Rapid Learning of Focused Cardiac Ultrasound for Early Identification of COVID-19 Complications: A Collaborative Effort.
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ABSTRACT:
SUBMITTER: Sertich AP
PROVIDER: S-EPMC7826155 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Transcranial focused ultrasound is a non-invasive therapeutic modality that can be used to treat essential tremor. Beams of energy are focused into a small spot in the thalamus, resulting in tissue heating and ablation. Here, we report on a rapid 3D numeric simulation framework that can be used to predict focal spot characteristics prior to the application of ultrasound. By comparing with magnetic resonance proton resonance frequency shift thermometry (MR thermometry) data acquired during treatments of essential tremor, we verified that our simulation framework can be used to predict focal spot position, and with patient-specific calibration, predict focal spot temperature rise. Preliminary data suggests that lateral smearing of the focal spot can be simulated. The framework may also be relevant for other therapeutic ultrasound applications such as blood brain barrier opening and neuromodulation.
| S-EPMC6538644 | biostudies-literature
Project description:Currently, no non-invasive cardiac pacing device acceptable for prolonged use in conscious patients exists. High Intensity Focused Ultrasound (HIFU) can be used to perform remote pacing using reversibility of electromechanical coupling of cardiomyocytes. Here we described an extracorporeal cardiac stimulation device and study its efficacy and safety. We conducted experiments ex vivo and in vivo in a large animal model (pig) to evaluate clinical potential of such a technique. The stimulation threshold was determined in 10 different ex vivo hearts and different clinically relevant electrical effects such as consecutive stimulations of different heart chambers with a single ultrasonic probe, continuous pacing or the inducibility of ventricular tachycardia were shown. Using ultrasonic contrast agent, consistent cardiac stimulation was achievable in vivo for up to 1?hour sessions in 4 different animals. No damage was observed in inversion-recovery MR sequences performed in vivo in the 4 animals. Histological analysis revealed no differences between stimulated and control regions, for all ex vivo and in vivo cases.
| S-EPMC5101517 | biostudies-literature
Project description:BackgroundThree cases of the application of focused cardiac ultrasound in patients with coronavirus disease 2019 are presented.MethodsCardiac point-of-care ultrasound, limited transthoracic echocardiography, and critical care echocardiography were applied in cases of heart failure, pulmonary embolism, and myocarditis with thrombus respectively.ResultsThe impact on patient management and the global context of each presentation are discussed.ConclusionsFocused cardiac point-of-care ultrasound played an important, front-line role in the bedside management of patients during the COVID-19 pandemic in Wuhan, China.
| S-EPMC7144595 | biostudies-literature
Project description:Background: Focused cardiac ultrasound (FCU) is widely used by healthcare providers to answer specific questions about cardiac structure and function at the bedside. Currently, no widely accepted FCU image acquisition checklist exists to assess learners with varying skill levels from different specialties. Objective: The primary objective of this project was to develop a consensus-based FCU image acquisition checklist using a multispecialty group of point-of-care ultrasound (POCUS) experts. Methods: The essential components of an FCU examination were identified on the basis of published recommendations from echocardiography and international ultrasound societies. A checklist of the essential components of an FCU examination was drafted. A panel of POCUS experts from different medical specialties in the United States and Canada was convened to vote on each checklist item by answering two questions: 1) Is this item important to include in a checklist of essential FCU skills applicable to any medical specialty? and 2) Should the learner be required to successfully complete this item to be considered competent? A modified Delphi approach was used to assess the level of agreement for each checklist item during four rounds of voting. Checklist items that achieved an agreement of 80% or greater were included in the final checklist. Results: Thirty-one POCUS experts from seven different medical specialties voted on sixty-five items to be included in the FCU image acquisition assessment tool. The majority of POCUS experts (61%) completed all four rounds of voting. During the first round of voting, 59 items reached consensus, and after revision and revoting, an additional 3 items achieved 80% or greater consensus. A total of 62 items were included in the final checklist, and 57 items reached consensus as a requirement for demonstration of competency. Conclusion: We have developed a multispecialty, consensus-based FCU image acquisition checklist that may be used to assess the skills of learners from different specialties. Future steps include studies to develop additional validity evidence for the use of the FCU assessment tool and to evaluate its utility for the translation of skills into clinical practice.
