International consensus on anatomical structures to identify on ultrasound for the performance of basic blocks in ultrasound-guided regional anesthesia

Building Blocks-A Block-by-Block Approach to Better Emergency Care in Children

OBJECTIVE

We describe a case series of regional nerve blocks, which comprise an adapted framework for the pediatric emergency setting and were performed by pediatric emergency medicine physicians.

METHODS

A case series of 8 different ultrasound-guided nerve blocks and 1 anatomical block, performed in 11 pediatric patients, aged 7 weeks to 17 years.

RESULTS

All blocks resulted in adequate analgesia. No procedural complications were observed.

CONCLUSION

We describe a set of nerve blocks performed by emergency medicine physicians in the pediatric population in an ED setting. In suitable settings, this is a safe and effective tool for procedural analgesia or for pain management. In such cases, performing an ultrasound-guided nerve block in the ED is a viable alternative for repeated doses of opiates, deep procedural sedation, or the operating theater. We propose this set of regional anesthesia procedures as a pediatric-adapted toolkit for the emergency physician to be performed in children in the ED setting. Adopting this set of procedures ensures better and safer care for children and provides a training framework for pediatric ED physicians.

The educational impact of technology-enhanced learning in regional anaesthesia: a scoping review

BACKGROUND

Effective training in regional anaesthesia (RA) is paramount to ensuring widespread competence. Technology-based learning has assisted other specialties in achieving more rapid procedural skill acquisition. If applicable to RA, technology-enhanced training has the potential to provide an effective learning experience and to overcome barriers to RA training. We review the current evidence base for use of innovative technologies in assisting learning of RA.

METHODS

Using scoping review methodology, three databases (MEDLINE, Embase, and Web of Science) were searched, identifying 158 relevant citations. Citations were screened against defined eligibility criteria with 27 studies selected for inclusion. Data relating to study details, technological learning interventions, and impact on learner experience were extracted and analysed.

RESULTS

Seven different technologies were used to train learners in RA: artificial intelligence, immersive virtual reality, desktop virtual reality, needle guidance technology, robotics, augmented reality, and haptic feedback devices. Of 27 studies, 26 reported a positive impact of technology-enhanced RA training, with different technologies offering benefits for differing components of RA training. Artificial intelligence improved sonoanatomical knowledge and ultrasound skills for RA, whereas needle guidance technologies enhanced confidence and improved needling performance, particularly in novices. Immersive virtual reality allowed more rapid acquisition of needling skills, but its functionality was limited when combined with haptic feedback technology. User friendly technologies enhanced participant experience and improved confidence in RA; however, limitations in technology-assisted RA training restrict its widespread use.

CONCLUSIONS

Technology-enhanced RA training can provide a positive and effective learning experience, with potential to reduce the steep learning curve associated with gaining RA proficiency. A combined approach to RA education, using both technological and traditional approaches, should be maintained as no single method has been shown to provide comprehensive RA training.

Regional anaesthesia truncal blocks for acute postoperative pain and recovery: a narrative review

Significant acute postoperative pain remains prevalent among patients who undergo truncal surgery and is associated with increased morbidity, prolonged patient recovery, and increased healthcare costs. The provision of high-quality postoperative analgesia is an important component of postoperative care, particularly within enhanced recovery programmes. Regional anaesthetic techniques have become increasingly prevalent within multimodal analgesic regimens and the widespread adoption of ultrasonography has facilitated the development of novel fascial plane blocks. The number of described fascial plane blocks has increased significantly over the past decade, leading to a burgeoning area of clinical investigation. Their applications are increasing, and truncal fascial plane blocks are increasingly recommended as part of procedure-specific guidelines. Some fascial plane blocks have been shown to be more efficacious than others, with favourable side-effect profiles compared with neuraxial analgesia, and are increasingly utilised in breast, thoracic, and other truncal surgery. However, use of these blocks is debated in regional anaesthesia circles because of limitations in our understanding of their mechanisms of action. This narrative review evaluates available evidence for the analgesic efficacy of the most commonly practised fascial plane blocks in breast, thoracic, and abdominal truncal surgery, in particular their efficacy compared with systemic analgesia, alternative blocks, and neuraxial techniques. We also highlight areas where investigations are ongoing and suggest priorities for original investigations.

