Metastatic Pulmonary Calcification: Single-Center Review of Typical and Atypical Imaging Features.

PURPOSE: The purpose of this study is to bring attention to an atypical form of metastatic pulmonary calcification, which is conventionally described as a metabolic process with upper lobe predominance in patients with a specific clinical history, which has not been reported as a distinct entity. METHODS: Patients with metastatic pulmonary calcification (MPC) were first identified with mPower keyword search, including MPC or metastatic calcifications on computed tomography chest radiological reports. Patients were then filtered on likelihood of MPC based off imaging reports. Images were then reviewed by three senior radiologists for pertinent characteristics such as location of MPC, degree of calcifications and pleural effusions. Based on the predominant location of MPC, cases were labeled as either typical or atypical. Clinical and imaging characteristics relevant to MPC were noted and compared across typical and atypical cases. RESULTS: In our study, we describe 25 patients with MPC, 13 defined as typical MPC and 12 with atypical MPC. Through consensus of senior radiologists, MPC was deemed to be mild (52%), moderate (44%), or severe (4%). Twenty-three patients (92%) had underlying renal disease including 21 requiring dialysis at the time of diagnosis. Outside of age at diagnosis, there was no significant clinical difference between the two groups. Evaluation of imaging characteristics (average HU attenuation, 267; range, 186-295), pattern and distribution of calcification, and clinical history strongly supported a diagnosis of atypical MPC. CONCLUSION: This study presents several cases of lower lobe subpleural MPC associated with pleural effusions, which has not been reported as a distinct entity, despite comprising a significant portion of MPC cases at our institution.

Results From the Big Ten COVID-19 Cardiac Registry: Impact of SARS-COV-2 on Myocardial Involvement.

OBJECTIVE: COVID-19 has been associated with myocardial involvement in collegiate athletes. The first report from the Big Ten COVID-19 Cardiac Registry (Registry) was an ecological study that reported myocarditis in 37 of 1597 athletes (2.3%) based on local clinical diagnosis. Our objective was to assess the relationship between athlete and clinical characteristics and myocardial involvement. DESIGN: Cross-sectional study. SETTING: We analyzed data from 1218 COVID-19 positive Big Ten collegiate athletes who provided informed consent to participate in the Registry. PARTICIPANTS: 1218 athletes with a COVID-19-positive PCR test before June 1, 2021. ASSESSMENT OF INDEPENDENT VARIABLES: Demographic and clinical characteristics of athletes were obtained from the medical record. MAIN OUTCOME MEASURES: Myocardial involvement was diagnosed based on local clinical, cardiac magnetic resonance (CMR), electrocardiography, troponin assay, and echocardiography. We assessed the association of clinical factors with myocardial involvement using logistic regression and estimated the area under the receiver operating characteristic (ROC) curve. RESULTS: 25 of 1218 (2.0%) athletes met criteria for myocardial involvement. The logistic regression model used to predict myocardial involvement contained indicator variables for chest pain, new exercise intolerance, abnormal echocardiogram (echo), and abnormal troponin. The area under the ROC curve for these indicators was 0.714. The presence of any of these 4 factors in a collegiate athlete who tested positive for COVID-19 would capture 55.6% of cases. Among noncases without missing data, 86.9% would not be flagged for possible myocardial involvement. CONCLUSION: Myocardial involvement was infrequent. We predicted case status with good specificity but deficient sensitivity. A diagnostic approach for myocardial involvement based exclusively on symptoms would be less sensitive than one based on symptoms, echo, and troponin level evaluations. Abnormality of any of these evaluations would be an indication for CMR.

Sociodemographic biases in a commercial AI model for intracranial hemorrhage detection.

