Robotic-assisted ultrasound for fetal imaging: Evolution from single-arm to dual-arm system

© Springer Nature Switzerland AG 2019. The development of robotic-assisted extracorporeal ultrasound systems has a long history and a number of projects have been proposed since the 1990s focusing on different technical aspects. These aim to resolve the deficiencies of on-site manual manipulation of hand-held ultrasound probes. This paper presents the recent ongoing developments of a series of bespoke robotic systems, including both single-arm and dual-arm versions, for a project known as intelligent Fetal Imaging and Diagnosis (iFIND). After a brief review of the development history of the extracorporeal ultrasound robotic system used for fetal and abdominal examinations, the specific aim of the iFIND robots, the design evolution, the implementation details of each version, and the initial clinical feedback of the iFIND robot series are presented. Based on the preliminary testing of these newly-proposed robots on 42 volunteers, the successful and reliable working of the mechatronic systems were validated. Analysis of a participant questionnaire indicates a comfortable scanning experience for the volunteers and a good acceptance rate to being scanned by the robots

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.Comment: Accepted by Medical Image Analysi

Improving access to ultrasound imaging in northern, remote communities

Access to healthcare services—including access to medical imaging—is an important determinant of health outcomes. This thesis aims to improve understanding of and address gaps in access to ultrasound imaging for patients in northern, remote communities, and advance a novel ultrasound technology with the ultimate goal of improving patient care and health outcomes. This thesis first brings greater understanding of patients’ perceptions of access and factors which shape access to ultrasound imaging in northern, remote communities in Saskatchewan, Canada. A qualitative study was performed using interpretive description as a methodological approach and a multi-dimensional conceptualization of access to care as a theoretical framework. The study identified barriers which patients in northern, remote communities face in accessing ultrasound imaging, and demonstrated that geographic remoteness from imaging facilities was a central barrier. To determine whether disparities in access to ultrasound imaging resulted in disparities in utilization of ultrasound services, two population-based studies assessed the association between sociodemographic and geographic factors and obstetrical and non-obstetrical ultrasound utilization in Saskatchewan. In the first study investigating obstetrical ultrasound utilization, multivariate logistic regression analysis demonstrated that women living in rural areas, remote areas, and low income neighbourhoods, as well as status First Nations women, were less likely to have a second trimester ultrasound, an important aspect of prenatal care. In a second study investigating non-obstetrical ultrasound utilization across the entire provincial population, multivariate Poisson regression analysis similarly demonstrated lower rates of non-obstetrical ultrasound utilization among individuals living in rural and remote areas, individuals residing in low income neighbourhoods, and status First Nations persons. To address the barriers which patients in northern, remote communities face in accessing ultrasound imaging and to minimize disparities in ultrasound imaging utilization as identified in previous studies in this thesis, telerobotic ultrasound technology was investigated as a solution to improve access to ultrasound imaging. Using this technology, radiologists and sonographers could remotely manipulate an ultrasound probe via a robotic arm, thereby remotely performing an ultrasound exam while patients remained in their home community. A clinical trial comparing conventional and telerobotic ultrasound approaches was undertaken, validating this technology for obstetrical ultrasound imaging. To determine the feasibility of using telerobotic technology to establish an ultrasound service delivery model to remotely provide diagnostic ultrasound exams in underserved communities, pilot telerobotic ultrasound clinics were developed in three northern, remote communities. Telerobotic ultrasound exams were sufficient for diagnosis in the majority of cases, minimizing travel or reducing wait times for these patients. This technology was subsequently evaluated during a COVID-19 outbreak in northern Saskatchewan, demonstrating the potential of this technology to provide critical ultrasound services to an underserved northern population and minimize health inequities during the COVID-19 pandemic. An economic evaluation was performed to compare a service delivery model using telerobotic ultrasound technology to alternative service delivery models. Telerobotic ultrasound combined with an itinerant sonographer service was found to be the lowest cost option from both a publicly funded healthcare payer perspective and a societal perspective for many northern, remote communities. This thesis provides key insights for health system leaders seeking improved understanding and novel solutions to improve access to ultrasound imaging in northern, remote communities. Findings suggest that telerobotic ultrasound is a viable solution to improve access to ultrasound imaging and reduce costs associated with ultrasound service delivery. Evidence in this thesis may be used to help improve ultrasound services and health equity for patients in underserved northern, remote communities. Continued respectful collaboration with northern, remote, Indigenous peoples and communities will be a critical aspect to ensure that ultrasound services meet community needs