Leading in the development, standardised evaluation, and adoption of artificial intelligence in clinical practice: regional anaesthesia as an example

A recent study by Suissa and colleagues explored the clinical relevance of a medical image segmentation metric (Dice metric) commonly used in the field of artificial intelligence (AI). They showed that pixel-wise agreement for physician identification of structures on ultrasound images is variable, and a relatively low Dice metric (0.34) correlated to a substantial agreement on subjective clinical assessment. We highlight the need to bring structure and clinical perspective to the evaluation of medical AI, which clinicians are best placed to direct.

Research priorities in regional anaesthesia: an international Delphi study

BACKGROUND

Regional anaesthesia use is growing worldwide, and there is an increasing emphasis on research in regional anaesthesia to improve patient outcomes. However, priorities for future study remain unclear. We therefore conducted an international research prioritisation exercise, setting the agenda for future investigators and funding bodies.

METHODS

We invited members of specialist regional anaesthesia societies from six continents to propose research questions that they felt were unanswered. These were consolidated into representative indicative questions, and a literature review was undertaken to determine if any indicative questions were already answered by published work. Unanswered indicative questions entered a three-round modified Delphi process, whereby 29 experts in regional anaesthesia (representing all participating specialist societies) rated each indicative question for inclusion on a final high priority shortlist. If ≥75% of participants rated an indicative question as 'definitely' include in any round, it was accepted. Indicative questions rated as 'definitely' or 'probably' by <50% of participants in any round were excluded. Retained indicative questions were further ranked based on the rating score in the final Delphi round. The final research priorities were ratified by the Delphi expert group.

RESULTS

There were 1318 responses from 516 people in the initial survey, from which 71 indicative questions were formed, of which 68 entered the modified Delphi process. Eleven 'highest priority' research questions were short listed, covering themes of pain management; training and assessment; clinical practice and efficacy; technology and equipment.

CONCLUSIONS

We prioritised unanswered research questions in regional anaesthesia. These will inform a coordinated global research strategy for regional anaesthesia and direct investigators to address high-priority areas.

Artificial intelligence for ultrasound scanning in regional anaesthesia: a scoping review of the evidence from multiple disciplines

BACKGROUND

Artificial intelligence (AI) for ultrasound scanning in regional anaesthesia is a rapidly developing interdisciplinary field. There is a risk that work could be undertaken in parallel by different elements of the community but with a lack of knowledge transfer between disciplines, leading to repetition and diverging methodologies. This scoping review aimed to identify and map the available literature on the accuracy and utility of AI systems for ultrasound scanning in regional anaesthesia.

METHODS

A literature search was conducted using Medline, Embase, CINAHL, IEEE Xplore, and ACM Digital Library. Clinical trial registries, a registry of doctoral theses, regulatory authority databases, and websites of learned societies in the field were searched. Online commercial sources were also reviewed.

RESULTS

In total, 13,014 sources were identified; 116 were included for full-text review. A marked change in AI techniques was noted in 2016-17, from which point on the predominant technique used was deep learning. Methods of evaluating accuracy are variable, meaning it is impossible to compare the performance of one model with another. Evaluations of utility are more comparable, but predominantly gained from the simulation setting with limited clinical data on efficacy or safety. Study methodology and reporting lack standardisation.

CONCLUSIONS

There is a lack of structure to the evaluation of accuracy and utility of AI for ultrasound scanning in regional anaesthesia, which hinders rigorous appraisal and clinical uptake. A framework for consistent evaluation is needed to inform model evaluation, allow comparison between approaches/models, and facilitate appropriate clinical adoption.

Augmented Reality in Ultrasound-Guided Regional Anaesthesia: An Exploratory Study on Models With Potential Implications for Training