PURPOSE: To evaluate whether a commercial AI tool for intracranial hemorrhage (ICH) detection on head CT exhibited sociodemographic biases. METHODS: Our retrospective study reviewed 9736 consecutive, adult non-contrast head CT scans performed between November 2021 and February 2022 in a single healthcare system. Each CT scan was evaluated by a commercial ICH AI tool and a board-certified neuroradiologist; ground truth was defined as final radiologist determination of ICH presence/absence. After evaluating the AI tool's aggregate diagnostic performance, sub-analyses based on sociodemographic groups (age, sex, race, ethnicity, insurance status, and Area of Deprivation Index [ADI] scores) assessed for biases. χ2 test or Fisher's exact tests evaluated for statistical significance with p ≤ 0.05. RESULTS: Our patient population was 50% female (mean age 60 ± 19 years). The AI tool had an aggregate accuracy of 93% [9060/9736], sensitivity of 85% [1140/1338], specificity of 94% [7920/ 8398], positive predictive value (PPV) of 71% [1140/1618] and negative predictive value (NPV) of 98% [7920/8118]. Sociodemographic biases were identified, including lower PPV for patients who were females (67.3% [62,441/656] vs. 72.7% [699/962], p = 0.02), Black (66.7% [454/681] vs. 73.2% [686/937], p = 0.005), non-Hispanic/non-Latino (69.7% [1038/1490] vs. 95.4% [417/437]), p = 0.009), and who had Medicaid/Medicare (69.9% [754/1078]) or Private (66.5% [228/343]) primary insurance (p = 0.003). Lower sensitivity was seen for patients in the third quartile of national (78.8% [241/306], p = 0.001) and state ADI scores (79.0% [22/287], p = 0.001). CONCLUSIONS: In our healthcare system, a commercial AI tool had lower performance for ICH detection than previously reported and demonstrated several sociodemographic biases.

Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease Using Transfer Learning of Deep Learning-Based ASL Denoising.

BACKGROUND: Arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) denoising through deep learning (DL) often faces insufficient training data from patients. One solution is to train DL models using healthy subjects' data which are more widely available and transfer them to patients' data. PURPOSE: To evaluate the transferability of a DL-based ASL MRI denoising method (DLASL). STUDY TYPE: Retrospective. SUBJECTS: Four hundred and twenty-eight subjects (189 females) from three cohorts. FIELD STRENGTH/SEQUENCE: 3 T two-dimensional (2D) echo-planar imaging (EPI)-based pseudo-continuous ASL (PCASL) and 2D EPI-based pulsed ASL (PASL) sequences. ASSESSMENT: DLASL was trained using young healthy adults' PCASL data (Dataset 1: 250/30 subjects as training/validation set) and was directly transferred (DTF) to PCASL data from Dataset 2 (45 subjects test set) of normal controls (NC) and Alzheimer's disease (AD) groups. DLASL was fine-tuned (DLASLFT) and tested on PASL data from Dataset 3 (103 subjects test set) of NC and AD. An existing non-DL method (NonDL) was used for comparison. Cerebral blood flow (CBF) images from ASL MRI were compared between NC and AD to assess characteristic hypoperfusion (lower CBF) patterns in AD. CBF image quality and CBF map sensitivity for detecting hypoperfusion using peak t-value and suprathreshold cluster size are outcome measures. STATISTICAL TESTS: Paired t-test, two-sample t-test, one-way analysis of variance, and Tukey honestly significant difference, and linear mixed-effects models were used. P < 0.05 was considered statistically significant. RESULTS: Mean contrast-to-noise ratio (CNR) of Dataset 2 showed that DTF outperformed NonDL (AD: 3.38 vs. 2.64, NC: 3.80 vs. 3.36). On Dataset 3, DLASLFT outperformed NonDL measured by mean CNR (AD: 2.45 vs. 1.87, NC: 2.54 vs. 2.17) and mean radiologic score (2.86 vs. 2.44). Image quality improvement was significant on both test sets. DTF and DLASLFT improved sensitivity for detecting AD-related hypoperfusion patterns compared with NonDL. DATA CONCLUSION: We demonstrated the DLASL's transferability across different ASL sequences and different populations. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Cardiac MRI Findings of Myocarditis After COVID-19 mRNA Vaccination in Adolescents.