Knowledge-based Robot Control

The paper is related with the problem of developing autonomous intelligent robots for complex environments. In details it outlines a knowledge-based robot control architecture that combines several techniques in order to supply an ability to adapt and act autonomously in complex environments. The described architecture has been implemented as a robotic system that demonstrates its operation in dynamic environment. Although the robotic system demonstrates a certain level of autonomy, the experiments show that there are situation, in which the developed base architecture should be complemented with additional modules. The last few chapters of the paper describe the experimentation results and the current state of further research towards the developed architecture

Ultrasound in augmented reality: a mixed-methods evaluation of head-mounted displays in image-guided interventions

Purpose: Augmented reality (AR) and head-mounted displays (HMD) in medical practice are current research topics. A commonly proposed use case of AR-HMDs is to display data in image-guided interventions. Although technical feasibility has been thoroughly shown, effects of AR-HMDs on interventions are not yet well researched, hampering clinical applicability. Therefore, the goal of this study is to better understand the benefits and limitations of this technology in ultrasound-guided interventions. Methods: We used an AR-HMD system (based on the first-generation Microsoft Hololens) which overlays live ultrasound images spatially correctly at the location of the ultrasound transducer. We chose ultrasound-guided needle placements as a representative task for image-guided interventions. To examine the effects of the AR-HMD, we used mixed methods and conducted two studies in a lab setting: (1) In a randomized crossover study, we asked participants to place needles into a training model and evaluated task duration and accuracy with the AR-HMD as compared to the standard procedure without visual overlay and (2) in a qualitative study, we analyzed the user experience with AR-HMD using think-aloud protocols during ultrasound examinations and semi-structured interviews after the task. Results: Participants (n = 20) placed needles more accurately (mean error of 7.4 mm vs. 4.9 mm, p = 0.022) but not significantly faster (mean task duration of 74.4 s vs. 66.4 s, p = 0.211) with the AR-HMD. All participants in the qualitative study (n = 6) reported limitations of and unfamiliarity with the AR-HMD, yet all but one also clearly noted benefits and/or that they would like to test the technology in practice. Conclusion: We present additional, though still preliminary, evidence that AR-HMDs provide benefits in image-guided procedures. Our data also contribute insights into potential causes underlying the benefits, such as improved spatial perception. Still, more comprehensive studies are needed to ascertain benefits for clinical applications and to clarify mechanisms underlying these benefits

Image-guided therapy system for interstitial gynecologic brachytherapy in a multimodality operating suite

In this contribution, an image-guided therapy system supporting gynecologic radiation therapy is introduced. The overall workflow of the presented system starts with the arrival of the patient and ends with follow-up examinations by imaging and a superimposed visualization of the modeled device from a PACS system. Thereby, the system covers all treatments stages (pre-, intra- and postoperative) and has been designed and constructed by a computer scientist with feedback from an interdisciplinary team of physicians and engineers. This integrated medical system enables dispatch of diagnostic images directly after acquisition to a processing workstation that has an on-board 3D Computer Aided Design model of a medical device. Thus, allowing precise identification of catheter location in the 3D imaging model which later provides rapid feedback to the clinician regarding device location. Moreover, the system enables the ability to perform patient-specific pre-implant evaluation by assessing the placement of interstitial needles prior to an intervention via virtual template matching with a diagnostic scan.Comment: 7 pages, 3 figure