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.

Vertebral arteriovenous fistula (VAVF) is a rare lesion characterized by an abnormal connection between the extracranial vertebral artery and the surrounding venous plexus. It typically arises due to penetrating injury, although it can occasionally result from blunt trauma. Brachial plexus injury (BPI) is also infrequently associated with VAVF. We present a rare case of VAVF caused by blunt trauma, which resulted in BPI. The patient, who had previously sustained a C2 fracture and C2–3 myelopathy from a bicycle accident, presented with new-onset weakness in the right upper extremity. His previous clinical history led to an initial suspicion of either an exacerbation of a pre-existing lesion or a shoulder injury. However, electromyography indicated that the weakness was due to BPI. Further evaluations later revealed VAVF to be the primary cause of the BPI. VAVF must be recognized as a rare potential reason for BPI, as timely intervention is essential for improving patient recovery and prognosis.

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: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.

Background: Carbapenem resistance in Pseudomonas aeruginosa is a serious global health problem. We investigated the clonal distribution and its association with the carbapenem resistance mechanisms of carbapenem-non-susceptible P. aeruginosa isolates from three Korean hospitals. Methods: A total of 155 carbapenem-non-susceptible P. aeruginosa isolates collected between 2011 and 2019 were analyzed for sequence types (STs), antimicrobial susceptibility, and carbapenem resistance mechanisms, including carbapenemase production, the presence of resistance genes, OprD mutations, and the hyperproduction of AmpC β-lactamase. Results: Sixty STs were identified in carbapenem-non-susceptible P. aeruginosa isolates.Two high-risk clones, ST235 (N = 41) and ST111 (N = 20), were predominant; however, sporadic STs were more prevalent than high-risk clones. The resistance rate to amikacin was the lowest (49.7%), whereas that to piperacillin was the highest (92.3%). Of the 155 carbapenem-non-susceptible isolates, 43 (27.7%) produced carbapenemases. Three metalloβ-lactamase (MBL) genes, blaIMP-6 (N = 38), blaVIM-2 (N = 3), and blaNDM-1 (N = 2), were detected. blaIMP-6 was detected in clonal complex 235 isolates. Two ST773 isolates carried blaNDM-1 and rmtB. Frameshift mutations in oprD were identified in all isolates tested, regardless of the presence of MBL genes. Hyperproduction of AmpC was detected in MBL gene–negative isolates. Conclusions Frameshift mutations in oprD combined with MBL production or hyperproduction of AmpC are responsible for carbapenem resistance in P. aeruginosa. Further attention is required to curb the emergence and spread of new carbapenem-resistant P. aeruginosa clones.