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: 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.

Purpose: Deficiency of 21-hydroxylase (21-OHD) is an autosomal recessively inherited disorder that is characterized by adrenal insufficiency and androgen excess. This study was performed to investigate the clinical utility of prenatal diagnosis of 21-OHD using molecular genetic testing in families at risk. Methods: This study included 27 pregnant women who had previously borne a child with 21-OHD. Fetal tissues were obtained using chorionic villus sampling (CVS) or amniocentesis. After the genomic DNA was isolated, Sanger sequencing of CYP21A2 and multiplex ligation-dependent probe amplification were performed. The clinical and endocrinological findings were reviewed retrospectively. Results: A total of 39 prenatal genetic tests was performed on 27 pregnant women and their fetal tissues. The mean gestational age at the time of testing was 11.7 weeks for CVS and 17.5 weeks for amniocentesis. Eleven fetuses (28.2%) were diagnosed with 21-OHD. Among them, 10 fetuses (90.9%) harbored the same mutation as siblings who were previously diagnosed with 21-OHD. Among these, 4 fetuses (3 males and 1 female) identified as affected were born alive. All 4 patients have been treated with hydrocortisone, 9α-fludrocortisone, and sodium chloride since a mean of 3.7 days of life. The male patients did not show hyponatremia and dehydration, although they harbored pathogenic variants associated with the salt-wasting type of 21-OHD. Conclusion This study demonstrated the diagnostic efficacy and clinical consequences of diagnosis by prenatal genetic testing in families at risk for 21-OHD. All patients identified as affected were treated with hydrocortisone and 9α-fludrocortisone early after birth, which can prevent a life-threatening adrenal crisis.

Purpose: Androgen insensitivity syndrome (AIS) is a rare X-linked recessive disorder caused by unresponsiveness to androgens because of mutations in the AR gene. Here, we investigated the clinical outcomes and molecular spectrum of AR variants in patients with AIS attending a single academic center. Methods: This study included 19 patients with AIS who were confirmed by molecular analysis of AR. Clinical features and endocrinological findings were retrospectively collected, including presenting features, external genitalia, sex of rearing, timing of gonadectomy, pubertal outcomes, and sex hormone levels. Molecular analysis of AR was performed using Sanger, targeted gene panel, or whole-exome sequencing. Results: Among all 19 patients, 14 (74%) were classified as having complete AIS (CAIS), whereas 5 (26%) had partial AIS (PAIS). All patients with CAIS, and 3 patients with PAIS were reared as female. One patient with CAIS manifested a mixed germ cell tumor at the age of 30 years. Molecular analysis of AR identified 19 sequence variants; 12 (63%) were previously reported, and the remaining 7 (37%) were novel. Missense mutations were the most common type (12 of 19, 63%), followed by small deletions, nonsense mutations, an insertion, and a splice site mutation. Conclusion Here, we describe the clinical outcomes and molecular characteristics of 19 Korean patients with AIS. Patients with PAIS manifested various degrees of masculinization of the external genitalia. Nonsense and frameshift mutations were frequent in patients with CAIS, whereas patients with PAIS harbored exclusively missense mutations.

Shared decision-making is a two-way symmetrical communication process in which clinicians and patients work together to achieve the best outcome. This study aimed to develop self-assessment items as a decision aid for choosing a dialysis modality in patients with chronic kidney disease (CKD) and to assess the construct validity of the newly developed items. Methods: Five focus group interviews were performed to extract specific self-assessment items regarding patient values in choosing a dialysis modality. After survey items were refined, a survey of 330 patients, consisting of 152 hemodialysis (HD) and 178 peritoneal dialysis (PD) patients, was performed to validate the self-assessment items. Results: The self-assessment for the decision aid was refined to 35 items. The structure of the final items appeared to have three dimensions of factors; health, lifestyle, and dialysis environment. The health factor consisted of 12 subscales (α = 0.724), the lifestyle factor contained 11 subscales (α = 0.624), and the dialysis environment factor was represented by 12 subscales (α = 0.694). A structural equation model analysis showed that the relationship between the decision aid factors (health, lifestyle, and dialysis environment), patients’ CKD perception, and cognition of shared decision-making differed between HD patients and PD patients. Conclusion: We developed and validated self-assessment items as part of a decision aid to help patients with CKD. This attempt may assist CKD patients in making informed and shared decisions closely aligned with their values when considering dialysis modality.

Purpose: Osteogenesis imperfecta (OI) is a rare bone fragility disorder caused by defects in type 1 collagen biosynthesis. This study investigated the genotype-phenotype correlations and the efficacy of pamidronate therapy in patients with OI in a single academic center. Methods: This study included 24 patients with OI. A clinical scoring system was used to evaluate disorder severity. COL1A1 and COL1A2 genes were analyzed in 13 patients using Sanger sequencing. Genotype-phenotype correlations and the efficacy of pamidronate therapy were analyzed through a retrospective medical chart review. Results: Of the 24 patients, 18 (75%) were classified as type I (12 with type Ia and 6 with type Ib), 2 as type III (8.4%), and 4 as type IV (16.7%). Type Ia patients showed relatively higher lumbar bone mineral density (BMD) standard deviation scores (SDS) and lower clinical scores than those with other types. Seven patients with qualitative mutations had lower lumbar BMD-SDS (P=0.015) and higher clinical scores (P=0.008) than 6 patients with quantitative mutations. The annual fracture frequency and lumbar BMD-SDS improved in patients with qualitative mutations after pamidronate treatment. Conclusion This study demonstrated that OI patients with qualitative mutations in COL1A1/2 had a more severe phenotype than those with quantitative mutations. Patients with qualitative mutations showed a significant reduction in fracture frequency and an increase in lumbar BMD-SDS after pamidronate treatment. Clinical score and genotype might be helpful for predicting phenotype and response to pamidronate therapy in OI patients.