Ultrasound Plane Pose Regression: Assessing Generalized Pose Coordinates in the Fetal Brain.

In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dimensional (3D) map of the fetus from a two-dimensional (2D) US image represents a significant challenge in skill acquisition. We aim to build a US plane localization system for 3D visualization, training, and guidance without integrating additional sensors. This work builds on top of our previous work, which predicts the six-dimensional (6D) pose of arbitrarily oriented US planes slicing the fetal brain with respect to a normalized reference frame using a convolutional neural network (CNN) regression network. Here, we analyze in detail the assumptions of the normalized fetal brain reference frame and quantify its accuracy with respect to the acquisition of transventricular (TV) standard plane (SP) for fetal biometry. We investigate the impact of registration quality in the training and testing data and its subsequent effect on trained models. Finally, we introduce data augmentations and larger training sets that improve the results of our previous work, achieving median errors of 2.97 mm and 6.63° for translation and rotation, respectively.

Probe motion during mid-trimester fetal anomaly scan in the clinical setting: A prospective observational study.

INTRODUCTION: This study aims to investigate probe motion during full mid-trimester anomaly scans. METHODS: We undertook a prospective, observational study of obstetric sonographers at a UK University Teaching Hospital. We collected prospectively full-length video recordings of routine second-trimester anomaly scans synchronized with probe trajectory tracking data during the scan. Videos were reviewed and trajectories analyzed using duration, path metrics (path length, velocity, acceleration, jerk, and volume) and angular metrics (spectral arc, angular area, angular velocity, angular acceleration, and angular jerk). These trajectories were then compared according to the participant level of expertise, fetal presentation, and patient BMI. RESULTS: A total of 17 anomaly scans were recorded. The average velocity of the probe was 12.9 ± 3.4 mm/s for the consultants versus 24.6 ± 5.7 mm/s for the fellows (p = 0.02), the average acceleration 170.4 ± 26.3 mm/s2 versus 328.9 ± 62.7 mm/s2 (p = 0.02), and the average jerk 7491.7 ± 1056.1 mm/s3 versus 14944.1 ± 3146.3 mm/s3 (p = 0.02), the working volume 9.106 ± 4.106 mm3 versus 29.106 ± 11.106 mm3 (p = 0.03), respectively. The angular metrics were not significantly different according to the participant level of expertise, the fetal presentation, or to patients BMI. CONCLUSION: Some differences in the probe path metrics (velocity, acceleration, jerk and working volume) were noticed according to operator's level.

Intraoperative Needle Tip Tracking with an Integrated Fibre-Optic Ultrasound Sensor.

Ultrasound is an essential tool for guidance of many minimally-invasive surgical and interventional procedures, where accurate placement of the interventional device is critical to avoid adverse events. Needle insertion procedures for anaesthesia, fetal medicine and tumour biopsy are commonly ultrasound-guided, and misplacement of the needle may lead to complications such as nerve damage, organ injury or pregnancy loss. Clear visibility of the needle tip is therefore critical, but visibility is often precluded by tissue heterogeneities or specular reflections from the needle shaft. This paper presents the in vitro and ex vivo accuracy of a new, real-time, ultrasound needle tip tracking system for guidance of fetal interventions. A fibre-optic, Fabry-Pérot interferometer hydrophone is integrated into an intraoperative needle and used to localise the needle tip within a handheld ultrasound field. While previous, related work has been based on research ultrasound systems with bespoke transmission sequences, the new system-developed under the ISO 13485 Medical Devices quality standard-operates as an adjunct to a commercial ultrasound imaging system and therefore provides the image quality expected in the clinic, superimposing a cross-hair onto the ultrasound image at the needle tip position. Tracking accuracy was determined by translating the needle tip to 356 known positions in the ultrasound field of view in a tank of water, and by comparison to manual labelling of the the position of the needle in B-mode US images during an insertion into an ex vivo phantom. In water, the mean distance between tracked and true positions was 0.7 ± 0.4 mm with a mean repeatability of 0.3 ± 0.2 mm. In the tissue phantom, the mean distance between tracked and labelled positions was 1.1 ± 0.7 mm. Tracking performance was found to be independent of needle angle. The study demonstrates the performance and clinical compatibility of ultrasound needle tracking, an essential step towards a first-in-human study.

