Hepatocellular carcinoma (HCC) progresses through multiple stages of hepatocarcinogenesis, with each stage characterized by specific changes in vascular supply, drainage, and microvascular structure. These vascular changes significantly influence the imaging findings of HCC, enabling non-invasive diagnosis. Vascular changes in HCC are closely related to aggressive histological characteristics and treatment responses. Venous drainage from the tumor toward the portal vein in the surrounding liver facilitates vascular invasion, and the unique microvascular pattern of vessels that encapsulate the tumor cluster (known as a VETC pattern) promotes vascular invasion and metastasis. Systemic treatments for HCC, which are increasingly being used, primarily target angiogenesis and immune checkpoint pathways, which are closely intertwined. By understanding the complex relationship between histopathological vascular changes in hepatocarcinogenesis and their implications for imaging findings, radiologists can enhance the accuracy of imaging diagnosis and improve the prediction of prognosis and treatment response.This, in turn, will ultimately lead to better patient care.

Objective: This study aimed to investigate the feasibility of using artificial intelligence (AI) to identify normal chest radiography (CXR) from the worklist of radiologists in a health-screening environment. Materials and Methods: This retrospective simulation study was conducted using the CXRs of 5887 adults (mean age ± standard deviation, 55.4 ± 11.8 years; male, 4329) from three health screening centers in South Korea using a commercial AI (Lunit INSIGHT CXR3, version 3.5.8.8). Three board-certified thoracic radiologists reviewed CXR images for referable thoracic abnormalities and grouped the images into those with visible referable abnormalities (identified as abnormal by at least one reader) and those with clearly visible referable abnormalities (identified as abnormal by at least two readers). With AI-based simulated exclusion of normal CXR images, the percentages of normal images sorted and abnormal images erroneously removed were analyzed. Additionally, in a random subsample of 480 patients, the ability to identify visible referable abnormalities was compared among AI-unassisted reading (i.e., all images read by human readers without AI), AI-assisted reading (i.e., all images read by human readers with AI assistance as concurrent readers), and reading with AI triage (i.e., human reading of only those rendered abnormal by AI). Results: Of 5887 CXR images, 405 (6.9%) and 227 (3.9%) contained visible and clearly visible abnormalities, respectively. With AI-based triage, 42.9% (2354/5482) of normal CXR images were removed at the cost of erroneous removal of 3.5% (14/405) and 1.8% (4/227) of CXR images with visible and clearly visible abnormalities, respectively. In the diagnostic performance study, AI triage removed 41.6% (188/452) of normal images from the worklist without missing visible abnormalities and increased the specificity for some readers without decreasing sensitivity. Conclusion This study suggests the feasibility of sorting and removing normal CXRs using AI with a tailored cut-off to increase efficiency and reduce the workload of radiologists.

Background/Aims: Intrahepatic cholangiocarcinoma (iCCA) with a ductal plate malformation (DPM) pattern is a recently recognized rare variant. The genomic profile of iCCA with DPM pattern needs to be elucidated. Methods: Cases of iCCA with DPM pattern were retrospectively reviewed based on the medical records, pathology slides, and magnetic resonance imaging (MRI) reports collected between 2010 to 2019 at a single center. Massive parallel sequencing was performed for >500 cancerrelated genes. Results: From a total of 175 iCCAs, five (2.9%) cases of iCCA with DPM pattern were identified. All cases were of the small duct type, and background liver revealed chronic B viral or alcoholic hepatitis. Three iCCAs with DPM pattern harbored MRI features favoring the diagnosis of hepatocellular carcinoma, whereas nonspecific imaging features were observed in two cases. All patients were alive without recurrence during an average follow-up period of 57 months. Sequencing data revealed 64 mutated genes in the five cases, among which FGFR2 and PTPRT were most frequently mutated (three cases each) including an FGFR2-TNC fusion in one case. Mutations in ARID1A and CDKN2A were found in two cases, and mutations in TP53, BAP1, ATM, NF1, and STK11 were observed in one case each. No IDH1, KRAS, or PBRM1 mutations were found. Conclusions iCCAs with DPM pattern have different clinico-radio-pathologic and genetic characteristics compared to conventional iCCAs. Moreover, FGFR2 and FGFR2 variants were identified. Altogether, these findings further suggest that iCCA with DPM pattern represents a specific subtype of small duct type iCCA.

