Purpose: This study evaluated the educational impact of an artificial intelligence (AI)–based decision support system for breast ultrasonography (US) on medical professionals not specialized in breast imaging. Methods: In this multi-case, multi-reader study, educational materials, including American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors, were provided alongside corresponding AI results during training. The AI system presented results in the form of AIheatmaps, AI scores, and AI-provided BI-RADS assessment categories. Forty-two readers evaluated the test set in three sessions: the first session (S1) occurred before the educational intervention, the second session (S2) followed education without AI assistance, and the third session (S3) took place after education with AI assistance. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and overall performance, were compared between the sessions. Results: The mean sensitivity increased from 66.5% (95% confidence interval [CI], 59.2% to 73.7%) to 88.7% (95% CI, 84.1% to 93.3%), with a statistically significant difference (P<0.001), and the AUC non-significantly increased from 0.664 (95% CI, 0.606 to 0.723) to 0.684 (95% CI, 0.620 to 0.748) (P=0.300). Both measures were higher in S2 than in S1. The AI-achieved AUC was comparable to that of the expert reader (0.747 [95% CI, 0.640 to 0.855] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.217). Additionally, with AI assistance, the mean AUC for inexperienced readers was not significantly different from that of the expert reader (0.745 [95% CI, 0.660 to 0.830] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.120). Conclusion The mean AUC and sensitivity improved after incorporating AI into breast US education and interpretation. AI systems with high-level performance for breast US can potentially be used as educational tools in the interpretation of breast US images.

Background: Studies on predictive markers of insulin resistance (IR) and elevated liver transaminases in children and adolescents are limited. We evaluated the predictive capabilities of the single-point insulin sensitivity estimator (SPISE) index, metabolic score for insulin resistance (METS-IR), homeostasis model assessment of insulin resistance (HOMA-IR), the triglyceride (TG)/ high-density lipoprotein cholesterol (HDL-C) ratio, and the triglyceride-glucose index (TyG) for IR and alanine aminotransferase (ALT) elevation in this population. Methods: Data from 1,593 participants aged 10 to 18 years were analyzed using a nationwide survey. Logistic regression analysis was performed with IR and ALT elevation as dependent variables. Receiver operating characteristic (ROC) curves were generated to assess predictive capability. Proportions of IR and ALT elevation were compared after dividing participants based on parameter cutoff points. Results: All parameters were significantly associated with IR and ALT elevation, even after adjusting for age and sex, and predicted IR and ALT elevation in ROC curves (all P<0.001). The areas under the ROC curve of SPISE and METS-IR were higher than those of TyG and TG/HDL-C for predicting IR and were higher than those of HOMA-IR, TyG, and TG/HDL-C for predicting ALT elevation. The proportions of individuals with IR and ALT elevation were higher among those with METS-IR, TyG, and TG/ HDL-C values higher than the cutoff points, whereas they were lower among those with SPISE higher than the cutoff point. Conclusion SPISE and METS-IR are superior to TG/HDL-C and TyG in predicting IR and ALT elevation. Thus, this study identified valuable predictive markers for young individuals.

Background: Sclerostin, initially recognized for its pivotal role in bone metabolism, has gained attention for its multifaceted impact on overall human health. However, its influence on frailty—a condition that best reflects biological age—has not been thoroughly investigated. Methods: We collected blood samples from 244 older adults who underwent comprehensive geriatric assessments. Sclerostin levels were quantified using an enzyme-linked immunosorbent assay. Frailty was assessed using two validated approaches: the phenotypic model by Fried and the deficit accumulation frailty index (FI) by Rockwood. Results: After controlling for sex, age, and body mass index, we found that serum sclerostin levels were significantly elevated in frail individuals compared to their robust counterparts (P<0.001). There was a positive correlation between serum sclerostin concentrations and the FI (P<0.001). Each standard deviation increase in serum sclerostin was associated with an odds ratio of 1.87 for frailty (P=0.003). Moreover, participants in the highest quartile of sclerostin levels had a significantly higher FI and a 9.91-fold increased odds of frailty compared to those in the lowest quartile (P=0.003 and P=0.039, respectively). Conclusion These findings, which for the first time explore the association between circulating sclerostin levels and frailty, have significant clinical implications, positioning sclerostin as one of potential blood-based biomarkers for frailty that captures the comprehensive physical, mental, and social aspects of the elderly, extending beyond its traditional role in bone metabolism.

