http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
간섬유화의 비침습적 진단: transient elastography (FibroScan(R))
김승업 대한간학회 2011 Clinical and Molecular Hepatology(대한간학회지) Vol.17 No.1(S)
Transient elastography (TE, FibroScan(R)) is a novel non-invasive method that has been proposed for the assessment of liver fibrosis in patients with chronic liver diseases, by measuring liver stiffness. TE is a rapid and user-friendly technique that can be easily performed at the bedside or in the outpatient clinic with immediate results and good reproducibility. Combining TE with serum markers increases diagnostic accuracy and as a result, liver biopsy could be avoided for initial assessment in some patients with chronic liver disease. As TE has excellent patient acceptance it could be useful for monitoring fibrosis progression and regression in the individual case, but more data are awaited for this application. Guidelines are needed for the use of TE in clinical practice.
간경변증과 문맥압항진증의 영상진단 : 초음파를 이용한 간탄력도 검사
김승업 대한간학회 2013 간학회 싱글토픽 심포지움 Vol.2013 No.1
Although liver biopsy is the best method for assessing liver fibrosis, it is an invasive procedure, with rare, but potentially life-threatening, complications. Thus, attempts to develop non-invasive methods have led to the use of transient elastography (FibroScan®; EchoSens, Paris, France) and acoustic radiation force impulse (ARFI) elastography (Acuson S2000; Siemens, Mountain View, USA) for assessment of liver fibrosis. Transient elastography is a novel non-invasive method that has been proposed for the assessment of liver fibrosis in patients with chronic liver diseases, by measuring liver stiffness. Transient elastography is a rapid and user-friendly technique that can be easily performed at the bedside or in the outpatient clinic with immediate results and good reproducibility Combining transient elastography with serum markers increases diagnostic accuracy and as a result, liver biopsy could be avoided.for initial assessment in some patients with chronic liver disease. As transient elastography has excellent patient acceptance, it could be useful for monitoring fibrosis progression and regression in the individual case, but more data are awaited for this application. Recently, ARFI elastography, which uses radiation forced impulses to measure liver stiffness while using B-mode ultrasonography, has been introduced. Transient elastography has a fixed region of interest (ROI) at a fixed insertion depth, whereas ARFI enables elastography inside a flexible ROI of lxo.6 em diameter at variable insertion depths. Therefore, liver stiffness measurement (LSM) in patients with ascites and obesity is feasible. Furthermore, ARFI elastography has the advantage that it enables LSM during a routine ultrasonographic evaluation of the abdomen. Based on the cumulated knowledge, guidelines are being awaited for the use of transient elastography and ARFI elastography in clinical practice.
Serum Dickkopf-1 as a Biomarker for the Diagnosis of Hepatocellular Carcinoma
김승업,박전한,한광협,김현숙,이재면,이현규,김혜미,최성훈,백신화,김범경,박준용,김도영,안상훈,이종두 연세대학교의과대학 2015 Yonsei medical journal Vol.56 No.5
Purpose: Dickkopf-1 (DKK-1) is a Wnt/β-catenin signaling pathway inhibitor. We investigated whether DKK-1 is related to progressionin hepatocellular carcinoma (HCC) cells and HCC patients. Materials and Methods: In vitro reverse-transcription polymerase chain reaction (RT-PCR), wound healing assays, invasion assays,and ELISAs of patient serum samples were employed. The diagnostic accuracy of the serum DKK-1 ELISA was assessed usingreceiver operating characteristic (ROC) curves and area under ROC (AUC) analyses. Results: RT-PCR showed high DKK-1 expression in Hep3B and low in 293 cells. Similarly, the secreted DKK-1 concentration in the culture media was high in Hep3B and low in 293 cells. Wound healing and invasion assays using 293, Huh7, and Hep3B cells showed that DKK-1 overexpression promoted cell migration and invasion, whereas DKK-1 knock-down inhibited them. When serum DKK-1 levels were assessed in 370 participants (217 with HCC and 153 without), it was significantly higher in HCC patients than in control groups (median 1.48 ng/mL vs. 0.90 ng/mL, p<0.001). The optimum DKK-1 cutoff level was 1.01 ng/mL (AUC=0.829; sensitivity 90.7%; specificity 62.0%). Although DKK-1 had a higher AUC than alpha-fetoprotein (AFP) and des-gamma-carboxy prothrombin (DCP) (AUC=0.829 vs. 0.794 and 0.815, respectively), they were statistically similar (all p>0.05). When three biomarkerswere combined (DKK-1 plus AFP plus DCP), they showed significantly higher AUC (AUC=0.952) than single marker, DKK-1 plus AFP, or DKK-1 plus DCP (all p<0.001). Conclusion: DKK-1 might be a key regulator in HCC progression and a potential therapeutic target in HCC. Serum DKK-1 could complement the diagnostic accuracy of AFP and DCP.
김승업,이우범,김욱현,강병욱 한국융합신호처리학회 2001 융합신호처리학회 논문지 (JISPS) Vol.2 No.2
The main purpose of this study is to propose the algorithm about the extraction of the facial feature. To achieve the above goal, first of all, this study produces binary image for input color image. It calculates area after pixel labeling by variant block-units. Secondly, by contour following, circumference have been calculated. So the proper degree of resemblance about area, circumference, the proper degree of a circle and shape have been calculated using the value of area and circumference. And Third, the algorithm about the methods of extracting parameters which are about the feature of eyes, nose, and mouse using the proper degree of resemblance, general structures and characteristics(symmetrical distance) in face have been accomplished. And then the feature parameters of the front face have been extracted. In this study, twelve facial feature parameters have been extracted by 297 test images taken from 100 people, and 92.93 % of the extracting rate has been shown. 본 논문에서는 얼굴의 특징 추출 알고리즘을 제안한다. 사람의 얼굴에 대한 특징 인수를 추출하기 위하여 우선 이진 영상을 생성한다. 하나 하나의 고립된 영역으로 분리하기 위하여 화소 라베링을 한 후 만들어진 가변 블록 단위로 면적을 구하고, 윤곽선 추적 방법에 의하여 둘레를 추한 후 면적, 둘레, 원형도 및 모양의 유사도를 구한다. 전체 유사도와 일반적인 구조 및 특징을 활용하여 눈, 코, 입의 특징 요소를 추출한 후 12개의 얼굴의 특징 인수들을 추출한다. 얼굴의 왼쪽 눈과 오른쪽 눈 사이의 거리, 왼쪽 눈과 코와의 거리, 오른쪽 눈과 코와의 거리, 왼쪽 눈과 입과의 거리, 오른쪽 눈과 입과의 거리, 코와 입과의 거리 및 각 거리간의 기울기를 이용하여 100명으로부터 획득한 297개의 원 영상을 대상으로 12개의 특징 인수를 추출한 결과 92.73%의 추출 성공률을 보였다.