Incidentally detected gallbladder polyps (GBPs) and gallbladder wall thickening (GBWT) are frequently encountered in clinical practice. However, characterizing GBPs and GBWT in asymptomatic patients can be challenging and may result in overtreatment, including unnecessary follow-ups or surgeries. The Korean Society of Abdominal Radiology (KSAR) Clinical Practice Guideline Committee has developed expert recommendations that focus on standardized imaging interpretation and follow-up strategies for both GBPs and GBWT, with support from the Korean Society of Radiology and KSAR. These guidelines, which address 24 key questions, aim to standardize the approach for the interpretation of imaging findings, reporting, imaging-based workups, and surveillance of incidentally detected GBPs and GBWT. This recommendation promotes evidence-based practice, facilitates communication between radiologists and referring physicians, and reduces unnecessary interventions.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

This report presents radiologic changes after clinical improvement in a patient with acute interstitial nephritis (AIN). A 45-year-old female patient was referred for decreased renal function. Eight months prior, she had undergone hysterectomy and received chemotherapy. At the start of chemotherapy, her baseline creatinine level was 0.55 mg/dL, which rose to 1.46 mg/dL. Multiple imaging modalities performed when decreased renal function was observed revealed bilateral renal enlargement with increased cortical attenuation on computed tomography (CT), cortical hyperechogenicity on ultrasonography, and diffusion restriction in the renal cortices on magnetic resonance imaging. A renal biopsy was performed, and AIN was diagnosed. Follow-up laboratory tests showed that kidney function had improved to normal levels, and CT at that time showed a reduction in the size of both kidneys. Radiologic changes can serve as clues for the diagnosis of AIN. This is the first report to confirm radiological changes after the clinical improvement of AIN, thereby providing novel information about the course of AIN.

Incidentally detected gallbladder polyps (GBPs) and gallbladder wall thickening (GBWT) are frequently encountered in clinical practice. However, characterizing GBPs and GBWT in asymptomatic patients can be challenging and may result in overtreatment, including unnecessary follow-ups or surgeries. The Korean Society of Abdominal Radiology (KSAR) Clinical Practice Guideline Committee has developed expert recommendations that focus on standardized imaging interpretation and follow-up strategies for both GBPs and GBWT, with support from the Korean Society of Radiology and KSAR. These guidelines, which address 24 key questions, aim to standardize the approach for the interpretation of imaging findings, reporting, imaging-based workups, and surveillance of incidentally detected GBPs and GBWT. This recommendation promotes evidence-based practice, facilitates communication between radiologists and referring physicians, and reduces unnecessary interventions.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

This report presents radiologic changes after clinical improvement in a patient with acute interstitial nephritis (AIN). A 45-year-old female patient was referred for decreased renal function. Eight months prior, she had undergone hysterectomy and received chemotherapy. At the start of chemotherapy, her baseline creatinine level was 0.55 mg/dL, which rose to 1.46 mg/dL. Multiple imaging modalities performed when decreased renal function was observed revealed bilateral renal enlargement with increased cortical attenuation on computed tomography (CT), cortical hyperechogenicity on ultrasonography, and diffusion restriction in the renal cortices on magnetic resonance imaging. A renal biopsy was performed, and AIN was diagnosed. Follow-up laboratory tests showed that kidney function had improved to normal levels, and CT at that time showed a reduction in the size of both kidneys. Radiologic changes can serve as clues for the diagnosis of AIN. This is the first report to confirm radiological changes after the clinical improvement of AIN, thereby providing novel information about the course of AIN.

BACKGROUND/OBJECTIVES: Isoflavones are estrogen-like compounds found in plants and their health effects remain equivocal. We investigated dietary isoflavone intake and its associated factors in Korean breast cancer survivors, with a comparison to cancer-free women. SUBJECTS/METHODS: The usual dietary intake of breast cancer survivors (n = 981, mean age 52 yrs) in 9 hospitals between 2012 and 2019 was assessed using 3-day food records or food frequency questionnaires (FFQs). They were age-matched to 2,943 cancer-free women who completed FFQs as part of a nationwide study conducted between 2012 and 2016. We used the flavonoid database of common Korean foods and the Phenol-Explorer database to estimate isoflavone intake. The contribution of each food or food group to the total isoflavone intake was calculated. The adjusted least-squares means of dietary isoflavone intake according to lifestyle and clinical factors were calculated using generalized linear models. RESULTS: Breast cancer survivors had a higher mean dietary isoflavone intake (23.59 mg/day) than cancer-free women (17.81 mg/day). Major food sources, including tofu, soybeans, and doenjang, contributed to over 70% of the isoflavone intake in both groups. When we estimated dietary isoflavone intake according to lifestyle characteristics, isoflavone intake increased with higher scores of adherence to the American Cancer Society dietary guidelines but decreased with increasing body mass index in both groups. Among cancer-free women, dietary isoflavone intake was higher among those who had never smoked and among dietary supplement users. Among breast cancer survivors, dietary isoflavone intakes did not vary with clinical characteristics, including time since surgery and estrogen receptor status. CONCLUSION Breast cancer survivors were more likely to consume isoflavones than agematched cancer-free women. Dietary isoflavone intake was associated with healthy lifestyle characteristics in women both with and without breast cancer. Further research is needed to understand the role of the higher isoflavone intake among breast cancer survivors compared to cancer-free women on their prognosis.