BACKGROUND. A possible association has been reported between COVID-19 messenger RNA (mRNA) vaccination and myocarditis. OBJECTIVE. The purpose of our study was to describe cardiac MRI findings in patients with myocarditis after COVID-19 mRNA vaccination. METHODS. This retrospective study included patients without known prior SARS-CoV-2 infection who underwent cardiac MRI between May 14, 2021, and June 14, 2021, for suspected myocarditis within 2 weeks of COVID-19 mRNA vaccination. Information regarding clinical presentation, hospital course, and events after hospital discharge were recorded. A cardiothoracic imaging fellow and cardiothoracic radiologist reviewed cardiac MRI examinations in consensus. Data were summarized descriptively. RESULTS. Of 52 patients without known prior SARS-CoV-2 infection who underwent cardiac MRI during the study period, five underwent MRI for suspected myocarditis after recent COVID-19 mRNA vaccination. All five patients were male patients ranging in age from 16 to 19 years (mean, 17.2 ± 1.0 [SD] years) who presented within 4 days of receiving the second dose of a COVID-19 mRNA vaccine. Troponin levels were elevated in all patients (mean peak troponin I value, 6.82 ± 4.13 ng/mL). Alternate possible causes of myocarditis were deemed clinically unlikely on the basis of medical history, physical examination findings, myocarditis viral panel, and toxicology screening. Cardiac MRI findings were consistent with myocarditis in all five patients on the basis of the Lake Louise criteria, including early gadolinium enhancement and late gadolinium enhancement (LGE) in all patients and corresponding myocardial edema in four patients. All five patients had a favorable hospital course and were discharged from the hospital in stable condition with improved or resolved symptoms after hospitalization (mean length of hospital stay, 4.8 days). Two patients underwent repeat cardiac MRI that showed persistent, although decreased, LGE. Three patients reported mild intermittent self-resolving chest pain after hospital discharge, and two patients had no recurrent symptoms after discharge. CONCLUSION. In this small case series, all patients with myocarditis after COVID-19 vaccination were male adolescents and had a favorable initial clinical course. All patients showed cardiac MRI findings typical of myocarditis from other causes. LGE persisted in two patients who underwent repeat MRI. These observations do not establish causality. CLINICAL IMPACT. Radiologists should be aware of a possible association of COVID-19 mRNA vaccination and myocarditis and recognize the role of cardiac MRI in the assessment of suspected myocarditis after COVID-19 vaccination.

Prone Chest Radiographs: Distinguishing Features and Identification of Support Devices.

PURPOSE: Prone position is known to improve acute lung injury, and chest radiographs are often necessary to monitor disease and confirm support device placement. However, there is a paucity of literature regarding radiographs obtained in this position. We evaluated prone radiographs for distinguishing features and ability to identify support devices. METHODS: Pairs of prone and supine radiographs obtained during the COVID-19 pandemic were assessed retrospectively. IRB approval and waiver of informed consent were obtained. Radiographs were assessed for imaging adequacy, distinguishing features, and support device identification (endotracheal tube, enteric tube, or central line). Radiographs were reviewed by ≥ 2 cardiothoracic radiologists. RESULTS: Radiographs from 81 patients (63yo ± 13, 30% women) were reviewed. Prone and supine radiographs were comparable for imaging the lung bases (81% vs. 90%, p = 0.35) and apices (93% vs. 94%, p = 1); prone radiographs more frequently had significant rotation (36% vs. 19%, p = 0.021). To identify prone technique, scapula tip located beyond the rib border was 89% sensitive (95%CI 80-95%) and 85% specific (76-92%), and a fundal stomach bubble was 44% sensitive (33-56%) and 90% specific (81-96%). For women, displaced breast shadow was 46% sensitive (26-67%) and 92% specific (73-99%). Prone and supine radiographs each identified > 99% of support devices. Prone exams trended toward increased rate of malpositioned device (12% vs. 6%, p = 0.07). CONCLUSION: Scapula position reliably distinguishes prone from supine position; fundal stomach bubble or displaced breast shadow is specific for prone position. Prone radiographs reliably identify line and tube position, which is particularly important as prone patients appear at increased risk for malpositioned devices.

Early pulmonary complications related to cancer treatment in children.

In this review, we summarize early pulmonary complications related to cancer therapy in children and highlight characteristic findings on imaging that should be familiar to a radiologist reviewing imaging from pediatric cancer patients.

A pilot study of deep learning-based CT volumetry for traumatic hemothorax.

