.3%, 63.5%, 50%, 74.3%, 52.7%, 48.6%, specificities of 71.4%, 85.7%, 100%, 71.4%, 81%, 81%, respectively. EVG, CSA (odds ratio 3.258, 95% CI 1.597-6.647; 1.029, 95% CI 1.008-1.050) were found to be independent predictive factors. However, there was no significant difference of the included indices between the bleeding and non-bleeding group (p > 0.05). CONCLUSIONS: CT can be used as a noninvasive method to predict the severity of EV, which may reduce the invasive screening of endoscopy.

Polysaccharide of Atractylodis Macrocephalae Rhizoma inhibits expression of immune checkpoint PD-L1 by targeting miR-34a in esophageal carcinoma cells / 中国中药杂志

The immune checkpoint programmed cell death-ligand 1(PD-L1)-mediated immunosuppression is among the important features of tumor. PD-L1, an immunosuppressant, can induce T cell failure by binding to programmed cell death-1(PD-1). Thus, the key to restoring the function of T cells is inhibiting the expression of PD-L1. The Chinese medicinal Atractylodis Macrocephalae Rhizoma(AMR) has the anti-tumor, anti-inflammatory, antioxidant, and hypoglycemic activities, and the polysaccharide in AMR(PAMR) plays a crucial role in immunoregulation, but the influence on the immune checkpoints which are closely related to immunosuppression has not been reported. MicroRNA-34 a(miR-34 a) expression in esophageal carcinoma tissue is significantly lower than that in normal tissue. This study aims to investigate the inhibitory effect of PAMR on esophageal carcinoma cells, and the relationship between its inhibitory effect on PD-L1 expression and miR-34 a, which is expected to clarify the anti-tumor mechanism of PAMR. Firstly, different human esophageal carcinoma cell lines(EC9706, EC-1, TE-1, EC109 cells) were screend out, and expression of PD-L1 was determined. Then, EC109 cells, with high expression of PD-L1, were selected for further experiment. The result showed that PAMR suppressed EC109 cell growth. According to the real-time quantitative PCR(qPCR) and Western blot, it significantly suppressed the mRNA and protein expression of PD-L1, while promoting the expression of tumor suppressor miR-34 a. The confocal microscopy and luci-ferase assay proved that PAMR alleviated the inhibitory effect of PD-L1 while blocked miR-34 a. Additionally, the expression of PD-L1 was controlled by miR-34 a, and the combination of miR-34 a inhibitor with high-dose PAMR reversed the inhibitory effect of PAMR on PD-L1 protein expression. Thus, the PAMR may inhibit PD-L1 by increasing the expression of miR-34 a and regulating its downstream target genes. In conclusion, PAMR inhibits the expression of PD-L1 mainly by inducing miR-34 a.

Gastrointestinal stromal tumors: associations between contrast-enhanced CT images and KIT exon 11 gene mutation.

BACKGROUND: Mutation screening for gastrointestinal stromal tumor (GIST) is crucial and the c kit gene (KIT) exon 11 mutation is the most common type. This study aimed to explore the associations between GIST with KIT exon 11 mutation and contrast-enhanced computed tomography (CT) images. METHODS: Pathologically proven GISTs with definitive genotype testing results in our hospital were retrospectively included. Abdominal contrast-enhanced CT images were analyzed. Conventional CT image features and radiomic features were recorded and extracted to build the following models: model [CT], model [radiomic + clinic] and model [CT + radiomic + clinic]. The diagnostic performances of GISTs with KIT exon 11 mutation and KIT exon 11 deletion involving codons 557-558 were evaluated. RESULTS: In total, 327 GISTs (255 with KIT exon 11 mutation, and 73 with KIT exon 11 mutation deletion involving codons 557-558) were included. Significant CT features were found for GISTs with KIT exon 11 mutation. The area under curves (AUCs) of the models for KIT exon 11 mutation were 0.7158, 0.7530, and 0.8375 in the training cohort, and 0.6777, 0.7349, and 0.8105 in validation cohort, respectively. The AUCs of the models for KIT exon 11 mutation deletion involving codons 557-558 were 0.7155, 8621, and 0.8691 in the training cohort, and 0.7099, 0.8355, and 0.8488 in the validation cohort, respectively. The model [CT + radiomic + clinic] demonstrated the highest AUCs for prediction of KIT exon 11 mutation and those with deletion involving codons 557-558 (P<0.05), respectively. The model [radiomic + clinic] showed higher diagnostic performance than model [CT] significantly. CONCLUSIONS: Our results demonstrated the associations between GIST with KIT exon 11 mutation and contrast-enhanced CT images. We found combing conventional image analysis and texture analysis is a useful tool to distinguish GIST with KIT exon 11 mutation. CT radiogenomics exhibited good application potential in predict the KIT exon 11 mutation of GIST.

