• Korean Journal of Radiology
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• v.23 no.9
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• pp.878-888
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• 2022

Objective: To investigate the clinical impact of a quality improvement program including dedicated emergency radiology personnel (QIP-DERP) on the management of emergency surgical patients in the emergency department (ED). Materials and Methods: This retrospective study identified all adult patients (n = 3667) who underwent preoperative body CT, for which written radiology reports were generated, and who subsequently underwent non-elective surgery between 2007 and 2018 in the ED of a single urban academic tertiary medical institution. The study cohort was divided into periods before and after the initiation of QIP-DERP. We matched the control group patients (i.e., before QIP-DERP) to the QIP-DERP group patients using propensity score (PS), with a 1:2 matching ratio for the main analysis and a 1:1 ratio for sub-analyses separately for daytime (8:00 AM to 5:00 PM on weekdays) and after-hours. The primary outcome was timing of emergency surgery (TES), which was defined as the time from ED arrival to surgical intervention. The secondary outcomes included ED length of stay (LOS) and intensive care unit (ICU) admission rate. Results: According to the PS-matched analysis, compared with the control group, QIP-DERP significantly decreased the median TES from 16.7 hours (interquartile range, 9.4-27.5 hours) to 11.6 hours (6.6-21.9 hours) (p < 0.001) and the ICU admission rate from 33.3% (205/616) to 23.9% (295/1232) (p < 0.001). During after-hours, the QIP-DERP significantly reduced median TES from 19.9 hours (12.5-30.1 hours) to 9.6 hours (5.7-19.1 hours) (p < 0.001), median ED LOS from 9.1 hours (5.6-16.5 hours) to 6.7 hours (4.9-11.3 hours) (p < 0.001), and ICU admission rate from 35.5% (108/304) to 22.0% (67/304) (p < 0.001). Conclusion: QIP-DERP implementation improved the quality of emergency surgical management in the ED by reducing TES, ED LOS, and ICU admission rate, particularly during after-hours.

• Korean Journal of Radiology
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• v.21 no.8
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• pp.955-966
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• 2020

Ultrasound (US) is an attractive diagnostic approach to identify both common and uncommon nipple pathologies, such as duct ectasia, nipple abscess, nipple leiomyoma, nipple adenoma, fibroepithelial polyp, ductal carcinoma in situ (restricted to nipple), invasive carcinoma, and Paget's disease. US is the reliable first-line imaging technique to assess nipple pathologies. It is useful to identify and characterize nipple lesions. Additionally, we have presented the mammography and MRI outcomes correlated with histopathologic features for the relevant cases.

• Journal of the Korean Society of Radiology
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• v.81 no.4
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• pp.852-862
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• 2020

Interventional radiology (IR) embolization requires image guidance to steer catheters to the site of bleeding, where embolic agents such as Gelfoam or coils are administered to stem blood flow. In addition to treating iatrogenic trauma, embolization is suitable for injuries precluding surgery such as blush-bleeding of the liver or kidney and for locating and treating intimal blood vessel tears. However, during hospital off-hours (such as nights and holidays), experienced IR personnel are not always available. In such situations, there is a dire need to build a coordinated IR team to treat seriously injured patients rapidly and reliably. This article reviews the current principles and techniques used in IR such as virtual fluoroscopy and their usefulness, and makes a convincing case for emergency IR.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.752-760
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• 2023

Radiologists and trauma surgeons should monitor for early killers among patients with thoracic trauma, such as tension pneumothorax, tracheobronchial injuries, flail chest, aortic injury, mediastinal hematomas, and severe pulmonary parenchymal injury. With the advent of cutting-edge technology, rapid volumetric computed tomography of the chest has become the most definitive diagnostic tool for establishing or excluding thoracic trauma. With the notion of "time is life" at emergency settings, radiologists must find ways to shorten the turnaround time of reports. One way to interpret chest findings is to use a systemic approach, as advocated in this study. Our interpretation of chest findings for thoracic trauma follows the acronym "ABC-Please" in which "A" stands for abnormal air, "B" stands for abnormal bones, "C" stands for abnormal cardiovascular system, and "P" in "Please" stands for abnormal pulmonary parenchyma and vessels. In the future, utilizing an artificial intelligence software can be an alternative, which can highlight significant findings as "warm zones" on the heatmap and can re-prioritize important examinations at the top of the reading list for radiologists to expedite the final reports.

