Hereditary angioedema (HAE), a rare but life-threatening condition, manifests as acute attacks of facial, laryngeal, genital, or peripheral swelling or abdominal pain secondary to intra-abdominal edema. Resulting from mutations affecting C1 esterase inhibitor (C1-INH), inhibitor of the first complement system component, attacks are not histamine-mediated and do not respond to antihistamines or corticosteroids. Low awareness and resemblance to other disorders often delay diagnosis; despite availability of C1-INH replacement in some countries, no approved, safe acute attack therapy exists in the United States. The biennial C1 Esterase Inhibitor Deficiency Workshops resulted from a European initiative for better knowledge and treatment of HAE and related diseases. This supplement contains work presented at the third workshop and expanded content toward a definitive picture of angioedema in the absence of allergy. Most notably, it includes cumulative genetic investigations; multinational laboratory diagnosis recommendations; current pathogenesis hypotheses; suggested prophylaxis and acute attack treatment, including home treatment; future treatment options; and analysis of patient subpopulations, including pediatric patients and patients whose angioedema worsened during pregnancy or hormone administration. Causes and management of acquired angioedema and a new type of angioedema with normal C1-INH are also discussed. Collaborative patient and physician efforts, crucial in rare diseases, are emphasized. This supplement seeks to raise awareness and aid diagnosis of HAE, optimize treatment for all patients, and provide a platform for further research in this rare, partially understood disorder.

Transitory ascites demonstrated by abdominal US is a clue to the diagnosis of an acute abdominal attack of HAE. The possibility of HAE should always be considered whenever unexplained abdominal pain recurs with or without ascites.

There was no significant difference in the effectiveness and in the number of minor and major complications between fibroids with <10 cm largest diameter compared to those >10 cm.

PurposeOur study aimed to evaluate the technical success rate, interobserver reproducibility, and accuracy of shearwave elastography (SWE) in the staging of hepatitis C virus (HCV)‐associated liver fibrosis.MethodsA total of 10 healthy controls and 49 patients with chronic liver disease were enrolled prospectively. Two examiners performed point shearwave elastography (pSWE) and two‐dimensional shearwave elastography (2D‐SWE) measurements with an RS85A ultrasound scanner using the S‐Shearwave application (Samsung Medison, Hongcheon, Korea). The performance of S‐Shearwave in the staging (METAVIR F0‐F4) of liver fibrosis was compared with prior transient elastography (TE) with receiver operating characteristic (ROC) curve analysis.ResultsThe interobserver reproducibility was excellent with pSWE (ICC = 0.92, 95% CI: 0.86‐0.95, P < .001). A very good agreement was found between pSWE and TE measurements (ICC =0.85, 95% CI: 0.78‐0.89, P < .001). The ROC analysis determined the optimal cut‐off values of pSWE for the staging of chronic hepatitis C‐associated fibrosis (F2, 1.46 m/s; F3, 1.63 m/s; F4, 1.95 m/s). Both observers achieved excellent diagnostic accuracy (AUROC: 94% vs 97%) in the detection of significant (≥F2) liver fibrosis.ConclusionThe interobserver agreement is excellent with S‐Shearwave pSWE, and observers can diagnose significant liver fibrosis with a comparable accuracy to TE.

Background CT texture analysis (CTTA) has been successfully used to assess tissue heterogeneity in multiple diseases. The purpose of this work is to demonstrate the value of three-dimensional CTTA in the evaluation of diffuse liver disease. We aimed to develop CTTA based prediction models, which can be used for staging of fibrosis in different anatomic liver segments irrespective of variations in scanning parameters. Methods We retrospectively collected CT scans of thirty-two chronic hepatitis patients with liver fibrosis. The CT examinations were performed on either a 16- or a 64-slice scanner. Altogether 354 anatomic liver segments were manually highlighted on portal venous phase images, and 1117 three-dimensional texture parameters were calculated from each segment. The segments were divided between groups of low-grade and high-grade fibrosis using shear-wave elastography. The highly-correlated features (Pearson r > 0.95) were filtered out, and the remaining 453 features were normalized and used in a classification with k-means and hierarchical cluster analysis. The segments were split between the train and test sets in equal proportion (analysis I) or based on the scanner type (analysis II) into 64-slice train 16-slice validation cohorts for machine learning classification, and a subset of highly prognostic features was selected with recursive feature elimination. Results A classification with k-means and hierarchical cluster analysis divided segments into four main clusters. The average CT density was significantly higher in cluster-4 (110 HU ± SD = 10.1HU) compared to the other clusters (c1: 96.1 HU ± SD = 11.3HU; p < 0.0001; c2: 90.8 HU ± SD = 16.8HU; p < 0.0001; c3: 93.1 HU ± SD = 17.5HU; p < 0.0001); but there was no difference in liver stiffness or scanner type among the clusters. The optimized random forest classifier was able to distinguish between low-grade and high-grade fibrosis with excellent cross-validated accuracy in both the first and second analysis (AUC = 0.90, CI = 0.85–0.95 vs. AUC = 0.88, CI = 0.84–0.91). The final support vector machine model achieved an excellent prediction rate in the second analysis (AUC = 0.91, CI = 0.88–0.94) and an acceptable prediction rate in the first analysis (AUC = 0.76, CI = 0.67–0.84). Conclusions In conclusion, CTTA-based models can be successfully applied to differentiate high-grade from low-grade fibrosis irrespective of the imaging platform. Thus, CTTA may be useful in the non-invasive prognostication of patients with chronic liver disease.