PURPOSE: We employ nnU-Net, a state-of-the-art self-configuring deep learning-based semantic segmentation method for quantitative visualization of hemothorax (HTX) in trauma patients, and assess performance using a combination of overlap and volume-based metrics. The accuracy of hemothorax volumes for predicting a composite of hemorrhage-related outcomes - massive transfusion (MT) and in-hospital mortality (IHM) not related to traumatic brain injury - is assessed and compared to subjective expert consensus grading by an experienced chest and emergency radiologist. MATERIALS AND METHODS: The study included manually labeled admission chest CTs from 77 consecutive adult patients with non-negligible (≥ 50 mL) traumatic HTX between 2016 and 2018 from one trauma center. DL results of ensembled nnU-Net were determined from fivefold cross-validation and compared to individual 2D, 3D, and cascaded 3D nnU-Net results using the Dice similarity coefficient (DSC) and volume similarity index. Pearson's r, intraclass correlation coefficient (ICC), and mean bias were also determined for the best performing model. Manual and automated hemothorax volumes and subjective hemothorax volume grades were analyzed as predictors of MT and IHM using AUC comparison. Volume cut-offs yielding sensitivity or specificity ≥ 90% were determined from ROC analysis. RESULTS: Ensembled nnU-Net achieved a mean DSC of 0.75 (SD: ± 0.12), and mean volume similarity of 0.91 (SD: ± 0.10), Pearson r of 0.93, and ICC of 0.92. Mean overmeasurement bias was only 1.7 mL despite a range of manual HTX volumes from 35 to 1503 mL (median: 178 mL). AUC of automated volumes for the composite outcome was 0.74 (95%CI: 0.58-0.91), compared to 0.76 (95%CI: 0.58-0.93) for manual volumes, and 0.76 (95%CI: 0.62-0.90) for consensus expert grading (p = 0.93). Automated volume cut-offs of 77 mL and 334 mL predicted the outcome with 93% sensitivity and 90% specificity respectively. CONCLUSION: Automated HTX volumetry had high method validity, yielded interpretable visual results, and had similar performance for the hemorrhage-related outcomes assessed compared to manual volumes and expert consensus grading. The results suggest promising avenues for automated HTX volumetry in research and clinical care.

Lung-RADS Version 1.0 versus Lung-RADS Version 1.1: Comparison of Categories Using Nodules from the National Lung Screening Trial.

Background The American College of Radiology updated Lung Imaging Reporting and Data System (Lung-RADS) version 1.0 to version 1.1 in May 2019, with the two key changes involving perifissural nodules (PFNs) and ground-glass nodules (GGNs) now designated as a negative screening result. This study examines the effects of these changes using National Lung Screening Trial (NLST) data. Purpose To determine the frequency of PFNs and GGNs reclassified from category 3 or 4A to the more benign category 2 in the updated Lung-RADS version 1.1, as compared with Lung-RADS version 1.0, using CT scans from the NLST. Materials and Methods In this secondary analysis of the NLST, the authors studied all noncalcified nodules (NCNs) found on the incident scan. Nodules were evaluated using criteria from both Lung-RADS version 1.0 and version 1.1, which were compared to determine changes in the number of nodules deemed benign. A McNemar test was used to assess statistical significance. Results A total of 2813 patients (mean age ± standard deviation, 62 years ± 5; 1717 men) with 4408 NCNs were studied. Of the largest 1092 solid NCNs measuring at least 6 mm but less than 10 mm, 216 (19.8%) were deemed PFNs (category 2) using Lung-RADS version 1.1. Eleven of the 1092 solid NCNs (1.0%) were malignant, but none were PFNs. Of 161 GGNs, three (1.9%) were category 3 according to Lung-RADS version 1.0, of which two (66.7%) were down-classified to category 2 with version 1.1. One of the three down-categorized GGNs (version 1.1) proved to be malignant (false-negative finding). Statistically significant improvement for Lung-RADS version 1.1 was found for total nodules (P < .01) and PFNs (P < .01), but not GGNs (P = .48). Conclusion This secondary analysis of National Lung Screening Trial data shows that Lung Imaging Reporting and Data System version 1.1 decreased the number of false-positive results. This was related to the down-classification of perifissural nodules in the range of 6 up to 10 mm. The increase in allowable nodule size for ground-glass nodules in category 2 from 20 mm (version 1.0) to 30 mm (version 1.1) showed no benefit. © RSNA, 2021 See also the editorial by Mayo and Lam in this issue.

Preprocedure CT Findings of Right Heart Failure as a Predictor of Mortality After Transcatheter Aortic Valve Replacement.

