Treatment of a Sequential Giant Fusiform Aneurysm of the Basilar Trunk

We report an exceptional case of a de novo giant fusiform aneurysm of the basilar trunk, which developed shortly after the therapeutic occlusion of the right internal carotid artery for a fusiform carotid aneurysm. It would appear to be appropriate to call this entity a sequential giant fusiform aneurysm. The patient was successfully treated with endovascular occlusion of the giant basilar trunk aneurysm following bypass surgery

Strengthening deep-learning models for intracranial hemorrhage detection: strongly annotated computed tomography images and model ensembles

Background and purposeMultiple attempts at intracranial hemorrhage (ICH) detection using deep-learning techniques have been plagued by clinical failures. We aimed to compare the performance of a deep-learning algorithm for ICH detection trained on strongly and weakly annotated datasets, and to assess whether a weighted ensemble model that integrates separate models trained using datasets with different ICH improves performance.MethodsWe used brain CT scans from the Radiological Society of North America (27,861 CT scans, 3,528 ICHs) and AI-Hub (53,045 CT scans, 7,013 ICHs) for training. DenseNet121, InceptionResNetV2, MobileNetV2, and VGG19 were trained on strongly and weakly annotated datasets and compared using independent external test datasets. We then developed a weighted ensemble model combining separate models trained on all ICH, subdural hemorrhage (SDH), subarachnoid hemorrhage (SAH), and small-lesion ICH cases. The final weighted ensemble model was compared to four well-known deep-learning models. After external testing, six neurologists reviewed 91 ICH cases difficult for AI and humans.ResultsInceptionResNetV2, MobileNetV2, and VGG19 models outperformed when trained on strongly annotated datasets. A weighted ensemble model combining models trained on SDH, SAH, and small-lesion ICH had a higher AUC, compared with a model trained on all ICH cases only. This model outperformed four deep-learning models (AUC [95% C.I.]: Ensemble model, 0.953[0.938–0.965]; InceptionResNetV2, 0.852[0.828–0.873]; DenseNet121, 0.875[0.852–0.895]; VGG19, 0.796[0.770–0.821]; MobileNetV2, 0.650[0.620–0.680]; p < 0.0001). In addition, the case review showed that a better understanding and management of difficult cases may facilitate clinical use of ICH detection algorithms.ConclusionWe propose a weighted ensemble model for ICH detection, trained on large-scale, strongly annotated CT scans, as no model can capture all aspects of complex tasks

Risk of Incident Dementia According to Metabolic Health and Obesity Status in Late Life: A Population-Based Cohort Study.

CONTEXT: The risk for dementia among subjects who are obese with normal metabolic profiles, or called metabolically healthy obese (MHO), remains uninvestigated. OBJECTIVE: To determine the association between late-life metabolic health and obesity status and risk of incident dementia. DESIGN: Retrospective cohort study. SETTING: The National Health Insurance System, Republic of Korea. PATIENTS: A total of 12,296,863 adults >50 years old who underwent health examinations from 2009 to 2012 without baseline history of dementia. MAIN OUTCOME MEASURE: Incident overall dementia, Alzheimer's disease (AD), and vascular dementia (VaD). RESULTS: Among subjects ≥60 years old, 363,932 (6.4%) developed dementia during a median follow-up of 65 months (interquartile range 51 to 74 months). The MHO group showed the lowest incidence of overall dementia [hazard ratio (HR) 0.85; 95% CI, 0.84 to 0.86] and AD (HR 0.87; 95% CI, 0.86 to 0.88), but not VaD, compared with the metabolically healthy nonobese group. All components of metabolic syndrome except obesity significantly elevated the risk of dementia, and these associations were more pronounced in VaD. In particular, being underweight dramatically increased the risk of dementia. CONCLUSIONS: The MHO phenotype in late life demonstrated lower risk of overall dementia and AD but not VaD. Additional studies in other populations are warranted to elucidate current results and may predict individuals most at risk for developing dementia

