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DongJoonKim,DongIkKim,Seung-KooLee,SiYeonKim 대한영상의학회 2003 Korean Journal of Radiology Vol.4 No.3
Objective: To evaluate the efficacy of endosaccular Guglielmi detachable coil (GDC) treatment of unruptured aneurysms causing cranial nerve (CN) symptoms. Materials and Methods: Among a database of 218 patients whose aneurysms were treated using GDC, seven patients met the criteria for unruptured aneurysms presenting with symptoms and signs of CN palsy. Changes in CN symptoms before and after GDC treatment were reviewed. Results: Aneurysms were located in the internal carotid-posterior communicating artery (n=3), the basilar bifurcation (n=1) and the cavernous internal carotid artery (n=3). CN symptoms included ptosis (n=6), mydriasis (n=2), and extraocular muscle (EOM) disorder (CN III: n=4; CN VI: n=3). Overall, improvement or resolution of CN symptoms after treatment was noted in five patients. CN symptoms in cases involving small ( 10 mm) and intradural aneurysms tended to respond better to GDC treatment. Ptosis was the initial symptom to show improvement, while EOM dysfunction responded least favourably. Conclusion: GDC coil packing appears to be an appropriate treatment method for the relief of CN symptoms associated with intracranial aneurysms.
LB30057 Inhibits Platelet Aggregation and Vascular Relaxation Induced by Thrombin
Byoung-InJung,Kyu-TaeKang,배옥남,Moo-YeolLee,Seung-MinChung,Sang-KooLee,In-ChulKim,Jin-HoChung 대한약학회 2002 Archives of Pharmacal Research Vol.25 No.6
Previous study showed that an amidrazonophenylalanine derivative, LB30057, which has high water solubility, inhibited the catalytic activity of thrombin potently by interaction with the active site of thrombin. In the current investigation, we examined whether LB30057 inhibited platelet aggregation and vascular relaxation induced by thrombin. Treatment with LB30057 to plateletrich plasma (PRP) isolated from human blood resulted in a concentration-dependent inhibition of thrombin-induced aggregation. Values for IC50 and IC100 were 54 ± 4 nM and 96 ± 3 nM, respectively. This inhibition was agonist (thrombin) specific, since IC50 values for collagen and ADP were much greater than those for thrombin. In addition, concentration-dependent inhibitory effects were observed on the serotonin secretion induced by thrombin in PRP. Consistent with these findings, thrombin-induced increase in cytosolic calcium levels was inhibited in a concentration-dependent manner. When LB30057 was treated with aortic rings isolated from rats, LB30057 resulted in a concentration-dependent inhibition of thrombin-induced vascular relaxation. All these results suggest that LB30057 is a potent inhibitor of platelet aggregation and blood vessel relaxation induced by thrombin.
박예원,Yoon Seong Choi,Sung Soo Ahn,Jong Hee Chang,SeHoonKim,Seung-KooLee 대한영상의학회 2019 Korean Journal of Radiology Vol.20 No.9
ObjectiveTo assess whether radiomics features derived from multiparametric MRI can predict the tumor grade of lower-grade gliomas (LGGs; World Health Organization grade II and grade III) and the nonenhancing LGG subgroup. Materials and MethodsTwo-hundred four patients with LGGs from our institutional cohort were allocated to training (n = 136) and test (n = 68) sets. Postcontrast T1-weighted images, T2-weighted images, and fluid-attenuated inversion recovery images were analyzed to extract 250 radiomics features. Various machine learning classifiers were trained using the radiomics features to predict the glioma grade. The trained classifiers were internally validated on the institutional test set and externally validated on a separate cohort (n = 99) from The Cancer Genome Atlas (TCGA). Classifier performance was assessed by determining the area under the curve (AUC) from receiver operating characteristic curve analysis. An identical process was performed in the nonenhancing LGG subgroup (institutional training set, n = 73; institutional test set, n = 37; and TCGA cohort, n = 37) to predict the glioma grade. ResultsThe performance of the best classifier was good in the internal validation set (AUC, 0.85) and fair in the external validation set (AUC, 0.72) to predict the LGG grade. For the nonenhancing LGG subgroup, the performance of the best classifier was good in the internal validation set (AUC, 0.82), but poor in the external validation set (AUC, 0.68). ConclusionRadiomics feature-based classifiers may be useful to predict LGG grades. However, radiomics classifiers may have a limited value when applied to the nonenhancing LGG subgroup in a TCGA cohort.