Irritable bowel syndrome (IBS) is a chronic, disabling, and functional bowel disorder that significantly affects social functioning and reduces quality of life and increases social costs. The Korean Society of Neurogastroenterology and Motility published clinical practice guidelines on the management of IBS based on a systematic review of the literature in 2017, and planned to revise these guidelines in light of new evidence on the pathophysiology, diagnosis, and management of IBS. The current revised version of the guidelines is consistent with the previous version and targets adults diagnosed with or suspected of having IBS. These guidelines were developed using a combination of de novo and adaptation methods, with analyses of existing guidelines and discussions within the committee, leading to the identification of key clinical questions. Finally, the guidelines consisted of 22 recommendations, including 3 concerning the definition and risk factors of IBS, 4 regarding diagnostic modalities and strategies, 2 regarding general management, and 13 regarding medical treatment. For each statement, the advantages, disadvantages, and precautions were thoroughly detailed. The modified Delphi method was used to achieve expert consensus to adopt the core recommendations of the guidelines. These guidelines serve as a reference for clinicians (including primary care physicians, general healthcare providers, medical students, residents, and other healthcare professionals) and patients, helping them to make informed decisions regarding IBS management.

Frailty is a condition marked by a progressive decline in physiological functioning due to aging, leading to increased disease morbidity and rising healthcare costs. Therefore, it is important to prevent frailty through proper management. Not only does a lack of physical activity contribute to frailty, but inadequate dietary intake, resulting from decreased appetite and malabsorption, is also a significant risk factor. This study aimed to develop a 16-week algorithm to assess the nutritional risks associated with frailty, provide personalized nutritional solutions, and manage frailty risk factors through continuous monitoring and periodic reassessment. A total of 20 indicators were selected to create a nutritional health score. The selected indicators encompassed nutritional risk factors for frailty, disease history, and hematological factors. Reassessments were designed to occur at four-week intervals to revise personalized management goals and adjust solutions. Metrics were prioritized to provide a personalized solution. A user-friendly monitoring system was developed that leveraged voice recognition technology to determine compliance. It is anticipated that the algorithm will serve several purposes. First, this outcome will allow us to help prevent and delay the onset of frailty by utilizing a mobile app. Second, it will reduce the time and economic costs associated with nutritional management. Finally, it will facilitate future professional counseling and monitoring.

Irritable bowel syndrome (IBS) is a chronic, disabling, and functional bowel disorder that significantly affects social functioning and reduces quality of life and increases social costs. The Korean Society of Neurogastroenterology and Motility published clinical practice guidelines on the management of IBS based on a systematic review of the literature in 2017, and planned to revise these guidelines in light of new evidence on the pathophysiology, diagnosis, and management of IBS. The current revised version of the guidelines is consistent with the previous version and targets adults diagnosed with or suspected of having IBS. These guidelines were developed using a combination of de novo and adaptation methods, with analyses of existing guidelines and discussions within the committee, leading to the identification of key clinical questions. Finally, the guidelines consisted of 22 recommendations, including 3 concerning the definition and risk factors of IBS, 4 regarding diagnostic modalities and strategies, 2 regarding general management, and 13 regarding medical treatment. For each statement, the advantages, disadvantages, and precautions were thoroughly detailed. The modified Delphi method was used to achieve expert consensus to adopt the core recommendations of the guidelines. These guidelines serve as a reference for clinicians (including primary care physicians, general healthcare providers, medical students, residents, and other healthcare professionals) and patients, helping them to make informed decisions regarding IBS management.

Frailty is a condition marked by a progressive decline in physiological functioning due to aging, leading to increased disease morbidity and rising healthcare costs. Therefore, it is important to prevent frailty through proper management. Not only does a lack of physical activity contribute to frailty, but inadequate dietary intake, resulting from decreased appetite and malabsorption, is also a significant risk factor. This study aimed to develop a 16-week algorithm to assess the nutritional risks associated with frailty, provide personalized nutritional solutions, and manage frailty risk factors through continuous monitoring and periodic reassessment. A total of 20 indicators were selected to create a nutritional health score. The selected indicators encompassed nutritional risk factors for frailty, disease history, and hematological factors. Reassessments were designed to occur at four-week intervals to revise personalized management goals and adjust solutions. Metrics were prioritized to provide a personalized solution. A user-friendly monitoring system was developed that leveraged voice recognition technology to determine compliance. It is anticipated that the algorithm will serve several purposes. First, this outcome will allow us to help prevent and delay the onset of frailty by utilizing a mobile app. Second, it will reduce the time and economic costs associated with nutritional management. Finally, it will facilitate future professional counseling and monitoring.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Irritable bowel syndrome (IBS) is a chronic, disabling, and functional bowel disorder that significantly affects social functioning and reduces quality of life and increases social costs. The Korean Society of Neurogastroenterology and Motility published clinical practice guidelines on the management of IBS based on a systematic review of the literature in 2017, and planned to revise these guidelines in light of new evidence on the pathophysiology, diagnosis, and management of IBS. The current revised version of the guidelines is consistent with the previous version and targets adults diagnosed with or suspected of having IBS. These guidelines were developed using a combination of de novo and adaptation methods, with analyses of existing guidelines and discussions within the committee, leading to the identification of key clinical questions. Finally, the guidelines consisted of 22 recommendations, including 3 concerning the definition and risk factors of IBS, 4 regarding diagnostic modalities and strategies, 2 regarding general management, and 13 regarding medical treatment. For each statement, the advantages, disadvantages, and precautions were thoroughly detailed. The modified Delphi method was used to achieve expert consensus to adopt the core recommendations of the guidelines. These guidelines serve as a reference for clinicians (including primary care physicians, general healthcare providers, medical students, residents, and other healthcare professionals) and patients, helping them to make informed decisions regarding IBS management.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Frailty is a condition marked by a progressive decline in physiological functioning due to aging, leading to increased disease morbidity and rising healthcare costs. Therefore, it is important to prevent frailty through proper management. Not only does a lack of physical activity contribute to frailty, but inadequate dietary intake, resulting from decreased appetite and malabsorption, is also a significant risk factor. This study aimed to develop a 16-week algorithm to assess the nutritional risks associated with frailty, provide personalized nutritional solutions, and manage frailty risk factors through continuous monitoring and periodic reassessment. A total of 20 indicators were selected to create a nutritional health score. The selected indicators encompassed nutritional risk factors for frailty, disease history, and hematological factors. Reassessments were designed to occur at four-week intervals to revise personalized management goals and adjust solutions. Metrics were prioritized to provide a personalized solution. A user-friendly monitoring system was developed that leveraged voice recognition technology to determine compliance. It is anticipated that the algorithm will serve several purposes. First, this outcome will allow us to help prevent and delay the onset of frailty by utilizing a mobile app. Second, it will reduce the time and economic costs associated with nutritional management. Finally, it will facilitate future professional counseling and monitoring.