CT-derived quantitative liver volumetric parameters for prediction of severe esophageal varices and the risk of first variceal hemorrhage.

PURPOSE: To assess whether CT (computed tomography)-derived quantitative parameters of liver lobe volume can predict severe esophageal varices (EV) and the risk of first varicealhemorrhage (FVH) in patients with liver cirrhosis. METHODS: A total of 217 endoscopically confirmed EV patients were included in this retrospective study and were divided into a low-risk EV group (mild-to-moderate EV, n = 83) and a high-risk EV group (severe EV, n = 134), a FVH group (n = 17) and a non-FVH group (n = 27), patients' clinical findings were recorded. The left, right, caudate lobe, total liver volume and the corresponding functional volume were measured respectively, and the ratio of caudate volume/total volume (CV/TV), caudate functional volume/total functional volume (CFV/TFV) were calculated. Univariate and multivariate logistic analysis were used to determine the independent factors and the receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic performance. RESULTS: CV, CFV, CV/TV, CFV/TFV were significantly different in the EV severity study and FVH study (p < 0.05). Multivariate analysis indicated that CV/TV and ascites were independent predictive factors for severe EV, a predictive model combing those two factors revealed a satisfactory diagnostic performance (area under the curve (AUC), 0.853, 95 %CI 0.797-0.905). Furthermore, CV/TV and the presence of red color sign under endoscopy were found to be independent predictive factors for FVH, and the former showed a better discriminative performance than the latter (AUC, 0.851 vs 0.779). CONCLUSIONS: CT-derived quantitative parameters of CV, CFV, CV/TV, CFV/TFV may be used as an alternative to endoscopy in predicting severe varices and the risk of bleeding.

Use of computed tomography for distinguishing heterotopic pancreas from gastrointestinal stromal tumor and leiomyoma.

PURPOSE: To determine whether morphologic features and semiquantitative parameters of computed tomography (CT) could be used to distinguish heterotopic pancreas from gastrointestinal stromal tumor (GIST) and leiomyoma. METHODS: This retrospective study evaluated CT images of heterotopic pancreases (n = 28), GISTs (n = 57), and leiomyomas (n = 26) located in the upper gastrointestinal tract. Morphologic imaging features of lesions were analyzed, including location, contour, margin, attenuation, growth pattern, enhancement type, enhancement degree, enlarged vessels feeding or draining the mass, hyperenhancement of the overlying mucosa, low intralesional attenuation, calcification, and a duct-like structure. Semiquantitative parameters included long diameter (LD), short diameter (SD), LD/SD ratio, and lesion and aorta CT values during plain CT (Lp and Ap), arterial phase (La and Aa), and venous phase (Lv and Av). Diagnostic performance of these findings and parameters were evaluated by receiver operating characteristic (ROC) analysis. RESULTS: Morphologic CT findings (including lesion contour, margin, attenuation, growth pattern, enhancement type, and enhancement degree) and semiquantitative parameters except for LD/SD were demonstrated to be significant for differentiating heterotopic pancreas from GIST and leiomyoma (all P < 0.01). Of these, location, low intralesional attenuation, duct-like structure and LD, SD, Lv, and Sv values showed good diagnostic performance with the areas under curve (AUC) higher than 0.70. The presence of a duct-like structure demonstrated the best diagnostic ability with AUC of 0.929 [95% confidence interval (CI) 0.864-0.969], sensitivity of 5.7% (95% CI 67.3-96.0), and specificity of 100% (95% CI 95.7-100), respectively. When the three morphologic features (location, low intralesional attenuation, duct-like structure) were used in combination, the AUC was improved to 0.980 (95% CI 0.952-1). CONCLUSION: CT features, especially the morphologic features, could be used to differentiate heterotopic pancreas from GIST and leiomyoma in the upper gastrointestinal tract and, thus, provide a more accurate method for non-invasive preoperative diagnosis. Additionally, the presence of a duct-like structure demonstrated to be a reliable indicator for heterotopic pancreas among the morphologic and semiquantitative CT features.

