Feasibility of a 5G-Based Robot-Assisted Remote Ultrasound System for Cardiopulmonary Assessment of Patients With Coronavirus Disease 2019

Effectiveness and feasibility of 5G-based remote interactive ultrasound training in critical care

BACKGROUND

Ultrasound has widely used in various medical fields related to critical care. While online and offline ultrasound trainings are faced by certain challenges, remote ultrasound based on the 5G cloud platform has been gradually adopted in many clinics. However, no study has used the 5G remote ultrasound cloud platform operating system for standardized critical care ultrasound training. This study aimed to evaluate the feasibility and effectiveness of 5G-based remote interactive ultrasound training for standardized diagnosis and treatment in critical care settings.

METHODS

A 5G-based remote interactive ultrasound training system was constructed, and the course was piloted among critical care physicians. From July 2022 to July 2023, 90 critical care physicians from multiple off-site locations were enrolled and randomly divided into experimental and control groups. The 45 physicians in the experimental group were trained using the 5G-based remote interactive ultrasound training system, while the other 45 in the control group were taught using theoretical online videos. The theoretical and practical ultrasonic capabilities of both groups were evaluated before and after the training sessions, and their levels of satisfaction with the training were assessed as well.

RESULTS

The total assessment scores for all of the physicians were markedly higher following the training (80.7 ± 11.9) compared to before (42.1 ± 13.4) by a statistically significant margin (P < 0.001). Before participating in the training, the experimental group scored 42.2 ± 12.5 in the critical care ultrasound competency, and the control group scored 41.9 ± 14.3-indicating no significant differences in their assessment scores (P = 0.907). After participating in the training, the experimental group's assessment scores were 88.4 ± 6.7, which were significantly higher than those of the control group (72.9 ± 10.8; P < 0.001). The satisfaction score of the experimental group was 42.6 ± 2.3, which was also significantly higher than that of the control group (34.7 ± 3.1, P < 0.001).

CONCLUSION

The 5G-based remote interactive ultrasound training system was well-received and effective for critical care. These findings warrant its further promotion and application.

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.

Design and testing of ultrasound probe adapters for a robotic imaging platform

Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military settings. Ultrasound imaging can be used to rapidly identify free fluid in abdominal and thoracic cavities which could necessitate immediate surgical intervention. However, proper ultrasound image capture requires a skilled ultrasonography technician who is likely unavailable at the point of injury where resources are limited. Instead, robotics and computer vision technology can simplify image acquisition. As a first step towards this larger goal, here, we focus on the development of prototypes for ultrasound probe securement using a robotics platform. The ability of four probe adapter technologies to precisely capture images at anatomical locations, repeatedly, and with different ultrasound transducer types were evaluated across more than five scoring criteria. Testing demonstrated two of the adapters outperformed the traditional robot gripper and manual image capture, with a compact, rotating design compatible with wireless imaging technology being most suitable for use at the point of injury. Next steps will integrate the robotic platform with computer vision and deep learning image interpretation models to automate image capture and diagnosis. This will lower the skill threshold needed for medical imaging-based triage, enabling this procedure to be available at or near the point of injury.

A 5G-based telerobotic ultrasound system provides qualified abdominal ultrasound services for patients on a rural island: a prospective and comparative study of 401 patients

PURPOSE

To explore the feasibility of a 5G-based telerobotic ultrasound (US) system for providing qualified abdominal US services on a rural island.

METHODS

This prospective study involved two medical centers (the tele-radiologist site's hospital and the patient site's hospital) separated by 72 km. Patients underwent 5G-based telerobotic US by tele-radiologists and conventional US by on-site radiologists from September 2020 to March 2021. The clinical feasibility and diagnostic performance of the 5G-based telerobotic abdominal US examination were assessed based on safety, duration, image quality, diagnostic findings, and questionnaires.

RESULTS

A total of 401 patients (217 women and 184 men; mean age, 54.96 ± 15.43 years) were enrolled. A total of 90.1% of patients indicated no discomfort with the telerobotic US examination. For the examination duration, telerobotic US took longer than conventional US (12.54 ± 3.20 min vs. 7.23 ± 2.10 min, p = 0.001). For image quality scores, the results of the two methods were similar (4.54 ± 0.63 vs. 4.57 ± 0.61, p = 0.112). No significant differences were found between the two methods in measurements for the aorta, portal vein, gallbladder, kidney (longitudinal diameter), prostate, and uterus; however, telerobotic US underestimated the transverse diameter of the kidney (p < 0.05). A total of 504 positive results, including 31 different diseases, were detected. Among them, 455 cases were identified by the two methods; 17 cases were identified by telerobotic US only; and 32 cases were identified by conventional US only. There was good consistency in the diagnosis of 29 types of disease between the two methods (κ = 0.773-1.000). Furthermore, more than 90% of patients accepted the telerobotic US examination and agreed to pay additional fees in future.

CONCLUSION

The 5G-based telerobotic US system can expand access to abdominal US services for patients in rural areas, thereby reducing health care disparities.

Feasibility and Safety of 5G-Based Telerobotic Abdominal Ultrasonography

OBJECTIVE

Telemedicine can offer services to remote patients regardless of the distance. Fifth-generation (5G) mobile networks may make telemedicine practical because of their low latency. This study aimed to evaluate the feasibility and safety of a novel 5G robot-assisted remote abdominal ultrasound (AUS) telemedicine technology in clinical applications in distant locations.

METHODS

We performed 5G-based telerobotic AUS in patients who were located more than 100 km away from the physicians.

RESULTS

The telerobotic AUS had a longer examination time than the conditional bedside AUS; however, the complete examination rate was not inferior. None of the volunteers experienced discomfort during the examination and the examination time was acceptable for all.

CONCLUSION

Our findings confirm the feasibility and safety of 5G-based telerobotic AUS in clinical practice.

Percutaneous nephrolithotomy guided by 5G-powered robot-assisted teleultrasound diagnosis system: first clinical experience with a novel tele-assistance approach (IDEAL stage 1)

BACKGROUND

To demonstrate the technical feasibility of percutaneous nephrolithotomy (PCNL) guided by 5G-powered robot-assisted teleultrasound diagnosis system (RTDS) in a complex kidney-stone (CKS) cohort and present our preliminary outcomes. PCNL is highly skill-required, which hinders it popularization in primary medical units of remote regions. We designed an innovative tele-assistance approach to make PCNL easy to be operated by inexperienced surgeons.

METHODS

This was a prospective proof-of-concept study (IDEAL phase 1) on intraoperative tele-assistance provided by online urological experts via a 5G-powered RTDS. Total 15 CKS patients accepted this technology. Online experts manipulated a simulated probe to assist unskilled local operators by driving a patient-side robot-probe to guide and monitor the steps of access establishment and finding residual stones.

RESULTS

Median total delay was 177ms despite one-way network-connecting distance > 5,800 km. No perceptible delay of audio-visual communication, driving robot-arm or dynamic ultrasound images was fed back. Successful tele-assistance was obtained in all cases. The first-puncture access-success rate was 78.6% with a one-session SF rate of 71.3% and without complications of grade III-V.

CONCLUSIONS

The current technology based on 5G-powered RTDS can provide high-quality intraoperative tele-assistance, which has preliminarily shown satisfactory outcomes and reliable safety. It will break down a personal competence-based barrier to endow PCNL with more popular utilization.

TRIAL REGISTRATION

The study was approved by ethics committee of the Xinjiang Kezhou People's Hospital and ethics committee of the First Affiliated Hospital of Nanjing Medical University and was registered on http://www.chictr.org.cn (ChiCTR2200065849, 16/11/2022).

