Background/Aims: To analyze the characteristics of the sputum microbiota of patients with nontuberculous mycobacteria pulmonary disease (NTM-PD) based on treatment status. Methods: Twenty-eight sputum samples from 14 patients with NTM-PD, including 14 samples from the microbiologically cured group (7 at baseline and 7 during follow-up) and 14 from the treatment-refractory group (7 at baseline and 7 during follow-up) were included in this study. Bacterial microbiota was analyzed by sequencing the V3–V4 region of the 16S rRNA gene. Results: Among the 14 patients, most had infections with Mycobacterium avium complex (n = 6), followed by Mycobacterium abscessus (n = 5); three patients exhibited mixed infection with both organisms. Alpha-diversity was higher in the cured group than in the treatment refractory group in both the baseline sputum (ACE, p = 0.005; Chao1, p = 0.010; Jackknife, p = 0.022, 0.043; Shannon, p = 0.048) and follow-up sputum (ACE, p = 0.018). Linear discriminant analysis effect size revealed that several taxa showed differential distributions based on treatment status. At the species level, Streptococcus pneumoniae, Prevotella melaninogenica, Haemophilus parahaemolyticus, Haemophilus haemolyticus, Fusobacterium nucleatum, Neisseria elongata, and Prevotella denticola were more abundant in sputum from the microbiologically cured group than in that from the refractory group (all p < 0.05). Conclusions In contrast to patients with treatment-refractory NTM-PD, those with stable disease without recurrence had higher microbial diversity in their sputum, including several predominant taxa.

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.

Background: This study compares ultrasound and surgical findings of anatomical variations in de Quervain’s disease. Methods: Seventy-four wrists from patients with unilateral de Quervain’s disease were examined through ultrasonography and surgery. Presence of intracompartment septum, abductor pollicis longus (APL) slips, and selective stenosis were verified by both methods. Two orthopedic surgeons assessed ultrasound findings for intra- and interobserver reliability. Results: Amongst 74 participants (43 women and 31 men), 60.8% had a complete septum, 31.1% had an incomplete septum, and 8.1% had no septum; 70.3% had multi-slip APL and 66.2% had extensor pollicis brevis stenosis. Surgical and ultrasonographic findings displayed a high level of sensitivity and specificity. Intraobserver reliability was high, and interobserver reliability was substantial. Conclusions The study confirms ultrasonography’s reliability in identifying anatomical variations in de Quervain’s disease, with high sensitivity, specificity, and substantial intra- and interobserver reliability, emphasizing its usefulness in preoperative assessment and planning.

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.

Background/Aims: To analyze the characteristics of the sputum microbiota of patients with nontuberculous mycobacteria pulmonary disease (NTM-PD) based on treatment status. Methods: Twenty-eight sputum samples from 14 patients with NTM-PD, including 14 samples from the microbiologically cured group (7 at baseline and 7 during follow-up) and 14 from the treatment-refractory group (7 at baseline and 7 during follow-up) were included in this study. Bacterial microbiota was analyzed by sequencing the V3–V4 region of the 16S rRNA gene. Results: Among the 14 patients, most had infections with Mycobacterium avium complex (n = 6), followed by Mycobacterium abscessus (n = 5); three patients exhibited mixed infection with both organisms. Alpha-diversity was higher in the cured group than in the treatment refractory group in both the baseline sputum (ACE, p = 0.005; Chao1, p = 0.010; Jackknife, p = 0.022, 0.043; Shannon, p = 0.048) and follow-up sputum (ACE, p = 0.018). Linear discriminant analysis effect size revealed that several taxa showed differential distributions based on treatment status. At the species level, Streptococcus pneumoniae, Prevotella melaninogenica, Haemophilus parahaemolyticus, Haemophilus haemolyticus, Fusobacterium nucleatum, Neisseria elongata, and Prevotella denticola were more abundant in sputum from the microbiologically cured group than in that from the refractory group (all p < 0.05). Conclusions In contrast to patients with treatment-refractory NTM-PD, those with stable disease without recurrence had higher microbial diversity in their sputum, including several predominant taxa.

Background: This study compares ultrasound and surgical findings of anatomical variations in de Quervain’s disease. Methods: Seventy-four wrists from patients with unilateral de Quervain’s disease were examined through ultrasonography and surgery. Presence of intracompartment septum, abductor pollicis longus (APL) slips, and selective stenosis were verified by both methods. Two orthopedic surgeons assessed ultrasound findings for intra- and interobserver reliability. Results: Amongst 74 participants (43 women and 31 men), 60.8% had a complete septum, 31.1% had an incomplete septum, and 8.1% had no septum; 70.3% had multi-slip APL and 66.2% had extensor pollicis brevis stenosis. Surgical and ultrasonographic findings displayed a high level of sensitivity and specificity. Intraobserver reliability was high, and interobserver reliability was substantial. Conclusions The study confirms ultrasonography’s reliability in identifying anatomical variations in de Quervain’s disease, with high sensitivity, specificity, and substantial intra- and interobserver reliability, emphasizing its usefulness in preoperative assessment and planning.

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.

Background/Aims: To analyze the characteristics of the sputum microbiota of patients with nontuberculous mycobacteria pulmonary disease (NTM-PD) based on treatment status. Methods: Twenty-eight sputum samples from 14 patients with NTM-PD, including 14 samples from the microbiologically cured group (7 at baseline and 7 during follow-up) and 14 from the treatment-refractory group (7 at baseline and 7 during follow-up) were included in this study. Bacterial microbiota was analyzed by sequencing the V3–V4 region of the 16S rRNA gene. Results: Among the 14 patients, most had infections with Mycobacterium avium complex (n = 6), followed by Mycobacterium abscessus (n = 5); three patients exhibited mixed infection with both organisms. Alpha-diversity was higher in the cured group than in the treatment refractory group in both the baseline sputum (ACE, p = 0.005; Chao1, p = 0.010; Jackknife, p = 0.022, 0.043; Shannon, p = 0.048) and follow-up sputum (ACE, p = 0.018). Linear discriminant analysis effect size revealed that several taxa showed differential distributions based on treatment status. At the species level, Streptococcus pneumoniae, Prevotella melaninogenica, Haemophilus parahaemolyticus, Haemophilus haemolyticus, Fusobacterium nucleatum, Neisseria elongata, and Prevotella denticola were more abundant in sputum from the microbiologically cured group than in that from the refractory group (all p < 0.05). Conclusions In contrast to patients with treatment-refractory NTM-PD, those with stable disease without recurrence had higher microbial diversity in their sputum, including several predominant taxa.