Introduction Needle tip visualisation is a key skill required for the safe practice of ultrasound-guided regional anaesthesia (UGRA). This exploratory study assesses the utility of a novel augmented reality device, NeedleTrainer™, to differentiate between anaesthetists with varying levels of UGRA experience in a simulated environment. Methods Four groups of five participants were recruited (n = 20): novice, early career, experienced anaesthetists, and UGRA experts. Each participant performed three simulated UGRA blocks using NeedleTrainer™ on healthy volunteers (n = 60). The primary aim was to determine whether there was a difference in needle tip visibility, as calculated by the device, between groups of anaesthetists with differing levels of UGRA experience. Secondary aims included the assessment of simulated block conduct by an expert assessor and subjective participant self-assessment. Results The percentage of time the simulated needle tip was maintained in view was higher in the UGRA expert group (57.1%) versus the other three groups (novice 41.8%, early career 44.5%, and experienced anaesthetists 43.6%), but did not reach statistical significance (p = 0.05). An expert assessor was able to differentiate between participants of different UGRA experience when assessing needle tip visibility (novice 3.3 out of 10, early career 5.1, experienced anaesthetists 5.9, UGRA expert group 8.7; p < 0.01) and final needle tip placement (novice 4.2 out of 10, early career 5.6, experienced anaesthetists 6.8, UGRA expert group 8.9; p < 0.01). Subjective self-assessment by participants did not differentiate UGRA experience when assessing needle tip visibility (p = 0.07) or final needle tip placement (p = 0.07). Discussion An expert assessor was able to differentiate between participants with different levels of UGRA experience in this simulated environment. Objective NeedleTrainer™ and subjective participant assessments did not reach statistical significance. The findings are novel as simulated needling using live human subjects has not been assessed before, and no previous studies have attempted to objectively quantify needle tip visibility during simulated UGRA techniques. Future research should include larger sample sizes to further assess the potential use of such technology.

Komplexe Schmerztherapie unter Einbeziehung eines Ischiadikus- und Saphenuskatheters in palliativer Situation bei ausgeprägter Metastasierung eines Bronchialkarzinoms

Hintergrund Kontinuierliche periphere Nervenblockaden (Continuous peripheral nerve blocks, CPNB) werden am häufigsten zur perioperativen Analgesie bei chirurgischen Eingriffen eingesetzt. Alternative Indikationen wie die Behandlung tumorbedingter Schmerzen sind die Ausnahme, gleichwohl das Verfahren auch hier effektiv eingesetzt werden kann.

Fallbericht Bei einer 59-jährigen Patientin mit Bronchialkarzinom konnte der durch Metastasierung in der Tibia verursachte starke Schmerz mittels 28-tägiger CPNB des N. ischiadicus und des N. saphenus bis zu ihrem Versterben effektiv behandelt werden. Neben der Schmerzreduktion auf ein Minimum wurde die vorhergehende opioidassoziierte Vigilanzminderung verringert, wodurch sich die Lebensqualität in der letzten Lebensphase steigern ließ.

Schlussfolgerungen CPNB können auch in der Palliativmedizin regional begrenzte Schmerzen effektiv behandeln. Aufgrund der notwendigen Versorgungsstrukturen wird es aber ein Verfahren bleiben, das nur für einzelne Palliativpatient*innen sinnvoll und indiziert ist.

Assistive artificial intelligence for ultrasound image interpretation in regional anaesthesia: an external validation study

BACKGROUND

Ultrasonound is used to identify anatomical structures during regional anaesthesia and to guide needle insertion and injection of local anaesthetic. ScanNav Anatomy Peripheral Nerve Block (Intelligent Ultrasound, Cardiff, UK) is an artificial intelligence-based device that produces a colour overlay on real-time B-mode ultrasound to highlight anatomical structures of interest. We evaluated the accuracy of the artificial-intelligence colour overlay and its perceived influence on risk of adverse events or block failure.

METHODS

Ultrasound-guided regional anaesthesia experts acquired 720 videos from 40 volunteers (across nine anatomical regions) without using the device. The artificial-intelligence colour overlay was subsequently applied. Three more experts independently reviewed each video (with the original unmodified video) to assess accuracy of the colour overlay in relation to key anatomical structures (true positive/negative and false positive/negative) and the potential for highlighting to modify perceived risk of adverse events (needle trauma to nerves, arteries, pleura, and peritoneum) or block failure.

RESULTS

The artificial-intelligence models identified the structure of interest in 93.5% of cases (1519/1624), with a false-negative rate of 3.0% (48/1624) and a false-positive rate of 3.5% (57/1624). Highlighting was judged to reduce the risk of unwanted needle trauma to nerves, arteries, pleura, and peritoneum in 62.9-86.4% of cases (302/480 to 345/400), and to increase the risk in 0.0-1.7% (0/160 to 8/480). Risk of block failure was reported to be reduced in 81.3% of scans (585/720) and to be increased in 1.8% (13/720).

CONCLUSIONS

Artificial intelligence-based devices can potentially aid image acquisition and interpretation in ultrasound-guided regional anaesthesia. Further studies are necessary to demonstrate their effectiveness in supporting training and clinical practice.