Neuronal Autophagy in Depression and Regulatory Effect of Traditional Chinese Medicine： A Review / 中国实验方剂学杂志

Depression is a mental illness characterized by persistent negative feelings， which has seriously threatened people's health. In recent years， neuronal autophagy， an important stress response， has also been regarded as a hypothesis for the pathogenesis of depression. Relevant studies have shown that either insufficient or excessive autophagy triggers neuronal damage， and activated or inhibited neuronal autophagy can be observed in animal models of depression. Therefore， neuronal autophagy may be a double-edged sword involved in the pathogenesis of depression. It is believed in traditional Chinese medicine （TCM） that the occurrence of this disease is closely related to liver depression and spleen deficiency. Chinese medicine regulates the neuronal autophagy via multiple ways. The TCM monomers that regulate neuron autophagy are capable of protecting nerves or penetrating the blood-brain barrier. TCM compounds designed for soothing liver or invigorating spleen have been proved effective against this disease， demonstrating that the core pathogenesis of depression lies in liver depression and spleen deficiency. The regulatory effects of TCM on neuronal autophagy in depression models might result from its action on multiple targets， multiple pathways， and multiple systems. This paper discussed the limitations in current research based on the involvement of neuronal autophagy in depression and its treatments， in order to provide ideas for later similar research and that concerning TCM treatment of depression.

Current and Potential Applications of Artificial Intelligence in Gastrointestinal Stromal Tumor Imaging.

The most common mesenchymal tumors are gastrointestinal stromal tumors (GISTs), which have malignant potential and can occur anywhere along the gastrointestinal system. Imaging methods are important and indispensable of GISTs in diagnosis, risk staging, therapy, and follow-up. The recommended imaging method for staging and follow-up is computed tomography (CT) according to current guidelines. Artificial intelligence (AI) applies and elaborates theses, procedures, modes, and utilization systems for simulating, enlarging, and stretching the intellectual capacity of humans. Recently, researchers have done a few studies to explore AI applications in GIST imaging. This article reviews the present AI studies in GISTs imaging, including preoperative diagnosis, risk stratification and prediction of prognosis, gene mutation, and targeted therapy response.

A New Diagnostic Criterion with Gadoxetic Acid-Enhanced MRI May Improve the Diagnostic Performance for Hepatocellular Carcinoma.

BACKGROUND: To prospectively establish and validate new diagnostic criterion (DC) for liver-specific contrast agents and further compared the diagnostic sensitivity and specificity with conventional DC. METHODS: Institutional Review Board approved and written informed consent were obtained for this prospective study. Two board-certified reviewers established the reference standard as hepatocellular carcinoma (HCC), non-HCC lesions by using marks on all cross-sectional MR images. Another 2 abdominal radiologists independently performed the marked lesion observations using 5 different DCs, including DC-1: arterial phase hyperenhancement (APHE) and portal venous phase washout; DC-2: APHE and hepatobiliary phase (HBP) hypointensity; DC-3: APHE and diffusion-weighted imaging (DWI) hyperintensity; DC-4: HBP hypointensity and DWI hyperintensity; DC-5: HBP hypointensity, DWI hyperintensity and excluded these markedly T2 hyperintensity. Diagnostic performance of sensitivity, specificity, and accuracy for each imaging DC was calculated, per-lesion diagnostic sensitivity and specificity of imaging criteria were compared by using McNemars test. RESULTS: A total of 215 patients were included (mean age 53.82 ± 11.24 years; range 24-82 years) with 265 hepatic nodules (175 HCCs and 90 non-HCCs). The DC-4 (93.71%; 164/175) and DC-5 (92.57%; 162/175) yielded the highest diagnostic sensitivity and was better than DC-1 (72.57%; 127/175), DC-2 (82.86%; 145/175), and DC-3 (82.29%; 144/175) (all p < 0.001). The specificity of DC-1 (94.44%; 85/90) was significantly higher than that with DC-2 (83.33%; 75/90), DC-3 (84.44%; 76/90), DC-4 (74.44%; 67/90), and DC-5 (82.22%; 74/90) (all p < 0.05). Additionally, the DC-4 and DC-5 achieved the highest area under curve value of 0.841 (95% CI 0.783-0.899) and 0.874 (95% CI 0.822-0.925). CONCLUSIONS: The combined use of HBP hypointensity and DWI hyperintensity as a new DC for HCC enables a high diagnostic sensitivity and comparable specificity.

