Complications after 100 sessions of cone-beam computed tomography-guided lung radiofrequency ablation: a single-center, retrospective experience

Objective To evaluate complications after consecutive 100 sessions of cone-beam computed tomography (CBCT)-guided radiofrequency ablation (RFA) of lung tumors Materials and methods A retrospective study was conducted from January 2016 and October 2018. All procedures were performed using a CBCT virtual navigation guidance system, combining three-dimentional CBCT, needle planning software, and real-time fluoroscopy. Complications were evaluated for each RFA session in 63 consecutive patients (31 male, 32 female; mean age 58.0 years) with 121 lung tumors who underwent 100 sessions of CBCT-guided lung ablation with an internally cooled RFA system. Complications were recorded using the Common Terminology Criteria of Adverse Events (CTCAE) 5.0. A major complication was defined as a grade 3 or 4 adverse event. Results There was no postprocedural mortality. The major and minor complication rates were 5% and 28%, respectively. The major complications were significant pulmonary hemorrhage (1%), large hemothorax requiring drainage (1%), pneumonia treated with antibiotics (2%), and delayed bronchopleural fistula (1%). The minor complications were pneumothorax (15%), hemoptysis (11%), and subcutaneous emphysema (2%). Of the 15 pneumothoraces, percutaneous catheter drainage was required in six sessions. Pneumothorax was more likely to occur if RFA was performed on two or more tumors at one session. Immediate, periprocedural and delayed complications were 23%, 9%, and 1%, respectively. Conclusion CBCT-guided RFA of lung tumors is a relatively safe procedure with acceptable morbidity

Metabolic-Associated Fatty Liver Disease is Associated with Colorectal Adenomas in Young and Older Korean Adults

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The impact of insulin resistance on the association between metabolic syndrome and lung function: the Kangbuk Samsung Health Study

Abstract Background/Objective Metabolic syndrome (MS) is related to lung dysfunction. However, its impact according to insulin resistance (IR) remains unknown. Therefore, we evaluated whether the relation of MS with lung dysfunction differs by IR. Subject/Methods This cross-sectional study included 114,143 Korean adults (mean age, 39.6 years) with health examinations who were divided into three groups: metabolically healthy (MH), MS without IR, and MS with IR. MS was defined as presence of any MS component, including IR estimated by HOMA-IR ≥ 2.5. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for lung dysfunction were obtained in MS, MS without IR, and MS with IR groups compared with the MH (reference) group. Results The prevalence of MS was 50.7%. The percent predicted forced expiratory volume in 1 s (FEV1%) and forced vital capacity (FVC%) showed statistically significant differences between MS with IR and MH and between MS with IR and MS without IR (all P < 0.001). However, those measures did not vary between MH and MS without IR (P = 1.000 and P = 0.711, respectively). Compared to MH, MS was not at risk for FEV1% < 80% (1.103 (0.993–1.224), P = 0.067) or FVC% < 80% (1.011 (0.901–1.136), P = 0.849). However, MS with IR was clearly associated with FEV1% < 80% (1.374 (1.205–1.566) and FVC% < 80% (1.428 (1.237–1.647) (all p < 0.001), though there was no evident association for MS without IR (FEV1%: 1.078 (0.975–1.192, P = 0.142) and FVC%: 1.000 (0.896–1.116, p = 0.998)). Conclusion The association of MS with lung function can be affected by IR. However, longitudinal follow-up studies are required to validate our findings

Nutritional Status and Diet Style Affect Cognitive Function in Alcoholic Liver Disease

Malnutrition and cognitive dysfunction are typical features of alcoholic liver disease (ALD) and are correlated with the development of complications. The aim of this study is to explore the effect of nutritional state and diet on cognitive function in ALD. A total of 43 patients with compensated alcoholic cirrhosis were enrolled, and a neuropsychological test was assessed according to body mass index (BMI, &lt;22 and &ge;22). In the ALD animal study, mice were divided into five groups (n = 9/group; normal liquid, 5% EtOH + regular liquid, 5% EtOH + high-carbohydrate liquid, 5% EtOH + high-fat liquid, and 5% EtOH + high-protein liquid diet) and fed the same calories for eight weeks. To assess cognitive function, we performed T-maze studies weekly before/after alcohol binging. In cognitive function (BMI &lt; 22/&ge;22), language score of Korea mini-mental state (7.4 &plusmn; 1.4/7.9 &plusmn; 0.4), Boston naming (11.7 &plusmn; 2.7/13.0 &plusmn; 1.8), forward digit span (6.7 &plusmn; 1.8/7.5 &plusmn; 1.6), Korean color word stroop (24.2 &plusmn; 26.5/43.6 &plusmn; 32.4), and interference score (33.9 &plusmn; 31.9/52.3 &plusmn; 33.9) revealed significant differences. In the T-maze test, alcohol significantly delayed the time to reach food, and binge drinking provided a temporary recovery in cognition. The alcohol-induced delay was significantly reduced in the high-carbohydrate and high-fat diet groups. Synaptic function exhibited no changes in all groups. Cognitive dysfunction is affected by nutritional status and diet in ALD

