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Objectives: Lung ultrasound (LUS) holds the promise of an accurate, radiation-free, and affordable diagnostic and monitoring tool in coronavirus disease 2019 (COVID-19) pneumonia. We sought to evaluate the usefulness of LUS in the diagnosis of patients with respiratory distress and suspicion of interstitial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia, in comparison to other imaging modalities., Methods: This was a multicenter, retrospective study. LUS was performed, on Emergency Department (ED) arrival of patients presenting for possible COVID-19 evaluation, by trained emergency physicians, before undergoing conventional radiologic examination or while waiting for the report. Scans were performed using longitudinal transducer orientation of the lung regions. CXR was interpreted by radiologists staffing ED radiology. Subjects were divided into two group based on molecular test results. LUS findings were compared to COVID test results, nonlaboratory data, and other imaging for each patient. Categorical variables were expressed as percentages and continuous variables as median ± standard error., Results: A total of 479 patients were enrolled, 87% diagnosed with SARS-CoV-2 by molecular testing. COVID positive and COVID negative patients differed with respect to sex, presence of fever, and white blood cells count. Most common findings on lung point of care ultrasound (POCUS) for COVID-positive patients were B-lines, irregular pleural lines, and small consolidation. Normal chest X-ray was found in 17.89% of cases., Conclusions: This 479 patient cohort, with COVID-19, found LUS to be noninferior to chest X-ray (CXR) for diagnostic accuracy. In this study, COVID-positive patients are most likely to show B lines and sub-pleural consolidations on LUS examination., (© 2022 American Institute of Ultrasound in Medicine.)

Objectives: A paucity of point-of-care ultrasound (POCUS) databases limits machine learning (ML). Assess feasibility of training ML algorithms to visually estimate left ventricular ejection fraction (EF) from a subxiphoid (SX) window using only apical 4-chamber (A4C) images., Methods: Researchers used a long-short-term-memory algorithm for image analysis. Using the Stanford EchoNet-Dynamic database of 10,036 A4C videos with calculated exact EF, researchers tested 3 ML training permeations. First, training on unaltered Stanford A4C videos, then unaltered and 90° clockwise (CW) rotated videos and finally unaltered, 90° rotated and horizontally flipped videos. As a real-world test, we obtained 615 SX videos from Harbor-UCLA (HUCLA) with EF calculations in 5% ranges. Researchers performed 1000 randomizations of EF point estimation within HUCLA EF ranges to compensate for ML and HUCLA EF mismatch, obtaining a mean value for absolute error (MAE) comparison and performed Bland-Altman analyses., Results: The ML algorithm EF mean MAE was estimated at 23.0, with a range of 22.8-23.3 using unaltered A4C video, mean MAE was 16.7, with a range of 16.5-16.9 using unaltered and 90° CW rotated video, mean MAE was 16.6, with a range of 16.3-16.8 using unaltered, 90° CW rotated and horizontally flipped video training. Bland-Altman showed weakest agreement at 40-45% EF., Conclusions: Researchers successfully adapted unrelated ultrasound window data to train a POCUS ML algorithm with fair MAE using data manipulation to simulate a different ultrasound examination. This may be important for future POCUS algorithm design to help overcome a paucity of POCUS databases., (© 2021 American Institute of Ultrasound in Medicine.)

Objectives: To test deep learning (DL) algorithm performance repercussions by introducing novel ultrasound equipment into a clinical setting., Methods: Researchers introduced prospectively obtained inferior vena cava (IVC) videos from a similar patient population using novel ultrasound equipment to challenge a previously validated DL algorithm (trained on a common point of care ultrasound [POCUS] machine) to assess IVC collapse. Twenty-one new videos were obtained for each novel ultrasound machine. The videos were analyzed for complete collapse by the algorithm and by 2 blinded POCUS experts. Cohen's kappa was calculated for agreement between the 2 POCUS experts and DL algorithm. Previous testing showed substantial agreement between algorithm and experts with Cohen's kappa of 0.78 (95% CI 0.49-1.0) and 0.66 (95% CI 0.31-1.0) on new patient data using, the same ultrasound equipment., Results: Challenged with higher image quality (IQ) POCUS cart ultrasound videos, algorithm performance declined with kappa values of 0.31 (95% CI 0.19-0.81) and 0.39 (95% CI 0.11-0.89), showing fair agreement. Algorithm performance plummeted on a lower IQ, smartphone device with a kappa value of -0.09 (95% CI -0.95 to 0.76) and 0.09 (95% CI -0.65 to 0.82), respectively, showing less agreement than would be expected by chance. Two POCUS experts had near perfect agreement with a kappa value of 0.88 (95% CI 0.64-1.0) regarding IVC collapse., Conclusions: Performance of this previously validated DL algorithm worsened when faced with ultrasound studies from 2 novel ultrasound machines. Performance was much worse on images from a lower IQ hand-held device than from a superior cart-based device., (© 2021 American Institute of Ultrasound in Medicine.)