CLINICAL TRIAL REGISTRATION

NCT04906018.

Complications and Technical Consideration of Ultrasound-Guided Rectus Sheath Blocks: A Retrospective Analysis of 4033 Patients

BACKGROUND

Although the ultrasound-guided rectus sheath block (RSB) is usually regarded as an easy and safe procedure in clinical settings, there is currently no report on complications incidence. Therefore, the present study investigated complications in a large cohort and described the technical considerations to minimize complications of real-time ultrasound-guided RSBs.

METHODS

This was a retrospective cohort study of patients who underwent real-time ultrasound-guided RSBs for perioperative pain control in laparoscopic surgery with an umbilical port between February 1, 2017, and February 28, 2021, at the Asan Medical Center in South Korea. All RSBs were performed bilaterally using a 23-gauge Quincke needle, and a bilateral 2-block placement was regarded as 1 RSB. Patient data, including demographics, preoperative laboratory data, preoperative antiplatelet or anticoagulant medication with the duration of discontinuation, and type of surgery, were collected to show the study population characteristics and explore potential factors associated with adverse events such as hematoma. Ultrasound images of patients and adverse events of RSBs, including extrarectus sheath injections, vascular injuries, bowel injury, or local anesthetic systemic toxicity, were also analyzed accordingly.

RESULTS

A total of 4033 procedures were analyzed. The mean body mass index of the patients was 24.1 (21.8-26.5) kg/m2. The preoperative laboratory data were within normal range in 4028 (99.9%) patients. Preoperative antiplatelets or anticoagulants were administered in 17.3% of the patients. Overall, 96 complications (2.4%) were observed. Among them, extrarectus sheath injection occurred in 88 cases (2.2%), which included preperitoneal injection (0.9%) and intraperitoneal injection (1.3%). Vascular injuries constituted 8 cases (0.2%) and all vascular injuries resulted in hematoma: 7 cases of inferior epigastric artery injury with rectus sheath hematoma and 1 of inferior mesenteric artery injury with retroperitoneal hematoma. Bowel injury or local anesthetic systemic toxicity was not reported.

CONCLUSIONS

In this study of RSBs performed on 4033 patients using a 23-gauge Quincke needle in patients with low body mass index, there were 8 cases (0.2%) of vascular injury, all of which accompanied hematoma.

Evaluation of the impact of assistive artificial intelligence on ultrasound scanning for regional anaesthesia

BACKGROUND

Ultrasound-guided regional anaesthesia relies on the visualisation of key landmark, target, and safety structures on ultrasound. However, this can be challenging, particularly for inexperienced practitioners. Artificial intelligence (AI) is increasingly being applied to medical image interpretation, including ultrasound. In this exploratory study, we evaluated ultrasound scanning performance by non-experts in ultrasound-guided regional anaesthesia, with and without the use of an assistive AI device.

METHODS

Twenty-one anaesthetists, all non-experts in ultrasound-guided regional anaesthesia, underwent a standardised teaching session in ultrasound scanning for six peripheral nerve blocks. All then performed a scan for each block; half of the scans were performed with AI assistance and half without. Experts assessed acquisition of the correct block view and correct identification of sono-anatomical structures on each view. Participants reported scan confidence, experts provided a global rating score of scan performance, and scans were timed.

RESULTS

Experts assessed 126 ultrasound scans. Participants acquired the correct block view in 56/62 (90.3%) scans with the device compared with 47/62 (75.1%) without (P=0.031, two data points lost). Correct identification of sono-anatomical structures on the view was 188/212 (88.8%) with the device compared with 161/208 (77.4%) without (P=0.002). There was no significant overall difference in participant confidence, expert global performance score, or scan time.

CONCLUSIONS

Use of an assistive AI device was associated with improved ultrasound image acquisition and interpretation. Such technology holds potential to augment performance of ultrasound scanning for regional anaesthesia by non-experts, potentially expanding patient access to these techniques.

CLINICAL TRIAL REGISTRATION

NCT05156099.