CT Manifestations and Clinical Characteristics of 1115 Patients with Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: We aimed to assess the prevalence of significant computed tomographic(CT) manifestations and describe some notable features based on chest CT images, as well as the main clinical features of patients with coronavirus disease 2019(COVID-19). MATERIALS AND METHODS: A systematic literature search of PubMed, EMBASE, the Cochrane Library, and Web of Science was performed to identify studies assessing CT features, clinical, and laboratory results of COVID-19 patients. A single-arm meta-analysis was conducted to obtain the pooled prevalence and 95% confidence interval (95% CI). RESULTS: A total of 14 articles (including 1115 patients) based on chest CT images were retrieved. In the lesion patterns on chest CTs, we found that pure ground-glass opacities (GGO) (69%, 95% CI 58-80%), consolidation (47%, 35-60%) and "air bronchogram sign" (46%, 25-66%) were more common than the atypical lesion of "crazy-paving pattern" (15%, 8-22%). With regard to disease extent and involvement, 70% (95% CI 46-95%) of cases showed a location preference for the right lower lobe, 65% (58-73%) of patients presented with ≥3 lobes involvement, and meanwhile, 42% (32-53%) of patients had involvement of all five lobes, while 67% (55-78%) of patients showed a predominant peripheral distribution. An understanding of some important CT features might be helpful for medical surveillance and management. In terms of clinical features, muscle soreness (21%, 95% CI 15-26%) and diarrhea (7%, 4-10%) were minor symptoms compared to fever (80%, 74-87%) and cough (53%, 33-72%). CONCLUSION: Chest CT manifestations in patients with COVID-19, as well as its main clinical characteristics, might be helpful in disease evolution and management.

Quantitative analysis of chest CT imaging findings with the risk of ARDS in COVID-19 patients: a preliminary study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has rapidly become a pandemic worldwide. The value of chest computed tomography (CT) is debatable during the treatment of COVID-19 patients. Compared with traditional chest X-ray radiography, quantitative CT may supply more information, but its value on COVID-19 patients was still not proven. METHODS: An automatic quantitative analysis model based on a deep network called VB-Net for infection region segmentation was developed. A quantitative analysis was performed for patients diagnosed as severe COVID 19. The quantitative assessment included volume and density among the infectious area. The primary clinical outcome was the existence of acute respiratory distress syndrome (ARDS). A univariable and multivariable logistic analysis was done to explore the relationship between the quantitative results and ARDS existence. RESULTS: The VB-Ne model was sensitive and stable for pulmonary lesion segmentation, and quantitative analysis indicated that the total volume and average density of the lung lesions were not related to ARDS. However, lesions with specific density changes showed some influence on the risk of ARDS. The proportion of lesion density from -549 to -450 Hounsfield unit (HU) was associated with increased risk of ARDS, while the density was ranging from -149 to -50 HU was related to a lowered risk of ARDS. CONCLUSIONS: The automatic quantitative model based on VB-Ne can supply useful information for ARDS risk stratification in COVID-19 patients during treatment.

Multiparametric radiomics nomogram may be used for predicting the severity of esophageal varices in cirrhotic patients.

