Emergency Radiology最新文献

Purpose: This study aimed to evaluate the clinical outcomes, technical success, and complications associated with the placement of Abre™ venous stents for central venous stenosis/occlusion (CVS/CVO).

Materials and methods: A retrospective review was conducted, identifying 21 patients who underwent Abre™ venous stent placement for SVC syndrome at a single institution. Demographic and clinical data were collected, including stent configurations, procedural details, and follow-up outcomes. Primary stent patency, symptom resolution, and survival rates were analyzed. Survival curves were generated using Kaplan-Meier analysis, and complications were recorded.

Results: Facial and/or upper extremity edema was present in all patients, and malignancy accounted for SVC syndrome in 71.4% of cases, with lung cancer as the predominant etiology (66.6%). The technical success rate was 100%. Clinical symptom resolution was achieved in all patients. The 30-day mortality rate was 23.8%, with all cases involving oncology patients. At six months, cross-sectional imaging showed a primary stent patency rate of 93%, and this remained stable through 12 months. The mean survival time for the cancer subgroup was 337.2 ± 343 days, while the overall cohort mean was 885.8 ± 453.7 days.

Conclusion: The Abre™ venous stent demonstrates potential as an effective stent for SVC syndrome, achieving high symptom relief and patency rates. However, further long-term studies and randomized controlled trials are necessary to validate these findings.

Purpose: To illustrate the imaging findings of orbital compartment syndrome (OCS) in patients with orbital mucormycosis and to identify the red flag signs on imaging for prompt diagnosis and timely intervention.

Methods: We conducted a retrospective analysis of CT and MRI scans from patients diagnosed with sino-nasal mucormycosis within three months of a confirmed COVID-19 infection. Microbiologically proven cases of mucormycosis were included. Images were analysed for: Route of spread; proptosis; tenting of globe, Retro-orbital fat/extraocular muscle (EOM) nonenhancement; Intra-orbital abscess, superior ophthalmic vein (SOV) thrombosis, stretching/thickening/enhancement/diffusion restriction of optic nerve, orbital coat, and EOM. Descriptive statistics were elaborated in the form of mean/standard deviations for continuous variables and frequencies and percentages for categorical variables.

Results: Out of 138 patients with mucormycosis, 49 had orbital involvement, OCS was present in 16 orbits. The mean age was 48.6 years with M: F of 2.75:1. Adjacent sinuses were involved in all patients. Spread along nerves and nasolacrimal duct was seen in 94% patients. Globe tenting was seen in all and thickening/coat enhancement in 53.3%. Optic nerve (ON) was thickened in 87.5%, diffusion restriction of ON and EOM in 78.5% cases. Non enhancement of retro-orbital fat was seen in 50% and intra-orbital abscess in 62.5% cases.

Conclusions: OCS is a vision-threatening orbital emergency, leading to OIS and permanent blindness, if not managed promptly. Imaging features that warrant immediate clinical/ surgical intervention to avoid permanent loss of vision are distorted globe, posterior tenting of the globe, stretching of the optic nerve, non-enhancement of retro-bulbar fat and extra-ocular muscles (EOMs).

Purpose: Vertigo and dizziness are common complaints at emergency departments (ED), often leading to computed tomography (CT) and CT angiography (CTA) studies, which when used non-selectively, have low clinical utility. The study assesses whether two quality improvement interventions (educational rounds and clinical decision making support tool) can better align CTA ordering rates with clinical practice guidelines in the ED workup of vertigo/dizziness at a large community hospital.

Methods: CTA head and neck imaging rates were collected for patients presenting to the hospital's ED with dizziness/vertigo as the chief complaint during 6-month pre- and post-intervention periods and compared rates using the Chi-Square Test. The interventions were joint ED/Diagnostic Imaging/Stroke Neurology rounds discussing CTA head/neck indications and dissemination of a clinical decision making support tool.

Results: The absolute reduction was 5.79% (N = 4,230, p < 0.001) in CTA rates for patients presenting with dizziness/vertigo between the pre- and post-intervention periods. For vertigo, the absolute reduction was 12.27% (N = 402, p < 0.005). For dizziness, the absolute reduction was 5.17% (N = 3828, p < 0.001). Despite the global decrease in CTA studies, there was no statistically significant decrease in CTA rates for the patients who were diagnosed with cerebrovascular accident or transient ischemic attack in the ED, indicating that the interventions were effective in limiting to the targeted CTA studies.