Magnetic resonance imaging in late pregnancy to improve labour and delivery outcomes - a systematic literature review.

BACKGROUND: Magnetic resonance imaging (MRI) provides excellent soft tissue visualisation which may be useful in late pregnancy to predict labour outcome and maternal/neonatal birth trauma. OBJECTIVE: To study if MRI in late pregnancy can predict maternal and neonatal outcomes of labour and birth. METHODS: Systematic review of studies that performed MRI in late pregnancy or immediately postpartum. Studies were included if they imaged maternal pelvic or neonatal structures and assessed birth outcome. Meta-analysis was not performed due to the heterogeneity of studies. RESULTS: Eighteen studies were selected. Twelve studies explored the value of MRI pelvimetry measurement and its utility to predict cephalopelvic disproportion (CPD) and vaginal breech birth. Four explored cervical imaging in predicting time interval to birth. Two imaged women in active labour and assessed mouldability of the fetal skull. No marker of CPD had both high sensitivity and specificity for predicting labour outcome. The fetal pelvic index yielded sensitivities between 59 and 60%, and specificities between 34 to 64%. Similarly, although the sensitivity of the cephalopelvic disproportion index in predicting labour outcome was high (85%), specificity was only 56%. In women with breech presentation, MRI was demonstrated to reduce the rates of emergency caesarean section from 35 to 19%, and allowed better selection of vaginal breech birth. Live birth studies showed that the fetal head undergoes a substantial degree of moulding and deformation during cephalic vaginal birth, which is not considered during pelvimetry. There are conflicting studies on the role of MRI in cervical imaging and predicting time interval to birth. CONCLUSION: MRI is a promising imaging modality to assess aspects of CPD, yet no current marker of CPD accurately predicts labour outcome. With advances in MRI, it is hoped that novel methods can be developed to better identify individuals at risk of obstructed or pathological labour. Its role in exploring fetal head moulding as a marker of CPD should be further explored.

Deep learning-based plane pose regression in obstetric ultrasound.

PURPOSE: In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dimensional (3D) map of the fetus from a two-dimensional (2D) US image represents a major challenge in skill acquisition. We aim to build a US plane localisation system for 3D visualisation, training, and guidance without integrating additional sensors. METHODS: We propose a regression convolutional neural network (CNN) using image features to estimate the six-dimensional pose of arbitrarily oriented US planes relative to the fetal brain centre. The network was trained on synthetic images acquired from phantom 3D US volumes and fine-tuned on real scans. Training data was generated by slicing US volumes into imaging planes in Unity at random coordinates and more densely around the standard transventricular (TV) plane. RESULTS: With phantom data, the median errors are 0.90 mm/1.17[Formula: see text] and 0.44 mm/1.21[Formula: see text] for random planes and planes close to the TV one, respectively. With real data, using a different fetus with the same gestational age (GA), these errors are 11.84 mm/25.17[Formula: see text]. The average inference time is 2.97 ms per plane. CONCLUSION: The proposed network reliably localises US planes within the fetal brain in phantom data and successfully generalises pose regression for an unseen fetal brain from a similar GA as in training. Future development will expand the prediction to volumes of the whole fetus and assess its potential for vision-based, freehand US-assisted navigation when acquiring standard fetal planes.

Simulation and beyond - Principles of effective obstetric training.

