Pancreatico-duodenal artery aneurysm (PDAA) associated with stenosis or occlusion of the celiac trunk is a rare condition. Furthermore, PDAAs associated with stenosis of the superior mesenteric artery (SMA) are even more uncommon, with only six cases reported in the literature. We report a case of a 61-year old male patient who presented with hematemesis, haematochezia and haemorrhagic shock. The upper gastrointestinal endoscopy revealed an ulcerous lesion at the third portion of the duodenum, without achieving the haemostasis. The emergency laparotomy (suture of the lesion and gastro-entero-anastomosis) permitted temporary haemostasis. Computed tomography angiography identified the PDAA ruptured into the third portion of the duodenum and the SMA stenosis at its origin; a dense network of collateral vessels was present. The patient was successfully managed with coil embolization. Short and mid-term follow-up were without incidents.

The ability of texture analysis (TA) features to discriminate between different types of infected fluid collections, as seen on computed tomography (CT) images, has never been investigated. The study comprised forty patients who had pathological post-operative fluid collections following gastric cancer surgery and underwent CT scans. Patients were separated into six groups based on advanced microbiological analysis of the fluid: mono bacterial (n = 16)/multiple-bacterial (n = 24)/fungal (n = 14)/non-fungal (n = 26) infection and drug susceptibility tests into: multiple drug-resistance bacteria (n = 23) and non-resistant bacteria (n = 17). Dedicated software was used to extract the collections’ TA parameters. The parameters obtained were used to compare fungal and non-fungal infections, mono-bacterial and multiple-bacterial infections, and multiresistant and non-resistant infections. Univariate and receiver operating characteristic analyses and the calculation of sensitivity (Se) and specificity (Sp) were used to identify the best-suited parameters for distinguishing between the selected groups. TA parameters were able to differentiate between fungal and non-fungal collections (ATeta3, p = 0.02; 55% Se, 100% Sp), mono and multiple-bacterial (CN2D6AngScMom, p = 0.03); 80% Se, 64.29% Sp) and between multiresistant and non-multiresistant collections (CN2D6Contrast, p = 0.04; 100% Se, 50% Sp). CT-based TA can statistically differentiate between different types of infected fluid collections. However, it is unclear which of the fluids’ micro or macroscopic features are reflected by the texture parameters. In addition, this cohort is used as a training cohort for the imaging algorithm, with further validation cohorts being required to confirm the changes detected by the algorithm.

Background: Hepatocellular carcinoma (HCC) is one of the most frequent cancers worldwide, with a high mortality. Most patients present with late stage disease, when the treatment options are limited to systemic chemotherapy. The purpose of our study was to evaluate the significance of p53 and EGFR expression in HCC, and to determine whether these two markers correlate with conventional parameters of prognosis. Materials and Methods: Our study included a total of 45 patients, diagnosed histopathologically with HCC. Clinicopathological data including sex, age, tumor necrosis, tumor size, histologic grading, tumor stage, the presence of cirrhosis and chronic hepatitis, were recorded from the Institute database. Three independent microscopic fields were selected for each sample and all the tumor cells within each microscopic field were counted, and then the positive percent of p53 cells were calculated. Three staining patterns were recognized: diffuse, heterogenous and focal. The intensity of EGFR staining was scored on a scale of 0-3+: 0 no staining; 1+ when a weak membrane staining was observed; 2+ when membrane staining is more intense than in 1+, but less than 3+, and 3+ when intense dark brown staining delineated the membrane. To determine the relationship between EGFR expression and p53, we performed double staining in the same HCC specimens. Results: By immunohistochemical staining, p53 protein was detected in tumor cell nuclei in 20 HCCs (44%). We found a significant correlation between the intensity of p53 expression and the histological grade (p=0.008). EGFR expression was detected in 17 (38%) cases, linked to histological grade (p=0.039). Moreover, the intensity of p53 expression was significantly correlated with EGFR intensity (p=0.014). Conclusions: Our results suggest that overexpression of p53 and EGFR plays an important role in hepatocarcinogenesis and contributes to more advanced disease. These markers are not only valuable predictors of prognosis in HCC, but they are also rational targets for new anti-tumor strategies.