Osimertinib in Patients with T790M-Positive Advanced Non-small Cell Lung Cancer: Korean Subgroup Analysis from Phase II Studies

Purpose Osimertinib is a third-generation, irreversible, oral epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) that potently and selectively inhibits both EGFR sensitizing mutation and EGFR T790M and has demonstrated efficacy in non-small cell lung cancer (NSCLC) central nervous system (CNS) metastases. We present results of a subgroup analysis of Korean patients from the pooled data of two global phase II trials: AURA extension (NCT01802632) and AURA2 (NCT02094261). Materials and Methods Enrolled patients had EGFR T790M-positive NSCLC and disease progression during or after EGFR-TKI therapy. Patients received osimertinib 80 mg orally once daily until disease progression. The primary endpoint was objective response rate (ORR). Results In total, 66 Korean patients received osimertinib treatment with a median treatment duration of 19 months. In the evaluable-for-response population (n=62), ORR was 74% (95% confidence interval [CI], 61.5 to 84.5) and median duration of response was 9.8 months (95% CI, 7.1 to 16.8). In the full analysis set (n=66), median progression-free survival was 10.9 months (95% CI, 8.3 to 15.0; data cutoff November 1, 2016), and median overall survival was 29.2 months (95% CI, 24.8 to 35.7; data cutoff May 1, 2018). Eight patients with CNS metastases were evaluable for response, none of whom showed CNS progression. The most common adverse events were rash (53%), cough (33%), paronychia, diarrhea, and decreased appetite (each 32%). Conclusion Efficacy and safety profiles of osimertinib in this subgroup are consistent with the global phase II pooled population, which supports osimertinib as a recommended treatment for Korean patients with T790M positive NSCLC.

In vitro antioxidant and anti-adipogenic effects of slendesta, standard potato extracts containing 5% protease inhibitor II

Background: The objective of the present study is to observe the anti-adipogenic effects of Slendesta (SLD), a standard potato protein extracts containing 5% potato protease inhibitor II (PI2) on the 3T3-L1 preadipocytes which are able to differentiate into mature adipocytes and accumulate lipids, as an obesity model with cytotoxicity and antioxidant effects.Materials and Methods: The cytotoxicity of SLD was observed against 3T3-L1 preadipocyte cell line by MTT assay, and also antiadipogenic effects were observed through lipid accumulation assay during 3T3-L1 differentiation as comparing with N-Acetyl-Lcysteine (NAC). In addition, antioxidant effects of SLD were detected by free radical scavenging capacity and superoxide dismutase (SOD)-like activity as comparing with ascorbic acid.Results: The SLD showed obvious cytotoxicity against 3T3-L1 pre-adipocyte cell line at higher concentrations, from 1.5 mg/ml for 72 h treatment, and the cytotoxic IC50 of SLD after 24, 48 and 72 h treatment times were detected as 10.11 ± 0.67, 5.71 ± 0.37 and 5.34 ± 0.21 mg/ml, respectively. The SLD also concentration-dependently inhibited the lipid accumulations formatted during 3T3-L1 cell differentiations. The adipogenic specific genes including PPARγ, C/EBPα, C/EBPβ and leptin were found to be reduced in SLD and NAC-treated cells compared to control cells. Furthermore, the SLD effectively showed DPPH radical scavenging activity (IC50 = 161.98 ± 64.65 μg/ml) and SOD-like effects (IC50 = 284.54 ± 54.47 μg/ml), and the cellular ROS was significantly inhibited in the SLD-treated cells compared to control cells.Conclusion: The results suggest that SLD effectively inhibit the differentiations of 3T3-L1 preadipose cell probably through antioxidant activities and direct cytotoxicity in case of higher concentration, along with satiety effects mediated by increases of circulating cholecystokinin. These findings are considered as direct evidences that SLD may serve as a predictable functional ingredient for obesity as an alternative therapy.Key words: Slendesta, potato protease inhibitor II, 3T3-L1 cell, cytotoxicity, anti-adipogenic effects, antioxidant effects