OBJECTIVE: The purpose of this study is to determine whether imaging features of right heart failure seen on CT performed before transcatheter aorta valve replacement (TAVR) predict poor outcomes after the procedure. MATERIALS AND METHODS: We retrospectively evaluated findings on CT performed before TAVR for 505 consecutive patients seen from 2014 to 2018. Of these patients, 300 underwent TAVR. Patient demographic characteristics and clinical and procedural data were recorded. Imaging features, including signs of right heart failure, left heart failure, lung disease, coronary artery disease, and concomitant mitral valve and apparatus calcifications were evaluated. The primary outcome was all-cause mortality at 1 year after TAVR. Patients were divided into two groups: those who were alive (group 1) and those who had died (group 2) by 1 year after TAVR. These groups were compared using the Mann-Whitney U test and the Pearson chi-square and Fisher exact tests when applicable. Multivariate logistic regression with a backward stepwise approach was performed. Results were correlated with echo-cardiography findings. RESULTS: A total of 31 patients (10.3%) died within 1 year of TAVR. The presence and size of pericardial effusions were strongly associated with mortality within 1 year after TAVR (p = 0.002). Pericardial effusion was noted in 25 patients in group 1 (9.3%) and eight patients in group 2 (25.8%). Increased size of the main pulmonary artery was associated with death (p = 0.024), with a median main pulmonary artery size of 2.9 cm (interquartile range, 2.6-3.3 cm) in group 1 and 3.2 cm (interquartile range, 2.9-3.5 cm) in group 2. In multivariate analysis, pericardial effusion size and pulmonary artery size, both of which are indicative of right heart failure, were predictors of death, independent of the routinely used clinical Society of Thoracic Surgeons score (AUC, 0.758; 95% CI, 0.671-0.845). Depressed right ventricular ejection fraction, as identified on echocardiography, was associated with mortality within 1 year after TAVR (p = 0.034), further corroborating the CT findings. CONCLUSION: Features related to right heart failure on pre-TAVR CT were associated with increased all-cause mortality within the first year after TAVR, even after adjustment for the Society of Thoracic Surgeons score. Such imaging findings can help in further risk stratification of patients before TAVR.

Utilization of Coronary Artery Disease Reporting and Data System: A Survey of Cardiovascular Imaging Societies.

OBJECTIVE: This survey was performed to determine the extent of utilization of Coronary Artery Disease Reporting and Data System (CAD-RADS) since its introduction in 2016 among members of cardiovascular imaging societies. METHODS: A survey regarding use of CAD-RADS was distributed to members of North American Society for Cardiovascular Imaging and Society for Cardiovascular Computed Tomography. RESULTS: A total of 246 surveys were completed, and results show that, although most respondents are familiar with CAD-RADS (95%), less than half (45%) report using CAD-RADS for all coronary CTA. Rates of CAD-RADS utilization were similar among physicians who work in a variety of settings. Years of clinical experience did not affect the rates of CAD-RADS utilization; however, a higher weekly volume of cardiac computed tomography was associated with higher rates of CAD-RADS utilization. CONCLUSIONS: Four years after the introduction of CAD-RADS, the reporting system is used by less than half of surveyed members of North American Society for Cardiovascular Imaging and Society for Cardiovascular Computed Tomography regardless of practice model and range of practice experience with cardiac computed tomography.

Computed tomography angiography as an adjunct to computational fluid dynamics for prediction of oxygenator thrombus formation.

INTRODUCTION: Extracorporeal membrane oxygenation circuit performance can be compromised by oxygenator thrombosis. Stagnant blood flow in the oxygenator can increase the risk of thrombus formation. To minimize thrombogenic potential, computational fluid dynamics is frequently applied for identification of stagnant flow conditions. We investigate the use of computed tomography angiography to identify flow patterns associated with thrombus formation. METHODS: A computed tomography angiography was performed on a Quadrox D oxygenator, and video densitometric parameters associated with flow stagnation were measured from the acquired videos. Computational fluid dynamics analysis of the same oxygenator was performed to establish computational fluid dynamics-based flow characteristics. Forty-one Quadrox D oxygenators were sectioned following completion of clinical use. Section images were analyzed with software to determine oxygenator clot burden. Linear regression was used to correlate clot burden to computed tomography angiography and computational fluid dynamics-based flow characteristics. RESULTS: Clot burden from the explanted oxygenators demonstrated a well-defined pattern, with the largest clot burden at the corner opposite the blood inlet and outlet. The regression model predicted clot burden by region of interest as a function of time to first opacification on computed tomography angiography (R2 = 0.55). The explanted oxygenator clot burden map agreed well with the computed tomography angiography predicted clot burden map. The computational fluid dynamics parameter of residence time, when summed in the Z-direction, was partially predictive of clot burden (R2 = 0.35). CONCLUSION: In the studied oxygenator, clot burden follows a pattern consistent with clinical observations. Computed tomography angiography-based flow analysis provides a useful adjunct to computational fluid dynamics-based flow analysis in understanding oxygenator thrombus formation.