Optic nerve sheath diameter (ONSD) ultrasound is becoming increasingly more popular for estimating raised intracranial pressure (ICP). We performed a systematic review and analysis of the diagnostic accuracy of ONSD when compared to the standard invasive ICP measurement., Method: We performed a systematic search of PUBMED and EMBASE for studies including adult patients with suspected elevated ICP and comparing sonographic ONSD measurement to a standard invasive method. Quality of studies was assessed using the QUADAS-2 tool by two independent authors. We used a bivariate model of random effects to summarize pooled sensitivity, specificity, and diagnostic odds ratio (DOR). Heterogeneity was investigated by meta-regression and sub-group analyses., Results: We included 18 prospective studies (16 studies including 619 patients for primary outcome). Only one study was of low quality, and there was no apparent publication bias. Pooled sensitivity was 0.9 [95% confidence intervals (CI): 0.85-0.94], specificity was 0.85 (95% CI: 0.8-0.89), and DOR was 46.7 (95% CI: 26.2-83.2) with partial evidence of heterogeneity. The Area-Under-the-Curve of the summary Receiver-Operator-Curve was 0.93 (95% CI: 0.91-0.95, P < .05). No covariates were significant in the meta-regression. Subgroup analysis of severe traumatic brain injury and parenchymal ICP found no heterogeneity. ICP and ONSD had a correlation coefficient of 0.7 (95% CI: 0.63-0.76, P < .05)., Conclusion: ONSD is a useful adjunct in ICP evaluation but is currently not a replacement for invasive methods where they are feasible., (© 2021 American Institute of Ultrasound in Medicine.)

Scarce data exist regarding the natural history of lung lesions detected on ultrasound in those who survive severe COVID-19 pneumonia., Objective: We performed a prospective analysis of point-of-care ultrasound (POCUS) findings in critically ill COVID-19 patients during and after hospitalization., Methods: We enrolled 171 COVID-19 intensive care unit patients. POCUS of the lungs was performed with phased array (2-4 MHz), convex (2-6 MHz) and linear (10-15 MHz) transducers, scanning 12 lung areas. Chest computed tomography angiography was performed to exclude suspected pulmonary embolism. Survivors were clinically and sonographically evaluated during a 4 month period for evidence of residual lung injury. Chest computed tomography angiography and echocardiography were used to exclude pulmonary hypertension (PH) and chest high-resolution-computed-tomography to exclude interstitial lung disease (ILD) in symptomatic survivors., Results: Cox regression analysis showed that lymphocytopenia (hazard ratio [HR]: 0.88, 95% confidence intervals [CI]: 0.68-0.96, p = .048), increased lactate (HR: 1.17, 95% CI: 0.94-1.46, p = 0.049), and D-dimers (HR: 1.21, 95% CI: 1.03-1.44, p = .03) were mortality predictors. Non-survivors had increased incidence of pulmonary abnormalities (B-lines, pleural line irregularities, and consolidations) compared to survivors (p < .05). During follow-up, POCUS with clinical and laboratory parameters integrated in the semi-quantitative Riyadh-Residual-Lung-Injury scale had sensitivity of 0.82 (95% CI: 0.76-0.89) and specificity of 0.91 (95% CI: 0.94-0.95) in predicting ILD. The prevalence of PH and ILD (non-specific-interstitial-pneumonia) was 7% and 11.8%, respectively., Conclusion: POCUS showed ability to monitor the evolution of severe COVID-19 pneumonia after hospital discharge, supporting its integration in clinical predictive models of residual lung injury., (© 2020 American Institute of Ultrasound in Medicine.)

Objectives: To create a deep learning algorithm capable of video classification, using a long short-term memory (LSTM) network, to analyze collapsibility of the inferior vena cava (IVC) to predict fluid responsiveness in critically ill patients., Methods: We used a data set of IVC ultrasound (US) videos to train the LSTM network. The data set was created from IVC US videos of spontaneously breathing critically ill patients undergoing intravenous fluid resuscitation as part of 2 prior prospective studies. We randomly selected 90% of the IVC videos to train the LSTM network and 10% of the videos to test the LSTM network's ability to predict fluid responsiveness. Fluid responsiveness was defined as a greater than 10% increase in the cardiac index after a 500-mL fluid bolus, as measured by bioreactance., Results: We analyzed 211 videos from 175 critically ill patients: 191 to train the LSTM network and 20 to test it. Using standard data augmentation techniques, we increased our sample size from 191 to 3820 videos. Of the 175 patients, 91 (52%) were fluid responders. The LSTM network was able to predict fluid responsiveness moderately well, with an area under the receiver operating characteristic curve of 0.70 (95% confidence interval [CI], 0.43-1.00), a positive likelihood ratio of infinity, and a negative likelihood ratio of 0.3 (95% CI, 0.12-0.77). In comparison, point-of-care US experts using video review offline and manual diameter measurement via software caliper tools achieved an area under the receiver operating characteristic curve of 0.94 (95% CI, 0.83-0.99)., Conclusions: We demonstrated that an LSTM network can be trained by using videos of IVC US to classify IVC collapse to predict fluid responsiveness. Our LSTM network performed moderately well given the small training cohort but worse than point-of-care US experts. Further training and testing of the LSTM network with a larger data sets is warranted., (© 2020 American Institute of Ultrasound in Medicine.)