Past and Present of Point-of-Care Ultrasound (PoCUS): A Narrative Review

This article aims to conduct a literature review to gain insight into point-of-care ultrasound (PoCUS). PoCUS is a rapid, accurate, non-invasive, and radiation-free imaging modality that can be used in stable and unstable patients. PoCUS can be performed parallel to physical examination, resuscitation, and stabilization; repeated exams in critical patients are essential for improving sensitivity. The review highlights how PoCUS, which was initially used to detect free intraperitoneal fluid in trauma patients, has developed into a life-saving diagnostic tool that could be utilized by treating physicians during various stages of diagnosis, resuscitation, operation, and postoperative critical care when managing sick patients. The review also notes the barriers to the widespread uptake of PoCUS in general internal medicine and the recent commercial availability of "pocket" or handheld probes that have made PoCUS more readily available. This review concludes that adopting a focused binary decision-making approach can maximize PoCUS's value in many clinical settings, including emergency departments, intensive care units, and operation theatres. Overall, the review emphasizes the importance of awareness of common indications, limitations, and strengths of this evolving and promising technology to determine its future trajectory: Providing comprehensive PoCUS training within internal medicine curriculums and supporting trainers to do so.

Robotic ultrasound imaging: State-of-the-art and future perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques. Additionally, we present the challenges that the scientific community needs to face in the coming years in order to achieve its ultimate goal of developing intelligent robotic sonographer colleagues. These colleagues are expected to be capable of collaborating with human sonographers in dynamic environments to enhance both diagnostic and intraoperative imaging.

Tele-Mentored Handheld Ultrasound System for General Practitioners: A Prospective, Descriptive Study in Remote and Rural Communities

BACKGROUND

Rural general practitioners (GPs) have insufficient diagnostic information to deal with complex clinical scenarios due to the inequality in medical imaging resources in rural and remote communities. The objective of this study is to explore the value of a tele-mentored handheld ultrasound (tele-HHUS) system, allowing GPs to provide ultrasound (US) services in rural and remote communities.

METHODS

Overall, 708 patients underwent tele-HHUS examination between March and October 2021 and March and April 2022 across thirteen primary hospitals and two tertiary-care general hospitals. All US examinations were guided and supervised remotely in real time by US experts more than 300 km away using the tele-HHUS system. The following details were recorded: location of tele-HHUS scanning, primary complaints, clinical diagnosis, and US findings. The recommendations (referral or follow-up) based on clinical experience alone were compared with those based on clinical experience with tele-HHUS information.

RESULTS

Tele-HHUS examinations were performed both in hospital settings (90.6%, 642/708) and out of hospital settings (9.4%, 66/708). Leaving aside routine physical examinations, flank pain (14.2%, 91/642) was the most common complaint in inpatients, while chest distress (12.1%, 8/66) and flank discomfort (12.1%, 8/66) were the most common complaints in out-of-hospital settings. Additionally, the referral rate increased from 5.9% to 8.3% (kappa = 0.202; p = 0.000).

CONCLUSIONS

The tele-HHUS system can help rural GPs perform HHUS successfully in remote and rural communities. This novel mobile telemedicine model is valuable in resource-limited areas.

A long distance telesurgical demonstration on robotic surgery phantoms over 5G

PURPOSE

Using robotic technology and communications infrastructure to remotely perform surgery has been a persistent goal in medical research in the past three decades. The recent deployment of the Fifth-Generation Wireless Networks has revitalized the research efforts in the telesurgery paradigm. Offering low latency and high bandwidth communication, they are well suited for applications that require real-time data transmission and can allow smoother communication between surgeon and patient, making it possible to remotely perform complex surgeries. In this paper, we investigate the effects of the 5 G network on surgical performance during a telesurgical demonstration where the surgeon and the robot are separated by nearly 300 km.

METHODS

The surgeon performed surgical exercises on a robotic surgery training phantom using a novel telesurgical platform. The master controllers were connected to the local site on a 5 G network, teleoperating the robot remotely in a hospital. A video feed of the remote site was also streamed. The surgeon performed various tasks on the phantom such as cutting, dissection, pick-and-place and ring tower transfer. To assess the usefulness, usability and image quality of the system, the surgeon was subsequently interviewed using three structured questionnaires.

RESULTS

All tasks were completed successfully. The low latency and high bandwidth of the network resulted into a latency of 18 ms for the motion commands while the video delay was about 350 ms. This enabled the surgeon to operate smoothly with a high-definition video from about 300 km away. The surgeon viewed the system's usability in a neutral to positive way while the video image was rated as of good quality.

CONCLUSION

5 G networks provide significant advancement in the field of telecommunications, offering faster speeds and lower latency than previous generations of wireless technology. They can serve as an enabling technology for telesurgery and further advance its application and adoption.

Digital Transformation in the Diagnostics and Therapy of Cardiovascular Diseases: Comprehensive Literature Review

BACKGROUND

The digital transformation of our health care system has experienced a clear shift in the last few years due to political, medical, and technical innovations and reorganization. In particular, the cardiovascular field has undergone a significant change, with new broad perspectives in terms of optimized treatment strategies for patients nowadays.

OBJECTIVE

After a short historical introduction, this comprehensive literature review aimed to provide a detailed overview of the scientific evidence regarding digitalization in the diagnostics and therapy of cardiovascular diseases (CVDs).

METHODS

We performed an extensive literature search of the PubMed database and included all related articles that were published as of March 2022. Of the 3021 studies identified, 1639 (54.25%) studies were selected for a structured analysis and presentation (original articles: n=1273, 77.67%; reviews or comments: n=366, 22.33%). In addition to studies on CVDs in general, 829 studies could be assigned to a specific CVD with a diagnostic and therapeutic approach. For data presentation, all 829 publications were grouped into 6 categories of CVDs.

RESULTS

Evidence-based innovations in the cardiovascular field cover a wide medical spectrum, starting from the diagnosis of congenital heart diseases or arrhythmias and overoptimized workflows in the emergency care setting of acute myocardial infarction to telemedical care for patients having chronic diseases such as heart failure, coronary artery disease, or hypertension. The use of smartphones and wearables as well as the integration of artificial intelligence provides important tools for location-independent medical care and the prevention of adverse events.

CONCLUSIONS

Digital transformation has opened up multiple new perspectives in the cardiovascular field, with rapidly expanding scientific evidence. Beyond important improvements in terms of patient care, these innovations are also capable of reducing costs for our health care system. In the next few years, digital transformation will continue to revolutionize the field of cardiovascular medicine and broaden our medical and scientific horizons.

Development and Evaluation of a Mixed-Reality Tele-ultrasound System

OBJECTIVE

The objective of this feasibility study was to develop and assess a tele-ultrasound system that would enable an expert sonographer (situated at the remote site) to provide real-time guidance to an operator (situated at the imaging site) using a mixed-reality environment.

METHODS

An architecture along with the operational workflow of the system is designed and a prototype is developed that enables guidance in form of audiovisual cues. The visual cues comprise holograms (of the ultrasound images and ultrasound probe) and is rendered to the operator using a head-mounted display device. The position and orientation of the ultrasound probe's hologram are remotely controlled by the expert sonographer and guide the placement of a physical ultrasound probe at the imaging site. The developed prototype was evaluated for its performance on a network. In addition, a user study (with 12 participants) was conducted to assess the operator's ability to align the probe under different guidance modes.

RESULTS

The network performance revealed the view of the imaging site and ultrasound images were transferred to the remote site in 233 ± 42 and 158 ± 38 ms, respectively. The expert sonographer was able to transfer, to the imaging site, data related to position and orientation of the ultrasound probe's hologram in 78 ± 13 ms. The user study indicated that the audiovisual cues are sufficient for an operator to position and orient a physical probe for accurate depiction of the targeted tissue (p < 0.001). The probe's placement translational and rotational errors were 1.4 ± 0.6 mm and 5.4 ± 2.2º.

CONCLUSION

The work illustrates the feasibility of using a mixed-reality environment for effective communication between an expert sonographer (ultrasound physician) and an operator. Further studies are required to determine its applicability in a clinical setting during tele-ultrasound.

The feasibility and satisfaction study of 5G-based robotic teleultrasound diagnostic system in health check-ups

Objective

Regular check-up with ultrasound in underserved rural and/or remote areas is hampered due to the limited availability of sonologists and ultrasound devices. This study aimed to assess the feasibility and satisfaction of health check-ups with a 5G-based robotic teleultrasound diagnostic system.