Chest CT and Coronavirus Disease (COVID-19): A Critical Review of the Literature to Date.

OBJECTIVE. Coronavirus disease (COVID-19) is a global pandemic. Studies in the radiology literature have suggested that CT might be sufficiently sensitive and specific in diagnosing COVID-19 when used in lieu of a reverse transcription-polymerase chain reaction test; however, this suggestion runs counter to current society guidelines. The purpose of this article is to critically review some of the most frequently cited studies on the use of CT for detecting COVID-19. CONCLUSION. To date, the radiology literature on COVID-19 has consisted of limited retrospective studies that do not substantiate the use of CT as a diagnostic test for COVID-19.

Ventricular arrhythmia ablation lesions detectability and temporal changes on cardiac magnetic resonance.

BACKGROUND: Cardiac magnetic resonance (CMR) characteristics of ventricular radiofrequency ablation (RFA) lesions have only been incompletely defined. AIM: To determine the detectability and imaging characteristics of ventricular RFA lesions in an unselected patient cohort undergoing ventricular arrhythmia ablation. METHODS AND RESULTS: A retrospective chart review (n = 249) identified 36 patients with either pre-/postablation CMR (n = 14) or only postablation CMR (n = 22). Ablation lesions could be identified in 50% (n = 18) of patients. Nonvisualized lesions had more preexisting transmural late gadolinium enhancement (LGE) >75% at the ablation sites (21% vs 0.0%, P = .042), more prevalent ICD artifact (50% vs 0%, P = .001), and lower ejection fraction (35.8 ± 14.2% vs 45.3 ± 13.4%, P = .048). Early CMR imaging demonstrated a central "black" signal void (microvascular obstruction [MVO], n = 12, 67%) up to 32 days post-RFA, whereas late imaging showed a homogenously "white" gadolinium enhancement pattern (n = 6, 33%). MVO was only observed in nonfibrotic myocardium without preexisting LGE (n = 12) but was not observed in the scar with preexisting LGE (n = 3, P = .002) suggesting different wash-in/wash-out kinetics in scar/nonscar myocardium. Signal intensity (1909 vs 2534, P = .009) and contrast-to-noise ratio (-7.8 vs 16.3, P = .009) were significantly different between MVO and LGE lesions, respectively. CONCLUSION: Ventricular ablation lesions visualization is negatively affected by preexisting transmural scar, ICD artifact, and low ejection fraction. The transition of "black" MVO appearance to "white" LGE appearance on CMR occurs around 1 month following ablation, suggesting a change in histological characteristics of ablation lesions. This may affect the utility of CMR in the evaluation of the ventricular lesions, when undergoing real-time or repeat VT ablations.

A Pilot Study of Ultrasonography-Naïve Operators' Ability to Use Tele-Ultrasonography to Assess the Heart and Lung.

INTRODUCTION: Remotely tele-mentored ultrasound (RTMUS) involves the real-time guidance of US-naïve providers as they perform point-of-care ultrasound (POCUS) by remotely located, US-proficient providers via telemedicine. The concordance between RTMUS and POCUS in the evaluation of critically ill patients has not been reported. This study sought to evaluate the concordance between RTMUS and POCUS for the cardiopulmonary evaluation of patients in acute respiratory insufficiency and/or shock. METHODS: Ultrasound-naÏve nurses performed RTMUS on critically ill patients. Concordance between RTMUS and POCUS (performed by critical care fellows) in the evaluation of the heart and lungs was reported. The test characteristics of RTMUS were calculated using POCUS as a gold standard. Concordance between RTMUS and available transthoracic echocardiography (TTE) and computed tomography (CT) scans was also reported. RESULTS: Twenty patients were enrolled. Concordance between RTMUS and POCUS was good (90%-100%) for left ventricle function, right ventricle (RV) dilatation/dysfunction, pericardial effusion, lung sliding, pulmonary interstitial syndrome, pleural effusion, and fair (80%) for lung consolidation. Concordance between RTMUS and TTE or CT was similar. RTMUS was highly specific (88%-100%) for all abnormalities evaluated and highly sensitive (89%-100%) for most abnormalities although sensitivity for the detection of RV dilatation/dysfunction (33%) and pulmonary interstitial syndrome (71%) was negatively impacted by false negatives. CONCLUSIONS: RTMUS may be a reasonable substitute for POCUS in the cardiopulmonary evaluation of patients with acute respiratory insufficiency and/or shock. These findings should be validated on a larger scale.