Background: Cranioplasty for the treatment of cephalhematomas in small infants with limited blood volume is challenging because of massive bleeding. This study aimed to elucidate the correlation between cephalhematoma size and intraoperative blood loss and identify criteria that can predict large intraoperative blood loss. Methods: We reviewed the medical records of 120 pediatric patients aged less than 24 months who underwent cranioplasty for treatment of a cephalhematoma. The cephalhematoma sizes in preoperative brain computed tomography (CT) were measured using ImageJ. Results: Pearson correlation showed that the cephalhematoma size in the pre-operative brain CT was weakly correlated with intraoperative blood loss (Pearson coefficient = 0.192, P = 0.037). In a multivariable logistic regression analysis, a cephalhematoma size greater than 113.5 cm3 was found to be a risk factor for large blood loss. The area under the curve in the receiver operating characteristic plot of the multivariable model was 0.714 (0.619–0.809). Conclusions A cephalhematoma size cutoff value of 113.5 cm3, as measured in the preoperative CT imaging, can predict intraoperative blood loss exceeding 30% of the total body blood volume. The establishment of a transfusion strategy prior to surgery based on cephalhematoma size could be useful in pediatric cranioplasty.

Background: There is increasing interest in the quality of health care and considerable efforts are being made to improve it. Rheumatoid arthritis (RA) is a disease that can result in favorable outcomes when appropriate diagnosis and treatment are provided. However, several studies have shown that RA is often managed inappropriately. Therefore, the Korean College of Rheumatology aimed to develop quality indicators (QIs) to evaluate and improve the health care of patients with RA. Methods: Preliminary QIs were derived based on the existing guidelines and QIs for RA. The final QIs were determined through two separate consensus meetings of experts. The consensus was achieved through a panel of experts who voted using the modified Delphi method. Results: Fourteen final QIs were selected among 70 preliminary QIs. These included early referral to and regular follow-up with a rheumatologist, radiographs of the hands and feet, early initiation and maintenance of disease-modifying anti-rheumatic drug (DMARD) therapy, periodic assessment of disease activity, screening for drug safety and comorbidities,including viral hepatitis and tuberculosis before biologic DMARD therapy, periodic laboratory testing, supplementation with folic acid, assessment of the risk for cervical spine instability before general anesthesia, patient education, and specialized nurse. Conclusion These QIs can be used to assess and improve the quality of health care for patients with RA.

Background: There is increasing interest in the quality of health care and considerable efforts are being made to improve it. Rheumatoid arthritis (RA) is a disease that can result in favorable outcomes when appropriate diagnosis and treatment are provided. However, several studies have shown that RA is often managed inappropriately. Therefore, the Korean College of Rheumatology aimed to develop quality indicators (QIs) to evaluate and improve the health care of patients with RA. Methods: Preliminary QIs were derived based on the existing guidelines and QIs for RA. The final QIs were determined through two separate consensus meetings of experts. The consensus was achieved through a panel of experts who voted using the modified Delphi method. Results: Fourteen final QIs were selected among 70 preliminary QIs. These included early referral to and regular follow-up with a rheumatologist, radiographs of the hands and feet, early initiation and maintenance of disease-modifying anti-rheumatic drug (DMARD) therapy, periodic assessment of disease activity, screening for drug safety and comorbidities,including viral hepatitis and tuberculosis before biologic DMARD therapy, periodic laboratory testing, supplementation with folic acid, assessment of the risk for cervical spine instability before general anesthesia, patient education, and specialized nurse. Conclusion These QIs can be used to assess and improve the quality of health care for patients with RA.