Methods

In this prospective study, sonologists from two hospitals manipulated the telerobotic ultrasound system to perform teleultrasound check-ups of the liver, gallbladder, pancreas, spleen, kidneys, bladder, prostate (male), uterus and ovaries (female) for the subjects. The feasibility and satisfaction of health check-ups with a 5G-based robotic teleultrasound diagnostic system were evaluated in terms of examination results, examination duration, and satisfaction questionnaire survey.

Results

A total of 546 subjects were included with the most frequently diagnosed being abdominal disorders (n = 343) and male reproductive illnesses (n = 97), of which fatty liver (n = 204) and prostatic calcification (n = 54) were the most. The median teleultrasound examination duration (interquartile range) for men and women was 9 (9-11) min and 9 (7-11) min (p = 0.236), respectively. All the subjects were satisfied with this new type of telerobotic ultrasound check-ups and 96% reported no fear of the robotic arm during the examination.

Conclusion

The 5G-based teleultrasound robotic diagnostic system in health check-ups is feasible and satisfactory, indicating that this teleultrasound robot system may have significant application value in underserved rural and/or remote areas to mitigate disparity in achieving health equity.

Interaction between maintenance variables of medical ultrasound scanners through multifactor dimensionality reduction

BACKGROUND

Proper maintenance of electro-medical devices is crucial for the quality of care to patients and the economic performance of healthcare organizations. This research aims to identify the interaction between Ultrasound scanners (US) maintenance variables as a function of maintenance indicators: US in service or decommissioned, excessive number of failures, and failure rate. Knowing those interactions, specific maintenance measures will be developed to improve the reliability of the US.

RESEARCH DESIGN AND METHODS

Multifactor Dimensionality Reduction (MDR) method was eployed to analyze data from 222 US and their four-year maintenance history. Models were developed based on the variables with the greatest influence on maintenance indicators, where US were classified according to the associated risk.

RESULTS

US with more than one major failure or at least one major component replacement had up to 496.4% more failures than the average. Failure rate increased by up to 188.7% over the average for those US with more than three moderate failures, three replacements, or both.

CONCLUSIONS

This study identifies and quantifies the causes of risk to establish a specific maintenance plan for US. It helps to better understand the degradation of US to optimize their operation and maintenance.

A review on tele-manipulators for remote diagnostic procedures and surgery

With modern medicine and healthcare services improving in leaps and bounds, the integration of telemedicine has helped in expanding these specialised healthcare services to remote locations. Healthcare telerobotic systems form a component of telemedicine, which allows medical intervention from a distance. It has been nearly 40 years since a robotic technology, PUMA 560, was introduced to perform a stereotaxic biopsy in the brain. The use of telemanipulators for remote surgical procedures began around 1995, with the Aesop, the Zeus, and the da Vinci robotic surgery systems. Since then, the utilisation of robots has steadily increased in diverse healthcare disciplines, from clinical diagnosis to telesurgery. The telemanipulator system functions in a master–slave protocol mode, with the doctor operating the master system, aided by audio-visual and haptic feedback. Based on the control commands from the master, the slave system, a remote manipulator, interacts directly with the patient. It eliminates the requirement for the doctor to be physically present in the spatial vicinity of the patient by virtually bringing expert-guided medical services to them. Post the Covid-19 pandemic, an exponential surge in the utilisation of telerobotic systems has been observed. This study aims to present an organised review of the state-of-the-art telemanipulators used for remote diagnostic procedures and surgeries, highlighting their challenges and scope for future research and development.

Current Applications of Robot-Assisted Ultrasound Examination

Despite advances in miniaturization and automation, the need for expert acquisition of a full echocardiogram, including Doppler, has restricted access in remote areas. Recent developments in robotics, teleoperation, and upgraded telecommunications infrastructure may provide a solution to this deficiency. Robot-assisted teleoperated ultrasound examination can aid medical diagnosis in remote locations and may improve health inequalities between rural and urban settings. This review aimed to analyze the status of teleoperated robotic systems for ultrasound examinations, evaluate clinical and preclinical applications, identify limitations, and outline future directions for clinical use. Overall, robot-assisted teleoperated ultrasound is feasible and safe in the reported clinical and preclinical studies, with the robots able to follow the hand movements performed by sonographers and researchers from a distance or in local networks. Moreover, multiple types of ultrasound examinations have been performed in remote areas, with a high success rate nearly comparable to that of conventional sonography. The studies showed that although a low-bandwidth link can be used to control a robot, the bandwidth requirements for real-time transmission of video and ultrasound images are significantly higher. Furthermore, if haptic feedback is implemented, the bandwidth requirements are increased. Haptically enabled systems that improve robotic control are necessary for accelerating the introduction to clinical use. Haptic feedback and enhanced front-end interface control for remote users are vital aspects required for clinical application. The incorporation of artificial intelligence through either aiding in window acquisition (knowledge of anatomical landmarks to adjust scanning planes) or through measurement and disease identification is yet to be researched. However, it has the potential to lead to dramatic advances. A new generation of robots is in development, and several projects in the preclinical stage reveal a promising future to overcome the shortage of health professionals in remote areas.

Towards fully automated robotic platform for remote auscultation

BACKGROUND

Since most developed countries are facing an increase in the number of patients per healthcare worker due to a declining birth rate and an ageing population, relatively simple and safe diagnosis tasks may need to be performed using robotics and automation technologies, without specialists and hospitals. This study presents an automated robotic platform for remote auscultation, which is a highly cost-effective screening tool for detecting abnormal clinical signs.

METHOD

The developed robotic platform is composed of a 6-degree-of-freedom cooperative robotic arm, LiDAR camera, and a spring-based mechanism holding an electric stethoscope. The platform enables autonomous stethoscope positioning based on external body information acquired using the LiDAR camera-based multi-way registration; the platform also ensures safe and flexible contact, maintaining the contact force within a certain range through the passive-actuated mechanism.

RESULTS

Our preliminary results confirm that the robotic platform enables estimation of the landing positions required for cardiac examinations based on the depth and landmark information of the body surface. It also handles the stethoscope while maintaining the contact force without relying on the push-in displacement by the robotic arm.

CONCLUSION

The developed robotic platform enables the estimation of the landing positions and handling the stethoscope while maintaining the contact force, which promises the potential of automatic remote auscultation.

5G-Based Telerobotic Ultrasound System Improves Access to Breast Examination in Rural and Remote Areas: A Prospective and Two-Scenario Study

OBJECTIVE

Ultrasound (US) plays an important role in the diagnosis and management of breast diseases; however, effective breast US screening is lacking in rural and remote areas. To alleviate this issue, we prospectively evaluated the clinical availability of 5G-based telerobotic US technology for breast examinations in rural and remote areas.

METHODS

Between September 2020 and March 2021, 63 patients underwent conventional and telerobotic US examinations in a rural island (Scenario A), while 20 patients underwent telerobotic US examination in a mobile car located in a remote county (Scenario B) in May 2021. The safety, duration, US image quality, consistency, and acceptability of the 5G-based telerobotic US were assessed.

RESULTS

In Scenario A, the average duration of the telerobotic US procedure was longer than that of conventional US (10.3 ± 3.3 min vs. 7.6 ± 3.0 min, p = 0.017), but their average imaging scores were similar (4.86 vs. 4.90, p = 0.159). Two cases of gynecomastia, one of lactation mastitis, and one of postoperative breast effusion were diagnosed and 32 nodules were detected using the two US methods. There was good interobserver agreement between the US features and BI-RADS categories of the identical nodules (ICC = 0.795-1.000). In Scenario B, breast nodules were detected in 65% of the patients using telerobotic US. Its average duration was 10.1 ± 2.3 min, and the average imaging score was 4.85. Overall, 90.4% of the patients were willing to choose telerobotic US in the future, and tele-sonologists were satisfied with 85.5% of the examinations.

CONCLUSION

The 5G-based telerobotic US system is feasible for providing effective breast examinations in rural and remote areas.

5G-based remote magnetically controlled capsule endoscopy for examination of the stomach and small bowel

BACKGROUND AND AIMS

Remote endoscopy can improve diagnostic efficiency of gastrointestinal (GI) diseases for patients in remote areas. A novel remote magnetically controlled capsule endoscopy (MCE) system based on a 5G network was developed for real-time remote GI examinations. We aimed to evaluate the feasibility and safety of the 5G-based remote MCE for examination of the stomach and small bowel.