Conclusions: This project was effective in improving patient safety and system efficiency, while providing a framework for low-burden, effective, practice-modifying quality improvement initiatives.

Background: Emergency/trauma radiology artificial intelligence (AI) is maturing along all stages of technology readiness, with research and development (R&D) ranging from data curation and algorithm development to post-market monitoring and retraining.

Purpose: To develop an expert consensus document on best research practices and methodological priorities for emergency/trauma radiology AI.

Methods: A Delphi consensus exercise was conducted by the ASER AI/ML expert panel between 2022-2024. In phase 1, a steering committee (7 panelists) established key themes- curation; validity; human factors; workflow; barriers; future avenues; and ethics- and generated an edited, collated long-list of statements. In phase 2, two Delphi rounds using anonymous RAND/UCLA Likert grading were conducted with web-based data capture (round 1) and a bespoke excel document with literature hyperlinks (round 2). Between rounds, editing and knowledge synthesis helped maximize consensus. Statements reaching ≥80% agreement were included in the final document.

Results: Delphi rounds 1 and 2 consisted of 81 and 78 items, respectively.18/21 expert panelists (86%) responded to round 1, and 15 to round 2 (17% drop-out). Consensus was reached for 65 statements. Observations were summarized and contextualized. Statements with unanimous consensus centered around transparent methodologic reporting; testing for generalizability and robustness with external data; and benchmarking performance with appropriate metrics and baselines. A manuscript draft was circulated to panelists for editing and final approval.

Conclusions: The document is meant as a framework to foster best-practices and further discussion among researchers working on various aspects of emergency and trauma radiology AI.

Purpose: Acute abdominal aortic dissection (AD) is a serious disease. Early detection based on ultrasound (US) can improve the prognosis of AD, especially in emergency settings. We explored the ability of deep learning (DL) to diagnose abdominal AD in US images, which may help the diagnosis of AD by novice radiologists or non-professionals.

Methods: There were 374 US images from patients treated before June 30, 2022. The images were classified as AD-positive and AD-negative images. Among them, 90% of images were used as the training set, and 10% of images were used as the test set. A Densenet-169 model and a VGG-16 model were used in this study and compared with two human readers.

Results: DL models demonstrated high sensitivity and AUC for diagnosing abdominal AD in US images, and DL models showed generally better performance than human readers.

Conclusion: Our findings demonstrated the efficacy of DL-aided diagnosis of abdominal AD in US images, which can be helpful in emergency settings.

Acute appendicitis is a common surgical emergency that can be challenging to diagnose due to its varied clinical presentations. Standard imaging methods include ultrasonography, computed tomography (CT), and Magnetic resonance imaging (MRI), but fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18 F-FDG PET/CT), typically used for oncology, can incidentally detect appendicitis through increased radiotracer uptake associated with inflammation. The paper discusses two cases where acute appendicitis was identified during PET/CT scans conducted for cancer evaluations. In cancer patients, diagnosing appendicitis is difficult due to overlapping symptoms from chemotherapy, metastasis, or radiation effects. Clinicians and radiologists must remain vigilant for incidental appendicitis findings in PET/CT scans, as early diagnosis can prevent complications despite its rarity in oncology imaging.

Purpose: B-lines in lung ultrasound have been a critical clue for detecting pulmonary edema. However, distinguishing B-lines from other artifacts is a challenge, especially for novice point of care ultrasound (POCUS) practitioners. This study aimed to determine the efficacy of automatic detection of B-lines using artificial intelligence (Auto B-lines) for detecting pulmonary edema.

Methods: A retrospective study was conducted on dyspnea patients treated at the emergency department between January 2023 and June 2024. Ultrasound documentation and electronic emergency department medical records were evaluated for sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of auto B-lines in detection of pulmonary edema.

Results: Sixty-six patients with a final diagnosis of pulmonary edema were enrolled, with 54.68% having positive B-lines in lung ultrasound. Auto B-lines had 95.6% sensitivity (95% confidence interval [CI]: 0.92-0.98) and 77.2% specificity (95% CI: 0.74-0.80). Physicians demonstrated 82.7% sensitivity (95% CI: 0.79-0.97) and 63.09% sensitivity (95% CI: 0.58-0.69).

