Objective: Perinatal depression often remains undertreated due to concerns about antidepressant exposure during fertility treatment, pregnancy, or breastfeeding. Non-pharmacological, home-based interventions such as transcranial direct current stimulation (tDCS) present a promising alternative; however, real-world evidence in perinatal populations remains limited. Methods: This prospective observational study included 38 women who received infertility, pregnancy, or postpartum treatment at four hospitals in South Korea. Participants self-administered anodal tDCS targeting the left dorsolateral prefrontal cortex for 20–28 sessions over 4 weeks. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D) at baseline and weeks 2, 4, and 8. Subjective health perception was measured at baseline using a 5-point Likert scale. Results: Time had a significant effect on depressive symptoms (Wald χ2=90.75, p<0.001), with the largest reduction observed during the first 2 weeks. The CES-D scores remained significantly lower than baseline at week 8, 4 weeks after treatment ended. Subjective health perception was significantly associated with baseline depression severity (Wald χ2=26.41, p<0.001), and its interaction with time was also significant (Wald χ2=320.18, p<0.001). Participants with poorer perceived health (scores 4–5) experienced greater depressive symptom reductions than those with more favorable perceptions (scores 1–2). Conclusion Home-based tDCS was feasible and associated with clinically meaningful improvement in depressive symptoms among perinatal women. Those who initially perceived their health more negatively showed greater response, suggesting subjective health perception may serve as a useful moderator and potential marker to inform personalized treatment strategies.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

The impact of baseline estimated glomerular filtration rate (eGFR) on the risk of adverse outcomes according to metabolic parameter variabilities in chronic kidney disease has rarely been investigated. Methods: We conducted a retrospective nationwide cohort study using the National Health Insurance System data in Korea from 2007 to 2013 to identify individuals with three or more health screenings. The metabolic components variability was defined as intraindividual variability between measurements using the variability independent of the mean. The metabolic variability score was defined as the total number of high-variability metabolic components. Multivariable-adjusted Cox regression analysis was conducted to evaluate the risks of all-cause mortality, myocardial infarction, and ischemic stroke. Results: During a mean follow-up of 6.0 ± 0.7 years, 223,531 deaths, 107,140 myocardial infarctions, and 116,182 ischemic strokes were identified in 9,971,562 patients. Low eGFR categories and higher metabolic variability scores were associated with a higher risk of adverse outcomes. The degree of association between metabolic variability and adverse outcomes was significantly larger in those with low eGFR categories than in those with preserved eGFR (p for interaction < 0.001). Representatively, those with high metabolic variability in the eGFR of <15 mL/min/1.73 m2 group showed a prominently higher risk for all-cause mortality (adjusted hazard ratio [aHR], 5.28; 95% confidence interval [CI], 4.02–6.94) when the degree was compared to the findings in those with preserved (eGFR of ≥60 mL/min/1.73 m2) kidney function (aHR, 2.55; 95% CI, 2.41–2.69). Conclusion: The degree of adverse association between metabolic variability and poor prognosis is accentuated in patients with impaired kidney function.

Early-onset diabetes mellitus has a significant lifetime burden and is associated with higher morbidity and mortality. Since insulin resistance is one of the mechanisms of podocyte injury, we aimed to evaluate the effect of albuminuria on newly developed early-onset type 2 diabetes mellitus (T2DM). Methods: We screened 6,891,399 subjects aged ≥20 and <40 years without a history of prediabetes or diabetes from the Korean National Health Insurance Service database between 2009 and 2012. A multivariate Cox proportional hazard model was used to identify the impact of albuminuria on early-onset T2DM. Results: Among a total of 5,383,779 subjects, 62,148 subjects (1.2%) developed early-onset diabetes over 7.3 ± 1.2 years. Albuminuria was significantly associated with early-onset T2DM (adjusted hazard ratio [aHR], 1.62; 95% confidence interval [CI], 1.55–1.70) after adjustment for age, sex, anthropometric data, physical exercise status, serum glucose, and total cholesterol. The risk of early-onset T2DM increased more in subjects with more components of metabolic syndrome (MetS). Among each component of MetS, hypertriglyceridemia was prominently associated with early-onset T2DM (aHR, 2.02; 95% CI, 1.81–2.25) in subjects with albuminuria. Conclusion: Dipstick albuminuria was significantly associated with early-onset T2DM in young adult populations. Close monitoring of albuminuria is warranted for disease risk modification, especially in subjects with MetS.

Purpose: To report a case of orbital apex syndrome resulting from invasive fungal sinusitis attributed to the unusual Candida glabrata species.Case summary: A 76-year-old patient presented with persistent left-sided orbital pain, headaches, and blurred vision for 3 weeks. The patient had a history of uncontrolled diabetes, chronic kidney failure, and angina, and was treated for a COVID-19 infection 1 month prior to admission. Contrast-enhanced computed tomography scans revealed extensive bilateral sinusitis affecting the left optic nerve. The patient underwent endoscopic sinus surgery, which included nasal cavity biopsy, conducted by an otorhinolaryngologist. Histopathological analysis using Gömöri methenamine silver stains identified Candida. Cultures from sinus specimens later grew Candida glabrata. Treatment involved daily IV amphotericin B followed by oral itraconazole. After 6 months, the patient fully recovered from fungal sinusitis but continued to experience negative light perception in the left eye and progressed to complete ophthalmoplegia, consistent with orbital apex syndrome. Conclusions Reports of invasive fungal sinusitis caused by Candida infections are rare globally. This report marks the first occurrence in this country. Effective management requires careful assessment and appropriate treatment tailored to the specific species, especially considering the risk of orbital extension of the inflammatory lesion.

Purpose: This study aimed to determine whether zero echo time magnetic resonance imaging (ZTE-MRI), as an alternative imaging modality, and conventional computed tomography (CT) have similar diagnostic qualities for assessing pediatric osseous pathologies. Materials and Methods: Twenty-six sets of pediatric musculoskeletal CT and MRI scans (15 boys and 11 girls; mean age, 12 ± 4 years; range, 5–23 years) acquired at Seoul National University Children’s Hospital (January 2021 to November 2023) were retrospectively evaluated. CT-like images from ZTE-MRI were generated using grayscale inversion. Two radiologists independently assessed ZTE-MRI image quality (S anat) on a 5-point scale (1 = nondiagnostic, 5 = excellent) and a comparative scale (–2 = CT greater, 0 = same, 2 = ZTE-MRI greater) for lesion delineation (Scomp). The confidence interval of proportions and intraclass correlation coefficient were calculated to assess inter-rater agreement, and Wilcoxon rank-sum test, Mann–Whitney U test, or paired t-test was used to compare image quality or cortical thickness between the modalities. Results: ZTE-MRI demonstrated diagnostic quality (S anat ≥ 3) in 85%–96% of the cases, 89%–96% for cortical delineation, 92%–100% for intramedullary cavity (IMC) delineation, and 92% for lesion delineation. Compared with conventional CT, ZTE-MRI showed comparable diagnostic power (Scomp ≥ –1) in 92%–96% of the cases, with Scomp scores indicating no significant difference in lesion delineation (p = 0.53 in reader 1 and p = 0.25 in reader 2). There was a preference for CT over ZTE-MRI in terms of overall image quality and delineation of the cortex and IMC (p < 0.001). Cortical thickness was not significantly different (p = 0.11) between ZTE-MRI and CT. Conclusion ZTE-MRI demonstrated diagnostic quality comparable to that of CT, particularly in lesion delineation. In addition to the unique information that conventional MRI can provide, ZTE-MRI can provide additional information about osseous structures similar to that provided by CT, which we believe will be valuable in the future.