From its start in China in December 2019, infection by the new SARS-CoV2 spread fast all over the world. It can present as severe respiratory distress in the elderly or a vasculitis in a child, most of whom are typically completely asymptomatic. This makes infection detection based on clinical grounds exceedingly difficult. Lung ultrasound has become an important tool in diagnosis and follow-up of patient with COVID-19 infection.Here we review available, up to date literature on ultrasound use for COVID-19 suspected pediatric patients and contrast it to published findings in adult patients., (© 2020 American Institute of Ultrasound in Medicine.)

Objectives: To perform a prospective longitudinal analysis of lung ultrasound findings in critically ill patients with coronavirus disease 2019 (COVID-19)., Methods: Eighty-nine intensive care unit (ICU) patients with confirmed COVID-19 were prospectively enrolled and tracked. Point-of-care ultrasound (POCUS) examinations were performed with phased array, convex, and linear transducers using portable machines. The thorax was scanned in 12 lung areas: anterior, lateral, and posterior (superior/inferior) bilaterally. Lower limbs were scanned for deep venous thrombosis and chest computed tomographic angiography was performed to exclude suspected pulmonary embolism (PE). Follow-up POCUS was performed weekly and before hospital discharge., Results: Patients were predominantly male (84.2%), with a median age of 43 years. The median duration of mechanical ventilation was 17 (interquartile range, 10-22) days; the ICU length of stay was 22 (interquartile range, 20.2-25.2) days; and the 28-day mortality rate was 28.1%. On ICU admission, POCUS detected bilateral irregular pleural lines (78.6%) with accompanying confluent and separate B-lines (100%), variable consolidations (61.7%), and pleural and cardiac effusions (22.4% and 13.4%, respectively). These findings appeared to signify a late stage of COVID-19 pneumonia. Deep venous thrombosis was identified in 16.8% of patients, whereas chest computed tomographic angiography confirmed PE in 24.7% of patients. Five to six weeks after ICU admission, follow-up POCUS examinations detected significantly lower rates (P < .05) of lung abnormalities in survivors., Conclusions: Point-of-care ultrasound depicted B-lines, pleural line irregularities, and variable consolidations. Lung ultrasound findings were significantly decreased by ICU discharge, suggesting persistent but slow resolution of at least some COVID-19 lung lesions. Although POCUS identified deep venous thrombosis in less than 20% of patients at the bedside, nearly one-fourth of all patients were found to have computed tomography-proven PE., (© 2020 American Institute of Ultrasound in Medicine.)

Objectives: Deep learning for medical imaging analysis uses convolutional neural networks pretrained on ImageNet (Stanford Vision Lab, Stanford, CA). Little is known about how such color- and scene-rich standard training images compare quantitatively to medical images. We sought to quantitatively compare ImageNet images to point-of-care ultrasound (POCUS), computed tomographic (CT), magnetic resonance (MR), and chest x-ray (CXR) images., Methods: Using a quantitative image quality assessment technique (Blind/Referenceless Image Spatial Quality Evaluator), we compared images based on pixel complexity, relationships, variation, and distinguishing features. We compared 5500 ImageNet images to 2700 CXR, 2300 CT, 1800 MR, and 18,000 POCUS images. Image quality results ranged from 0 to 100 (worst). A 1-way analysis of variance was performed, and the standardized mean-difference effect size value (d) was calculated., Results: ImageNet images showed the best image quality rating of 21.7 (95% confidence interval [CI], 0.41) except for CXR at 13.2 (95% CI, 0.28), followed by CT at 35.1 (95% CI, 0.79), MR at 31.6 (95% CI, 0.75), and POCUS at 56.6 (95% CI, 0.21). The differences between ImageNet and all of the medical images were statistically significant (P ≤ .000001). The greatest difference in image quality was between ImageNet and POCUS (d = 2.38)., Conclusions: Point-of-care ultrasound (US) quality is significantly different from that of ImageNet and other medical images. This brings considerable implications for convolutional neural network training with medical images for various applications, which may be even more significant in the case of US images. Ultrasound deep learning developers should consider pretraining networks from scratch on US images, as training techniques used for CT, CXR, and MR images may not apply to US., (© 2020 American Institute of Ultrasound in Medicine.)

