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: Few studies have investigated the association between smoking and microvascular complications in the Asian population with type 2 diabetes mellitus (T2DM). We aimed to investigate the relationship between smoking status and microvascular complications in Korean patients with T2DM. Materials and Methods: From the Korean National Diabetes Program cohort, we included 2316 Korean male with T2DM who had baseline clinical information available, including their smoking status, and underwent diabetic complication studies. Results: Compared to non-smokers, current smokers had higher odds of any-microvascular complications [adjusted odds ratio (aOR) 1.45, 95% confidence interval (CI) 1.07–1.97, p=0.016]. The odds of neuropathy were significantly higher; however, the odds of retinopathy were significantly lower in current smokers than in nonsmokers (all p<0.05). Among those who underwent repeated complication tests after 3 years, the risk of newly developed retinopathy was significantly increased in ex-smokers [aOR 3.77 (95% CI 1.61–8.87), p=0.002]. Within ex-smokers, long smoking duration and smoking cessation within the recent 5 years were associated with an increased risk of newly developed retinopathy (all p<0.05). Conclusion Male smokers had higher odds of having overall diabetic microvascular complications, including neuropathy. However, the odds of having retinopathy were significantly lower among current smokers. More attention and research are needed regarding the increased risk of retinopathy development in ex-smokers who have recently stopped smoking after a long history of smoking.

Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD. Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28–24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00–16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD. Conclusion Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at followup chest CT can be predictors of clinically significant ILDs.

BACKGROUND/OBJECTIVES: Recently, herbal medicines have gained attention for the treatment of benign prostatic hyperplasia (BPH), a common disease in elderly men. In this study, we aimed to determine the effect of ethanol extract of Asparagi radix (EAR), which is traditionally used to treat various diseases, on BPH development using a testosteroneinduced BPH model.MATERIALS/METHODS: Testosterone propionate (TP)-treated Sprague–Dawley rats were used to establish a BPH model in vivo. EAR was orally administered along with TP, and finasteride was used as a positive control. All rats were sacrificed at the end of the experiment, and pathological changes in the prostate tissue and levels of key biomarkers associated with BPH pathogenesis were assessed. RESULTS: Oral administration of EAR significantly inhibited TP-induced BPH by reducing the prostate weight, lumen size, and epithelial thickness in a concentration-dependent manner. EAR also significantly abrogated the expression of 5α-reductase type 2 (SRD5A2), proliferating cell nuclear antigen, and prostate-specific antigen (PSA) induced by TP.Additionally, serum levels of testosterone, dihydrotestosterone, and PSA were elevated in the TP-induced group but decreased in the EAR-treated group. EAR also decreased the expression levels of the androgen receptor (AR) and its coactivators in TP-induced BPH model rats. CONCLUSION Our findings revealed that EAR protected against BPH by inhibiting 5α-reductase activity and AR signaling pathway, suggesting its potential for BPH treatment.

Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD (n = 23, 23%) and those who were not (n = 78, 77%). Logistic regression analysis was used to identify significant parameters for the clinical diagnosis of ILD. Results: Twenty-three patients (n = 23, 23%) were subsequently diagnosed with clinically significant ILDs at follow-up (mean, 8.7 years). Subpleural fibrotic ILAs on initial CT and signs of progression on follow-up CT were common in the ILD group (both p < 0.05). Logistic regression analysis revealed that emerging respiratory symptoms (odds ratio [OR], 5.56; 95% confidence interval [CI], 1.28–24.21; p = 0.022) and progression of ILAs at follow-up chest CT (OR, 4.07; 95% CI, 1.00–16.54; p = 0.050) were significant parameters for clinical diagnosis of ILD. Conclusion Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at followup chest CT can be predictors of clinically significant ILDs.

BACKGROUND/OBJECTIVES: Recently, herbal medicines have gained attention for the treatment of benign prostatic hyperplasia (BPH), a common disease in elderly men. In this study, we aimed to determine the effect of ethanol extract of Asparagi radix (EAR), which is traditionally used to treat various diseases, on BPH development using a testosteroneinduced BPH model.MATERIALS/METHODS: Testosterone propionate (TP)-treated Sprague–Dawley rats were used to establish a BPH model in vivo. EAR was orally administered along with TP, and finasteride was used as a positive control. All rats were sacrificed at the end of the experiment, and pathological changes in the prostate tissue and levels of key biomarkers associated with BPH pathogenesis were assessed. RESULTS: Oral administration of EAR significantly inhibited TP-induced BPH by reducing the prostate weight, lumen size, and epithelial thickness in a concentration-dependent manner. EAR also significantly abrogated the expression of 5α-reductase type 2 (SRD5A2), proliferating cell nuclear antigen, and prostate-specific antigen (PSA) induced by TP.Additionally, serum levels of testosterone, dihydrotestosterone, and PSA were elevated in the TP-induced group but decreased in the EAR-treated group. EAR also decreased the expression levels of the androgen receptor (AR) and its coactivators in TP-induced BPH model rats. CONCLUSION Our findings revealed that EAR protected against BPH by inhibiting 5α-reductase activity and AR signaling pathway, suggesting its potential for BPH treatment.