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.

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.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

The prevalence of prediabetes has steadily increased in Korea, driven by rising obesity rates and lifestyle changes. A structured lifestyle modification program has been shown to significantly reduce the prevalence of diabetes among adults with prediabetes, with this effect sustained over time. Lifestyle modifications including medical nutrition, exercise, and behavioral psychological therapy are effective for preventing and managing diabetes, with medical nutrition therapy playing a crucial role. This study reviews the latest academic guidelines and medical nutrition therapy for diabetes prevention and to introduce the KDPS-hLSM (Korean Diabetes Prevention Study hospital-based lifestyle modification).

Gestational diabetes mellitus (GDM) affects 2~10% of pregnant women worldwide, with an increasing prevalence in South Korea that reached 18.2% in 2021. Unmanaged GDM can lead to serious complications for both mother and fetus. Effective management requires blood glucose monitoring and lifestyle changes, but many women lack sufficient knowledge about the condition. This study explores the use of smart platforms, like continuous glucose monitoring devices and mobile apps, to improve GDM education. Devices such as Dexcom G7 and FreeStyle Libre 2 enable real-time blood glucose monitoring, while apps like Health2Sync help patients share data with healthcare providers. Although these technologies offer major benefits, challenges remain in patient engagement, data accuracy, and accessibility. In conclusion, while smart platforms can enhance GDM management, they must be combined with ongoing professional support to improve health outcomes.

Background/Aims: Cardiovascular disease is the leading cause of death worldwide. This study aimed to investigate the recent nationwide trends in major dietary risk factors for dyslipidemia and atherosclerosis. Methods: We estimated age-standardized mean intakes of fresh fruits, fresh vegetables, whole grains, dietary fiber, and sugar-sweetened beverages (SSBs); and mean percentage of energy intake from protein, total fat, saturated fat, and polyunsaturated fat using nationally representative samples from the Korean National Health Examination and Nutrition Survey 2013–2022. To assess overall diet quality, we calculated mean Korean Healthy Eating Index (KHEI) (range 0–100, higher scores indicating greater diet quality). Results: In 2013–2022, there were overall decreasing trends in age-standardized mean KHEI score and intakes of fresh fruits and vegetables, whole grains, and dietary fiber; and overall increasing trends in mean intakes of SSBs, protein, and dietary fat among both male and female. The KHEI score increased in older adults aged ≥ 60 years, whereas it decreased among younger adults. Throughout the study period, younger adults tended to have lower intakes of fresh fruits, fresh vegetables, and whole grains; higher intakes of SSBs, protein, and dietary fat; and lower KHEI score. The mean KHEI score was lower in male (vs. female) and lower (vs. higher) income groups. Conclusions Our data suggest that, from 2013 to 2022, there was a trend toward an unhealthy diet in Korean adults. Our findings also suggest dietary inequalities among age, sex, and income groups, suggesting the need for more intense interventions targeting the vulnerable populations.

Purpose: This study elucidates the mechanism of the physiological effect of cannabidiol (CBD) by assessing its impact on lipopolysaccharide (LPS)-induced inflammation in RWPE-1 cells and prostatitis-induced by 17β-estradiol and dihydrotestosterone in a rat model, focusing on its therapeutic potential for chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Materials and Methods: RWPE-1 cells were stratified in vitro into three groups: (1) controls, (2) cells with LPS-induced inflammation, and (3) cells with LPS-induced inflammation and treated with CBD. Enzyme-linked immunosorbent assays and western blots were performed on cellular components and supernatants after administration of CBD. Five groups of six Sprague–Dawley male rats were assigned: (1) control, (2) CP/CPPS, (3) CP/CPPS and treated with 50 mg/kg CBD, (4) CP/CPPS and treated with 100 mg/kg CBD, and (5) CP/CPPS and treated with 150 mg/kg CBD. Prostatitis was induced through administration of 17β-estradiol and dihydrotestosterone. After four weeks of CBD treatment, a pain index was evaluated, and prostate tissue was collected for subsequent histologic examination and western blot analysis. Results: CBD demonstrated efficacy in vivo for CP/CPPS and in vitro for inflammation. It inhibited the toll-like receptor 4 (TLR4)uclear factor-kappa B (NF-κB) pathway by activating the CB2 receptor, reducing expression of interleukin-6, tumor necrosis factor-alpha, and cyclooxygenase-2 (COX2) (p<0.01). CBD exhibited analgesic effects by activating and desensitizing the TRPV1 receptor. Conclusions CBD inhibits the TLR4/NF-κB pathway by activating the CB2 receptor, desensitizes the TRPV1 receptor, and decreases the release of COX2. This results in relief of inflammation and pain in patients with CP/CPPS, indicating CBD as a potential treatment for CP/CPPS.