Objectives: We sought to create a deep learning (DL) algorithm to identify vessels, bones, nerves, and tendons on transverse upper extremity (UE) ultrasound (US) images to enable providers new to US-guided peripheral vascular access to identify anatomy., Methods: We used publicly available DL architecture (YOLOv3) and deidentified transverse US videos of the UE for algorithm development. Vessels, bones, tendons, and nerves were labeled with bounding boxes. A total of 203,966 images were generated from videos, with corresponding label box coordinates in a YOLOv3 format. Training accuracy, losses, and learning curves were tracked. As a final real-world test, 50 randomly selected images from unrelated UE US videos were used to test the DL algorithm. Four different versions of the YOLOv3 algorithm were tested with varied amounts of training and sensitivity settings. The same 50 images were labeled by 2 blinded point-of-care ultrasound (POCUS) experts. The area under the curve (AUC) was calculated for the DL algorithm and POCUS expert performance., Results: The algorithm outperformed POCUS experts in detection of all structures in the UE, with an AUC of 0.78 versus 0.69 and 0.71, respectively. When considering vessels, only one of the POCUS experts attained an AUC of 0.85, just ahead of the DL algorithm, with an AUC of 0.83., Conclusions: Our DL algorithm proved accurate at identifying 4 common structures on cross-sectional US imaging of the UE, which would allow novice POCUS providers to more confidently and accurately target vessels for cannulation, avoiding other structures. Overall, the algorithm outperformed 2 blinded POCUS experts., (© 2020 by the American Institute of Ultrasound in Medicine.)

Objectives: Little is known about optimal deep learning (DL) approaches for point-of-care ultrasound (POCUS) applications. We compared 6 popular DL architectures for POCUS cardiac image classification to determine whether an optimal DL architecture exists for future DL algorithm development in POCUS., Methods: We trained 6 convolutional neural networks (CNNs) with a range of complexities and ages (AlexNet, VGG-16, VGG-19, ResNet50, DenseNet201, and Inception-v4). Each CNN was trained by using images of 5 typical POCUS cardiac views. Images were extracted from 225 publicly available deidentified POCUS cardiac videos. A total of 750,018 individual images were extracted, with 90% used for model training and 10% for cross-validation. The training time and accuracy achieved were tracked. A real-world test of the algorithms was performed on a set of 125 completely new cardiac images. Descriptive statistics, Pearson R values, and κ values were calculated for each CNN., Results: Accuracy ranged from 96% to 85.6% correct for the 6 CNNs. VGG-16, one of the oldest and simplest CNNs, performed best at 96% correct with 232 minutes to train (R = 0.97; κ = 0.95; P < .00001). The worst-performing CNN was the newer DenseNet201, with 85.6% accuracy and 429 minutes to train (R = 0.92; κ = 0.82; P < .00001)., Conclusions: Six common image classification DL algorithms showed considerable variability in their accuracy and training time when trained and tested on identical data, suggesting that not all will perform optimally for POCUS DL applications. Contrary to well-established accuracies for CNNs, more modern and deeper algorithms yielded poorer results., (© 2019 by the American Institute of Ultrasound in Medicine.)

Recent applications of artificial intelligence (AI) and deep learning (DL) in health care include enhanced diagnostic imaging modalities to support clinical decisions and improve patients' outcomes. Focused on using automated DL-based systems to improve point-of-care ultrasound (POCUS), we look at DL-based automation as a key field in expanding and improving POCUS applications in various clinical settings. A promising additional value would be the ability to automate training model selections for teaching POCUS to medical trainees and novice sonologists. The diversity of POCUS applications and ultrasound equipment, each requiring specialized AI models and domain expertise, limits the use of DL as a generic solution. In this article, we highlight the most advanced potential applications of AI in POCUS tailored to high-yield models in automated image interpretations, with the premise of improving the accuracy and efficacy of POCUS scans., (© 2018 by the American Institute of Ultrasound in Medicine.)

Objectives: Point-of-care ultrasound (US) is an emerging tool used by pediatric emergency physicians in the last decade. Currently in the Middle East, point-of-care US use and education are at an early stage, with no designed curriculum or guidelines for its implementation in pediatric emergency medicine (EM). The objective of this article is to describe the clinical and educational uses of point-of-care US among certified pediatric EM physicians., Methods: A 19-question survey was sent to all certified pediatric emergency physicians and fellows in pediatric emergency fellowships in Saudi Arabia in February 2016. Reminders were sent weekly for 4 weeks., Results: The response rate was 84 of 88 (95%). Fifty-one of 84 (61%) reported using point-of-care US. Focused assessment with sonography for trauma was the most frequent use of point-of-care US (37%), followed by procedures (19%). The most common barrier for not using point-of-care US was limited training (86%). The most preferred tool for point-of-care US teaching was courses by EM physicians. Currently, there is no specific curriculum designed for pediatric EM in the Middle East., Conclusions: Despite the multiple applications of point-of-care US in pediatric EM, its use is still limited. Formal point-of-care US training with bedside sessions and courses was the mort preferred method of education. A designed curriculum needs to be implemented in pediatric emergency fellowships in Saudi Arabia., (© 2017 by the American Institute of Ultrasound in Medicine.)

