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: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Purpose: We investigated the clinical features, current negative-pressure wound therapy (NPWT) management strategies, and outcomes of pelvic-perineal soft tissue infection after open pelvic fractures. Materials and Methods: We analyzed the data of patients admitted to our trauma center with pelvic-perineal soft tissue after open pelvic fractures over a 7-year period. We investigated the injury severity score (ISS), medical costs, number of NPWTs, time required to reach definite wound coverage, complications, fracture classifications, transfusion requirements, interventions, length of stay (LOS) in hospital and intensive care unit (ICU), and prognosis. Results: Twenty patients with open pelvic fractures were treated with NPWT, and one patient who underwent NPWT died of pelvic sepsis during ICU treatment. The median LOS in hospital and medical costs were 98 [56–164] days and 106400 [65600–171100] USD, respectively. Patients treated with instillation NPWT (iNPWT, n=10) had a shorter NPWT duration (24 [13–39] vs. 46 [42–91] days, p=0.023), time to definite wound coverage (30 [21–43] vs. 49 [42–93] days, p=0.026), and hospital LOS (56 [43–72] vs. 158 [101–192] days, p=0.001), as well as lower medical costs (67800 [42500–102500] vs. 144200 [110400–236000] USD, p=0.009) compared to those treated with conventional NPWT. Conclusion NPWT is a feasible method for treating pelvic soft tissue infections in patients with open pelvic fractures. iNPWT can reduce the duration of NPWT, hospital LOS, and medical costs.

Fournier gangrene (FG) is a rare life-threatening infection j that can occasionally extend beyond the perineum into the retroperitoneal space. Preperitoneal involvement in female patients is extremely rare. We report a unique case of a 59-year-old female with FG, characterized by atypical preperitoneal extension. Despite initial treatment failure, the patient recovered following emergency debridement, and targeted antibiotic therapy. This case underscores the importance of early diagnosis, timely surgical intervention, and multidisciplinary care in managing atypical FG presentations in female patients. It emphasizes the need for prompt and aggressive management to improve survival in these rare instances.

Purpose: Some studies suggest that TP53 mutations are associated with the response to immune checkpoint inhibitors (ICI) in patients with non–small cell lung cancer (NSCLC) and also contribute to sex disparities in several cancers. Thus, we hypothesized that TP53 mutations might serve as sex-dependent genomic biomarkers of ICI treatment response in patients with NSCLC. Materials and Methods: Clinical data of 100 patients with metastatic NSCLC treated with ICI monotherapy at Seoul National University Bundang Hospital (SNUBH) were retrospectively reviewed. Genomic and clinical datasets of The Cancer Genome Atlas and an ICI-treated lung cancer cohort (cBioPortal) were also analyzed. Results: In SNUBH cohort, no statistically significant difference was observed in the median progression-free survival (PFS) according to TP53 mutation status (p=0.930); however, female patients with TP53 mutations (MT) had a significantly prolonged median PFS compared to wild-type (WT) (6.1 months in TP53 MT vs. 2.6 months in TP53 WT; p=0.021). Programmed death-ligand 1 (PD-L1) high (≥ 50%) expression was significantly enriched in female patients with TP53 MT (p=0.005). The analysis from publicly available dataset also revealed that females with NSCLC with TP53 MT showed significantly longer PFS than those with TP53 WT (p < 0.001). In The Cancer Genome Atlas analysis, expression of immune-related genes, and tumor mutation burden score in TP53 MT females were higher than in males without TP53 MT. Conclusion Female patients with NSCLC with TP53 mutations had high PD-L1 expression and showed favorable clinical outcomes following ICI therapy, suggesting a need for further research to explore the role of TP53 mutations for sex disparities in response to ICI therapy.

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: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Purpose: We investigated the clinical features, current negative-pressure wound therapy (NPWT) management strategies, and outcomes of pelvic-perineal soft tissue infection after open pelvic fractures. Materials and Methods: We analyzed the data of patients admitted to our trauma center with pelvic-perineal soft tissue after open pelvic fractures over a 7-year period. We investigated the injury severity score (ISS), medical costs, number of NPWTs, time required to reach definite wound coverage, complications, fracture classifications, transfusion requirements, interventions, length of stay (LOS) in hospital and intensive care unit (ICU), and prognosis. Results: Twenty patients with open pelvic fractures were treated with NPWT, and one patient who underwent NPWT died of pelvic sepsis during ICU treatment. The median LOS in hospital and medical costs were 98 [56–164] days and 106400 [65600–171100] USD, respectively. Patients treated with instillation NPWT (iNPWT, n=10) had a shorter NPWT duration (24 [13–39] vs. 46 [42–91] days, p=0.023), time to definite wound coverage (30 [21–43] vs. 49 [42–93] days, p=0.026), and hospital LOS (56 [43–72] vs. 158 [101–192] days, p=0.001), as well as lower medical costs (67800 [42500–102500] vs. 144200 [110400–236000] USD, p=0.009) compared to those treated with conventional NPWT. Conclusion NPWT is a feasible method for treating pelvic soft tissue infections in patients with open pelvic fractures. iNPWT can reduce the duration of NPWT, hospital LOS, and medical costs.

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.