BACKGROUND: To explore whether a multiparametric radiomics nomogram on computed tomography (CT) images based on radiomics and relevant parameters of esophageal varices (EV) can be used for predicting the EV severity in patients with cirrhotic livers. METHODS: From January 2016 to August 2018, 136 consecutive patients with clinicopathologically confirmed liver cirrhosis were included for the development of a predictive model. The patients were then divided into two groups, including non-conspicuous EV group (mild-to-moderate EV, n=30) and conspicuous EV group (severe EV, n=106) by using the endoscopic validation as the reference standard. The radiomic scores (Rad scores) were constructed using the binary logistic regression model from the radiomics features of regions of interest (ROIs) in the left liver (LL) and right liver (RL), respectively. The multiparametric nomogram combined the best performance Rad-score and EV-relevant factors, and the calibration, discrimination, and clinical usefulness of developed nomogram were evaluated using calibration curves, decision curve analysis (DCA) and net reclassification index (NRI) analysis respectively. RESULTS: The LL Rad-score calculated from radiomics features was selected with a relatively higher area under the curve (AUC) (AUC; 0.88, training cohort; 0.87, the validation cohort) compared with RL Rad-score (AUC; 0.86, training cohort; 0.83, the validation cohort). In addition, cross-sectional surface area (CSA) was identified as the important predictor (P<0.05), the multiparametric nomogram containing LL Rad-score and CSA was shown to have a better predictive performance and good calibration in the training model (C-index, 0.953, 95% CI, 0.892 to 0.973) and the validation cohort (C-index, 0.938, 95% CI, 0.841 to 0.961), resulting in an improved NRI (categorical NRI of 25.9%, P=0.0128; continuous NRI of 120%, P<0.001) and integrated discriminatory improvement (IDI) (IDI =13.9%, P<0.001). DCA demonstrated that the multiparametric radiomics nomogram was clinically useful. CONCLUSIONS: A multiparametric radiomics nomogram, which incorporates the liver radiomics signature and EV-relevant indices, is a useful tool for noninvasively predicting EV severity and may complement the standard endoscopy for evaluating EV severity in patients with cirrhosis.

An Unexpected Case Report of Adrenal Lymphangioma: Mimicking Metastatic Tumor on Imaging in a Patient With Pancreatic Cancer.

Adrenal lymphangioma is a very rare benign lesion worldwide and remains challenging for early diagnosis, especially when the patient has some complicated clinical disease. This is an unusual case of a 68-year-old man who was admitted to our hospital with a history of pancreatic tumor. Computed tomography (CT) images and subsequent magnetic resonance imaging (MRI) revealed a mass located in the left adrenal gland, presenting a similar enhancement pattern of the pancreatic tumor, and according to the imaging features, the patient was suspected to have an adrenal metastatic tumor originating from the pancreatic tumor. The patient underwent a surgical resection of the pancreatic tumor and the left adrenal gland. The pathologic diagnosis proved to be lymphangioma deriving from the left adrenal gland. This is the first report presenting an atypical adrenal lymphangioma mimicking a metastatic tumor of pancreatic origin, which might be suggestive in the diagnosis of adrenal lesions and the subsequent clinical treatment, especially when patient has a particular medical history. As we know, imaging examination is helpful for accurate preoperative diagnosis; however, the diagnosis of malignant tumor solely based on imaging procedures should be made cautiously by radiologists.

Computed Tomographic Portography with Esophageal Variceal Measurements in the Evaluation of Esophageal Variceal Severity and Assessment of Esophageal Variceal Volume Efficacy.

RATIONALE AND OBJECTIVES: The aim of our study is to evaluate the severity of esophageal varices (EV), based on the computed tomographic portography (CTP) measurement of EV in the distal esophagus and to assess the prediction value of EV volume. PATIENTS AND METHODS: A total of 53 EV patients examined by CTP within 4 weeks of upper endoscopy were evaluated, the patients were divided into a nonconspicuous EV group (mild-to-moderate EV, n = 28) and a conspicuous EV group (severe EV, n = 25) according to endoscopy results. The diameter, cross-sectional surface area (CSA), and volume of EV were measured independently using 3D-slicer (Boston) by two experienced abdominal radiologists blinded to endoscopy findings. The averaged values measured by the two observers were used in the final dataset, these indicators' predictive performances were studied by using receiver operating characteristic curve analysis, and the area under the curve (Az) and the cutoff values were calculated to distinguish mild-to-moderate from severe EV. RESULTS: The Az values of volume, diameter and CSA in differentiating severe EV were 0.817, 0.794, and 0.784 for observer-1, corresponding values for observer-2 were 0.796, 0.774, and 0.707, there was almost perfect interobserver agreement for all measurements. All indices were larger in the conspicuous group than the nonconspicuous group in both observers (p ≤ 0.01). In the final dataset, application of a 654.0-mm3-volume criterion yielded sensitivity, specificity of 96%, 50%, application of a 5.2-mm-diameter criterion yielded sensitivity, specificity of 80%, 75%, and application of a 68.6-mm2-CSA criterion yielded sensitivity, specificity of 52%, 93%. CONCLUSION: The volume of EV could be used as a new effective indictor for evaluating EV, and use of volume, diameter, and CSA of EV based on CTP allows discrimination between mild-to-moderate and severe EV in cirrhotic patients.