Transcranial color-coded Doppler sonography is a noninvasive bedside ultrasound application that combines both imaging of parenchymal structures and Doppler assessment of intracranial vessels. It may aid in rapid diagnoses and treatment decision making of patients with intracranial emergencies in point-of-care settings. This pictorial essay illustrates the technical aspects and emergency department applications of transcranial color-coded Doppler sonography, and provides some rationale for implementation of this technique into the emergency department practice., (© 2017 by the American Institute of Ultrasound in Medicine.)

Objectives: Despite the rise of ultrasound in medical education (USMED), multiple barriers impede the implementation of such curricula in medical schools. No studies to date have surveyed individuals who are successfully championing USMED programs. This study aimed to investigate the experiences with ultrasound integration as perceived by active USMED directors across the United States., Methods: In 2014, all allopathic and osteopathic medical schools in the United States were contacted regarding their status with ultrasound education. For schools with required point-of-care ultrasound curricula, we identified the USMED directors in charge of the ultrasound programs and sent them a 27-question survey. The survey included background information about the directors, ultrasound program details, the barriers directors faced toward implementation, and the directors' attitudes toward ultrasound education., Results: One-hundred seventy-three medical schools were contacted, and 48 (27.7%) reported having a formal USMED curriculum. Thirty-six USMED directors responded to the survey. The average number of years of USMED curriculum integration was 2.8 years (SD, 2.9). Mandatory ultrasound curricula had most commonly been implemented into years 1 and 2 of medical school (71.4% and 62.9%, respectively). The most common barriers faced by these directors when implementing their ultrasound programs were the lack of funding for faculty/ equipment (52.9%) and lack of time in current medical curricula (50.0%)., Conclusions: Financial commitments and the full schedules of medical schools are the current prevailing roadblocks to implementation of ultrasound education. Experiences drawn from current USMED directors in this study may be used to help programs starting their own curricula., (© 2016 by the American Institute of Ultrasound in Medicine.)

Objectives: Many medical schools are implementing point-of-care ultrasound in their curricula to help augment teaching of the physical examination, anatomy, and ultimately clinical management. However, point-of-care ultrasound milestones for medical students remain unknown. The purpose of this study was to formulate a consensus on core medical student clinical point-of-care ultrasound milestones across allopathic and osteopathic medical schools in the United States. Directors who are leading the integration of ultrasound in medical education (USMED) at their respective institutions were surveyed., Methods: An initial list of 205 potential clinical ultrasound milestones was developed through a literature review. An expert panel consisting of 34 USMED directors across the United States was used to produce consensus on clinical ultrasound milestones through 2 rounds of a modified Delphi technique, an established anonymous process to obtain consensus through multiple rounds of quantitative questionnaires., Results: There was a 100% response rate from the 34 USMED directors in both rounds 1 and 2 of the modified Delphi protocol. After the first round, 2 milestones were revised to improve clarity, and 9 were added on the basis of comments from the USMED directors, resulting in 214 milestones forwarded to round 2. After the second round, only 90 milestones were found to have a high level of agreement and were included in the final medical student core clinical ultrasound milestones., Conclusions: This study established 90 core clinical milestones that all graduating medical students should obtain before graduation, based on consensus from 34 USMED directors. These core milestones can serve as a guide for curriculum deans who are initiating ultrasound curricula at their institutions. The exact method of implementation and competency assessment needs further investigation., (© 2016 by the American Institute of Ultrasound in Medicine.)

Ultrasound assessment of patients in shock is becoming the standard of care in emergency and critical care settings worldwide. One of the most common protocols used for this assessment is the rapid ultrasound in shock (RUSH) examination. The RUSH protocol is a rapid evaluation of cardiac function, key vascular structures, and likely sources of hypotension. Stroke volume is an established important value to assess in the setting of shock, allowing the provider to predict the patient's response to treatment. However, the calculation of stroke volume or its surrogates is not part of any protocol, including RUSH. We propose the addition of ultrasound calculation of stroke volume or surrogates to the RUSH protocol and provide support for its utility and relative ease of calculation. The resulting product would be the RUSH velocity-time integral protocol., (© 2015 by the American Institute of Ultrasound in Medicine.)

Objectives: The purpose of this study was to compare sonographically guided vascular access using standard and echo-enhanced needles in a variety of tissue-simulating vascular phantoms., Methods: We conducted a prospective single-blinded observational study at an academic medical center. All participants performed real-time sonographically guided vascular access using both a standard 18-gauge needle and an echo-enhanced needle in both in-plane and out-of plane approaches on 3 different vascular access phantoms. The outcome measures included time to dye flash, first-pass success, visibility of the needle tip at the time of puncture, total number of attempts, number of redirections, and incidence of posterior wall penetration., Results: A total of 408 sonographically guided cannulations were performed by 34 participants. The time from needle stick to dye flash, first-pass success, and the total number of attempts were not significantly different between the two needles (P> .05). The tip of the needle was seen at the time of puncture in 79% of attempts with the standard needle (95% confidence interval [CI], 68%-86%) and in 86% of attempts with the echo-enhanced needle (95% CI, 76%-92%), although this difference was not significant (P= .103). The posterior wall was penetrated with the standard needle in 14% of attempts (95% CI, 9.6%-20%) and in 6% of attempts with the echo-enhanced needle (95% CI, 3.5%-11%), and the difference was significant (P < .02)., Conclusions: Echo-enhanced needles decreased the incidence of posterior wall punctures when compared to standard needles during sonographically guided vascular access. However, there were no significant differences in other sonographically guided vascular access metrics.