Recommendations for anatomical structures to identify on ultrasound for the performance of intermediate and advanced blocks in ultrasound-guided regional anesthesia

Recent recommendations describe a set of core anatomical structures to identify on ultrasound for the performance of basic blocks in ultrasound-guided regional anesthesia (UGRA). This project aimed to generate consensus recommendations for core structures to identify during the performance of intermediate and advanced blocks. An initial longlist of structures was refined by an international panel of key opinion leaders in UGRA over a three-round Delphi process. All rounds were conducted virtually and anonymously. Blocks were considered twice in each round: for “orientation scanning” (the dynamic process of acquiring the final view) and for “block view” (which visualizes the block site and is maintained for needle insertion/injection). A “strong recommendation” was made if ≥75% of participants rated any structure as “definitely include” in any round. A “weak recommendation” was made if >50% of participants rated it as “definitely include” or “probably include” for all rounds, but the criterion for strong recommendation was never met. Structures which did not meet either criterion were excluded. Forty-one participants were invited and 40 accepted; 38 completed all three rounds. Participants considered the ultrasound scanning for 19 peripheral nerve blocks across all three rounds. Two hundred and seventy-four structures were reviewed for both orientation scanning and block view; a “strong recommendation” was made for 60 structures on orientation scanning and 44 on the block view. A “weak recommendation” was made for 107 and 62 structures, respectively. These recommendations are intended to help standardize teaching and research in UGRA and support widespread and consistent practice.

Core outcome set for peripheral regional anesthesia research: a systematic review and Delphi study

BACKGROUND/IMPORTANCE

There is heterogeneity among the outcomes used in regional anesthesia research.

OBJECTIVE

We aimed to produce a core outcome set for regional anesthesia research.

METHODS

We conducted a systematic review and Delphi study to develop this core outcome set. A systematic review of the literature from January 2015 to December 2019 was undertaken to generate a long list of potential outcomes to be included in the core outcome set. For each outcome found, the parameters such as the measurement scale, timing and definitions, were compiled. Regional anesthesia experts were then recruited to participate in a three-round electronic modified Delphi process with incremental thresholds to generate a core outcome set. Once the core outcomes were decided, a final Delphi survey and video conference vote was used to reach a consensus on the outcome parameters.

RESULTS

Two hundred and six papers were generated following the systematic review, producing a long list of 224 unique outcomes. Twenty-one international regional anesthesia experts participated in the study. Ten core outcomes were selected after three Delphi survey rounds with 13 outcome parameters reaching consensus after a final Delphi survey and video conference.

CONCLUSIONS

We present the first core outcome set for regional anesthesia derived by international expert consensus. These are proposed not to limit the outcomes examined in future studies, but rather to serve as a minimum core set. If adopted, this may increase the relevance of outcomes being studied, reduce selective reporting bias and increase the availability and suitability of data for meta-analysis in this area.

Artificial Intelligence: Innovation to Assist in the Identification of Sono-anatomy for Ultrasound-Guided Regional Anaesthesia

Ultrasound-guided regional anaesthesia (UGRA) involves the targeted deposition of local anaesthesia to inhibit the function of peripheral nerves. Ultrasound allows the visualisation of nerves and the surrounding structures, to guide needle insertion to a perineural or fascial plane end point for injection. However, it is challenging to develop the necessary skills to acquire and interpret optimal ultrasound images. Sound anatomical knowledge is required and human image analysis is fallible, limited by heuristic behaviours and fatigue, while its subjectivity leads to varied interpretation even amongst experts. Therefore, to maximise the potential benefit of ultrasound guidance, innovation in sono-anatomical identification is required.Artificial intelligence (AI) is rapidly infiltrating many aspects of everyday life. Advances related to medicine have been slower, in part because of the regulatory approval process needing to thoroughly evaluate the risk-benefit ratio of new devices. One area of AI to show significant promise is computer vision (a branch of AI dealing with how computers interpret the visual world), which is particularly relevant to medical image interpretation. AI includes the subfields of machine learning and deep learning, techniques used to interpret or label images. Deep learning systems may hold potential to support ultrasound image interpretation in UGRA but must be trained and validated on data prior to clinical use.Review of the current UGRA literature compares the success and generalisability of deep learning and non-deep learning approaches to image segmentation and explains how computers are able to track structures such as nerves through image frames. We conclude this review with a case study from industry (ScanNav Anatomy Peripheral Nerve Block; Intelligent Ultrasound Limited). This includes a more detailed discussion of the AI approach involved in this system and reviews current evidence of the system performance.The authors discuss how this technology may be best used to assist anaesthetists and what effects this may have on the future of learning and practice of UGRA. Finally, we discuss possible avenues for AI within UGRA and the associated implications.