Background/Aims: To evaluate the associations between pediatric fatty liver severity, bioelectrical impedance analysis (BIA), and magnetic resonance imaging parameters, including total psoas muscle surface area (tPMSA) and paraspinal muscle fat (PMF). Methods: Children and adolescents who underwent BIA and liver magnetic resonance imaging between September 2022 and November 2023 were included. Linear regression analyses identified predictors of liver proton density fat fraction (PDFF) including BIA parameters, tPMSA, and PMF. Ordinal logistic regression analysis identified the association between these parameters and fatty liver grades. Pearson’s correlation coefficients were used to evaluate the relationships between tPMSA and muscle-related BIA parameters, and between PMF and fat-related BIA parameters. Results: Overall, 74 participants aged 8 to 16 years were included in the study. In the linear regression analyses, the percentage of body fat was positively associated with PDFF in all participants, whereas muscle-related BIA parameters were negatively associated with PDFF in participants with obesity. PMF and the PMF index were positively associated with PDFF in normalweight and overweight participants. In the ordinal logistic regression, percentage of body fat was positively associated with fatty liver grade in normal-weight and overweight participants and those with obesity, whereas muscle-related BIA parameters were negatively associated with fatty liver grade in participants with obesity. The PMF index was positively associated with fatty liver grade in normal/overweight participants. In the Pearson correlation analysis, muscle-related BIA parameters were correlated with tPMSA, and the fat-related BIA parameters were correlated with PMF. Conclusions BIA parameters and PMF are potential screening tools for assessing fatty liver in children.

Background: In vitro and animal studies have demonstrated that bone morphogenetic protein-7 (BMP-7), renowned for its osteogenic properties, also exerts beneficial effects on muscle metabolism by enhancing myogenesis and reversing muscle atrophy. Despite being proposed as a common regulatory factor for both muscle and bone, the impact of BMP-7 on human muscle health has not been thoroughly investigated. Methods: This cross-sectional study involved 182 community-dwelling older adults who underwent a comprehensive geriatric assessment in South Korea. Sarcopenia was diagnosed using Asian-specific cutoffs, and serum BMP-7 levels were quantified via enzyme immunoassay. Results: The mean age of the participants was 72.2±7.3 years, with 62.6% being female. After adjustments for confounders, serum BMP-7 levels were not significantly different between individuals with and without sarcopenia, nor were there differences based on skeletal muscle mass, strength, or physical performance levels (p=0.423 to 0.681). Likewise, no correlations were detected between circulating BMP-7 levels and any sarcopenia assessment metrics such as skeletal muscle index, grip strength, gait speed, or chair stand completion times (p=0.127 to 0.577). No significant associations were observed between increases in serum BMP-7 concentrations and the risk of sarcopenia or poor muscle phenotypes (p=0.431 to 0.712). Stratifying participants into quartiles based on serum BMP-7 levels also indicated no differences in sarcopenia-related parameters (p=0.663 to 0.996). Conclusion Despite experimental evidence supporting BMP-7’s role in muscle metabolism, this study found no significant association between serum BMP-7 levels and clinical indicators of muscle health in older adults. These findings challenge the utility of serum BMP-7 as a biomarker for sarcopenia in this demographic.

Purpose: We aimed to evaluate health-related quality of life (HRQoL) in intestinal failure (IF) patients after different modes of intestinal rehabilitation. Methods: HRQoL was assessed using the generic 36-item Short Form Survey (SF-36, ver. 2) and visual analogue scale (VAS) in 6 different areas: diet, sleep, gastrointestinal (GI) symptoms, diarrhea, musculoskeletal pain, and other symptoms. Results: Twenty-two patients completed the questionnaires, of which 7 had received intestinal transplant (ITx), 9 were continuing home total parenteral nutrition (HPN), and 6 had tapered off total parenteral nutrition (TPN). SF-36 physical component summary scores were highest in the ITx group (median, 65.6; interquartile range [IQR], 31.6–80.3) compared to the HPN (median, 48.4; IQR, 44.7–66.3) or tapered group (median, 54.2; IQR, 45.2–61.6). Mental component summary scores were lowest in the ITx group (median, 48.8; IQR, 37.1–63.6), compared to the TPN (median, 60.2; IQR, 41.6–78.5) or tapered group (median, 51.0; IQR, 48.8–56.0). Differences were not significant in all items of the SF-36. VAS scores showed that patients in the ITx group showed the best results in diet (0.9), gastrointestinal (GI) symptoms (1.4), and musculoskeletal pain (2.4). There was a significant difference in sleep (P = 0.036), with the ITx (1.43) and HPN groups (1.33) showing better outcomes compared with the tapered group (4.67). Patients in the tapered group showed the least favorable results in all performance areas, except GI symptoms. Conclusion SF-36 did not show a significant difference between the ITx, HPN, and tapered groups, but VAS showed a significant difference in sleep between groups. Further studies, including serial data, will allow a better understanding of the effects of different modes of intestinal rehabilitation.

