Neuromonitoring Using Neurosonography and Pupillometry in A Weaning and Early Neurorehabilitation Unit

Point-of-Care Ultrasound in Neurology - Report of the EAN SPN/ESNCH/ERcNsono Neuro-POCUS Working Group

In the last decade, ultrasound examination in neurology has been undergoing a significant expansion of its modalities. In parallel, there is an increasing demand for rapid and high-quality diagnostics in various acute diseases in the prehospital setting, the emergency room, intensive care unit, and during surgical or interventional procedures. Due to the growing need for rapid answers to clinical questions, there is particular demand for diagnostic ultrasound imaging. The Neuro-POCUS working group, a joint project by the European Academy of Neurology Scientific Panel Neurosonology, the European Society of Neurosonology and Cerebral Hemodynamics, and the European Reference Centers in Neurosonology (EAN SPN/ESNCH/ERcNsono Neuro-POCUS working group), was given the task of creating a concept for point-of-care ultrasound in neurology called "Neuro-POCUS". We introduce here a new ultrasound examination concept called point-of-care ultrasound in neurology (Neuro-POCUS) designed to streamline conclusive imaging outside of the ultrasound center, directly at the bedside. The aim of this study is to encourage neurologists to add quick and disease-oriented Neuro-POCUS to accompany the patient in the critical phase as an adjunct not a substitution for computed tomography, magnetic resonance imaging, or standard comprehensive neurosonology examination. Another goal is to avoid unwanted complications during imaging-free periods, ultimately resulting in advantages for the patient.

An Automated Algorithm for Optic Nerve Sheath Diameter Assessment from B-mode Ultrasound Images

BACKGROUND AND PURPOSE

The optic nerve sheath diameter (ONSD) is a promising surrogate marker for the detection of raised intracranial pressure (ICP). However, inconsistencies in manual ONSD assessment are thought to affect ONSD and the corresponding ONSD cutoff values for the diagnosis of elevated ICP, hereby hampering the full potential of ONSD. In this study, we developed an image intensity-invariant algorithm to automatically estimate ONSD from B-mode ultrasound images at multiple depths.

METHODS

The outcomes of the algorithm were validated against manual ONSD measurements by two human experts. Each expert analyzed the images twice (M1 and M2) in unknown order.

RESULTS

The algorithm proved capable of segmenting the ONSD in 39 of 42 images, hereby showing mean differences of -.08 ± .45 and -.05 ± .41 mm compared to averaged ONSD values (M1 + M2/2) of Operator 1 and Operator 2, respectively, whereas the mean difference between the two experts was .03 ± .26 mm. Moreover, differences between algorithm-derived and expert-derived ONSD values were found to be much smaller than the 1 mm difference that is expected between patients with normal and elevated ICP, making it likely that our algorithm can distinguish between these patient groups.

CONCLUSIONS

Our algorithm has the potential to improve the accuracy of ONSD as a surrogate marker for elevated ICP because it has no intrinsic variability. However, future research should be performed to validate if the algorithm does indeed result in more accurate noninvasive ICP predictions.