Motion-Based Technical Skills Assessment in Transoesophageal Echocardiography

Mazomenos, Evangelos B.; Vasconcelos, Francisco; Smelt, Jeremy; Prescott, Henry; Jahangiri, Marjan; Martin, Bruce; Smith, Andrew P.; Wright, Susan; Stoyanov, Danail

doi:10.1007/978-3-319-43775-0_9

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Kinematic metrics of skill in transesophageal echo (TEE) in the HeartWorks simulator. 61 Probe tip trajectory and depth of the transesophageal echo probe are smoother and more fluid for the expert than for the novice. Reproduced from ref.…”

Section: Simulation Of Cardiac Ultrasoundmentioning

confidence: 99%

Simulation for competency assessment in vascular and cardiac ultrasound

Sheehan

Zierler

2018

Vasc Med

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Healthcare providers who use peripheral vascular and cardiac ultrasound require specialized training to develop the technical and interpretive skills necessary to perform accurate diagnostic tests. Assessment of competence is a critical component of training that documents a learner's progress and is a requirement for competency-based medical education (CBME) as well as specialty certification or credentialing. The use of simulation for CBME in diagnostic ultrasound is particularly appealing since it incorporates both the psychomotor and cognitive domains while eliminating dependency on the availability of live patients with a range of pathology. However, successful application of simulation in this setting requires realistic, full-featured simulators and appropriate standardized metrics for competency testing. The principal diagnostic parameter in peripheral vascular ultrasound is measurement of peak systolic velocity (PSV) on Doppler spectral waveforms, and simulation of Doppler flow detection presents unique challenges. The computer-based duplex ultrasound simulator developed at the University of Washington uses computational fluid dynamics modeling and presents real-time color-flow Doppler images and Doppler spectral waveforms along with the corresponding B-mode images. This simulator provides a realistic scanning experience that includes measuring PSV in various arterial segments and applying actual diagnostic criteria. Simulators for echocardiography have been available since the 1990s and are currently more advanced than those for peripheral vascular ultrasound. Echocardiography simulators are now offered for both transesophageal echo and transthoracic echo. These computer-based simulators have 3D graphic displays that provide feedback to the learner and metrics for assessment of technical skill that are based on transducer tracking data. Such metrics provide a motion-based or kinematic analysis of skill in performing cardiac ultrasound. The use of simulation in peripheral vascular and cardiac ultrasound can provide a standardized and readily available method for training and competency assessment.

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Section: Simulation Of Cardiac Ultrasoundmentioning

confidence: 99%

Simulation for competency assessment in vascular and cardiac ultrasound

Sheehan

Zierler

2018

Vasc Med

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“…Average tool-tip velocity was calculated for each tool using the tangential velocity profile. Average tool velocity is another promising metric given its significant correlation to experience level in other catheter-based surgical domains such as transesophageal echocardiography [33]. Average velocity for each tool is calculated by taking the discrete sum of tangential velocity values, given by their index i, which is then divided by the total number of discrete velocity values N, as in Eq.…”

Section: Performance Measuresmentioning

confidence: 99%

Velocity-Domain Motion Quality Measures for Surgical Performance Evaluation and Feedback

Murali

Belvroy

Pandey

et al. 2021

Journal of Medical Devices

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Endovascular navigation proficiency requires a significant amount of manual dexterity from surgeons. Objective performance measures derived from endovascular tool tip kinematics have been shown to correlate with expertise; however, such metrics have not yet been used during training as a basis for real-time performance feedback. This paper evaluates a set of velocity-based performance measures derived from guidewire motion to determine their suitability for online performance evaluation and feedback. We evaluated the endovascular navigation skill of 75 participants using three metrics (spectral arc length, average velocity, and idle time) as they steered tools to anatomical targets using a virtual reality simulator. First, we examined the effect of navigation task and experience level on performance and found that novice performance was significantly different from intermediate and expert performance. Then we computed correlations between measures calculated online and spectral arc length, our “gold standard” metric, calculated offline (at the end of the trial, using data from the entire trial). Our results suggest that average velocity and idle time calculated online are strongly and consistently correlated with spectral arc length computed offline, which was not the case when comparing spectral arc length computed online and offline. Average velocity and idle time, both time-domain based performance measures, are therefore more suitable measures than spectral arc length, a frequency-domain based metric, to use as the basis of online performance feedback. Future work is needed to determine how to best provide real-time performance feedback to endovascular surgery trainees based on these metrics.

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“…Performance evaluation is a key element in interventional medicine and alternative, preferably automated, methods for evaluating TEE competency are necessary [14]. So far, objective assessment in TEE is focused exclusively on the kinematic analysis of the US probe with various motion parameters found to be indicative of the level of operational expertise [9,10]. Although these are important findings, probe kinematic information is not available in clinical settings and only captured in simulation systems.…”

Section: Introductionmentioning

confidence: 99%

Automated Performance Assessment in Transoesophageal Echocardiography with Convolutional Neural Networks

Mazomenos

Bansal

Martin

et al. 2018

Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

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Transoesophageal echocardiography (TEE) is a valuable diagnostic and monitoring imaging modality. Proper image acquisition is essential for diagnosis, yet current assessment techniques are solely based on manual expert review. This paper presents a supervised deep learning framework for automatically evaluating and grading the quality of TEE images. To obtain the necessary dataset, 38 participants of varied experience performed TEE exams with a high-fidelity virtual reality (VR) platform. Two Convolutional Neural Network (CNN) architectures, AlexNet and VGG, structured to perform regression, were finetuned and validated on manually graded images from three evaluators. Two different scoring strategies, a criteria-based percentage and an overall general impression, were used. The developed CNN models estimate the average score with a root mean square accuracy ranging between 84%-93%, indicating the ability to replicate expert valuation. Proposed strategies for automated TEE assessment can have a significant impact on the training process of new TEE operators, providing direct feedback and facilitating the development of the necessary dexterous skills.

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Motion-Based Technical Skills Assessment in Transoesophageal Echocardiography

Cited by 6 publications

References 12 publications

Simulation for competency assessment in vascular and cardiac ultrasound

Simulation for competency assessment in vascular and cardiac ultrasound

Velocity-Domain Motion Quality Measures for Surgical Performance Evaluation and Feedback

Automated Performance Assessment in Transoesophageal Echocardiography with Convolutional Neural Networks

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