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.

Background: The optimal duration and net clinical benefit of dual antiplatelet therapy (DAPT) after transcatheter aortic valve replacement (TAVR) have not been elucidated in realworld situations. Methods: Using nationwide claims data from 2013 to 2021, we selected patients who underwent TAVR and categorized them into two groups: short- and long-term (≤ 3 and > 3 months, respectively) DAPT group. Propensity score matching was used to balance baseline characteristics. The primary endpoint was the occurrence of net adverse clinical events (NACEs), including all-cause death, myocardial infarction, stroke, any coronary and peripheral revascularization, systemic thromboembolism, and bleeding events, at 1 year. Survival analyses were conducted using Kaplan-Meier estimation and Cox proportional hazards regression. Results: Patients who met the inclusion criteria (1,695) were selected. Propensity score matching yielded 1,215 pairs of patients: 416 and 799 in the short- and long-term DAPT groups, respectively. In the unmatched cohort, the mean ages were 79.8 ± 6.1 and 79.7 ± 5.8 years for the short- and long-term DAPT groups, respectively. In the matched cohort, the mean ages were 80.6 ± 5.9 and 79.9 ± 5.9 years for the short- and long-term DAPT groups, respectively. Over one year in the unmatched cohort, the NACE incidence was 11.9% and 11.5% in the short- and long-term DAPT groups, respectively (P = 0.893). The all-cause mortality rates were 7.4% and 4.7% (P = 0.042), composite ischemic event rates were 2.5% and 4.7% (P = 0.056), and bleeding event rates were 2.7% and 4.7% (P = 0.056) in the shortand long-term groups, respectively. In the matched cohort, the incidence of NACE was 9.6% in the short-term DAPT group and 11.6% in the long-term DAPT group, respectively (P = 0.329).The all-cause mortality rates were 6.5% and 4.9% (P = 0.298), composite ischemic event rates were 1.4% and 4.5% (P = 0.009), and bleeding event rates were 2.2% and 4.4% (P = 0.072) in the short- and long-term groups, respectively. Conclusion In patients who successfully underwent transfemoral TAVR, the short- and longterm DAPT groups exhibited similar one-year NACE rates. However, patients in the long-term DAPT group experienced more bleeding and ischemic events.

Background: This study aimed to generate a Z score calculation model for coronary artery diameter of normal children and adolescents to be adopted as the standard calculation method with consensus in clinical practice. Methods: This study was a retrospective, multicenter study that collected data from multiple institutions across South Korea. Data were analyzed to determine the model that best fit the relationship between the diameter of coronary arteries and independent demographic parameters. Linear, power, logarithmic, exponential, and square root polynomial models were tested for best fit. Results: Data of 2,030 subjects were collected from 16 institutions. Separate calculation models for each sex were developed because the impact of demographic variables on the diameter of coronary arteries differs according to sex. The final model was the polynomial formula with an exponential relationship between the diameter of coronary arteries and body surface area using the DuBois formula. Conclusion A new coronary artery diameter Z score model was developed and is anticipated to be applicable in clinical practice. The new model will help establish a consensus-based Z score model.

Objective: : Chronic subdural hematomas (cSDHs) are generally known to result from traumatic tears of bridging veins. However, the causes of repeat spontaneous cSDHs are still unclear. We investigated the changes in vasculature in the human dura mater and outer membrane (OM) of cSDHs to elucidate the cause of their spontaneous repetition. Methods: : The dura mater was obtained from a normal control participant and a patient with repeat spontaneous cSDHs. The pathological samples from the patient included the dura mater and OM tightly adhered to the inner dura. The samples were analyzed with a particular focus on blood and lymphatic vessels by immunohistochemistry, 3-dimensional imaging using a transparent tissue clearing technique, and electron microscopy. Results: : The dural border cell (DBC) layer of the dura mater and OM were histologically indistinguishable. There were 5.9 times more blood vessels per unit volume of tissue in the DBC layer and OM in the patient than in the normal control. The DBC layer and OM contained pathological sinusoidal capillaries not observed in the normal tissue; these capillaries were connected to the middle meningeal arteries via penetrating arteries. In addition, marked lymphangiogenesis in the periosteal and meningeal layers was observed in the patient with cSDHs. Conclusion : Neovascularization in the OM seemed to originate from the DBC layer; this is a potential cause of repeat spontaneous cSDHs. Embolization of the meningeal arteries to interrupt the blood supply to pathological capillaries via penetrating arteries may be an effective treatment option.