Crowdsourcing pneumothorax annotations using machine learning annotations on the NIH chest X-ray dataset.

Pneumothorax is a potentially life-threatening condition that requires prompt recognition and often urgent intervention. In the ICU setting, large numbers of chest radiographs are performed and must be interpreted on a daily basis which may delay diagnosis of this entity. Development of artificial intelligence (AI) techniques to detect pneumothorax could help expedite detection as well as localize and potentially quantify pneumothorax. Open image analysis competitions are useful in advancing state-of-the art AI algorithms but generally require large expert annotated datasets. We have annotated and adjudicated a large dataset of chest radiographs to be made public with the goal of sparking innovation in this space. Because of the cumbersome and time-consuming nature of image labeling, we explored the value of using AI models to generate annotations for review. Utilization of this machine learning annotation (MLA) technique appeared to expedite our annotation process with relatively high sensitivity at the expense of specificity. Further research is required to confirm and better characterize the value of MLAs. Our adjudicated dataset is now available for public consumption in the form of a challenge.

Use of ChatGPT to Assign BI-RADS Assessment Categories to Breast Imaging Reports.

The large language model GPT-4 showed limited utility in generating BI-RADS assessment categories for factitious breast imaging reports containing findings and impression sections, with frequent incorrect BI-RADS category assignments and poor reproducibility in assigned BI-RADS categories across independent tests for the same report using the same prompt.

Spaced radiology: encouraging durable memory using spaced testing in pediatric radiology.

Applied memory research in the field of cognitive and educational psychology has generated a large body of data to support the use of spacing and testing to promote long-term or durable memory. Despite the consensus of this scientific community, most learners, including radiology residents, do not utilize these tools for learning new information. We present a discussion of these parallel and synergistic learning techniques and their incorporation into a software platform, called Spaced Radiology, which we created for teaching radiology residents. Specifically, this software uses these evidence-based strategies to teach pediatric radiology through a flashcard deck system.

Assessment of Myocarditis: Cardiac MR, PET/CT, or PET/MR?

PURPOSE OF REVIEW: Diagnosis of myocarditis is challenging given its variable clinical manifestations and non-specific laboratory findings. Cardiac magnetic resonance (MR) is currently the preferred imaging modality for the diagnosis of myocarditis. 18F-fluoro-deoxy-glucose (FDG) positron emission tomography/computed tomography (PET/CT), as a functional imaging tool, has a potential role in the assessment of myocarditis by detecting the underlying myocardial inflammatory activity. Data are accumulating that simultaneous cardiac PET/MR may have complementary and incremental values for the evaluation of myocarditis compared to PET/CT or cardiac MR alone. The article aims to summarize the findings in the literature and discuss future directions of cardiac PET/MR for myocarditis. RECENT FINDINGS: The Lake Louis Criteria (CLL) of cardiac MR is widely used for the diagnosis of myocarditis. It has an overall acceptable sensitivity of 67% and specificity of 91% for acute myocarditis but does not have the same accuracy for chronic myocarditis. FDG PET/CT is capable of assessing myocarditis by providing metabolic information of inflammation as increased myocardial FDG uptake. In addition to reduced radiation exposure, FDG PET performed on a hybrid PET/MR may detect more myocarditis than FDG PET/CT, because of the delayed PET acquisition time on PET/MR. Case-based observations and small clinical studies of FDG PET/MR have shown that FDG PET findings as abnormally increased myocardial uptake correlate well with the cardiac MR biomarkers. FDG PET findings may add complementary and incremental values to cardiac MR by improving the sensitivity of cardiac MR for mild or borderline myocarditis, and increasing specificity for chronic myocarditis. Preliminary data from retrospective and case-based observational studies have suggested the complementary and incremental values of simultaneous cardiac FDG PET/MR for evaluation of myocarditis, compared to PET/CT or MR alone. Well-designed studies are needed to confirm the findings and to assess the value of cardiac PET/MR for clinical management and more importantly patient's outcome in both acute and chronic myocarditis.