Search

Glaucoma is a widespread ophthalmological disease, with a high impact and frequent visual morbidity. While the physiopathology of the two types of primary glaucoma (open angle and angle closure) has been studied, there seems to be little relationship between the two. In this study, we gather clinical and preclinical data to support the idea that the two primary glaucomas are “mirrored” in terms of morphological parameters and disease physiopathology. In short, primary angle closure glaucoma (PACG) is associated with hyperopia and low axial length, and primary open angle glaucoma (POAG) is associated with myopia and high axial length. Moreover, in PACG and in primary angle closure or primary angle closure suspect cases, while there is extensive iridotrabecular contact, the intraocular pressure (IOP) is still maintained in the lower half of the normal range throughout the evolution of the disease, which suggests a baseline trabecular hyperfiltration in PACG. In the opposite case, myopic eyes with open angles and a higher risk of developing POAG often have a baseline IOP in the upper half of the normal range, suggesting a baseline trabecular hypofiltration. As we explore clinical, genetic and animal model data regarding these opposing aspects, we hypothesize the existence of a mirroring relationship between PACG and POAG. Defining the relationship between the two potentially blinding diseases, with a high prevalence worldwide, may aid in understanding the mechanisms better and refining diagnosis and treatment. Thus, our theory has been named the Mirror Theory of Primary Glaucomas.

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.

Background: The coronavirus disease 2019 pandemic (COVID-19) is the most important global health crisis to date. In this study, we performed an analysis to find the association between liver damage, FIB-4 score and the severity of COVID-19 disease. Methods: We included a total of 580 patients that tested positive for SARS-CoV-2 infection and were hospitalized. No patient included had any known history of liver disease. Liver function tests were performed, and FIB-4 score was calculated in order to assess their involvement in the disease progression. Results: More than half of the patients had elevated liver function tests. Age, high body mass index, associated heart disease and diabetes were associated with poor outcome. Corticosteroids, antibiotics, and anticoagulants strongly correlated with liver injuries. Liver impairment and injury, as well as a FIB-4 score higher than 3.5, also correlated with higher degrees of disease severity. Conclusion: Liver injury and elevated FIB-4 score were associated with poor clinical outcome and disease severity, as well as being a valuable tool to predict COVID-19-related mortality.

The tumor microcirculation is characterized by an abnormal vascular network with dilated, tortuous and saccular vessels. Therefore, imaging the tumor vasculature and determining its morphometric characteristics represent a critical goal for optimizing the cancer treatment that targets the blood vessels (i.e. antiangiogenesis therapy). The aim of this study was to evaluate new vascular morphometric parameters in colorectal cancer, difficult to achieve through conventional immunohistochemistry, by using the confocal laser endomicroscopy method. Fresh biopsies from tumor and normal tissue were collected during colonoscopy from five patients with T3 colorectal carcinoma without metastasis and were marked with fluorescently labeled anti-CD31 antibodies. A series of optical slices spanning 250 µm inside the tissue were immediately collected for each sample using a confocal laser endomicroscope. All measurements were expressed as the mean ± standard error. The mean diameter of tumor vessels was significantly larger than the normal vessels (9.46±0.4 µm vs. 7.60±0.3 µm, p = 0.0166). The vessel density was also significantly higher in the cancer vs. normal tissue samples (5541.05±262.81 vs. 3755.79±194.96 vessels/mm3, p = 0.0006). These results were confirmed by immunohistochemistry. In addition, the tortuosity index and vessel lengths were not significantly different (1.05±0.016 and 28.30±3.27 µm in normal tissue, vs. 1.07±0.008 and 26.49±3.18 µm in tumor tissue respectively, p = 0.5357 and p = 0.7033). The daughter/mother ratio (ratio of the sum of the squares of daughter vessel radii over the square of the mother vessel radius) was 1.15±0.09 in normal tissue, and 1.21±0.08 in tumor tissue (p = 0.6531). The confocal laser endomicroscopy is feasible for measuring more vascular parameters from fresh tumor biopsies than conventional immunohistochemistry alone. Provided new contrast agents will be clinically available, future in vivo use of CLE could lead to identification of novel biomarkers based on the morphometric characteristics of tumor vasculature.

INTRODUCTION: 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. MATERIALS AND METHODS: 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. RESULTS: 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/mm(2) in the normal tissue vs. 242.4±16.1 vessels/mm(2) in the colorectal cancer samples (p = 0.1201). In the immunohistochemistry samples, the MVD was 211.2±42.9/mm(2) and 351.3±39.6/mm(2) 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. CONCLUSION: 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.