Purpose: This study evaluated the educational impact of an artificial intelligence (AI)–based decision support system for breast ultrasonography (US) on medical professionals not specialized in breast imaging. Methods: In this multi-case, multi-reader study, educational materials, including American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors, were provided alongside corresponding AI results during training. The AI system presented results in the form of AIheatmaps, AI scores, and AI-provided BI-RADS assessment categories. Forty-two readers evaluated the test set in three sessions: the first session (S1) occurred before the educational intervention, the second session (S2) followed education without AI assistance, and the third session (S3) took place after education with AI assistance. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and overall performance, were compared between the sessions. Results: The mean sensitivity increased from 66.5% (95% confidence interval [CI], 59.2% to 73.7%) to 88.7% (95% CI, 84.1% to 93.3%), with a statistically significant difference (P<0.001), and the AUC non-significantly increased from 0.664 (95% CI, 0.606 to 0.723) to 0.684 (95% CI, 0.620 to 0.748) (P=0.300). Both measures were higher in S2 than in S1. The AI-achieved AUC was comparable to that of the expert reader (0.747 [95% CI, 0.640 to 0.855] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.217). Additionally, with AI assistance, the mean AUC for inexperienced readers was not significantly different from that of the expert reader (0.745 [95% CI, 0.660 to 0.830] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.120). Conclusion The mean AUC and sensitivity improved after incorporating AI into breast US education and interpretation. AI systems with high-level performance for breast US can potentially be used as educational tools in the interpretation of breast US images.

Purpose: This study evaluated the educational impact of an artificial intelligence (AI)–based decision support system for breast ultrasonography (US) on medical professionals not specialized in breast imaging. Methods: In this multi-case, multi-reader study, educational materials, including American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors, were provided alongside corresponding AI results during training. The AI system presented results in the form of AIheatmaps, AI scores, and AI-provided BI-RADS assessment categories. Forty-two readers evaluated the test set in three sessions: the first session (S1) occurred before the educational intervention, the second session (S2) followed education without AI assistance, and the third session (S3) took place after education with AI assistance. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and overall performance, were compared between the sessions. Results: The mean sensitivity increased from 66.5% (95% confidence interval [CI], 59.2% to 73.7%) to 88.7% (95% CI, 84.1% to 93.3%), with a statistically significant difference (P<0.001), and the AUC non-significantly increased from 0.664 (95% CI, 0.606 to 0.723) to 0.684 (95% CI, 0.620 to 0.748) (P=0.300). Both measures were higher in S2 than in S1. The AI-achieved AUC was comparable to that of the expert reader (0.747 [95% CI, 0.640 to 0.855] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.217). Additionally, with AI assistance, the mean AUC for inexperienced readers was not significantly different from that of the expert reader (0.745 [95% CI, 0.660 to 0.830] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.120). Conclusion The mean AUC and sensitivity improved after incorporating AI into breast US education and interpretation. AI systems with high-level performance for breast US can potentially be used as educational tools in the interpretation of breast US images.

Purpose: This study aimed to evaluate the outcomes and current status of reduced-port laparoscopic distal gastrectomy (RLDG) compared with multiport laparoscopic distal gastrectomy (MLDG) based on a 2019 nationwide survey of surgical gastric cancer treatments by the Korean Gastric Cancer Association (KGCA). Materials and Methods: The study was conducted retrospectively from March to December 2020 using data from the 2019 KGCA nationwide survey database. To compare RLDG and MLDG based on age, sex, body mass index, American Society of Anesthesiologists score, histological type, tumor invasion, and lymph node metastasis, propensity score matching was performed. Results: Of the 14,076 registered patients with gastric cancer, the five-port approach was the most favored for multiport gastrectomy, accounting for 6,396 (70.9%) cases, followed by the four-port approach, with 1,462 (16.2%) cases. The single-port approach was used in 303 (3.4%) cases, the two-port approach in 95 (1.1%) cases, and the three-port approach in 731 (8.1%) cases. RLDG was performed in 805 patients (6.4%), MLDG was conducted in 4,831 patients (34.3%), and 804 patients were 1:1 matched in each group. The average operation time was shorter in the RLDG (168.2±49.1 min vs. 179.5±61.5 min, P<0.001). No significant difference was found in blood loss (84.8±115.9 cc vs. 75.5±119.6 cc, P=0.152), overall complication rates (11.3% vs. 13.1%, P=0.254), or complications ≥ to grade IIIa (3.2% vs. 4.4%, P=0.240). Conclusions This study revealed that RLDG is a safe and effective surgical option for gastric cancer with the potential to offer shorter operation times without increasing the risk of complications.