Poster Session 1, 2021 edition

This page gives an overview of title, presenter and abstract of all the poster presentations in the Poster Session 1 of the 2021 edition of the Point of Care Ultrasound conference. Find out more by opening this page.

The learningcurve for nurse-led ultrasound-guided peripheral intravenous cannulation in adult patients: a multicentre study
Fredericus H.J. van Loon, Catharina Hospital / Fontys Univerisity of Applied Sciences

Objectives: to lower the threshold for applying ultrasound guidance during peripheral intravenous cannulation, different nurses need to be trained and gain experience in using this technique. The current study focusses on the number of ultrasound-guided cannulations that are required in a fixed training curriculum before a nurse is competent.
Design: multicenter prospective observational study, divided into two phases after a theoretical training session.
Setting: the study was performed in a preoperative holding area of the theatre complex and on an oncology ward.
Participants: nurses followed a theory-based training, a hands-on training session and a supervised life-case training session.
Main outcome measures: the number of ultrasound-guided peripheral intravenous cannulations a participant needed to perform in the life-case setting to become competent. Cusum analysis was used to determine the learning curve of each individual participant. To add on this, interest was on the first attempt success rates and time needed regarding ultrasound-guided intravenous cannulation.
Results: 23 nurses participated, who performed 815 procedures. First attempt cannulation success was 70%, but increased to 98% on the fortieth attempt (P<0.001, χ2=19.64, df=1). The overall first attempt success rate during this study was 92%. The cusum learning curve for each practitioner showed that a mean number of 35 procedures was needed to achieve competency. Time needed to perform a procedure successfully decreased when more experience was achieved by the practitioner, from 14 ±4 minutes on first procedure to 3 ±1 minutes during the fortieth procedure (P<0.001, t=12.09).
Conclusion: competency in ultrasound-guided peripheral intravenous cannulation can be gained after following a fixed educational curriculum, resulting in an increased first attempt cannulation success as the number of performed procedures increased, while time required to obtain successful vascular access decreased.

Improving needle tip identification during ultrasound‐guided procedures in anaesthetic practice
Harm Scholten, Eindhoven University of Technology / Catharina Ziekenhuis

Ultrasound guidance is becoming standard practice for needle‐based interventions in anaesthetic practice, such as vascular access and peripheral nerve blocks. However, difficulties in aligning the needle and the transducer can lead to incorrect identification of the needle tip, possibly damaging structures not visible on the ultrasound screen. Additional techniques specifically developed to aid alignment of needle and probe or identification of the needle tip are now available. In this scoping review, advantages and limitations of the following categories of those solutions are presented: needle guides; alterations to needle or needle tip; three‐ and four‐dimensional ultrasound; magnetism, electromagnetic or GPS systems; optical tracking; augmented (virtual) reality; robotic assistance; and automated (computerised) needle detection. Most evidence originates from phantom studies, case reports and series, with few randomised clinical trials. Improved first‐pass success and reduced performance time are the most frequently cited benefits, whereas the need for additional and often expensive hardware is the greatest limitation to widespread adoption. Novice ultrasound users seem to benefit most and great potential lies in education. Future research should focus on reporting relevant clinical parameters to learn which technique will benefit patients most in terms of success and safety

Towards ultrasound-based flow monitoring in the CCA
Luuk van Knippenberg, Eindhoven University of Technology

Doppler ultrasound is the most common technique for non-invasive quantification of blood flow, which can be used to assess the cardiovascular condition. To estimate flow, the operator has to obtain a longitudinal image in which both Doppler angle and vessel diameter can be estimated. However, moving towards ultrasound-based monitoring, the need for an operator should be overcome. Previously, we showed that the Doppler angle can be estimated by fitting an ellipse to the vessel in cross-sectional ultrasound acquisitions, resulting in accurate angle-corrected velocities [1]. Yet, to achieve accurate estimates under various imaging conditions, thereby being operator-independent, the transmit parameters should adaptively be optimized.

In this work, we demonstrate an implementation on a research ultrasound system (Verasonics) that adaptively shifts the Doppler focus to the center of the vessel, varies the aperture width to realize a fixed F-number, and uses a steering angle that minimizes the Doppler angle. The velocity profile is estimated using a moving gate from which the average velocity is computed. The Verasonics sequence was tested in simulation mode, where various vessel orientations and positions were simulated.

Our simulations show that the transmit focus, steering angle and aperture width can be changed adaptively, enabling ultrasound-based flow monitoring. Compared to using non-steered beams, the estimated velocity profile and resulting average velocity are more accurate and have a smaller spread when adaptive beam steering is used (-1.9±10.5% and 5.6±14.4% error, respectively). In the future, we will also investigate the performance of the proposed method both in-vitro and in-vivo.