Conclusion: The auto B-lines were highly sensitive in diagnosing pulmonary edema in novice POCUS practitioners. The clinical integration of physicians and artificial intelligence enhances diagnostic capabilities.

Purpose: To evaluate the impact of overnight in-house emergency radiologist coverage on turnaround time (TAT) for emergent imaging of ED and inpatients, during the night and following morning, in a coverage model tailored to preserving resident autonomy.

Methods: Retrospective analysis of TAT for all emergent imaging of ED and inpatients at an academic Level-1 trauma center from September 2015 to August 2019, two years before and after changing coverage model. Median and 90th percentile were assessed for overnight (22:00-07:00 h.) and morning (07:00-10:00 h.) emergent imaging TAT for both the 'First report' and 'Final report'. Statistical significance of TAT changes between study years was assessed with quantile regression. Trainee report volumes and their rotation evaluations were assessed.

Results: 128,433 emergent ED and inpatient imaging studies (82,482 overnight and 45,951 morning) were included; 40,136 CTs, 83,993 X-rays, 2018 US and 2286 MRIs. Imaging volumes increased over time. Except 90th percentile MRI First report TAT, all overnight TAT metrics statistically significantly improved with the new coverage model. For example, ED CT median Final report TAT decreased from 8.45 h to 1.38 h. Morning imaging showed statistically significant reduction for all TATs, except for MRI TATs and 90th percentile US Final report TAT. For example, ED CT median Final report TAT decreased from 1.56 h to 1.19 h. Absolute imaging volume reported by trainees increased by 14% in the 4-year period and weighted average rotation evaluation on a 5-point scale was 3.9 in the post-implementation cohort.

Conclusion: Introduction of a tailored in-house overnight emergency radiologist coverage model can preserve resident autonomy and productivity while achieving statistically significant reduction of emergent imaging report turnaround time for emergent imaging overnight and the following morning. It may help mitigate ED overcrowding while preserving trainee educational experience.

Purpose: The aim of this study was to quantify the proportion of chest x-rays (CXRs) for non-traumatic chest pain (NTCP) in the emergency department (ED) that were abnormal and assess the clinical significance of these abnormalities. We also aimed to explore the variables associated with abnormal and clinically significant abnormal CXRs, to predict a population where CXRs can be safely avoided.

Methods: A single center retrospective cohort study was conducted including all adult patients presenting to a single ED with NTCP between 01 Jan 2022 and 31 Dec 2022. We categorized the CXRs into abnormal, or normal as reported by a radiologist. Abnormalities were categorized to be clinically significant based on potential or actual changes in patient management. The association of patient demographics, presenting vital signs, and clinical characteristics with clinically significant abnormalities were explored using multivariable logistic regression analysis.

Results: There were 3,419 eligible patient encounters included for analysis. Of these, 746 (21.8%; 95%CI: 20.4-23.2%) CXRs had at least one abnormality detected. There were 218 (6.4%; 95%CI: 6.1-7.9%) CXRs deemed to have clinically significant abnormalities. Age categories of 50-64 years (aOR 1.64; 95%CI 1.04-2.60), and age > 64 years (aOR 2.32; 95%CI: 1.51-3.57), history of congestive heart failure (CHF) (aOR 1.86; 95%CI: 1.08-3.21), smoking (aOR 1.27; 95%CI: 1.04-1.57), hemoptysis (aOR 6.69; 95%CI: 1.92-23.33), diminished lung sounds (aOR 4.87; 95%CI:2.95-8.05), rales (aOR 4.49; 95%CI: 2.82-7.15), and abnormal oxygen saturations (aOR 1.98; 95%CI: 1.40-2.79) were associated with clinically significant abnormalities on CXRs. In the absence of these variables, 1.4% (95%CI: 0.6-2.6%) of CXRs were abnormal with clinical significance.

Conclusions: CXRs have a relatively high yield of abnormalities among patients with NTCP. However, some CXRs could be safely avoided in the absence of variables associated with clinically significant abnormalities. Further validation of these clinical characteristics is required before translation to clinical practice.