Cutaneous abscesses are typically incised and drained on the basis of clinical assessment. In most cases this procedure is a safe practice. We report 6 cases in which point-of-care ultrasound interrogation of obvious abscesses revealed potential serious complications with planned incision and drainage. Management was altered in 5 of 6 cases, and potential vascular disasters were avoided. In 1 case, the ultrasound results were ignored, and incision and drainage was completed, confirming the suspected abscess was indeed a solid mass later diagnosed as a carcinoma. In this case series, point-of-care ultrasound interrogation provided rapid assessment and discovery of potentially catastrophic anatomic relationships, avoiding serious complications.

Objectives: Very little is known about publication rates of emergency ultrasound abstracts as peer-reviewed manuscripts in the years after their presentation at national meetings. The objectives of this study were to determine trends in publication patterns of emergency ultrasound abstracts presented at Society for Academic Emergency Medicine and American College of Emergency Physicians annual national meetings as full indexed articles in peer-reviewed journals and compare emergency ultrasound with emergency medical services (EMS) and toxicology subspecialties., Methods: A cross-sectional study was conducted at an academic medical center. All emergency ultrasound, EMS, and toxicology abstracts presented at both national meetings from 1999 to 2008 were entered into a database. An online PubMed/MEDLINE search was performed for full-length peer-reviewed manuscript publications corresponding to these abstracts. The proportion of abstracts presented, manuscript publication rate, time to publication, type of journal (emergency medicine versus non-emergency medicine), and journal impact factor were compared across the 3 subspecialties., Results: Over the 10-year period, 452 emergency ultrasound, 651 EMS, and 376 toxicology abstracts were presented at both meetings. The proportion of abstracts presented from 1999 to 2008 increased significantly for emergency ultrasound (1.7% versus 6.5%) compared with toxicology (3.5% versus 4.9%) and EMS (8.1% versus 5.8%; P < .01). There were no significant differences in manuscript publication rates between emergency ultrasound (22.8%), EMS (23.4%), and toxicology (20.7%). No significant differences were found in the time to publication (P = .53) and journal type (P = .2) between the 3 subspecialties., Conclusions: The emergency ultrasound manuscript publication rate and mean time to publication compare favorably with EMS and toxicology subspecialties.

Objective: The purpose of this study was to evaluate the frequency of inadequate needle chest thoracostomy in the prehospital setting in trauma patients suspected of having a pneumothorax (PTX) on the basis of physical examination., Methods: This study took place at a level I trauma center. All trauma patients arriving via emergency medical services with a suspected PTX and a needle thoracostomy were evaluated for a PTX with bedside ultrasound. Patients too unstable for ultrasound evaluation before tube thoracostomy were excluded, and convenience sampling was used. All patients were scanned while supine. Examinations began at the midclavicular line and included the second through fifth ribs. If no sliding lung sign (SLS) was noted, a PTX was suspected, and the lung point was sought for definitive confirmation. When an SLS was noted throughout and a PTX was ruled out on ultrasound imaging, the thoracostomy catheter was removed. Descriptive statistics were calculated., Results: A total of 57 patients were evaluated over a 3-year period. All had at least 1 needle thoracostomy attempted; 1 patient underwent 3 attempts. Fifteen patients (26%) had a normal SLS on ultrasound examination and no PTX after the thoracostomy catheter was removed. None of the 15 patients were later discovered to have a PTX on subsequent computed tomography., Conclusions: In this study, 26% of patients who received needle thoracostomy in the prehospital setting for a suspected PTX appeared not to have had a PTX originally, nor had 1 induced by the needle thoracostomy. It may be prudent to evaluate such patients with bedside ultrasound instead of automatically converting all needle thoracostomies to tube thoracostomies.

Objective: The purpose of this study was to compare infection rates of peripheral intravenous (IV) lines placed under ultrasound guidance with traditionally placed IV lines., Methods: We conducted a retrospective review of emergency department (ED) and hospital records of adult patients who had a peripheral IV line placed in the ED and were admitted to the hospital over a 1-year period. This study took place at a level I academic urban ED with an annual census of 75,000. All admitted patients with a peripheral IV placed under ultrasound guidance in the ED were identified. Control patients had a traditional landmark approach. Emergency department nurses followed standard aseptic precautions when inserting both ultrasound-guided as well as traditionally placed IV lines. Researchers reviewed all parts of the medical record, including ED and inpatient notes. Descriptive statistics and chi(2) and Fisher exact tests were used in data evaluation., Results: A total of 402 patients who had peripheral IV lines placed under ultrasound guidance were compared with 402 matched control patients. In the ultrasound-guided IV group, the mean time between insertion to catheter removal was 2.6 days compared with 2.4 days in the traditional group (P = .03). There were 2 documented infections in the ultrasound group and 3 in the traditional group, yielding infection rates of 5.2 per 1000 in the ultrasound-guided IV group and 7.8 per 1000 in the traditional approach group. There was no statistically significant difference between infection rates in the two groups (P = .68)., Conclusions: Both traditional and ultrasound-guided approaches had low infection rates, suggesting that there is no increased risk of infection with ultrasound guidance for peripheral IV lines.