METHODS

This was a prospective, nonrandomized, comparative study. Consecutive participants enrolled in the First People's Hospital of Yinchuan underwent remote MCE examinations performed by an endoscopist located in Changhai Hospital. Consecutive participants enrolled in Changhai Hospital underwent conventional MCE examinations performed by the same endoscopist. The main outcomes included the complete visualization rate of the stomach and small bowel, safety assessment and network latency time of remote MCE examinations.

RESULTS

From March 2021 to June 2021, 20 participants in each group were enrolled. The complete visualization rate of the stomach and small bowel was 100% in both groups (p > 0.999) without any adverse event. The median network latency time of remote MCE group was 19.948 ms. Gastric examination time (8.96 vs. 8.92 min, p = 0.234), maneuverability (15.00 vs. 15.00, p = 0.317), image quality (1.00 vs. 1.00, p > 0.999) and diagnostic yields in the stomach and small bowel (55% vs. 30%, 5% vs. 0%, both p > 0.05) were comparable between remote and conventional MCE groups. All participants in remote MCE group considered remote MCE acceptable and necessary.

CONCLUSIONS

5G-based remote MCE was a feasible and safe method for viewing the stomach and small bowel.

5G-Assisted Remote Guidance in Laparoscopic Simulation Training Based on 3D Printed Dry Lab Models

This is a pilot study to assess the utility of applying 5G-assisted remote guidance in laparoscopic simulation training. A single trainee of a junior surgeon was recruited to complete three steps of tasks including basic task 1, basic task 2, and model task, and the performance was recorded and evaluated. The operator completed each task three times. Except for basic task 1, all tasks were remotely guided by a more experienced surgeon using 5G technology. Tasks completion time and a 30-point objective structured assessment of technical skills (OSATS) score were utilized to assess the results of simulation training. All remote guidance processes were successfully completed without significant network latency. Through basic task 1, the operator quickly became familiar with the trained laparoscopic instruments. For basic task 2, OSATS scores increased from 16 to 24 points, and completion time decreased from 1500 to 986 s after training under 5G-assisted remote guidance. For model tasks, OSATS scores increased from 15 to 26 points, and completion time decreased from 1734 to 1142 s. This is a novel mode of laparoscopic simulation training to increase the convenience of training. Perhaps in the near future, surgeons can simulate difficult operations at home or in the office, and accurately grasp the possible situations that may occur in actual operations in advance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12262-022-03590-2.

A novel service robot assignment approach for COVID-19 infected patients: a case of medical data driven decision making

Coronavirus Disease-19 (COVID-19) is a major concern for the entire world in the current era. Coronavirus is a very dangerous infectious virus that spreads rapidly from person to person. It spreads in exponential manner on a global scale. It affects the doctors, nurse and other COVID-19 warriors those who are actively involved for the treatment of COVID-19 infected (CI) patients. So, it is very much essential to focus on automation and artificial intelligence (AI) in different hospitals for the treatment of such infected patients and all should be very much careful to break the chain of spreading this novel virus. In this paper, a novel patient service robots (PSRs) assignment framework and a priority based (PB) method using fuzzy rule based (FRB) approach is proposed for the assignment of PSRs for CI patients in hospitals in order to provide safety to the COVID-19 warriors as well as to the CI infected patients. This novel approach is mainly focused on lowering the active involvement of COVID-19 warriors for the treatment of high asymptotic COVID-19 infected (HACI) patients for handling this tough situation. In this work, we have focused on HACI and low asymptotic COVID-19 infected (LACI) patients. Higher priority is given to HACI patients as compared to LACI patients to handle this critical situation in order to increase the survival probability of these patients. The proposed method deals with situations that practically arise during the assignment of PSRs for the treatment of such patients. The simulation of the work is carried out using MATLAB R2015b.

How the 5G Enabled the COVID-19 Pandemic Prevention and Control: Materiality, Affordance, and (De-)Spatialization

5G, the most disruptive innovation, had played a significant role in the COVID-19 pandemic prevention and control. However, as a novel technology and context, we have little knowledge about how 5G enabled pandemic prevention and control. This study collected 212 cases and conducted qualitative research to explore how the 5G worked in prevention and control. Based on the concepts of materiality and affordance, we grounded two affordances of spatialization and de-spatialization from the data. Spatialization provides non-contact ways to complete the tasks which are supposed to be completed in contact, and de-spatialization provides remote operations to complete the tasks which are supposed to be completed on-site. Spatialization and de-spatialization enabled the diagnosis and treatment of the infectors to relieve the unbalance of medical staff, cutting the infectious route to contain the viral spread, and logistic supply to support the prevention and control. Our study offers theoretical contributions to digital pandemic prevention and control, and the literature on 5G also offers practical implications.

Successful Use of a 5G-Based Robot-Assisted Remote Ultrasound System in a Care Center for Disabled Patients in Rural China

Background

Disability has become a global population health challenge. Due to difficulties in self-care or independent living, patients with disability mainly live in community-based care centers or institutions for long-term care. Nonetheless, these settings often lack basic medical resources, such as ultrasonography. Thus, remote ultrasonic robot technology for clinical applications across wide regions is imperative. To date, few experiences of remote diagnostic systems in rural care centers have been reported.

Objective

To assess the feasibility of a fifth-generation cellular technology (5G)-based robot-assisted remote ultrasound system in a care center for disabled patients in rural China.

Methods

Patients underwent remote robot-assisted and bedside ultrasound examinations of the liver, gallbladder, spleen, and kidneys. We compared the diagnostic consistency and differences between the two modalities and evaluated the examination duration, image quality, and safety.

Results

Forty-nine patients were included (21 men; mean age: 61.0 ± 19.0 [range: 19–91] years). Thirty-nine and ten had positive and negative results, respectively; 67 lesions were detected. Comparing the methods, 41 and 8 patients had consistent and inconsistent diagnoses, respectively. The McNemar and kappa values were 0.727 and 0.601, respectively. The mean duration of remote and bedside examinations was 12.2 ± 4.5 (range: 5–26) min and 7.5 ± 1.8 (range: 5–13) min (p < 0.001), respectively. The median image score for original images on the patient side and transmitted images on the doctor side was 5 points (interquartile range: [IQR]: 4.7–5.0) and 4.7 points (IQR: 4.5–5.0) (p = 0.176), respectively. No obvious complications from the examination were reported.

Conclusions

A 5G-based robot-assisted remote ultrasound system is feasible and has comparable diagnostic efficiency to traditional bedside ultrasound. This system may provide a unique solution for basic ultrasound diagnostic services in primary healthcare settings.

Military training-related abdominal injuries and diseases: Common types, prevention and treatment

Military training is intense, difficult and often dangerous, so all kinds of injuries or diseases frequently occur during training. Most of the previous studies and reviews on military training-related injuries focused on musculoskeletal system, whereas there are no reviews of abdominal injuries and diseases. Although the incidence of military training-related abdominal injuries and diseases is relatively low, the patients' condition is often critical especially in the presence of abdominal organ injury, leading to multi-organ dysfunction syndrome and even death. This paper elaborates on common types of military training-related abdominal injuries and diseases as well as the prevention and treatment measures, which provides some basis for scientific and reasonable training and improvement of medical security.

The role of contemporary digital tools and technologies in COVID-19 crisis: An exploratory analysis

Following the COVID-19 pandemic, there has been an increase in interest in using digital resources to contain pandemics. To avoid, detect, monitor, regulate, track, and manage diseases, predict outbreaks and conduct data analysis and decision-making processes, a variety of digital technologies are used, ranging from artificial intelligence (AI)-powered machine learning (ML) or deep learning (DL) focused applications to blockchain technology and big data analytics enabled by cloud computing and the internet of things (IoT). In this paper, we look at how emerging technologies such as the IoT and sensors, AI, ML, DL, blockchain, augmented reality, virtual reality, cloud computing, big data, robots and drones, intelligent mobile apps, and 5G are advancing health care and paving the way to combat the COVID-19 pandemic. The aim of this research is to look at possible technologies, processes, and tools for addressing COVID-19 issues such as pre-screening, early detection, monitoring infected/quarantined individuals, forecasting future infection rates, and more. We also look at the research possibilities that have arisen as a result of the use of emerging technology to handle the COVID-19 crisis.

