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.

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.

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.

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.

Purpose: As the survival rate from pediatric cancers has increased significantly with advances in treatment modalities, long-term endocrine complications have also risen. This study investigated the frequencies and risks of endocrine sequelae in childhood cancer survivors who received hematopoietic stem cell transplantation (HSCT). Methods: This study included 200 pediatric patients who underwent HSCT. Clinical and endocrinological findings were collected retrospectively. The median follow-up duration after HSCT was 14 years. Results: Endocrine complications occurred in 135 patients (67.5%). Children who underwent HSCT at pubertal age (n=100) were at higher risk of endocrine complications than those who received it at prepubertal age (79% vs. 56%, P=0.001). The most common complication was hypogonadism (40%), followed by dyslipidemia (22%). Short stature and diabetes mellitus were more prevalent in the prepubertal group, whereas hypogonadism and osteoporosis were more common in the pubertal group. Being female, pubertal age at HSCT, and glucocorticoid use were predictors of an increased risk for any complication. Radiation exposure increased the risk of short stature and hypothyroidism. Hypogonadism was significantly associated with being female, pubertal age at HSCT, and high-dose radiation. Pubertal age at HSCT also increased the risks of osteoporosis and dyslipidemia. Conclusion This study demonstrates that long-term endocrine complications are common after HSCT in children and adolescents. Age at HSCT is a critical factor for endocrine complications after HSCT. These findings suggest that surveillance strategies for endocrine complications in childhood cancer survivors should be specified according to age at HSCT.

The Korea Nurses’ Health Study (KNHS) is an ongoing, large-scale, prospective cohort study of women nurses, focusing on the effects of occupational, environmental, and lifestyle factors on the health of women. The first KNHS survey was performed in 2013-2014 (n=20,613). As of December 2023, 11 follow-up surveys have been conducted. Participants who were pregnant were asked to participate in the early pregnancy survey (n=2,179) and postpartum survey after giving birth (n=2,790). The main variables included socio-demographic, work-related, lifestyle, physical, mental, and women’s health factors. Blood, urine, and toenail samples were collected from a participant subgroup of the first survey (n=1,983). The subgroups of the second survey completed a food frequency questionnaire in 2019 (n=300) and 2021 (n=871). In 2020, a subgroup of the first survey answered a coronavirus disease 2019-related survey (n=975). To examine various health-related factors in young adults, new participants were added to the KNHS cohort in the 11th (n=1,000) and 12th (n=1,002) surveys. The KNHS cohort will help identify health and illness determinants in Korean women. Data can be accessed at https://coda.nih.go.kr/frt/index.do.