Nutritional Status and Diet Style Affect Cognitive Function in Alcoholic Liver Disease

Malnutrition and cognitive dysfunction are typical features of alcoholic liver disease (ALD) and are correlated with the development of complications. The aim of this study is to explore the effect of nutritional state and diet on cognitive function in ALD. A total of 43 patients with compensated alcoholic cirrhosis were enrolled, and a neuropsychological test was assessed according to body mass index (BMI, n = 9/group; normal liquid, 5% EtOH + regular liquid, 5% EtOH + high-carbohydrate liquid, 5% EtOH + high-fat liquid, and 5% EtOH + high-protein liquid diet) and fed the same calories for eight weeks. To assess cognitive function, we performed T-maze studies weekly before/after alcohol binging. In cognitive function (BMI < 22/≥22), language score of Korea mini-mental state (7.4 ± 1.4/7.9 ± 0.4), Boston naming (11.7 ± 2.7/13.0 ± 1.8), forward digit span (6.7 ± 1.8/7.5 ± 1.6), Korean color word stroop (24.2 ± 26.5/43.6 ± 32.4), and interference score (33.9 ± 31.9/52.3 ± 33.9) revealed significant differences. In the T-maze test, alcohol significantly delayed the time to reach food, and binge drinking provided a temporary recovery in cognition. The alcohol-induced delay was significantly reduced in the high-carbohydrate and high-fat diet groups. Synaptic function exhibited no changes in all groups. Cognitive dysfunction is affected by nutritional status and diet in ALD

Screening mammography performance according to breast density: a comparison between radiologists versus standalone intelligence detection

Abstract Background Artificial intelligence (AI) algorithms for the independent assessment of screening mammograms have not been well established in a large screening cohort of Asian women. We compared the performance of screening digital mammography considering breast density, between radiologists and AI standalone detection among Korean women. Methods We retrospectively included 89,855 Korean women who underwent their initial screening digital mammography from 2009 to 2020. Breast cancer within 12 months of the screening mammography was the reference standard, according to the National Cancer Registry. Lunit software was used to determine the probability of malignancy scores, with a cutoff of 10% for breast cancer detection. The AI’s performance was compared with that of the final Breast Imaging Reporting and Data System category, as recorded by breast radiologists. Breast density was classified into four categories (A–D) based on the radiologist and AI-based assessments. The performance metrics (cancer detection rate [CDR], sensitivity, specificity, positive predictive value [PPV], recall rate, and area under the receiver operating characteristic curve [AUC]) were compared across breast density categories. Results Mean participant age was 43.5 ± 8.7 years; 143 breast cancer cases were identified within 12 months. The CDRs (1.1/1000 examination) and sensitivity values showed no significant differences between radiologist and AI-based results (69.9% [95% confidence interval [CI], 61.7–77.3] vs. 67.1% [95% CI, 58.8–74.8]). However, the AI algorithm showed better specificity (93.0% [95% CI, 92.9–93.2] vs. 77.6% [95% CI, 61.7–77.9]), PPV (1.5% [95% CI, 1.2–1.9] vs. 0.5% [95% CI, 0.4–0.6]), recall rate (7.1% [95% CI, 6.9–7.2] vs. 22.5% [95% CI, 22.2–22.7]), and AUC values (0.8 [95% CI, 0.76–0.84] vs. 0.74 [95% CI, 0.7–0.78]) (all P < 0.05). Radiologist and AI-based results showed the best performance in the non-dense category; the CDR and sensitivity were higher for radiologists in the heterogeneously dense category (P = 0.059). However, the specificity, PPV, and recall rate consistently favored AI-based results across all categories, including the extremely dense category. Conclusions AI-based software showed slightly lower sensitivity, although the difference was not statistically significant. However, it outperformed radiologists in recall rate, specificity, PPV, and AUC, with disparities most prominent in extremely dense breast tissue