Preliminary exploration of theory and practice training of 5G ultrasonic remote consultation in grassroot hospitals

Background

With the rapid development of science and technology, telemedicine diagnosis and treatment systems have gradually attracted increased attention and applications.5G ultrasound is an important branch of telemedicine, connecting grassroots hospitals at one end and provincal hospitals at the other, which provides remote guidance to grassroots doctors for ultrasound examination and image diagnosis. It is convenient for villagers obtaining diagnosis and advice from provincial ultrasound experts, saving time and economic costs, as well as benefiting from high-quality ultrasound medical resources. In this study, taishun County community grassroot hospitals were selected as the pilot study of 5G ultrasound application, to explore the effectiveness of their theory and practice, and gradually improve the remote ultrasound diagnosis and treatment standards, so as to improve their quality of grassroots hospitals and benefit grassroots people. 

Methods

This is a descriptive study. The Provincal Hospital will conduct ultrasonic theory and practice training for grassroot hospitals. The training subjects included 43 doctors in grassroots hospitals who were willing to carry out ultrasound examinations. Theories, skills training scores and trainees' questionnaires on teaching content were collected and analyzed. After passing theoretical and practical training, they will conduct ultrasound examinations in their respective communities and collect relevant cases. There are 148 cases thus far for analysis. It mainly included the type of disease, whether the patient was out-patient or inpatient, frequency of ultrasound visits in recent 5 years, and follow-up treatment measures.

Results

It mainly included three aspects: (1) Through theoretical and practical training, the ultrasonic diagnosis level of grassroot doctors was significantly improved. The difference in scores between the two practical trainings was statistically significant. (2) Forty-three questionnaires were sent out, feedback from trainees was very high. Most of them was very satisfied with our training. The total score of the questionnaire was 10, and 97.67% of them score more than 8. (3) In total, there were 148 remote consultation cases, including 67 males and 81 females, who were aged 21 to 101 years old (62.40 ± 15.73).mainly abdominal ultrasound, and typical cases involve fatty liver, hepatic cyst, gallbladder stone, kidney stone and so on. We analyzed case data and provided follow-up treatment recommendations.

Conclusion

As a “visual apparatus”, 5G ultrasound can be routinely carried out in grassroot hospitals, which can provide mutual benefit between doctors and patients and comprehensively promote healthy villages.

5G in Healthcare: from COVID-19 to Future Challenges

Worldwide up to May 2022 there have been 515 million cases of COVID-19 infection and over 6 million deaths. The World Health Organization estimated that 115,000 healthcare workers died from COVID-19 from January 2020 to May 2021. This toll on human lives prompted this review on 5G based networking primarily on major components of healthcare delivery: diagnosis, patient monitoring, contact tracing, diagnostic imaging tests, vaccines distribution, emergency medical services, telesurgery and robot-assisted tele-ultrasound. The positive impact of 5G as core technology for COVID-19 applications enabled exchange of huge data sets in fangcang (cabin) hospitals and real-time contact tracing, while the low latency enhanced robot-assisted tele-ultrasound, and telementoring during ophthalmic surgery. In other instances, 5G provided a supportive technology for applications related to COVID-19, e.g., patient monitoring. The feasibility of 5G telesurgery was proven, albeit by a few studies on real patients, in very low samples size in most instances. The important future applications of 5G in healthcare include surveillance of elderly people, the immunosuppressed, and nano- oncology for Internet of Nano Things (IoNT). Issues remain and these require resolution before routine clinical adoption. These include infrastructure and coverage; health risks; security and privacy protection of patients' data; 5G implementation with artificial intelligence, blockchain, and IoT; validation, patient acceptance and training of end-users on these technologies.

Use of Robots in Critical Care: Systematic Review

Background

The recent focus on the critical setting, especially with the COVID-19 pandemic, has highlighted the need for minimizing contact-based care and increasing robotic use. Robotics is a rising field in the context of health care, and we sought to evaluate the use of robots in critical care settings.

Objective

Although robotic presence is prevalent in the surgical setting, its role in critical care has not been well established. We aimed to examine the uses and limitations of robots for patients who are critically ill.

Methods

This systematic review was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. MEDLINE, Embase, IEEE Xplore, and ACM Library were searched from their inception to December 23, 2021. Included studies involved patients requiring critical care, both in intensive care units or high-dependency units, or settings that required critical care procedures (eg, intubation and cardiopulmonary resuscitation). Randomized trials and observational studies were included.

Results

A total of 33 studies were included. The greatest application of robots in the intensive care unit was in the field of telepresence, whereby robots proved advantageous in providing a reduced response time, earlier intervention, and lower mortality rates. Challenges of telepresence included regulatory and financial barriers. In therapy and stroke rehabilitation, robots achieved superior clinical outcomes safely. Robotic use in patient evaluation and assessment was mainly through ultrasound evaluation, obtaining satisfactory to superior results with the added benefits of remote assessment, time savings, and increased efficiency. Robots in drug dispensing and delivery increased efficiency and generated cost savings. All the robots had technological limitations and hidden costs.

Conclusions

Overall, our results show that robotic use in critical care settings is a beneficial, effective, and well-received intervention that delivers significant benefits to patients, staff, and hospitals. Looking ahead, it is necessary to form strong ethical and legislative frameworks and overcome various regulatory and financial barriers.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42021234162; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=234162

The evolving roles and impacts of 5G enabled technologies in healthcare: The world epidemic COVID-19 issues

The latest 5G technology is being introduced the Internet of Things (IoT) Era. The study aims to focus the 5G technology and the current healthcare challenges as well as to highlight 5G based solutions that can handle the COVID-19 issues in different arenas. This paper provides a comprehensive review of 5G technology with the integration of other digital technologies (like AI and machine learning, IoT objects, big data analytics, cloud computing, robotic technology, and other digital platforms) in emerging healthcare applications. From the literature, it is clear that the promising aspects of 5G (such as super-high speed, high throughput, low latency) have a prospect in healthcare advancement. Now healthcare is being adopted 5G-based technologies to aid improved health services, more effective medical research, enhanced quality of life, better experiences of medical professionals and patients in anywhere–anytime. This paper emphasizes the evolving roles of 5G technology for handling the epidemiological challenges. The study also discusses various technological challenges and prospective for developing 5G powered healthcare solutions. Further works will incorporate more studies on how to expand 5G-based digital society as well as to resolve the issues of safety–security–privacy and availability–accessibility–integrity in future health crises.

Ultrasound findings of lung ultrasonography in COVID-19: A systematic review

PURPOSE

To identify the defining lung ultrasound (LUS) findings of COVID-19, and establish its association to the initial severity of the disease and prognostic outcomes.

METHOD

Systematic review was conducted according to the PRISMA guidelines. We queried PubMed, Embase, Web of Science, Cochrane Database and Scopus using the terms ((coronavirus) OR (covid-19) OR (sars AND cov AND 2) OR (2019-nCoV)) AND (("lung ultrasound") OR (LUS)), from 31st of December 2019 to 31st of January 2021. PCR-confirmed cases of SARS-CoV-2 infection, obtained from original studies with at least 10 participants 18 years old or older, were included. Risk of bias and applicability was evaluated with QUADAS-2.

RESULTS

We found 1333 articles, from which 66 articles were included, with a pooled population of 4687 patients. The most examined findings were at least 3 B-lines, confluent B-lines, subpleural consolidation, pleural effusion and bilateral or unilateral distribution. B-lines, its confluent presentation and pleural abnormalities are the most frequent findings. LUS score was higher in intensive care unit (ICU) patients and emergency department (ED), and it was associated with a higher risk of developing unfavorable outcomes (death, ICU admission or need for mechanical ventilation). LUS findings and/or the LUS score had a good negative predictive value in the diagnosis of COVID-19 compared to RT-PCR.