Expression levels of autophagy related proteins and their prognostic significance in retinocytoma and retinoblastoma.

AIM: To discuss the prognostic significant of autophagy related proteins (ARPs) in retinoblastoma (RB) and to find the molecular marker to distinguish retinocytoma (RC) and RB by investigating the different expression profiling of microtubule-associated protein light chain 3 (LC3B) and other ARPs in RC and RB. METHODS: Specimens with retinocytoma region (RCR) or mainly composed with Flexner-Winterstein rosettes (FWR) were screen out from 219 paraffin-embedded RB samples and respectively taken as RCR group and FWR group. Others were taken as undifferentiated (UD) group. Immunochemistry (IHC) of LC3B and electronic microscopy was used to identify autophagy. The IHC scores of LC3B and other ARPs, such as Beclin, PTEN, p27, p16(INK4a), mTOR and BCL-2 were compared and correlation analysis was applied to find potential proteins which may involve in autophagy regulation. The prognostics significance of LC3B was evaluated by comparing the high risk features (HRFs) in 3 groups of total 219 samples. RESULTS: Twenty-one specimens with RCR and 36 specimens mainly composed with FWR were screen out. RCR cell had a high level of LC3B and lots of autophagic vacuoles. Beclin, PTEN, p27 had positive correlation with LC3, and p16(INK4a) had negative correlation, while the expression of mTOR and BCL-2 in RCR and RB region did not show any difference. Cases with RCR had lower rate of HRFs than undifferentiated cases. CONCLUSION: ARPs had different expression pattern between RCR and other pathological types of RB, and could be ideal markers to distinguish RC from RB. Our finding indicated cases with RCR had favorable prognosis just like those with FWR.

Modified Si-Miao-San ameliorates pancreatic B cell dysfunction by inhibition of reactive oxygen species-associated inflammation through AMP-kinase activation / 中国天然药物

AIM@#To observe the effect of modified Si-Miao-San (mSMS) on advanced glycation end products (AGEs)-induced pancreatic B cell dysfunction, as well as examining the underlying mechanisms.@*METHOD@#Pancreatic B cells (INS-1) were stimulated with advanced glycation end products (AGEs, 200 μg·mL(-1)) for 24 h to produce dysfunction in pancreatic B cells and the effects of mSMS observed on insulin secretion, NF-κB (p65) phosphorylation, reactive oxygen species (ROS) production, mitochondria membrane potential (Δψm), cell apoptosis, phosphorylation of AMP-kinase (AMPK), and caspase 3 activity.@*RESULTS@#The AGEs challenge resulted in increased basal insulin secretion, but decreased insulin secretion in response to high glucose, whereas this situation was reversed by mSMS treatment. AGEs stimulation induced NF-κB (p65) phosphorylation and reactive oxygen species (ROS) production, as well as Δψm collapse and cell apoptosis. mSMS inhibited ROS production and inhibited NF-κB activation by attenuating p65 phosphorylation. Meanwhile, AGEs-induced Δψm collapse and cell apoptosis were also reversed by mSMS treatment. Compound C, an inhibitor of AMP-Kinase (AMPK), abolished the beneficial effects of mSMS on the regulation of B cell function, indicating the involvement of AMPK.@*CONCLUSION@#mSMS ameliorated AGEs-induced B cell dysfunction by suppressing ROS-associated inflammation, and this action was related to its beneficial regulation of AMPK activity.