Current Applications of Robot-Assisted Ultrasound Examination

Digital health in cardiovascular medicine: An overview of key applications and clinical impact by the Portuguese Society of Cardiology Study Group on Digital Health

Digital health interventions including telehealth, mobile health, artificial intelligence, big data, robotics, extended reality, computational and high-fidelity bench simulations are an integral part of the path toward precision medicine. Current applications encompass risk factor modification, chronic disease management, clinical decision support, diagnostics interpretation, preprocedural planning, evidence generation, education, and training. Despite the acknowledged potential, their development and implementation have faced several challenges and constraints, meaning few digital health tools have reached daily clinical practice. As a result, the Portuguese Society of Cardiology Study Group on Digital Health set out to outline the main digital health applications, address some of the roadblocks hampering large-scale deployment, and discuss future directions in support of cardiovascular health at large.

Concept, Design, and Preclinical Testing of a Remote-Control Robotic System for Transesophageal Echocardiography

Background

Interventional echocardiography (IE) plays a critical role in guiding structural heart interventions. IE specialists face challenges including high radiation exposure and unfavorable ergonomics. To address these issues, a novel remote-control robotic (RCR) system for transesophageal echocardiography (TEE) control has been developed. This study aims to describe the novel RCR system and to assess its performance in bench tests and in vitro models in terms of functionality, image quality, and reproducibility.

Methods

Bench testing and in vitro testing were performed using the RCR system. All tests were performed using the GE 6VT-D TEE probe and the GE Vivid E95.

Results

Key findings include proof of concept through bench testing, remote control of all five degrees of freedom of the TEE probe, and reliable, fast, and accurate reproducibility using automated navigation. The ROB'E Base is securely attached to the operating table, optimizing the footprint in the operating room. The ROB'E Guide accurately performs the forward and backward motion of the flexible portion of the TEE probe, stabilizing the achieved positions and preventing twisting during rotation. The ROB'E RCR system can store and reproduce TEE probe positions and has demonstrated reliable and accurate automated reproducibility in both bench and in vitro tests.

Conclusions

The ROB'E RCR system for TEE overcomes the limitations of conventional IE by using a RCR approach that eliminates the need for the echocardiographer to be physically present in the operating room. Thus, it significantly reduces radiation exposure and demonstrates its capabilities to improve image quality, reproducibility, and overall safety in IE.

Satisfaction analysis of 5G remote ultrasound robot for diagnostics based on a structural equation model

Objectives

With the increasing application of 5G remote ultrasound robots in healthcare, robust methods are in critical demand to assess participant satisfaction and identify its influencing factors. At present, there is limited empirical research on multi-parametric and multidimensional satisfaction evaluation of participants with 5G remote ultrasound robot examination. Previous studies have demonstrated that structural equation modeling (SEM) effectively integrates various statistical techniques to examine the relationships among multiple variables. Therefore, this study aimed to evaluate the satisfaction of participants with 5G remote ultrasound robot examination and its influencing factors using SEM.

Methods

Between April and June 2022, 213 participants from Wuhan Automobile Manufacturing Company underwent remote ultrasound examinations using the MGIUS-R3 remote ultrasound robot system. After these examinations, the participants evaluated the performance of the 5G remote ultrasound robot based on their personal experiences and emotional responses. They completed a satisfaction survey using a self-developed questionnaire, which included 19 items across five dimensions: examination efficiency, examination perception, communication perception, value perception, and examination willingness. A SEM was established to assess the satisfaction of participants with the 5G remote ultrasound robot examinations and the influencing factors.

Results

A total of 201 valid questionnaires were collected. The overall satisfaction of participants with the 5G remote ultrasound robot examination was 45.43 ± 11.60, with 169 participants (84%) expressing satisfaction. In the path hypothesis relationship test, the dimensions of examination efficiency, examination perception, communication perception, and value perception had positive effects on satisfaction, with standardized path coefficients of 0.168, 0.170, 0.175, and 0.191. Satisfaction had a direct positive effect on examination willingness, with a standardized path coefficient of 0.260. Significant differences were observed across different educational levels in the dimensions of examination perception, communication perception, value perception, and examination willingness. Participants with different body mass indices also showed significant differences in examination perception; all p-values were less than 0.05.

Conclusion

In this study, value perception was identified as the most significant factor influencing satisfaction. It could be improved by enhancing participants' understanding of the accuracy and safety of 5G remote ultrasound robot examinations. This enhances satisfaction and the willingness to undergo examinations. Such improvements not only facilitate the widespread adoption of this technology but also promote the development of telemedicine services.

