Sedation and Analgesia for Toxic Epidermal Necrolysis in the Intensive Care Unit: Few Certainties, Many Questions Ahead.

Toxic epidermal necrolysis (TEN) is a rare, acute mucocutaneous life-threatening disease. Although research has focused on the pathophysiological and therapeutic aspects of the disease, there is a paucity of data in the literature regarding pain management and sedation in the intensive care unit (ICU). Most therapies have been extrapolated from other situations and/or the general ICU population. These patients present unique challenges during the progression of the disease and could end up requiring invasive mechanical ventilation due to inadequate pain management, which is potentially avoidable through a comprehensive treatment approach. In this review, we will present clinical and pathophysiological aspects of TEN, analyze pain pathways and relevant pharmacology, and propose therapeutic alternatives based on a rational and multimodal approach.

Modified Regularized Wavelength Average Velocity Estimator for normal excitation setup.

Crawling Waves Sonoelastography (CWS) is an ultrasound elastography approach for the Shear Waves Speed (SWS) estimation. Several studies show promising results for tissue characterization. The algorithms used to calculate the SWS have been commonly implemented considering an opposing vibration sources to the side of the tissue of interest. However, implementing this mechanical setup has important limitations considering the geometry of the body. For that reason, a propagation from the top to the surface can be useful. Previous estimators such as Phase Derivative have been modified and tested in phantom studies, however, the presences of artifacts limited the performed of the SWS map. In this study, the Regularized Wavelength Average Velocity Estimator (R-WAVE) technique is modified and evaluated (RWm) to be used for normal propagation. The results of heterogeneous simulations and phantoms experiments showed consistent results with the literature (ie: Simulations Max Bias PDm 11.64 % • RWm 10.21 %, Max CNR PDm 37.82 dB • RWm 44.42 dB, Phantom Experiments Max Bias PDm 15.42 % • RWm 13.99 %, Max CNR PDm 24.14 dB • RWm 26.40 dB). The result of this study shows the potential of RWm to characterize the stiffness of the tissue as well as to differentiate tumors on in vivo applications.Clinical relevance This study presents a modification of the regularized shear wave speed estimator based on crawling waves sonoelastography approach for medical tissue analysis. This technique can be used to discriminate benignant from malignant tumors.

Shear Wave Speed estimator using Continuous Wavelet Transform for Crawling Wave Sonoelastography.

Crawling Wave Sonoelastography (CWS) is an elastography ultrasound-based imaging approach that provides tissue stiffness information through the calculation of Shear Wave Speed (SWS). Many SWS estimators have been developed; however, they report important limitations such as the presence of artifacts, border effects or high computational cost. In addition, these techniques require a moving interference pattern which could be challenging for in vivo applications. In this study, a new estimator based on the Continuous Wavelet Transform (CWT) is proposed. This allows the generation of a SWS image for every sonoelasticity video frame. Testing was made with data acquired from experiments conducted on a gelatin phantom with a circular inclusion. It was excited with two vibration sources placed at both sides with frequencies ranging from 200 Hz to 360 Hz in steps of 20 Hz. Results show small variation of the SWS image across time. Additionally, images were compared with the Phase Derivative method (PD) and the Regularized Wavelength Average Velocity Estimator (R-WAVE). Similar SWS values were obtained for the three estimators within a certain region of interest in the inclusion (At 360 Hz, CWT: 5.01±0.2m/s, PD: 5.11±0.28m/s, R-WAVE: 4.51±0.62m/s) and in the background (At 360 Hz, CWT: 3.67±0.15m/s, PD: 3.69±0.23m/s, R-WAVE: 3.58±0.24m/s). CWT also presented the lowest coefficient of variation and the highest contrast-to-noise ratio for most frequencies, which allows better discrimination between regions.Clinical relevance-This study presents a new Shear Wave Speed estimator for Crawling Wave Sonoelastography, which can be useful to characterize soft tissue and detect lesions.