Project description:Background: Focused cardiac ultrasound (FCU) is a safe and efficient diagnostic intervention for internal medicine physicians. FCU is a highly teachable skill, but is used in routine cardiac assessment in only 20% of surveyed training programs.We developed an FCU curriculum for internal medicine residents and an assessment tool to evaluate the impact of the curriculum on trainee knowledge and confidence. Methods: Internal medicine residents rotating through clinical cardiology services underwent 30 minutes of didactic and 60 minutes of hands-on teaching on acquisition and interpretation of FCU. A 20 item pre and post-curriculum online survey was administered (November 2018-December 2019) to assess confidence and knowledge in FCU. Results: 79 of 116 (68%) residents completed the pre-survey and 50 completed the post-survey, of whom 34 received the curriculum. The mean change in confidence score in those who received versus did not receive the curriculum was 0.99 versus 0.39 (p=0.046) on a 5-point Likert scale. Among 33 residents who had paired pre- and post-surveys the mean change in confidence score was 1.2 versus 0.85 (p<0.001) in those who received versus did not receive the curriculum. The mean increase in knowledge score was 13% versus 7% respectively (p<0.0001). Conclusions: We instituted a novel curriculum for internal medicine residents to gain experience in image acquisition and interpretation. Both confidence and knowledge in FCU improved following the curriculum, indicating that this is a highly teachable skill. Additional analysis of the of the FCU study images will be useful for informing future interventions.
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.
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.
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.
Project description:The amyloid-β (Aβ) hypothesis implicates Aβ protein accumulation in Alzheimer's disease (AD) onset and progression. However, therapies targeting Aβ have proven insufficient in achieving disease reversal, prompting a shift to focus on early intervention and alternative therapeutic targets. Focused ultrasound (FUS) paired with systemically-introduced microbubbles (μB) is a non-invasive technique for targeted and transient blood-brain barrier opening (BBBO), which has demonstrated Aβ and tau reduction, as well as memory improvement in models of late-stage AD. However, similar to drug treatments for AD, this approach is not sufficient for complete reversal of advanced, symptomatic AD. Here we aim to determine whether early intervention with FUS-BBBO in asymptomatic AD could delay disease onset. Thus, the objective of this study is to measure the protective effects of FUS-BBBO on anxiety, memory and AD-associated protein levels in female and male triple transgenic (3xTg) AD mice treated at an early age and disease state. Here we show that early, repeated intervention with FUS-BBBO decreased anxiety-associated behaviors in the open field test by 463.02 and 37.42% in male and female cohorts, respectively. FUS-BBBO preserved female aptitude for learning in the active place avoidance paradigm, reducing the shock quadrant time by 30.03 and 31.01% in the final long-term and reversal learning trials, respectively. Finally, FUS-BBBO reduced hippocampal accumulation of Aβ40, Aβ42, and total tau in females by 12.54, 13.05, and 3.57%, respectively, and reduced total tau in males by 18.98%. This demonstration of both cognitive and pathological protection could offer a solution for carriers of AD-associated mutations as a safe, non-invasive technique to delay the onset of the cognitive and pathological effects of AD.
Project description:Introduction/purposeIncreasing 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.MethodsAfter 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%).ResultsThe 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.ConclusionThis 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.
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.
Project description:BackgroundFocused cardiac ultrasound (FOCUS) is a core competency for pediatric emergency medicine (PEM) fellows. The objectives of this study were (1) to evaluate test characteristics of PEM-fellow-performed FOCUS for pericardial effusion and diminished cardiac function and (2) to assess image interpretation independent of image acquisition.MethodsPEM fellows performed and interpreted FOCUS on patients who also received cardiology service echocardiograms, the reference standard. Subsequently, eight different PEM fellows remotely interpreted a subset of the PEM-acquired and cardiology-acquired echocardiograms.ResultsEight PEM fellows performed 54 FOCUS exams, of which two had pericardial effusion and four had diminished function. PEM fellow FOCUS had a sensitivity of 50.0% (95% CI 9.19-90.8) and specificity of 100.0% (95% CI 91.1-100.0) for detecting diminished function, and sensitivity of 50.0% (95% CI 2.67-97.33) and specificity of 98.1% (95% CI 88.42-99.9) for detecting pericardial effusions. When PEM fellows remotely interpreted 15 echocardiograms, the sensitivity was 81.3% (95% CI 70.7-88.8) and specificity 75% (95% CI 67.0-81.0) for detecting diminished function, and sensitivity of 76.3% (95% CI 65.0-85.0) and specificity 94.4% (95% CI 89.0-97.0) for detecting pericardial effusion. There were no differences in sensitivity and specificity of PEM fellows' interpretation of FOCUS studies compared to their interpretation of cardiology echocardiograms. Interrater reliability for interpretation of remote images (kappa) was 0.66 (95% CI 0.59-0.73) for effusion and 0.31 (95% CI 0.24-0.38) for function among the fellows.ConclusionNovice PEM fellow sonologists (a physician who performs and interprets ultrasound) in the majority of instances were able to acquire and remotely interpret FOCUS images with limited training. However, they made real-time interpretation errors and likely need further training to incorporate real-time image acquisition and interpretation into their practice.
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.