Simulation training provides a safe, non-judgmental environment where members of the multi-professional team can practice both their technical and non-technical skills. Poor teamwork and communication are recurring contributing factors to adverse maternal and neonatal outcomes. Simulation can improve outcomes and is now a compulsory part of the national training matrix. Components of successful training include involving the multi-professional team, high fidelity models, keeping training on-site, and focussing on human factors training; a key factor in adverse patient outcomes. The future of simulation training is an exciting field, with the advent of augmented reality devices and the use of artificial intelligence.

CAL-Tutor: A HoloLens 2 Application for Training in Obstetric Sonography and User Motion Data Recording.

Obstetric ultrasound (US) training teaches the relationship between foetal anatomy and the viewed US slice to enable navigation to standardised anatomical planes (head, abdomen and femur) where diagnostic measurements are taken. This process is difficult to learn, and results in considerable inter-operator variability. We propose the CAL-Tutor system for US training based on a US scanner and phantom, where a model of both the baby and the US slice are displayed to the trainee in its physical location using the HoloLens 2. The intention is that AR guidance will shorten the learning curve for US trainees and improve spatial awareness. In addition to the AR guidance, we also record many data streams to assess user motion and the learning process. The HoloLens 2 provides eye gaze, head and hand position, ARToolkit and NDI Aurora tracking gives the US probe positions and an external camera records the overall scene. These data can provide a rich source for further analysis, such as distinguishing expert from novice motion. We have demonstrated the system in a sample of engineers. Feedback suggests that the system helps novice users navigate the US probe to the standard plane. The data capture is successful and initial data visualisations show that meaningful information about user behaviour can be captured. Initial feedback is encouraging and shows improved user assessment where AR guidance is provided.

Dimensionless squared jerk: An objective differential to assess experienced and novice probe movement in obstetric ultrasound.

OBJECTIVE: Widely accepted, validated and objective measures of ultrasound competency have not been established for clinical practice. Outcomes of training curricula are often based on arbitrary thresholds, such as the number of clinical cases completed. We aimed to define metrics against which competency could be measured. METHOD: We undertook a prospective, observational study of obstetric sonographers at a UK University Teaching Hospital. Participants were either experienced in fetal ultrasound (n = 10, >200 ultrasound examinations) or novice operators (n = 10, <25 ultrasound examinations). We recorded probe motion data during the performance of biometry on a commercially available mid-trimester phantom. RESULTS: We report that Dimensionless squared jerk, an assessment of deliberate hand movements, independent of movement duration, extent, spurious peaks and dimension differed significantly different between groups, 19.26 (SD 3.02) for experienced and 22.08 (SD 1.05, p = 0.01) for novice operators, respectively. Experienced operator performance, was associated with a shorter time to task completion of 176.46 s (SD 47.31) compared to 666.94 s (SD 490.36, p = 0.0004) for novice operators. Probe travel was also shorter for experienced operators 521.23 mm (SD 27.41) versus 2234.82 mm (SD 188.50, p = 0.007) when compared to novice operators. CONCLUSION: Our results represent progress toward an objective assessment of technical skill in obstetric ultrasound. Repeating this methodology in a clinical environment may develop insight into the generalisability of these findings into ultrasound education.

A Systematic Review and Meta-analysis of the Use of High-Fidelity Simulation in Obstetric Ultrasound.

SUMMARY STATEMENT: There is little global consensus on how to train, assess, and evaluate skills in obstetric ultrasound. The outcomes of curricula, where present, are often based on the number of clinical cases completed, rather than objective outcomes. The central question in this review is whether simulation enhances training and prepares trainees for clinical practice. A systematic review was conducted of the currently available literature in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies considering the use of simulators in training or assessment of sonographers were eligible for inclusion. We conclude that simulation is best used for acquisition of technical skills and image optimization. Best outcomes are observed when simulation augments traditional learning, with a strong focus on specific, objective, and measurable skills. Integrating simulation into training curricula could allow trainees to contribute to clinical service while learning. How skills learned in a simulated environment translate to the clinic is poorly addressed by the literature.