Background: Cranioplasty for the treatment of cephalhematomas in small infants with limited blood volume is challenging because of massive bleeding. This study aimed to elucidate the correlation between cephalhematoma size and intraoperative blood loss and identify criteria that can predict large intraoperative blood loss. Methods: We reviewed the medical records of 120 pediatric patients aged less than 24 months who underwent cranioplasty for treatment of a cephalhematoma. The cephalhematoma sizes in preoperative brain computed tomography (CT) were measured using ImageJ. Results: Pearson correlation showed that the cephalhematoma size in the pre-operative brain CT was weakly correlated with intraoperative blood loss (Pearson coefficient = 0.192, P = 0.037). In a multivariable logistic regression analysis, a cephalhematoma size greater than 113.5 cm3 was found to be a risk factor for large blood loss. The area under the curve in the receiver operating characteristic plot of the multivariable model was 0.714 (0.619–0.809). Conclusions A cephalhematoma size cutoff value of 113.5 cm3, as measured in the preoperative CT imaging, can predict intraoperative blood loss exceeding 30% of the total body blood volume. The establishment of a transfusion strategy prior to surgery based on cephalhematoma size could be useful in pediatric cranioplasty.

Percutaneous transthoracic needle biopsy (PTNB) is one of the essential diagnostic procedures for pulmonary lesions. Its role is increasing in the era of CT screening for lung cancer and precision medicine. The Korean Society of Thoracic Radiology developed the first evidence-based clinical guideline for PTNB in Korea by adapting pre-existing guidelines. The guideline provides 39 recommendations for the following four main domains of 12 key questions: the indications for PTNB, pre-procedural evaluation, procedural technique of PTNB and its accuracy, and management of post-biopsy complications. We hope that these recommendations can improve the diagnostic accuracy and safety of PTNB in clinical practice and promote standardization of the procedure nationwide.

Background: The value of the Fracture Risk Assessment Tool (FRAX) and the trabecular bone score (TBS) for assessing osteoporotic fracture risk has not been fully elucidated in Koreans. We conducted this study to clarify the predictive value of FRAX adjusted by TBS for osteoporotic fractures in Korean women. Methods: After screening 7,192 eligible subjects from the Ansung cohort, 1,165 women aged 45 to 76 years with available bone mineral density (BMD) and TBS data were enrolled in this study. We assessed their clinical risk factors for osteoporotic fractures and evaluated the predictive value of FRAX with or without BMD and TBS. Results: During the mean follow-up period of 7.5 years, 99 (8.5%) women suffered major osteoporotic fractures (MOFs) and 28 (2.4%) experienced hip fractures. FRAX without BMD, BMD-adjusted FRAX, and TBS-adjusted FRAX were significantly associated with the risk of MOFs (hazard ratio [HR] per percent increase, 1.08; 95% confidence interval [CI], 1.03 to 1.14; HR, 1.09; 95% CI, 1.03 to 1.15; and HR, 1.07; 95% CI, 1.02 to 1.13, respectively). However, BMD-adjusted FRAX and TBS-adjusted FRAX did not predict MOFs better than FRAX without BMD based on the Harrell’s C statistic. FRAX probabilities showed limited value for predicting hip fractures. The cut-off values of FRAX without BMD, FRAX with BMD, and FRAX with BMD adjusted by TBS for predicting MOFs were 7.2%, 5.0%, and 6.7%, respectively. Conclusion FRAX with BMD and TBS adjustment did not show better predictive value for osteoporotic fractures in this study than FRAX without adjustment. Moreover, the cut-off values of FRAX probabilities for treatment might be lower in Korean women than in other countries.

In patients at high risk of hepatocellular carcinoma (HCC), such as those with chronic hepatitis or cirrhosis, the confirmative diagnosis of HCC can be made solely from characteristic imaging findings on contrast-enhanced CT or MR scans. However, in daily practice, HCCs showing atypical imaging features are frequently encountered. Since the criteria for diagnosis of HCC is based on dynamic contrast enhancement patterns, it is essential to thoroughly understand these patterns. In this article, we aim to use gadoxetate-enhanced MRI to comprehensively review the HCC enhancement patterns and the associated histopathologic findings with their prognostic factors.