No abstract

Central venous catheter misplacement is common (approximately 7%) after right subclavian vein catheterisation. To avoid it, ultrasound-guided tip navigation may be used during the catheterisation procedure to help direct the guidewire towards the lower superior vena cava. We aimed to determine the number of central venous catheter misplacements when using the right supraclavicular fossa ultrasound view to aid guidewire positioning in right infraclavicular subclavian vein catheterisation. We hypothesised that the incidence of catheter misplacements could be reduced to 1% when using this ultrasound technique. One -hundred and three adult patients were prospectively included. After vein puncture and guidewire insertion, we used the right supraclavicular fossa ultrasound view to confirm correct guidewire J-tip position in the lower superior vena cava and corrected the position of misplaced guidewires using real-time ultrasound guidance. Successful catheterisation of the right subclavian vein was achieved in all patients. The guidewire J-tip was initially misplaced in 15 patients, either in the ipsilateral internal jugular vein (n = 8) or in the left brachiocephalic vein (n = 7). In 12 patients it was possible to adjust the guidewire J-tip to a correct position in the lower superior vena cava. All ultrasound-determined final guidewire J-tip positions were consistent with the central venous catheter tip positions on chest X-ray. Three out of 103 catheters were misplaced, corresponding to an incidence (95%CI) of 2.9 (0.6-8.3) %. Although the hypothesis could not be confirmed, this study demonstrated the usefulness of the right supraclavicular fossa ultrasound view for real-time confirmation and correction of the guidewire position in right infraclavicular subclavian vein catheterisation.

The gold standard for the quantitative evaluation of steatosis is liver biopsy, but this is an invasive method. The recent trend is to investigate and develop novel non-invasive hepatic tissue evaluation methods, able to give performances close to biopsy, one of the possible solutions being ultrasound image analysis. Finding the most suitable descriptors of the histological tissue changes (invariant to the ultrasound device and patient) in this imaging modality is an important issue. Several such descriptors are reported in the literature, starting from simple intensity parameters to more sophisticated ones. Here we investigate the discrimination ability of the hepatic steatosis as opposed to healthy tissue by a set of computationally simple features, extracted from the gray level histogram of a small sized region of interest (ROI) positioned at three depths in the ultrasound hepatic image. The advantage of finding computationally simple features, as intensity histogram extracted features, can be the possibility to include their computation directly in ultrasound devices, provided they offer good tissue discrimination. The in-depth variations of some of the features investigated in this paper show a good discrimination in steatosis evaluation and quantification, close to the state of the art in the field.