Contrast-Enhanced Sonography of the Liver: How to Avoid Artifacts

Contrast-enhanced sonography (CEUS) is a very important diagnostic imaging tool in clinical settings. However, it is associated with possible artifacts, such as B-mode US-related artifacts. Sufficient knowledge of US physics and these artifacts is indispensable to avoid the misinterpretation of CEUS images. This review aims to explain the basic physics of CEUS and the associated artifacts and to provide some examples to avoid them. This review includes problems related to the frame rate, scanning modes, and various artifacts encountered in daily CEUS examinations. Artifacts in CEUS can be divided into two groups: (1) B-mode US-related artifacts, which form the background of the CEUS image, and (2) artifacts that are specifically related to the CEUS method. The former includes refraction, reflection, reverberation (multiple reflections), attenuation, mirror image, and range-ambiguity artifacts. In the former case, the knowledge of B-mode US is sufficient to read the displayed artifactual image. Thus, in this group, the most useful artifact avoidance strategy is to use the reference B-mode image, which allows for a simultaneous comparison between the CEUS and B-mode images. In the latter case, CEUS-specific artifacts include microbubble destruction artifacts, prolonged heterogeneous accumulation artifacts, and CEUS-related posterior echo enhancement; these require an understanding of the mechanism of their appearance in CEUS images for correct image interpretation. Thus, in this group, the most useful artifact avoidance strategy is to confirm the phenomenon's instability by changing the examination conditions, including the frequency, depth, and other parameters.

Feasibility and Safety of Percutaneous Puncture Guided by a 5G-Based Telerobotic Ultrasound System: An Experimental Study

PURPOSE

To evaluate the feasibility and safety of percutaneous puncture guided by a 5th generation mobile communication technology (5G)-based telerobotic ultrasound system in phantom and animal experiments.

MATERIALS AND METHODS

In the phantom experiment, 10 simulated lesions were punctured, once at each of two angles for each lesion, under the guidance of a telerobotic ultrasound system and ultrasound-guided freehand puncture. Student's t test was used to compare the two methods in terms of puncture accuracy, total operation duration, and puncture duration. In the animal experiment, under the guidance of the telerobotic ultrasound system, an 18G puncture needle was used to puncture 3 target steel beads in the liver, right kidney, and right gluteal muscle, respectively. The animal experiment had no freehand ultrasound-guided control group. After puncture, a CT scan was performed to verify the position of the puncture needle in relation to the target, and the complications and puncture duration, etc., were recorded.

RESULTS

In the phantom experiment, the mean accuracies of puncture under telerobotic ultrasound guidance and conventional ultrasound guidance were 1.8 ± 0.3 mm and 1.6 ± 0.3 mm (P = 0.09), respectively; therefore, there was no significant difference in the accuracy of the two guide methods. In the animal experiment, the first-attempt puncture success (the needle tip close to the target) rate was 93%. Polypnea occurred during one puncture. No other intraoperative or postoperative complications were observed.

CONCLUSION

Puncture guided by a 5G-based telerobotic ultrasound system has shown good feasibility and safety in phantom and animal experiments.

Development of artificial intelligence-based slow-motion echocardiography and clinical usefulness for evaluating regional wall motion abnormalities

The diagnostic accuracy of exercise stress echocardiography (ESE) for myocardial ischemia requires improvement, given that it currently depends on the physicians' experience and image quality. To address this issue, we aimed to develop artificial intelligence (AI)-based slow-motion echocardiography using inter-image interpolation. The clinical usefulness of this method was evaluated for detecting regional wall-motion abnormalities (RWMAs). In this study, an AI-based echocardiographic image-interpolation pipeline was developed using optical flow calculation and prediction for in-between images. The accuracy for detecting RWMAs and image readability among 25 patients with RWMA and 25 healthy volunteers was compared between four cardiologists using slow-motion and conventional ESE. Slow-motion echocardiography was successfully developed for arbitrary time-steps (e.g., 0.125×, and 0.5×) using 1,334 videos. The RWMA detection accuracy showed a numerical improvement, but it was not statistically significant (87.5% in slow-motion echocardiography vs. 81.0% in conventional ESE; odds ratio: 1.43 [95% CI: 0.78-2.62], p = 0.25). Interreader agreement analysis (Fleiss's Kappa) for detecting RWMAs among the four cardiologists were 0.66 (95%CI: 0.55-0.77) for slow-motion ESE and 0.53 (95%CI: 0.42-0.65) for conventional ESE. Additionally, subjective evaluations of image readability using a four-point scale showed a significant improvement for slow-motion echocardiography (2.11 ± 0.73 vs. 1.70 ± 0.78, p < 0.001).In conclusion, we successfully developed slow-motion echocardiography using in-between echocardiographic image interpolation. Although the accuracy for detecting RWMAs did not show a significant improvement with this method, we observed enhanced image readability and interreader agreement. This AI-based approach holds promise in supporting physicians' evaluations.