Comparison of the imaging and clinical characteristics between Initial and Recurrent Alcoholic Acute Pancreatitis: a retrospective cross-sectional study.

MATERIALS: Patients with alcoholic acute pancreatitis in our hospital were recruited from Jan 2019 to July 2022 and divided into IAAP and RAAP groups. All patients underwent Contrast-Enhanced Computerized Tomography (CECT) or Magnetic Resonance Imaging (MRI) after administration. Imaging manifestations, local complications, severity scores on the Modified CT/MR Severity Index (MCTSI/MMRSI), Extrapancreatic Inflammation on CT/MR (EPIC/M), clinical severity [Bedside Index for Severity in Acute Pancreatitis (BISAP) Acute Physiology and Chronic Health Evaluation (APACHE-II)], and clinical prognosis were compared between the two groups.Results: 166 patients were recruited for this study, including 134 IAAP (male sex 94%) and 32 RAAP patients (male sex 100%). On CECT or MRI, IAAP patients were more likely to develop ascites and Acute Necrosis collection (ANC) than RAAP patients (ascites:87.3%vs56.2%; P = .01; ANC:38%vs18.7%; P < .05). MCTSI/MMRSI and EPIC/M scores were higher in IAAP than in RAAP patients(MCTSI/MMRSI:6.2vs5.2; P < .05; EPIC/M:5.4vs3.8; P < .05).Clinical severity scores (APACHE-II and BISAP), length of stay, and systemic complications [Systemic Inflammatory Response Syndrome (SIRS), respiratory failure] were higher in the IAAP group than in the RAAP group (P < .05). No mortality outcomes were reported in either group while hospitalized.Conclusions: Patients with IAAP had more severe disease than those with RAAP. These results may be helpful for differentiating care paths for IAAP and RAAP, which are essential for management and timely treatment in clinical practice.

Five metastasis-related mRNAs signature predicting the survival of patients with liver hepatocellular carcinoma.

BACKGROUNDS: Liver hepatocellular carcinoma (HCC) is one of the most malignant tumors, of which prognosis is unsatisfactory in most cases and metastatic of HCC often results in poor prognosis. In this study, we aimed to construct a metastasis- related mRNAs prognostic model to increase the accuracy of prediction of HCC prognosis. METHODS: Three hundred seventy-four HCC samples and 50 normal samples were downloaded from The Cancer Genome Atlas (TCGA) database, involving transcriptomic and clinical data. Metastatic-related genes were acquired from HCMBD website at the same time. Two hundred thirty-three samples were randomly divided into train dataset and test dataset with a proportion of 1:1 by using caret package in R. Kaplan-Meier method and univariate Cox regression analysis and lasso regression analysis were performed to obtain metastasis-related mRNAs which played significant roles in prognosis. Then, using multivariate Cox regression analysis, a prognostic prediction model was established. Transcriptome and clinical data were combined to construct a prognostic model and a nomogram for OS evaluation. Functional enrichment in high- and low-risk groups were also analyzed by GSEA. An entire set based on The International Cancer Genome Consortium(ICGC) database was also applied to verify the model. The expression levels of SLC2A1, CDCA8, ATG10 and HOXD9 are higher in tumor samples and lower in normal tissue samples. The expression of TPM1 in clinical sample tissues is just the opposite. RESULTS: One thousand eight hundred ninety-five metastasis-related mRNAs were screened and 6 mRNAs were associated with prognosis. The overall survival (OS)-related prognostic model based on 5 MRGs (TPM1,SLC2A1, CDCA8, ATG10 and HOXD9) was significantly stratified HCC patients into high- and low-risk groups. The AUC values of the 5-gene prognostic signature at 1 year, 2 years, and 3 years were 0.786,0.786 and 0.777. A risk score based on the signature was a significantly independent prognostic factor (HR = 1.434; 95%CI = 1.275-1.612; P < 0.001) for HCC patients. A nomogram which incorporated the 5-gene signature and clinical features was also built for prognostic prediction. GSEA results that low- and high-risk group had an obviously difference in part of pathways. The value of this model was validated in test dataset and ICGC database. CONCLUSION: Metastasis-related mRNAs prognostic model was verified that it had a predictable value on the prognosis of HCC, which could be helpful for gene targeted therapy.

Radiomics models of contrast-enhanced computed tomography for predicting the activity and prognosis of acute pancreatitis.

BACKGROUND: The modified pancreatitis activity scoring system (mPASS) was proposed to assess the activity of acute pancreatitis (AP) while it doesn't include indicators that directly reflect pathophysiology processes and imaging characteristics. OBJECTIVES: To determine the threshold of admission mPASS and investigate radiomics and laboratory parameters to construct a model to predict the activity of AP. METHODS: AP inpatients at institution 1 were randomly divided into training and validation groups based on a 5:5 ratio. AP inpatients at Institution 2 were served as test group. The cutoff value of admission mPASS scores in predicting severe AP was selected to divide patients into high and low level of disease activity group. LASSO was used in screening features. Multivariable logistic regression was used to develop radiomics model. Meaningful laboratory parameters were used to construct combined model. RESULTS: There were 234 (48 years ± 10, 155 men) and 101 (48 years ± 11, 69 men) patients in two institutions. The threshold of admission mPASS score was 112.5 in severe AP prediction. The AUC of the radiomics model was 0.79, 0.72, and 0.76 and that of the combined model incorporating rad-score and white blood cell were 0.84, 0.77, and 0.80 in three groups for activity prediction. The AUC of the combined model in predicting disease without remission was 0.74. CONCLUSIONS: The threshold of admission mPASS was 112.5 in predicting severe AP. The model based on CECT radiomics has the ability to predict AP activity. Its ability to predict disease without remission is comparable to mPASS. CRITICAL RELEVANCE STATEMENT: This work is the first attempt to assess the activity of acute pancreatitis using contrast-enhanced CT radiomics and laboratory parameters. The model provides a new method to predict the activity and prognosis of AP, which could contribute to further management. KEY POINTS: Radiomics features and laboratory parameters are associated with the activity of acute pancreatitis. The combined model provides a new method to predict the activity and prognosis of AP. The ability of the combined model is comparable to the modified Pancreatitis Activity Scoring System.