The 2016 Surviving Sepsis Campaign guidelines define sepsis as life-threatening organ dysfunction caused by a dysregulated host response to infection. This study had the objective of assessing the efficacy of presepsin in the prognosis of sepsis. This was a single-center prospective study, performed in Craiova Emergency Hospital, that included 114 patients admitted in the Intensive Care Unit (ICU) department between 2018 and 2019 fulfilling the sepsis criteria. Including criteria were: age ≥ 18, sepsis diagnosed by the Sequential Organ Failure Assessment (SOFA) score of pulmonary, abdominal, urinary, surgical or unknown origin, as well as lactate levels ≥ 2 mmol/l and need of vasopressors for mean arterial pressure (MAP) ≥ 65 mmHg, despite adequate volume resuscitations for patients with septic shock. Patients younger than 18, pregnant, immunocompromised, or with terminal illnesses were excluded. Based on disease severity, patients were distributed into two study groups: sepsis—76 patients and septic shock—38 patients. As expected, SOFA score and most of its components (PaO₂/FiO₂, platelets, and Glasgow Coma Score (GCS)) were significantly modified for patients with septic shock compared to those in the sepsis group and for survivors versus non-survivors. Overall death rate was 34.2%, with a significantly higher value for patients with septic shock (55.3% vs. 23.7%, p = 0.035). Sepsis marker presepsin was significantly elevated in all patients (2047 ng/mL) and significantly increased for the septic shock patients (2538 ng/mL, p < 0.001) and non-survivors (3138 ng/mL, p < 0.001). A significant correlation was identified between the SOFA score and presepsin (r = 0.883, p < 0.001). The receiver operating characteristics (ROC)-Area Under Curve (AUC) analysis showed significant prognostic values for presepsin regarding both sepsis severity (AUC = 0.726, 95% confidence interval CI = 0.635–0.806) and mortality risk (AUC = 0.861, 95%CI = 0.784–0.919). In conclusion, under the revised definition of sepsis, presepsin could be a useful marker for prognosis of sepsis severity and mortality risk. Additional data are required to confirm the value of presepsin in sepsis prognosis.

Numerous anti-angiogenic agents are currently developed to limit tumor growth and metastasis. While these drugs offer hope for cancer patients, their transient effect on tumor vasculature is difficult to assess in clinical settings. Confocal laser endomicroscopy (CLE) is a novel endoscopic imaging technology that enables histological examination of the gastrointestinal mucosa. The aim of the present study was to evaluate the feasibility of using CLE to image the vascular network in fresh biopsies of human colorectal tissue. For this purpose we have imaged normal and malignant biopsy tissue samples and compared the vascular network parameters obtained with CLE with established histopathology techniques. Fresh non-fixed biopsy samples of both normal and malignant colorectal mucosa were stained with fluorescently labeled anti-CD31 antibodies and imaged by CLE using a dedicated endomicroscopy system. Corresponding biopsy samples underwent immunohistochemical staining for CD31, assessing the microvessel density (MVD) and vascular areas for comparison with CLE data, which were measured offline using specific software. The vessels were imaged by CLE in both normal and tumor samples. The average diameter of normal vessels was 8.5±0.9 µm whereas in tumor samples it was 13.5±0.7 µm (p = 0.0049). Vascular density was 188.7±24.9 vessels/mm² in the normal tissue vs. 242.4±16.1 vessels/mm² in the colorectal cancer samples (p = 0.1201). In the immunohistochemistry samples, the MVD was 211.2±42.9/mm² and 351.3±39.6/mm² for normal and malignant mucosa, respectively. The vascular area was 2.9±0.5% of total tissue area for the normal mucosa and 8.5±2.1% for primary colorectal cancer tissue. Selective imaging of blood vessels with CLE is feasible in normal and tumor colorectal tissue by using fluorescently labeled antibodies targeted against an endothelial marker. The method could be translated into the clinical setting for monitoring of anti-angiogenic therapy.

Despite significant advances in imaging techniques, the incidence of colorectal cancer has been increasing in recent years, with many cases still being diagnosed in advanced stages. Early detection and accurate staging remain the main factors that lead to a decrease in the cost and invasiveness of the curative techniques, significantly improving the outcome. However, the diagnosis of pedunculated early colorectal malignancy remains a current challenge. Data on the management of pedunculated cancer precursors, apart from data on nonpolypoid lesions, are still limited. An adequate technique for complete resection, which provides the best long-term outcome, is mandatory for curative intent. In this context, a discussion regarding the diagnosis of malignancy of pedunculated polyps, separate from non-pedunculated variants, is necessary. The purpose of this review is to provide a critical review of the most recent literature reporting the different features of malignant pedunculated colorectal polyps, including diagnosis and management strategies.

Contrast-enhanced ultrasound (CEUS) is widely used in the characterization of liver tumors; however, the evaluation of perfusion patterns using CEUS has a subjective character. This study aims to evaluate the accuracy of an automated method based on CEUS for classifying liver lesions and to compare its performance with that of two experienced clinicians. The system used for automatic classification is based on artificial intelligence (AI) algorithms. For an interpretation close to the clinical setting, both clinicians knew which patients were at high risk for hepatocellular carcinoma (HCC), but only one was aware of all the clinical data. In total, 49 patients with 59 liver tumors were included. For the benign and malignant classification, the AI model outperformed both clinicians in terms of specificity (100% vs. 93.33%); still, the sensitivity was lower (74% vs. 93.18% vs. 90.91%). In the second stage of multiclass diagnosis, the automatic model achieved a diagnostic accuracy of 69.93% for HCC and 89.15% for liver metastases. Readers demonstrated greater diagnostic accuracy for HCC (83.05% and 79.66%) and liver metastases (94.92% and 96.61%) compared to the AI system; however, both were experienced sonographers. The AI model could potentially assist and guide less-experienced clinicians to discriminate malignant from benign liver tumors with high accuracy and specificity.

Recent advances in the field of ultrasonography offer promising tools for the evaluation of liver tumors. We aim to assess the value of multimodal ultrasound in differentiating hepatocellular carcinomas (HCCs) from other liver lesions. We prospectively included 66 patients with 72 liver tumors. The histological analysis was the reference standard for the diagnosis of malignant liver lesions, and partially for benign tumors. All liver lesions were assessed by multiparametric ultrasound: standard ultrasound, contrast-enhanced ultrasound (CEUS), the point shear wave elastography (pSWE) using shear wave measurement (SWM) method and real-time tissue elastography (RTE). To diagnose HCCs, CEUS achieved a sensitivity, specificity, accuracy and positive predictive value (PPV) of 69.05%, 92.86%, 78.57% and 93.55%, respectively. The mean shear-wave velocity (Vs) value in HCCs was 1.59 ± 0.29 m/s, which was lower than non-HCC malignancies (p < 0.05). Using a cut-off value of 1.58 m/s, SWM achieved a sensitivity of 54.76%, and 82.35% specificity, for differentiating HCCs from other malignant lesions. The combination of SWM and CEUS showed higher sensitivity (79.55%) compared with each technique alone, while maintaining a high specificity (89.29%). In RTE, most HCCs (61.53%) had a mosaic pattern with dominant blue areas corresponding to type “c” elasticity. Elasticity type “c” was 70.59% predictive for HCCs. In conclusion, combining B-mode ultrasound, CEUS, pSWE and RTE can provide complementary diagnostic information and potentially decrease the requirements for other imaging modalities.