• Investigative Magnetic Resonance Imaging
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• v.22 no.1
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• pp.10-17
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• 2018

Purpose: To evaluate interpretation errors involving spine MRIs by residents in their second to fourth year of training, classified as minor, intermediate and major discrepancies, as well as the types of commonly discordant lesions with or without clinical significance. Materials and Methods: A staff radiologist evaluated both preliminary and final reports of 582 spine MRIs performed in the emergency room from March 2011 to February 2013, involving (1) the incidence of report discrepancy, classified as minor if there was sufficient description of the main MR findings without ancillary or incidental lesions not influencing the main diagnosis, treatment, or patients' clinical course; intermediate if the correct diagnosis was made with insufficient or inadequate explanation, potentially influencing treatment or clinical course; and major if the discrepancy affected the main diagnosis; and (2) the common causes of discrepancy. We analyzed the differences in the incidence of discrepancy with respect to the training years of residents, age and sex of patients. Results: Interpretation discrepancy occurred in 229 of the 582 cases (229/582, 39.3%), including 146 minor (146/582, 25.1%), 40 intermediate (40/582, 6.9%), and 43 major cases (43/582, 7.4%). The common causes of major discrepancy were: over-diagnosis of fracture (n = 10), missed cord lesion (n = 9), missed signal abnormalities associated with diffuse marrow (n = 5), and failure to provide differential diagnosis of focal abnormal marrow signal intensity (n = 5). No significant difference was found in the incidence of minor, intermediate, and major discrepancies according to the levels of residency, patients' age or sex. Conclusion: A 7.4% rate of major discrepancies was found in preliminary reporting of emergency MRIs of spine interpreted by radiology residents, probably related to a relative lack of clinical experience, indicating the need for additional training, especially involving spine trauma, spinal cord and bone marrow lesions.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.343-354
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• 2022

Objective: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children. Materials and Methods: This retrospective multi-center study consisted of a development dataset acquired from two hospitals (n = 149 and 264) and an external test set (n = 95) from a third hospital. Datasets included children with head trauma who underwent both skull radiography and cranial computed tomography (CT). The development dataset was split into training, tuning, and internal test sets in a ratio of 7:1:2. The reference standard for skull fracture was cranial CT. Two radiology residents, a pediatric radiologist, and two emergency physicians participated in a two-session observer study on an external test set with and without AI assistance. We obtained the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity along with their 95% confidence intervals (CIs). Results: The AI model showed an AUROC of 0.922 (95% CI, 0.842-0.969) in the internal test set and 0.870 (95% CI, 0.785-0.930) in the external test set. The model had a sensitivity of 81.1% (95% CI, 64.8%-92.0%) and specificity of 91.3% (95% CI, 79.2%-97.6%) for the internal test set and 78.9% (95% CI, 54.4%-93.9%) and 88.2% (95% CI, 78.7%-94.4%), respectively, for the external test set. With the model's assistance, significant AUROC improvement was observed in radiology residents (pooled results) and emergency physicians (pooled results) with the difference from reading without AI assistance of 0.094 (95% CI, 0.020-0.168; p = 0.012) and 0.069 (95% CI, 0.002-0.136; p = 0.043), respectively, but not in the pediatric radiologist with the difference of 0.008 (95% CI, -0.074-0.090; p = 0.850). Conclusion: A deep learning-based AI model improved the performance of inexperienced radiologists and emergency physicians in diagnosing pediatric skull fractures on plain radiographs.

• Korean Journal of Radiology
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• v.23 no.1
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• pp.124-138
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• 2022

Gastrointestinal (GI) emergencies in neonates and infants encompass from the beginning to the end of the GI tract. Both congenital and acquired conditions can cause various GI emergencies in neonates and infants. Given the overlapping or nonspecific clinical findings of many different neonatal and infantile GI emergencies and the unique characteristics of this age group, appropriate imaging is key to accurate and timely diagnosis while avoiding unnecessary radiation hazard and medical costs. In this paper, we discuss the radiological findings of essential neonatal and infantile GI emergencies, including esophageal atresia and tracheoesophageal fistula, hypertrophic pyloric stenosis, duodenal atresia, malrotation, midgut volvulus for upper GI emergencies, and jejunoileal atresia, meconium ileus, meconium plug syndrome, meconium peritonitis, Hirschsprung disease, anorectal malformation, necrotizing enterocolitis, and intussusception for lower GI emergencies.