Background/Aims: Studies on the clinical outcomes after detecting low-grade dysplasia (LGD) in patients with inflammatory bowel disease (IBD) are insufficient. This study evaluated the clinical features, frequency, and risk factors for advanced neoplasia in patients with IBD after an LGD diagnosis. Methods: The medical records of 166 patients with IBD from six university hospitals in Korea from 2010 to 2019 were reviewed retrospectively. LGD was diagnosed in all patients during surveillance. The frequency and risk factors for advanced neoplasia were evaluated, and the clinical features of patients with and without advanced neoplasia were compared. Results: Advanced neoplasia developed in 12 patients (six with large LGD, three with tubulovillous adenoma, and three with high-grade dysplasia), and all cases developed from UC. Patients with advanced neoplasia had significantly higher Mayo scores, and colitis-associated dysplasia was more common than sporadic lesions (83.3% vs. 29.9%; p<0.001). Multivariate analysis showed that colitis-associated LGD significantly increased the risk of developing advanced neoplasia (odds ratio [OR], 10.516; 95% confidence interval [CI], 2.064–53.577). Among patients with colitis-associated lesions, a significant risk factor for advanced neoplasia was a prior history of LGD (OR, 9.429; 95% CI, 1.330–66.863). Conclusions Advanced neoplasia developed in 7.2% of patients with IBD and LGD. Most advanced neoplasms developed from colitis-associated lesions, and the risk was higher in patients with a history of LGD before index colonoscopy.

Background: Respiratory infections play a major role in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study assessed the prevalence of bacterial and viral pathogens and their clinical impact on patients with AECOPD. Methods: This retrospective study included 1,186 patients diagnosed with AECOPD at 28 hospitals in South Korea between 2015 and 2018. We evaluated the identification rates of pathogens, basic patient characteristics, clinical features, and the factors associated with infections by potentially drug-resistant (PDR) pathogens using various microbiological tests. Results: Bacteria, viruses, and both were detected in 262 (22.1%), 265 (22.5%), and 129 (10.9%) of patients, respectively. The most common pathogens included Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). Notably, a history of pulmonary tuberculosis (odds ratio [OR], 1.66; p=0.046), bronchiectasis (OR, 1.99; p=0.032), and the use of a triple inhaler regimen within the past 6 months (OR, 2.04; p=0.005) were identified as significant factors associated with infection by PDR pathogens. Moreover, patients infected with PDR pathogens exhibited extended hospital stays (15.9 days vs. 12.4 days, p=0.018) and higher intensive care unit admission rates (15.9% vs. 9.5%, p=0.030). Conclusion This study demonstrates that a variety of pathogens are involved in episodes of AECOPD. Nevertheless, additional research is required to confirm their role in the onset and progression of AECOPD.

The integration of artificial intelligence (AI), especially deep learning techniques, is revolutionizing obstetrics and gynecology. AI algorithms can analyze complex medical data, including imaging and genomics, to manage high-risk conditions such as placenta accreta spectrum (PAS) and to improve the outcomes of assisted reproductive technology. Despite significant advancements, challenges persist, including issues with data standardization, ethical concerns, and the complexity of implementing deep learning models.Current Concepts: Deep learning has demonstrated high sensitivity and specificity in diagnosing conditions like PAS and fetal cardiac anomalies. It optimizes embryo selection, tailors hormonal therapy, and predicts preterm birth risks using advanced tools such as CADXpert. Additionally, radiomics combined with deep learning enhances magnetic resonance imaging-based diagnosis and prognosis, particularly in endometrial cancer. However, barriers such as limited model interpretability and regulatory compliance continue to restrict widespread implementation.Discussion and Conclusion: A multidisciplinary approach involving clinicians, data scientists, and policymakers is crucial to addressing these challenges. Efforts should concentrate on developing standardized datasets, creating explainable models, and establishing robust educational frameworks. Overcoming these barriers will enable precise diagnoses and personalized treatments, ultimately improving patient care and outcomes in obstetrics and gynecology.