Background: The optimal duration and net clinical benefit of dual antiplatelet therapy (DAPT) after transcatheter aortic valve replacement (TAVR) have not been elucidated in realworld situations. Methods: Using nationwide claims data from 2013 to 2021, we selected patients who underwent TAVR and categorized them into two groups: short- and long-term (≤ 3 and > 3 months, respectively) DAPT group. Propensity score matching was used to balance baseline characteristics. The primary endpoint was the occurrence of net adverse clinical events (NACEs), including all-cause death, myocardial infarction, stroke, any coronary and peripheral revascularization, systemic thromboembolism, and bleeding events, at 1 year. Survival analyses were conducted using Kaplan-Meier estimation and Cox proportional hazards regression. Results: Patients who met the inclusion criteria (1,695) were selected. Propensity score matching yielded 1,215 pairs of patients: 416 and 799 in the short- and long-term DAPT groups, respectively. In the unmatched cohort, the mean ages were 79.8 ± 6.1 and 79.7 ± 5.8 years for the short- and long-term DAPT groups, respectively. In the matched cohort, the mean ages were 80.6 ± 5.9 and 79.9 ± 5.9 years for the short- and long-term DAPT groups, respectively. Over one year in the unmatched cohort, the NACE incidence was 11.9% and 11.5% in the short- and long-term DAPT groups, respectively (P = 0.893). The all-cause mortality rates were 7.4% and 4.7% (P = 0.042), composite ischemic event rates were 2.5% and 4.7% (P = 0.056), and bleeding event rates were 2.7% and 4.7% (P = 0.056) in the shortand long-term groups, respectively. In the matched cohort, the incidence of NACE was 9.6% in the short-term DAPT group and 11.6% in the long-term DAPT group, respectively (P = 0.329).The all-cause mortality rates were 6.5% and 4.9% (P = 0.298), composite ischemic event rates were 1.4% and 4.5% (P = 0.009), and bleeding event rates were 2.2% and 4.4% (P = 0.072) in the short- and long-term groups, respectively. Conclusion In patients who successfully underwent transfemoral TAVR, the short- and longterm DAPT groups exhibited similar one-year NACE rates. However, patients in the long-term DAPT group experienced more bleeding and ischemic events.

Background: Sacubitril-valsartan reduces the risk of cardiovascular mortality among patients with heart failure with reduced ejection fraction (HFrEF). However, its long-term protective effects on cardiac function with concurrent acute kidney injury (AKI) remain unclear. This study investigated the recovery of cardiac function relative to kidney function decline. Methods: A total of 512 patients with HFrEF who started sacubitril-valsartan or valsartan treatment were enrolled in cohort 1. Additionally, patients who experienced AKI and underwent follow-up transthoracic echocardiography were enrolled in cohort 2. In cohort 1, short- and long-term kidney outcomes were analyzed. For cohort 2, changes in cardiac function in relation to changes in kidney function after drug initiation were analyzed. Results: The mean age of the patients was 68.3 ± 15.1 years, and 57.4% of the patients were male. AKI occurred in 15.9% of the sacubitril-valsartan group and 12.5% of the valsartan group. After AKI, 78.4% of patients in the sacubitril-valsartan group and 71.4% of those in the valsartan group underwent recovery. Furthermore, cardiovascular outcomes in patients who developed AKI after drug initiation were analyzed in cohort 2. The sacubitril-valsartan group showed a greater improvement in cardiac function compared with the valsartan group (12.4% ± 15.4% vs. 1.4% ± 5.7%, p = 0.046). The ratio of deltas of cardiac and kidney function in the sacubitril-valsartan and valsartan groups were –1.76 ± 2.58 and –0.20 ± 0.58, respectively (p = 0.03). Conclusion Patients with HFrEF treated with sacubitril-valsartan exhibited significant improvements in cardiovascular outcomes despite AKI.