Objective: The purpose of this study was to determine the utility of bedside sonography to differentiate soft tissue abnormalities from joint effusions., Methods: We conducted a retrospective review of emergency department (ED) patients presenting with joint pain, erythema, and swelling who received bedside sonography. The ED sonographic examinations were performed by emergency physician sonologists who were not involved in clinical assessment and management of these patients. The treating physician's opinions regarding the probability of joint effusion and need for aspiration were documented in the sonography log before the sonographic examination was performed. The bedside sonograms of all patients included in this study were also reviewed for accuracy. Descriptive statistics were used to summarize the data., Results: A total of 54 patients (mean age +/- SD, 41 +/- 18.9 years) were identified over a 1-year period. The symptomatic joints in our study subjects were as follows: knee, 24 of 54 (44%); elbow, 21 of 54 (38%); ankle, 8 of 54 (15%); and metatarsophalangeal joint, 1 of 54 (2%). Twenty-two of 54 patients (40.7%; 95% confidence interval [CI], 27.6%-53.8%) were found to have joint effusions on sonography. Sonography altered management in 35 of 54 patients (65%; 95% CI, 52%-77.5%). Joint aspiration was planned in 39 of 54 cases (72.2%; 95% CI, 60.2%-84.1%) before sonography. After sonography, only 20 of these patients (37%; 95% CI, 24.1%-49.9%) underwent joint aspiration. There was a statistically significant difference in treatment plans after the addition of bedside sonographic results (P < .01)., Conclusions: Our study suggests that bedside sonography is useful in differentiating joint effusions from soft tissue abnormalities and directing appropriate therapy.

Objective: Accidental arterial cannulation during ultrasound-guided central venous cannulation is rarely reported and should be much less likely with dynamic guidance. Although accidental arterial penetration with the needle may occur periodically without notice and with little harm, actual arterial dilation and line placement may result in serious complications., Methods: This series reports 6 such cases of accidental arterial cannulation and central line insertion under dynamic ultrasound guidance., Results: Two of the arterial cannulations resulted in airway loss, with 1 of these ending in death. The remaining 4 arterial lines led to serious local complications. Ultrasound video analysis of each line placement or postplacement analysis was reviewed, and common pitfalls were extracted. In 3 cases, a central line went directly through the internal jugular vein (IJ) and into the carotid artery. In 1 case, a cordis introducer sheath traveled through the posterior wall of the common femoral vein and into the deep femoral artery branch below. Each patient was hypotensive and hypoxic, making traditional safety checkpoints such as aspiration of bright red blood and pulsatile flow from the syringe hub less reliable in identifying accidental arterial cannulation. All ultrasound-guided cannulations were performed by a standard short-axis approach with high-resolution linear array ultrasound transducers on modern equipment., Conclusions: The short-axis approach, as seen in this series, can provide a false sense of security to the practitioner and allows for potentially dangerous accidental arterial cannulation. In the setting of critically ill patients, it may be prudent to not only visualize the entire path of the needle with the long-axis approach but also confirm correct cannulation by tracing the guide wire in the long axis before line placement.

Objective: Determining the correct position of endotracheal tubes in critically ill patients may be complicated by external factors such as noise, body habitus, and the need for ongoing resuscitation. Multiple detection techniques have been developed to determine the correct endotracheal tube position, recently including the use of sonography to evaluate lung expansion and diaphragmatic excursion. These techniques have also been applied to diagnosis of right endobronchial main stem intubation, which may be confused with a unilateral pneumothorax in some cases., Methods: We describe the sonographic findings in a case series of endobronchial main stem intubations and obstruction, highlighting the utility of this sonographic application. Previous literature and future applications are discussed., Results: Sonographic detection of the sliding lung sign, the lung pulse, and diaphragmatic excursion can accurately detect main stem bronchial intubation as well as bronchial obstruction., Conclusions: Clinical use of lung sonography may decrease the need for chest radiography and may allow more rapid diagnosis of main stem intubation and bronchial obstruction.