• Journal of the Korean Society of Radiology
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• v.84 no.4
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• pp.824-834
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• 2023

Interventional management is commonly used for traumatic injuries to the abdominal solid organs. The American Association for the Surgery of Trauma (AAST) and the World Society of Emergency Surgery (WSES) recently published guidelines for the management and treatment of liver, spleen, and kidney injuries, emphasizing the importance of interventions. Here, we discuss the characteristics of each organ and the procedure method for each organ that interventional radiologists need to know when treating trauma patients.

• Korean Journal of Radiology
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• v.24 no.3
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• pp.259-270
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• 2023

Objective: It is unknown whether artificial intelligence-based computer-aided detection (AI-CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical practice. We aimed to compare the accuracy of CR interpretation assisted by AI-CAD to that of conventional interpretation in patients who presented to the emergency department (ED) with acute respiratory symptoms using a pragmatic randomized controlled trial. Materials and Methods: Patients who underwent CRs for acute respiratory symptoms at the ED of a tertiary referral institution were randomly assigned to intervention group (with assistance from an AI-CAD for CR interpretation) or control group (without AI assistance). Using a commercial AI-CAD system (Lunit INSIGHT CXR, version 2.0.2.0; Lunit Inc.). Other clinical practices were consistent with standard procedures. Sensitivity and false-positive rates of CR interpretation by duty trainee radiologists for identifying acute thoracic diseases were the primary and secondary outcomes, respectively. The reference standards for acute thoracic disease were established based on a review of the patient's medical record at least 30 days after the ED visit. Results: We randomly assigned 3576 participants to either the intervention group (1761 participants; mean age ± standard deviation, 65 ± 17 years; 978 males; acute thoracic disease in 472 participants) or the control group (1815 participants; 64 ± 17 years; 988 males; acute thoracic disease in 491 participants). The sensitivity (67.2% [317/472] in the intervention group vs. 66.0% [324/491] in the control group; odds ratio, 1.02 [95% confidence interval, 0.70-1.49]; P = 0.917) and false-positive rate (19.3% [249/1289] vs. 18.5% [245/1324]; odds ratio, 1.00 [95% confidence interval, 0.79-1.26]; P = 0.985) of CR interpretation by duty radiologists were not associated with the use of AI-CAD. Conclusion: AI-CAD did not improve the sensitivity and false-positive rate of CR interpretation for diagnosing acute thoracic disease in patients with acute respiratory symptoms who presented to the ED.

• Journal of Yeungnam Medical Science
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• v.39 no.1
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• pp.77-80
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• 2022

Fistulas between the arteries and the gastrointestinal tract are rare but can be fatal. We present a case of an ilioenteric fistula between the left external iliac artery and sigmoid colon caused by radiotherapy for cervical cancer, which was treated with endovascular management using a stent graft. A 38-year-old woman underwent concurrent chemoradiotherapy for cervical cancer recurrence. Approximately 9 months later, the patient suddenly developed hematochezia. On her first visit to the emergency room of our hospital, computed tomography (CT) images did not reveal extravasation of contrast media. However, 8 hours later, she revisited the emergency room because of massive hematochezia with a blood pressure of 40/20 mmHg and a heart rate of 150 beats per minute. At that time, CT images showed the presence of contrast media in almost the entire colon. The patient was referred to the angiography room at our hospital for emergency angiography. Inferior mesenteric arteriography did not reveal any source of bleeding. Pelvic arteriography showed contrast media extravasation from the left external iliac artery to the sigmoid colon; this was diagnosed as an ilioenteric fistula and treated with a stent graft. When the bleeding focus is not detected on visceral angiography despite massive arterial bleeding, pelvic arteriography is recommended, especially in patients with a history of pelvic surgery or radiotherapy.