CONCLUSIONS

The most frequent ultrasound findings of COVID-19 are B-lines and pleural abnormalities. High LUS score is associated with developing unfavorable outcomes. The inclusion of pleural effusion in the LUS score and the standardisation of the imaging protocol in COVID-19 LUS remains to be defined.

Remote Ultrasound Scan Procedures with Medical Robots: Towards New Perspectives between Medicine and Engineering

Background

This review explores state-of-the-art teleoperated robots for medical ultrasound scan procedures, providing a comprehensive look including the recent trends arising from the COVID-19 pandemic.

Methods

Physicians' experience is included to indicate the importance of their role in the design of improved medical robots. From this perspective, novel classes of equipment for remote diagnostics based on medical robotics are discussed in terms of innovative engineering technologies.

Results

Relevant literature is reviewed under the system engineering point of view, organizing the discussion on the basis of the main technological focus of each contribution.

Conclusions

This contribution is aimed at stimulating new research to obtain faster results on teleoperated robotics for ultrasound diagnostics in response to the high demand raised by the ongoing pandemic.

Applications of Healthcare Robots in Combating the COVID-19 Pandemic

Due to the increasing number of COVID-19 cases, there is a remarkable demand for robots, especially in the clinical sector. SARS-CoV-2 mainly propagates due to close human interactions and contaminated surfaces, and hence, maintaining social distancing has become a mandatory preventive measure. This generates the need to treat patients with minimal doctor-patient interaction. Introducing robots in the healthcare sector protects the frontline healthcare workers from getting exposed to the coronavirus as well as decreases the need for medical personnel as robots can partially take over some medical roles. The aim of this paper is to highlight the emerging role of robotic applications in the healthcare sector and allied areas. To this end, a systematic review was conducted regarding the various robots that have been implemented worldwide during the COVID-19 pandemic to attenuate and contain the virus. The results obtained from this study reveal that the implementation of robotics into the healthcare field has a substantial effect in controlling the spread of SARS-CoV-2, as it blocks coronavirus propagation between patients and healthcare workers, along with other advantages such as disinfection or cleaning.

5G Use in Healthcare: The Future is Present

Background:

Most healthcare providers are unaware of the extraordinary opportunities for implementation in healthcare which can be enabled by 5G wireless networks. 5G created enormous opportunities for a myriad of new technologies, resulting in an integrated through 5G ‘ecosystem’. Although the new opportunities in healthcare are immense, medicine is slow to change, as manifest by the paucity of new, innovative applications based upon this ecosystem. Thus, emerges the need to “avoid technology surprise” - both laparoscopic and robotic assisted minimally invasive surgery were delayed for years because the surgical community was either unaware or unaccepting of a new technology.

Database:

PubMed (Medline) and Scopus (Elsevier) databases were searched and all published studies regarding clinical applications of 5G were retrieved. From a total of 40 articles, 13 were finally included in our review.

Discussion:

The important transformational properties of 5G communications and other innovative technologies are described and compared to healthcare needs, looking for opportunities, limitations, and challenges to implementation of 5G and the ecosystem it has spawned. Furthermore, the needs in the clinical applications, education and research in medicine and surgery, in addition to the administrative infrastructure are addressed. Additionally, we explore the nontechnical challenges, that either support or oppose this new healthcare renovation. Based upon proven advantages of these innovative technologies, current scientific evidence is analyzed for future trends for the transformation of healthcare. By providing awareness of these opportunities and their advantages for patients, it will be possible to decrease the prolonged timeframe for acceptance and implementation for patients.

Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review

BACKGROUND

Technologies have been extensively implemented to provide health care services for all types of clinical conditions during the COVID-19 pandemic. While several reviews have been conducted regarding technologies used during the COVID-19 pandemic, they were limited by focusing either on a specific technology (or features) or proposed rather than implemented technologies.

OBJECTIVE

This review aims to provide an overview of technologies, as reported in the literature, implemented during the first wave of the COVID-19 pandemic.

METHODS

We conducted a scoping review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Extension for Scoping Reviews. Studies were retrieved by searching 8 electronic databases, checking the reference lists of included studies and relevant reviews (backward reference list checking), and checking studies that cited included studies (forward reference list checking). The search terms were chosen based on the target intervention (ie, technologies) and the target disease (ie, COVID-19). We included English publications that focused on technologies or digital tools implemented during the COVID-19 pandemic to provide health-related services regardless of target health condition, user, or setting. Two reviewers independently assessed the eligibility of studies and extracted data from eligible papers. We used a narrative approach to synthesize extracted data.

RESULTS

Of 7374 retrieved papers, 126 were deemed eligible. Telemedicine was the most common type of technology (107/126, 84.9%) implemented in the first wave of the COVID-19 pandemic, and the most common mode of telemedicine was synchronous (100/108, 92.6%). The most common purpose of the technologies was providing consultation (75/126, 59.5%), followed by following up with patients (45/126, 35.7%), and monitoring their health status (22/126, 17.4%). Zoom (22/126, 17.5%) and WhatsApp (12/126, 9.5%) were the most commonly used videoconferencing and social media platforms, respectively. Both health care professionals and health consumers were the most common target users (103/126, 81.7%). The health condition most frequently targeted was COVID-19 (38/126, 30.2%), followed by any physical health conditions (21/126, 16.7%), and mental health conditions (13/126, 10.3%). Technologies were web-based in 84.1% of the studies (106/126). Technologies could be used through 11 modes, and the most common were mobile apps (86/126, 68.3%), desktop apps (73/126, 57.9%), telephone calls (49/126, 38.9%), and websites (45/126, 35.7%).

CONCLUSIONS

Technologies played a crucial role in mitigating the challenges faced during the COVID-19 pandemic. We did not find papers describing the implementation of other technologies (eg, contact-tracing apps, drones, blockchain) during the first wave. Furthermore, technologies in this review were used for other purposes (eg, drugs and vaccines discovery, social distancing, and immunity passport). Future research on studies on these technologies and purposes is recommended, and further reviews are required to investigate technologies implemented in subsequent waves of the pandemic.

Autonomous Scanning Target Localization for Robotic Lung Ultrasound Imaging

Under the ceaseless global COVID-19 pandemic, lung ultrasound (LUS) is the emerging way for effective diagnosis and severeness evaluation of respiratory diseases. However, close physical contact is unavoidable in conventional clinical ultrasound, increasing the infection risk for health-care workers. Hence, a scanning approach involving minimal physical contact between an operator and a patient is vital to maximize the safety of clinical ultrasound procedures. A robotic ultrasound platform can satisfy this need by remotely manipulating the ultrasound probe with a robotic arm. This paper proposes a robotic LUS system that incorporates the automatic identification and execution of the ultrasound probe placement pose without manual input. An RGB-D camera is utilized to recognize the scanning targets on the patient through a learning-based human pose estimation algorithm and solve for the landing pose to attach the probe vertically to the tissue surface; A position/force controller is designed to handle intraoperative probe pose adjustment for maintaining the contact force. We evaluated the scanning area localization accuracy, motion execution accuracy, and ultrasound image acquisition capability using an upper torso mannequin and a realistic lung ultrasound phantom with healthy and COVID-19-infected lung anatomy. Results demonstrated the overall scanning target localization accuracy of 19.67 ± 4.92 mm and the probe landing pose estimation accuracy of 6.92 ± 2.75 mm in translation, 10.35 ± 2.97 deg in rotation. The contact force-controlled robotic scanning allowed the successful ultrasound image collection, capturing pathological landmarks.

Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread rapidly and affected most of the world since its outbreak in Wuhan, China, which presents a major challenge to the emergency response mechanism for sudden public health events and epidemic prevention and control in all countries. In the face of the severe situation of epidemic prevention and control and the arduous task of social management, the tremendous power of science and technology in prevention and control has emerged. The new generation of information technology, represented by big data and artificial intelligence (AI) technology, has been widely used in the prevention, diagnosis, treatment and management of COVID-19 as an important basic support. Although the technology has developed, there are still challenges with respect to epidemic surveillance, accurate prevention and control, effective diagnosis and treatment, and timely judgement. The prevention and control of sudden infectious diseases usually depend on the control of infection sources, interruption of transmission channels and vaccine development. Big data and AI are effective technologies to identify the source of infection and have an irreplaceable role in distinguishing close contacts and suspicious populations. Advanced computational analysis is beneficial to accelerate the speed of vaccine research and development and to improve the quality of vaccines. AI provides support in automatically processing relevant data from medical images and clinical features, tests and examination findings; predicting disease progression and prognosis; and even recommending treatment plans and strategies. This paper reviews the application of big data and AI in the COVID-19 prevention, diagnosis, treatment and management decisions in China to explain how to apply big data and AI technology to address the common problems in the COVID-19 pandemic. Although the findings regarding the application of big data and AI technologies in sudden public health events lack validation of repeatability and universality, current studies in China have shown that the application of big data and AI is feasible in response to the COVID-19 pandemic. These studies concluded that the application of big data and AI technology can contribute to prevention, diagnosis, treatment and management decision making regarding sudden public health events in the future.

Tele-Operative Low-Cost Robotic Lung Ultrasound Scanning Platform for Triage of COVID-19 Patients

Novel severe acute respiratory syndrome coronavirus 2 (COVID-19) has become a pandemic of epic proportions, and global response to prepare health systems worldwide is of utmost importance. 2-dimensional (2D) lung ultrasound (LUS) has emerged as a rapid, noninvasive imaging tool for diagnosing COVID-19 infected patients. Concerns surrounding LUS include the disparity of infected patients and healthcare providers, and importantly, the requirement for substantial physical contact between the patient and operator, increasing the risk of transmission. New variants of COVID-19 will continue to emerge; therefore, mitigation of the virus's spread is of paramount importance. A tele-operative robotic ultrasound platform capable of performing LUS in COVID-19 infected patients may be of significant benefit, especially in low- and middle-income countries. The authors address the issues mentioned above surrounding the use of LUS in COVID-19 infected patients and the potential for extension of this technology in a resource-limited environment. Additionally, first-time application, feasibility, and safety were validated in healthy subjects. Preliminary results demonstrate that our platform allows for the successful acquisition and application of robotic LUS in humans.

Telerobotic Operation of Intensive Care Unit Ventilators

Since the first reports of a novel coronavirus (SARS-CoV-2) in December 2019, over 33 million people have been infected worldwide and approximately 1 million people worldwide have died from the disease caused by this virus, COVID-19. In the United States alone, there have been approximately 7 million cases and over 200,000 deaths. This outbreak has placed an enormous strain on healthcare systems and workers. Severe cases require hospital care, and 8.5% of patients require mechanical ventilation in an intensive care unit (ICU). One major challenge is the necessity for clinical care personnel to don and doff cumbersome personal protective equipment (PPE) in order to enter an ICU unit to make simple adjustments to ventilator settings. Although future ventilators and other ICU equipment may be controllable remotely through computer networks, the enormous installed base of existing ventilators do not have this capability. This paper reports the development of a simple, low cost telerobotic system that permits adjustment of ventilator settings from outside the ICU. The system consists of a small Cartesian robot capable of operating a ventilator touch screen with camera vision control via a wirelessly connected tablet master device located outside the room. Engineering system tests demonstrated that the open-loop mechanical repeatability of the device was 7.5 mm, and that the average positioning error of the robotic finger under visual servoing control was 5.94 mm. Successful usability tests in a simulated ICU environment were carried out and are reported. In addition to enabling a significant reduction in PPE consumption, the prototype system has been shown in a preliminary evaluation to significantly reduce the total time required for a respiratory therapist to perform typical setting adjustments on a commercial ventilator, including donning and doffing PPE, from 271 to 109 s.

Association of Lung Ultrasound Score with Mortality and Severity of COVID-19: A Meta-Analysis and Trial Sequential Analysis

OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic has rapidly spread all over the world. Lung ultrasound (LUS) has emerged as a useful tool for diagnosing many respiratory diseases. The prognostic role of LUS in COVID-19 patients has not yet been established.

METHODS

Several databases were searched on 09 April 2021. The difference in LUS score between the death and survival groups, and the relationship between LUS score and COVID-19 severity were both assessed.

RESULTS

The LUS score was significantly higher in the death group compared with the survival group (weighted mean difference (WMD) = 8.21, 95% CI: 4.74-11.67, P < 0.001), which was confirmed by trial sequential analysis. Those with mild/moderate, severe and critical COVID-19 had a progressively higher LUS score (critical vs. severe: WMD = 8.78, 95% CI: 4.17-13.38; P < 0.001; critical vs. mild/moderate/severe: WMD = 10.00, 95% CI: 6.83-13.17, P < 0.001; severe vs. moderate: WMD = 5.96, 95% CI: 3.48-8.44, P < 0.001; severe vs. mild/moderate: WMD = 7.31, 95% CI: 4.45-10.17, P < 0.001).

CONCLUSIONS

The LUS score was associated with mortality and severity of COVID-19. The LUS score might be a risk stratification tool for COVID-19 patients.

Progress in robotics for combating infectious diseases

The world was unprepared for the COVID-19 pandemic, and recovery is likely to be a long process. Robots have long been heralded to take on dangerous, dull, and dirty jobs, often in environments that are unsuitable for humans. Could robots be used to fight future pandemics? We review the fundamental requirements for robotics for infectious disease management and outline how robotic technologies can be used in different scenarios, including disease prevention and monitoring, clinical care, laboratory automation, logistics, and maintenance of socioeconomic activities. We also address some of the open challenges for developing advanced robots that are application oriented, reliable, safe, and rapidly deployable when needed. Last, we look at the ethical use of robots and call for globally sustained efforts in order for robots to be ready for future outbreaks.

Using remote consultation to enhance diagnostic accuracy of bedside transthoracic echocardiography during COVID-19 pandemic

Objective

The aim of this study was to evaluate the clinical significance of remote consultation over bedside transthoracic echocardiography (RC‐B‐TTE) for patients with coronavirus disease 2019 (COVID‐19).

Methods

Five frontline echocardiographers performed and interpreted B‐TTE for 30 patients with COVID‐19 in the isolation wards, and the on‐site B‐TTE reports (OSR) were generated. Then remote consultation over the 30 B‐TTE studies was conducted by two experienced echocardiographic consultants while blinded to the OSR, and the corresponding remote consultation reports (RCR) were generated. Subsequently, the five frontline echocardiographers were convened together to discuss the difference between the OSR and RCR, and to confirm the correct interpretation and the misdiagnosis using a “majority‐vote” consensus as the diagnostic “gold standard”. Afterwards the reasons for the misdiagnosis were given by the frontline echocardiographers themselves. The inter‐rater agreement between the OSR and the “gold standard” was assessed using Kappa coefficient and percent agreement.

Results

Complete correctness of the 30 copies of the RCR were determined by the 5 frontline echocardiographers. The reliability of the OSR in the findings of cardiac chamber dilation, left ventricular hypertrophy and pulmonary hypertension were weak (Kappa <0.6). The reliability of the OSR in the recognition of major cardiac abnormalities was very weak (Kappa =0.304, percent agreement =63.3%). Misdiagnosis of major abnormalities was found in 11 copies of OSR (11/30, 36.7%).

Conclusions

The protocol of RC‐B‐TTE has shown noticeable superiority in ameliorating diagnostic accuracy of echocardiography, which should be generalized to clinical practice during the COVID‐19 or similar pandemic.