[1] L. Van Knippenberg et al. “An Angle-Independent Cross-Sectional Doppler Method for Flow Estimation in the Common Carotid Artery,” IEEE TUFFC, 2020.

Carotid Doppler Ultrasound for Non-Invasive Haemodynamic Monitoring: A Narrative Review
Irene Suriani, Eindhoven University of Technology

Accurate haemodynamic monitoring is the cornerstone in the management of critically ill patients. The assessment of volume status (VS), fluid responsiveness (FR), and cardiac output (CO) guides the optimization of tissue and organ perfusion in order to prevent multiple organ failure. Recently, carotid doppler ultrasound (CDU) has been proposed as a non-invasive alternative for long-established invasive haemodynamic monitoring techniques. Considering the large heterogeneity in reported studies, we conducted a review of the literature to clarify the current status of CDU as a haemodynamic monitoring tool. EMBASE, PubMed, Scopus, and Web of Science were systematically searched, and over 40 studies were collected. Results from the most studied CDU-derived parameters were evaluated in different clinical settings and the most promising parameters were identified. Furthermore, clinical usability, feasibility, repeatability, and technical limitations were addressed. Overall median Pearson’s correlation coefficient of all CDU-derived parameters to cardiac output was 0.49 (IQR*: 0.10-0.89), p<.001. Correlations, however, varied significantly depending on the chosen settings and parameters. We found CDU respirophasic peak velocity variation to be the most promising parameter for the prediction of FR, with an AUROC of 0.87 (IQR: 0.82-0.91), a sensitivity of 81% (IQR: 75-86), and a specificity of 87% (IQR: 83-90). In the assessment of VS, CDU corrected flow time showed an AUROC of 0.86 (IQR: 0.76-0.96), a sensitivity of 75% (IQR: 66-84), and a specificity of 80% (IQR: 72-87). Based on our review, we suggest new directions towards standardization of future research in this field and effective use of this tool in clinical practice.

Wireless Augmented Reality Point Of Care Ultrasound
Stefan Maas, SomaView GmbH

To create a highly portable POCUS-solution a prototype for a wireless and augmented reality (AR) based ultrasound system was build and evaluated regarding time delay and image quality of the sent virtual ultrasound images visible on the AR glasses.

Material and Methods
The system consists of:

  • Q7 Wireless ultrasound scanner (Youkey Medical; probe L11-4Ks)
  • ARNI-transmission-box (SomaView)
  • AR-glasses Hololens 2 (Microsoft)
  • optical marker
  • software:
    • SonoiQ (Youkey Medical)
    • ARNI (SomaView; server and client version)

The Q7 sends ultrasound images wirelessly to the SonoiQ-software, processed on the ARNI-transmission-box. The ARNI-server on the same box grabs the images and sends them wirelessly to the ARNI-client, running on the Hololens 2.
The user views the virtual ultrasound images as AR-content
a) on a virtual screen in the Hololens 2 and,
b) due to the optical marker, directly beneath the Q7, superimposed over the currently scanned anatomical structures. This setup allows a direct AR-view into the human body.

The ARNI-prototype presents the AR-content in the Hololens 2 with a delay of <0.2 seconds delay and image quality were rated acceptable by the users. The ultrasound images beneath the transducer were rated as too small for some applications.

A combination of a wireless ultrasound scanner, AR-glasses and suitable AR-software can be used as a highly portable POCUS-solution. Further studies should explore ergonomic and accuracy aspects.

Automated ultrasound methods for cerebral blood flow velocity measurement in point-of-care settings
Jonathan Fincke, Philips Research North America

Transcranial ultrasound (TCD) exams could gain wider adoption in point-of-care settings for conditions such as traumatic brain injury and stroke if less experienced ultrasound users are able to confidently perform the exam. In this work, we describe our efforts to simplify the assessment of blood flow velocity in the middle cerebral artery (MCA) during a TCD exam using AI-based detection of the MCA. Such an assessment enables a non-invasive measurement of the intracranial pressure (ICP) using previously developed physiological model-based approaches. Ultrasound data (B-mode and Color Doppler, 2D and 3D data, about 21,000 images from 19 subjects) were collected from healthy human subjects using the Philips CX50 and Epiq ultrasound systems and separated into training, validation and test data sets. A tiny-yolo-v3 network architecture was trained to automatically detect and localize the MCA. Our results showed an accuracy of 90% accuracy with a sensitivity of 89% sensitivity and a specificity of 91% on test data sets for automated MCA localization. Such performance could provide an automated measurement of the blood flow velocity, which would enable ICP estimation when combined with appropriate physiological models. Our results show that it is possible deploy semi-autonomous TCD ultrasound systems that require less skill to operate.

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