No abstract

Perfluorocarbon (PFC) emulsions can be imaged directly by fluorine-19 MRI. We developed an optimized protocol for preparing PFC droplets of uniform size, evaluated use of the resulting droplets as blood pool contrast agents, studied their uptake by tumours and determined the spatial resolution with which they can be imaged at 4.7 T. Perfluorocarbon droplets of three different average sizes (324, 293 and 225 nm) were prepared using a microemulsifier. Images of PFC droplets with good signal-to-noise ratio were acquired with 625 microm in-plane resolution, 3 mm slice thickness and acquisition time of approximately 4.5 min per image. Kinetics of washout were determined using a simple mathematical model. The maximum uptake of the PFC droplets was three times greater at the tumour rim than in muscle, but the washout rate was two to three times slower in the tumour. The results are consistent with leakage of the droplets into the tumour extravascular space due to the hyper-permeability of tumour capillaries. PFC droplets may allow practical and quantitative measurements of blood volume and capillary permeability in tumours with reasonable spatial resolution.

A significant difference was found between the two types of needles in terms of reduced visualization of the 25G needle and suboptimal performance rating. However, this did not impact on overall results since both needles were equally successful in terms of a high diagnostic yield and overall accuracy.

Aim: It is well known that endoscopic ultrasound guided fine needle aspiration (EUS-FNA) has a high sensitivity (over 85%) and specificity (100%) for diagnosis of pancreatic cancer. The aim of the study was to establish a EUS based clinical diagnostic algorithm in patients with pancreatic masses and negative cytopathology after EUS-FNA, based on previously published results and cut-offs of real-time elastographic (RTE) EUS and contrast-enhanced harmonic (CEH) EUS. Material and methods: We included in the study a subgroup of 50 consecutive patients with focal pancreatic masses which underwent EUS examinations with negative EUS-FNA. RTE-EUS and CEH-EUS were performed sequentially in all patients. The sensitivity, specificity and accuracy of these methods were calculated separately. A clinical decision algorithm based on elastography followed by CEH was established. Results: For the diagnosis of possible malignancy, the sensitivity, specificity and accuracy of RTE-EUS were: 97.7%, 77.4%, and 84% respectively. CEH-EUS had similar results: 89.5%, 80.7%, and 84%, respectively. In 25 patients with soft/mixed appearance during elastography,sequential assessment using contrast-enhanced EUSwas performed. The specificity of CEH-EUS for detection of chronic pancreatitis in this sub-set of patients was excellent (100%). In other 25 patients with hard appearance in elastography (low strain) CEH-EUS had an excellent specificity (100%) and accuracy (93%) in the detection of pancreatic cancer. Conclusions: The proposed algorithm with sequential use of elastography followed by CEH could be a good clinical tool in the set of patients with negative EUS-FNA results for the differentiation between benign and malignant focal pancreatic masses.

Gastrointestinal cancers represent a major cause of morbidity and mortality, with incomplete response to chemotherapy in the advanced stages and poor prognosis. Angiogenesis plays a crucial part in tumor growth and metastasis, with most gastrointestinal cancers depending strictly on the development of a new and devoted capillary network. Confocal laser endomicroscopy is a new technology which allows in vivo microscopic analysis of the gastrointestinal mucosa and its microvascularization during ongoing endoscopy by using topically or systemically administered contrast agents. Targeting markers of angiogenesis in association with confocal laser endomicroscopic examination (immunoendoscopy), as a future challenge, will add functional analysis to the morphological aspect of the neoplastic process. This review describes previous experience in endomicroscopic examination of the upper and lower digestive tract with emphasis on vascularization, resulting in a broad spectrum of potential clinical applications, and also preclinical research that could be translated to human studies.

Power Doppler EUS provides useful information for the differential diagnosis of pancreatic masses. The results were in concordance with previous studies that showed a hypovascular pattern of pancreatic carcinoma, as well as the formation of collaterals in advanced cases due to the invasion of the splenic or portal veins. Further studies of dynamic EUS with contrast agents are necessary to better characterize pancreatic masses.

Differential diagnosis of focal pancreatic masses is based on endoscopic ultrasound (EUS) guided fine needle aspiration biopsy (EUS-FNA/FNB). Several imaging techniques (i.e. gray-scale, color Doppler, contrast-enhancement and elastography) are used for differential diagnosis. However, diagnosis remains highly operator dependent. To address this problem, machine learning algorithms (MLA) can generate an automatic computer-aided diagnosis (CAD) by analyzing a large number of clinical images in real-time. We aimed to develop a MLA to characterize focal pancreatic masses during the EUS procedure. The study included 65 patients with focal pancreatic masses, with 20 EUS images selected from each patient (grayscale, color Doppler, arterial and venous phase contrast-enhancement and elastography). Images were classified based on cytopathology exam as: chronic pseudotumoral pancreatitis (CPP), neuroendocrine tumor (PNET) and ductal adenocarcinoma (PDAC). The MLA is based on a deep learning method which combines convolutional (CNN) and long short-term memory (LSTM) neural networks. 2688 images were used for training and 672 images for testing the deep learning models. The CNN was developed to identify the discriminative features of images, while a LSTM neural network was used to extract the dependencies between images. The model predicted the clinical diagnosis with an area under curve index of 0.98 and an overall accuracy of 98.26%. The negative (NPV) and positive (PPV) predictive values and the corresponding 95% confidential intervals (CI) are 96.7%, [94.5, 98.9] and 98.1%, [96.81, 99.4] for PDAC, 96.5%, [94.1, 98.8], and 99.7%, [99.3, 100] for CPP, and 98.9%, [97.5, 100] and 98.3%, [97.1, 99.4] for PNET. Following further validation on a independent test cohort, this method could become an efficient CAD tool to differentiate focal pancreatic masses in real-time.

In this paper we discuss the construction and consolidation of the political brand 'The Tribune-Jester' in relation to the use of ethnic humor in the form of joking in Romanian parliamentary discourse by a controversial political figure of Romanian politics, Corneliu Vadim Tudor. The data come from transcripts of the meetings from the internet section 'Parliamentary Debates' of the Senate and are analyzed using concepts from discourse analysis, pragmatics and conversation analysis. Under the guise of humor, the Member of Parliament (MP) profits by the rules of parliamentary politics and succeeds in portraying himself as a populist politician, in rebelling against the establishment and in voicing his nationalistic attitudes.