| S-EPMC8043312 | biostudies-literature
Project description:Abstract Introduction/Purpose Increasing demand for training in focused cardiac ultrasound (FCU) is constrained by availability of supervisors to supervise training on patients. We designed and tested the feasibility of a cloud‐based (internet) system that enables remote supervision and monitoring of the learning curve of image quality and interpretative accuracy for one novice learner. Methods After initial training in FCU (iHeartScan and FCU TTE Course, University of Melbourne), a novice submitted the images and interpretation of 30 practice FCU examinations on hospitalised patients to a supervisor via a cloud‐based portal. Electronic feedback was provided by the supervisor prior to the novice performing each FCU examination, which included image quality score (for each view) and interpretation errors. The primary outcome of the study was the number of FCU scans required for two consecutive scans to score: (i) above the lower limit of acceptable total image quality score (64%), and (ii) below the upper limit of acceptable interpretive errors (15%). Results The number of FCU practice examinations required to meet adequate image quality and interpretation error standard was 10 and 13, respectively. Improvement in image acquisition continued, remaining within limits of acceptable image quality. Conversely, interpretive in‐accuracy (error > 15%) continued. Conclusion This electronic FCU mentoring system circumvents (but should not replace) the requirement for bed‐side supervision, which may increase the capacity of supervision of physicians learning FCU. The system also allows real‐time tracking of their progress and identifies weaknesses that may assist in guiding further training.
| S-EPMC8411726 | biostudies-literature
Project description:Background and purposeTranscranial MR imaging-guided focused ultrasound is a promising novel technique to treat multiple disorders and diseases. Planning for transcranial MR imaging-guided focused ultrasound requires both a CT scan for skull density estimation and treatment-planning simulation and an MR imaging for target identification. It is desirable to simplify the clinical workflow of transcranial MR imaging-guided focused ultrasound treatment planning. The purpose of this study was to examine the feasibility of deep learning techniques to convert MR imaging ultrashort TE images directly to synthetic CT of the skull images for use in transcranial MR imaging-guided focused ultrasound treatment planning.Materials and methodsThe U-Net neural network was trained and tested on data obtained from 41 subjects (mean age, 66.4 ± 11.0 years; 15 women). The derived neural network model was evaluated using a k-fold cross-validation method. Derived acoustic properties were verified by comparing the whole skull-density ratio from deep learning synthesized CT of the skull with the reference CT of the skull. In addition, acoustic and temperature simulations were performed using the deep learning CT to predict the target temperature rise during transcranial MR imaging-guided focused ultrasound.ResultsThe derived deep learning model generates synthetic CT of the skull images that are highly comparable with the true CT of the skull images. Their intensities in Hounsfield units have a spatial correlation coefficient of 0.80 ± 0.08, a mean absolute error of 104.57 ± 21.33 HU, and a subject-wise correlation coefficient of 0.91. Furthermore, deep learning CT of the skull is reliable in the skull-density ratio estimation (r = 0.96). A simulation study showed that both the peak target temperatures and temperature distribution from deep learning CT are comparable with those of the reference CT.ConclusionsThe deep learning method can be used to simplify workflow associated with transcranial MR imaging-guided focused ultrasound.