Autonomous Robotic Point-of-Care Ultrasound Imaging for Monitoring of COVID-19-Induced Pulmonary Diseases

The COVID-19 pandemic has emerged as a serious global health crisis, with the predominant morbidity and mortality linked to pulmonary involvement. Point-of-Care ultrasound (POCUS) scanning, becoming one of the primary determinative methods for its diagnosis and staging, requires, however, close contact of healthcare workers with patients, therefore increasing the risk of infection. This work thus proposes an autonomous robotic solution that enables POCUS scanning of COVID-19 patients’ lungs for diagnosis and staging. An algorithm was developed for approximating the optimal position of an ultrasound probe on a patient from prior CT scans to reach predefined lung infiltrates. In the absence of prior CT scans, a deep learning method was developed for predicting 3D landmark positions of a human ribcage given a torso surface model. The landmarks, combined with the surface model, are subsequently used for estimating optimal ultrasound probe position on the patient for imaging infiltrates. These algorithms, combined with a force–displacement profile collection methodology, enabled the system to successfully image all points of interest in a simulated experimental setup with an average accuracy of 20.6 ± 14.7 mm using prior CT scans, and 19.8 ± 16.9 mm using only ribcage landmark estimation. A study on a full torso ultrasound phantom showed that autonomously acquired ultrasound images were 100% interpretable when using force feedback with prior CT and 88% with landmark estimation, compared to 75 and 58% without force feedback, respectively. This demonstrates the preliminary feasibility of the system, and its potential for offering a solution to help mitigate the spread of COVID-19 in vulnerable environments.

Visual SLAM for robot navigation in healthcare facility

The COVID-19 pandemic has affected many countries, posing a threat to human health and safety, and putting tremendous pressure on the medical system. This paper proposes a novel SLAM technology using RGB and depth images to improve hospital operation efficiency, reduce the risk of doctor-patient cross-infection, and curb the spread of the COVID-19. Most current visual SLAM researches assume that the environment is stationary, which makes handling real-world scenarios such as hospitals a challenge. This paper proposes a method that effectively deals with SLAM problems for scenarios with dynamic objects, e.g., people and movable objects, based on the semantic descriptor extracted from images with help of a knowledge graph. Specifically, our method leverages a knowledge graph to construct a priori movement relationship between entities and establishes high-level semantic information. Built upon this knowledge graph, a semantic descriptor is constructed to describe the semantic information around key points, which is rotation-invariant and robust to illumination. The seamless integration of the knowledge graph and semantic descriptor helps eliminate the dynamic objects and improves the accuracy of tracking and positioning of robots in dynamic environments. Experiments are conducted using data acquired from healthcare facilities, and semantic maps are established to meet the needs of robots for delivering medical services. In addition, to compare with the state-of-the-art methods, a publicly available dataset is used in our evaluation. Compared with the state-of-the-art methods, our proposed method demonstrated great improvement with respect to both accuracy and robustness in dynamic environments. The computational efficiency is also competitive.

An Improved Sensing Method of a Robotic Ultrasound System for Real-Time Force and Angle Calibration

An ultrasonic examination is a clinically universal and safe examination method, and with the development of telemedicine and precision medicine, the robotic ultrasound system (RUS) integrated with a robotic arm and ultrasound imaging system receives increasing attention. As the RUS requires precision and reproducibility, it is important to monitor the real-time calibration of the RUS during examination, especially the angle of the probe for image detection and its force on the surface. Additionally, to speed up the integration of the RUS and the current medical ultrasound system (US), the current RUSs mostly use a self-designed fixture to connect the probe to the arm. If the fixture has inconsistencies, it may cause an operating error. In order to improve its resilience, this study proposed an improved sensing method for real-time force and angle calibration. Based on multichannel pressure sensors, an inertial measurement unit (IMU), and a novel sensing structure, the ultrasonic probe and robotic arm could be simply and rapidly combined, which rendered real-time force and angle calibration at a low cost. The experimental results show that the average success rate of the downforce position identification achieved was 88.2%. The phantom experiment indicated that the method could assist the RUS in the real-time calibration of both force and angle during an examination.

A 5G-powered robot-assisted teleultrasound diagnostic system in an intensive care unit

Background

Teleultrasound provides an effective solution to problems that arise from limited medical resources, a lack of local expertise, and scenarios where the risk of infection is high. This study aims to explore the feasibility of the application of a 5G-powered robot-assisted teleultrasound diagnostic system in an intensive care unit.

Methods

In this study, the robot-assisted teleultrasound diagnostic system MGIUS-R3 was used. Using 5G network technology, the doctor manipulates the robotic arm to perform teleultrasound examination. The doctor can adjust parameters via the teleultrasound control panel, and real-time transmission of audio, video and ultrasound images can facilitate simultaneous communication between both parties. All patients underwent robot-assisted teleultrasound examination and bedside ultrasound examination of the liver, gallbladder, pancreas, spleen, kidney, as well as assessment for pleural effusion and abdominal effusion. We evaluated the feasibility of the application of the robot-assisted teleultrasound diagnosis system in the intensive care unit in terms of consultation duration, image quality, and safety. We also compared diagnostic consistency and differences.

Results

Apart from one patient who was excluded due to severe intestinal gas interference and poor image quality, a total of 32 patients were included in this study. Every patient completed all relevant examinations. Among them, 20 patients were male; 12 were female. The average age of the patients was 61 ± 20 years. The average duration of teleultrasound diagnosis was 17 ± 7 min. Of the 32 patients, 26 had positive results, 6 had negative results, and 5 had inconsistent diagnoses. The overall diagnostic results were basically the same, and there were no differences in diagnostic levels between the two. The overall average image quality score was 4.73 points, which represented a high-quality image. After robot-assisted teleultrasound examination, no significant changes were observed in the vital signs of patients as compared to before examination, and no examination-related complications were found.

Conclusion

The 5G-powered robot-assisted teleultrasound diagnostic system was associated with the benefits of clear images, simple operation, relatively high levels of consistency in terms of diagnostic results, higher levels of safety, and has considerable application value in the intensive care unit.

Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review (Preprint).. [DOI: 10.2196/preprints.29136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

BACKGROUND

Technologies have been extensively implemented to provide health care services for all types of clinical conditions during the COVID-19 pandemic. While several reviews have been conducted regarding technologies used during the COVID-19 pandemic, they were limited by focusing either on a specific technology (or features) or proposed rather than implemented technologies.

OBJECTIVE

This review aims to provide an overview of technologies, as reported in the literature, implemented during the first wave of the COVID-19 pandemic.

METHODS

We conducted a scoping review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Extension for Scoping Reviews. Studies were retrieved by searching 8 electronic databases, checking the reference lists of included studies and relevant reviews (backward reference list checking), and checking studies that cited included studies (forward reference list checking). The search terms were chosen based on the target intervention (ie, technologies) and the target disease (ie, COVID-19). We included English publications that focused on technologies or digital tools implemented during the COVID-19 pandemic to provide health-related services regardless of target health condition, user, or setting. Two reviewers independently assessed the eligibility of studies and extracted data from eligible papers. We used a narrative approach to synthesize extracted data.

RESULTS

Of 7374 retrieved papers, 126 were deemed eligible. Telemedicine was the most common type of technology (107/126, 84.9%) implemented in the first wave of the COVID-19 pandemic, and the most common mode of telemedicine was synchronous (100/108, 92.6%). The most common purpose of the technologies was providing consultation (75/126, 59.5%), followed by following up with patients (45/126, 35.7%), and monitoring their health status (22/126, 17.4%). Zoom (22/126, 17.5%) and WhatsApp (12/126, 9.5%) were the most commonly used videoconferencing and social media platforms, respectively. Both health care professionals and health consumers were the most common target users (103/126, 81.7%). The health condition most frequently targeted was COVID-19 (38/126, 30.2%), followed by any physical health conditions (21/126, 16.7%), and mental health conditions (13/126, 10.3%). Technologies were web-based in 84.1% of the studies (106/126). Technologies could be used through 11 modes, and the most common were mobile apps (86/126, 68.3%), desktop apps (73/126, 57.9%), telephone calls (49/126, 38.9%), and websites (45/126, 35.7%).

CONCLUSIONS

Technologies played a crucial role in mitigating the challenges faced during the COVID-19 pandemic. We did not find papers describing the implementation of other technologies (eg, contact-tracing apps, drones, blockchain) during the first wave. Furthermore, technologies in this review were used for other purposes (eg, drugs and vaccines discovery, social distancing, and immunity passport). Future research on studies on these technologies and purposes is recommended, and further reviews are required to investigate technologies implemented in subsequent waves of the pandemic.