Objective: Eye conditions are common in emergency departments. Intraocular foreign bodies (IOFBs) are a frequent concern. Orbital computed tomography (CT) is traditionally used for evaluation. We sought to evaluate bedside ocular sonography for detecting metallic IOFBs., Methods: A pig model was chosen. A micrometer was used to create 3 precise metallic fragments: 0.012 x 0.012 x 0.012, 0.025 x 0.025 x 0.012, and 0.05 x 0.05 x 0.012 in. Individual eyes were randomized to the presence or absence of a foreign body. Randomization was also used to determine the specific size of any given IOFB. A standard 18-gauge spinal needle was used to puncture the sclera and introduce the IOFB into the vitreous. Each eye was then evaluated by 2 sonologists for the presence or absence of an IOFB., Results: A total of 28 eyes were used; 12 (43%) were randomized to no IOFB and 16 (57%) to the presence of an IOFB. Of the 16 eyes that received IOFBs, 8 (50%) were 0.012 x 0.012 x 0.012 in; 5 (31%) were 0.025 x 0.025 x 0.012 in; and 3 (19%) were 0.05 x 0.05 x 0.012 in. Sensitivity was 87.5% and specificity 95.8%. Positive predictive value (PPV) and negative predictive value (NPV) were 96.5% and 85.2%, respectively., Conclusions: Bedside sonography may identify the presence of metallic IOFBs. The PPV allows a high degree of certainty that an IOFB is actually present if seen and may negate the need for uninfused orbital CT. The NPV was 85.2%. Given the potential grave consequences of a missed IOFB, sonography cannot be used as the definitive test to rule out the presence of a metallic IOFB. In the presence of negative findings, further imaging is warranted.

Objective: The purpose of this study was to evaluate the utility of paraovarian pelvic mass mobility as an indicator of mass identity, corpus luteum versus other, in ruling out ectopic pregnancy., Methods: This was a retrospective study of all pelvic sonographic examinations on patients with first-trimester complications seen over an 18-month period at a large urban emergency department. All pregnant patients with signs or symptoms of concern for ectopic pregnancy were scanned to evaluate for intrauterine pregnancy. Masses suggestive of either a corpus luteum or an ectopic pregnancy were separated from the ovary with abdominal palpation and endovaginal transducer movement. The ultrasound director and assistant director reviewed videos of all scans. Results of mass separation and outcome were recorded. Independent movement of a mass and ovary was defined as movement of the mass away from the ovary, sliding past the ovary or rotation past the ovary. Statistical analysis included descriptive statistics, inter-rater reliability, the Fisher exact test, and sensitivity, specificity, and negative and positive predictive values., Results: A total of 78 patient scans fit the criteria, and in 27 of them, the mass separated from the ovary. Twenty-three patients had ectopic pregnancy as the final diagnosis, and in 2 of these, no independent mass movement occurred. Lack of independent movement of the mass and ovary was significantly more common in patients without a final diagnosis of ectopic pregnancy (P < .0001). The negative predictive value was 96.1%., Conclusions: Lack of independent movement of an adjacent mass and ovary was strongly associated with absence of ectopic pregnancy.

Objective: To determine the effect of soft tissue gas on the accuracy of foreign body detection by realtime sonography., Methods: This was a prospective randomized study using glass, metal, and bone inserted into turkey breasts to simulate human soft tissue foreign bodies. Air was subsequently injected around a random selection of the foreign bodies to simulate soft tissue gas that can accompany a blast or high-force injury. Using a linear transducer, physicians credentialed in the use of sonography were each asked to scan the breasts, identify the location of any foreign body, and describe whether the object located was bone, metal, or glass. They were also asked to describe the characteristics of the foreign body, including surface echogenicity, visibility, and artifacts, if any., Results: The sensitivity for localization of each foreign body by each sonographer was 100% (48 of 48) and was unaffected by the presence of soft tissue gas. The accuracy of classifying the foreign body was poor except with bone. Glass and metal were often confused with each other. With the addition of soft tissue gas over the foreign bodies, the sensitivity of classifying the foreign body was decreased further from a combined 58% to 28%. The presence of soft tissue gas decreased the amount of reflection of the foreign body and obscured the subtle differences in the brightness of each foreign body, leading to a decrease in the accuracy of identification but not localization of the foreign body., Conclusions: In an experimental model, soft tissue gas does not affect the localization of soft tissue foreign bodies. However, correct identification of the type of foreign body is limited by soft tissue gas because of loss of the typical sonographic characteristics.

Objective: To report on the use of bedside sonography in the diagnosis and treatment of penetrating extremity trauma., Methods: Sonography was performed in the emergency department of a level 1 trauma center with both curved and linear array transducers., Results: In both cases, foreign bodies and fractures resulting from gunshot wounds to the extremities were found. In addition, intra-abdominal and thoracic injuries were evaluated for using sonography., Conclusions: The increasing mobility and portability of sonography has led to its increasing use at the patient' bedside to diagnose a variety of conditions. It provides potential immediate diagnosis and has the flexibility for evaluating a multitude of injuries normally requiring several different imaging technologies. In circumstances in which conventional radiography is unavailable, such as at trauma scenes, mass casualty situations, or at the bedside with unstable patients, sonography can provide unique and essential information about these patients.