| S-EPMC7661089 | biostudies-literature
Project description:IntroductionFocused cardiac ultrasound (FoCUS) is widely used for the point-of-care evaluation of basic cardiac pathology, and there is a need for efficient and consistent training in this modality. We designed a simulator-based FoCUS curriculum that integrates instructional scaffolding and deliberate practice to create a directed, self-regulated learning experience for novices. The goal of this strategy was to guide the novice's learning efforts more efficiently and moderate cognitive load while retaining the benefits of independent learning.MethodsThe complex task of learning cardiac ultrasound is broken into discrete steps, with focused didactic information immediately followed by targeted simulator practice for each module. The practice complexity increases through successive modules, and learners ultimately apply their skills by completing unassisted simulator cases. Immediate visual and quantitative feedback is provided by the simulator whenever an ultrasound image was captured during practice. The entire curriculum is self-guided.ResultsSixteen nurse practitioners and resident physicians completed this FoCUS curriculum. In comparison to a previously validated, lecture-before-practice-style curriculum, the average time to completion decreased from 8.0 ± 2.5 hours to 4.7 ± 1.9 hours (p < .0001). There was no difference in posttraining cognitive or psychomotor outcomes between the curricula as measured by a simulator posttest.DiscussionA curriculum integrating scaffolding and deliberate practice provides a more efficient, but equally effective, means of teaching psychomotor and cognitive skills in FoCUS. These instructional design principles may translate to other operational learning tasks and allow novices to build skills and reach basic competency more rapidly.
| S-EPMC6342425 | biostudies-literature
Project description:AimsTo determine the frequency and pattern of cardiac complications in patients hospitalised with coronavirus disease (COVID-19).Methods and resultsCAPACITY-COVID is an international patient registry established to determine the role of cardiovascular disease in the COVID-19 pandemic. In this registry, data generated during routine clinical practice are collected in a standardised manner for patients with a (highly suspected) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection requiring hospitalisation. For the current analysis, consecutive patients with laboratory confirmed COVID-19 registered between 28 March and 3 July 2020 were included. Patients were followed for the occurrence of cardiac complications and pulmonary embolism from admission to discharge. In total, 3011 patients were included, of which 1890 (62.8%) were men. The median age was 67 years (interquartile range 56-76); 937 (31.0%) patients had a history of cardiac disease, with pre-existent coronary artery disease being most common (n=463, 15.4%). During hospitalisation, 595 (19.8%) patients died, including 16 patients (2.7%) with cardiac causes. Cardiac complications were diagnosed in 349 (11.6%) patients, with atrial fibrillation (n=142, 4.7%) being most common. The incidence of other cardiac complications was 1.8% for heart failure (n=55), 0.5% for acute coronary syndrome (n=15), 0.5% for ventricular arrhythmia (n=14), 0.1% for bacterial endocarditis (n=4) and myocarditis (n=3), respectively, and 0.03% for pericarditis (n=1). Pulmonary embolism was diagnosed in 198 (6.6%) patients.ConclusionThis large study among 3011 hospitalised patients with COVID-19 shows that the incidence of cardiac complications during hospital admission is low, despite a frequent history of cardiovascular disease. Long-term cardiac outcomes and the role of pre-existing cardiovascular disease in COVID-19 outcome warrants further investigation.
| S-EPMC7734244 | biostudies-literature
Project description:SummaryTraitpedia is a collaborative database aimed to collect binary traits in a tabular form for a growing number of species.Availability and implementationTraitpedia can be accessed from http://cbdm-01.zdv.uni-mainz.de/~munoz/traitpedia.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:For more than 70 years, the promise of noninvasive neuromodulation using focused ultrasound has been growing while diagnostic ultrasound established itself as a foundation of clinical imaging. Significant technical challenges have been overcome to allow transcranial focused ultrasound to deliver spatially restricted energy into the nervous system at a wide range of intensities. High-intensity focused ultrasound produces reliable permanent lesions within the brain, and low-intensity focused ultrasound has been reported to both excite and inhibit neural activity reversibly. Despite intense interest in this promising new platform for noninvasive, highly focused neuromodulation, the underlying mechanism remains elusive, though recent studies provide further insight. Despite the barriers, the potential of focused ultrasound to deliver a range of permanent and reversible neuromodulation with seamless translation from bench to the bedside warrants unparalleled attention and scientific investment. Focused ultrasound boasts a number of key features such as multimodal compatibility, submillimeter steerable focusing, multifocal, high temporal resolution, coregistration, and the ability to monitor delivered therapy and temperatures in real time. Despite the technical complexity, the future of noninvasive focused ultrasound for neuromodulation as a neuroscience and clinical platform remains bright.
| S-EPMC6361056 | biostudies-literature