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首页> 外文期刊>Kaohsiung Journal of Medical Sciences >Proposal of a diagnostic algorithm for intraductal ultrasonography to distinguish between benign and malignant biliary strictures
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Proposal of a diagnostic algorithm for intraductal ultrasonography to distinguish between benign and malignant biliary strictures

机译:导管内超声诊断算法的建议,以区分良性和恶性胆道狭窄

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摘要

To reexamine the recognizability of intraductal ultrasonography (IDUS) findings from an imaging database and propose a novel algorithm for clinical application. IDUS images of 102 patients who had undergone IDUS examinations for indeterminate causes of common bile duct dilation were independently reviewed by two endoscopists. The strength of the inter-rater agreement between the endoscopists was analyzed using Cohen's kappa (κ). An algorithm was implemented by arranging the IDUS characteristics according to their recognizability. The proposed algorithm was evaluated by examining the inter-rater agreement and diagnostic accuracy before and after the use of the algorithm. The strength of the inter-rater agreement was good for common bile duct stones with or without acoustic shadowing; intraluminal tumors; or bile duct wall thicknesses of more than or equal to 9?mm (κ??0.8); followed by intraluminal hypoechoic nodules without common bile duct stone characteristics (κ?=?0.771); and finally eccentric wall thickening, outer layer disruption, irregular mucosa, and destructed mural layers (κ: 0.595–0.419). Our algorithm improved the strength of inter-rater agreement with a diagnostic accuracy of 81.4%. We proposed an algorithm according to the recognizability of IDUS characteristics, and it can be used by endoscopists to evaluate such characteristics and determine the cause of biliary obstruction.
机译:要重新检查从成像数据库的导管内超声检查(IDUS)发现的可识别性,并提出一种新的临床应用算法。由两名内镜医师独立检查了102例因未确定原因引起的胆总管扩张而接受IDUS检查的IDUS图像。使用Cohen的kappa(κ)分析了内镜医师之间的评估者之间协议的强度。通过根据IDUS特征的可识别性排列算法。通过检查评分者之间的一致性和诊断准确性,对提出的算法进行了评估。评估者之间协议的强度对于有或没有声影遮盖的胆总管结石均有效。腔内肿瘤或胆管壁厚大于或等于9?mm(κ?>?0.8);或其次是没有胆总管结石特征的腔内低回声结节(κ= 0.771);最后是偏心壁增厚,外层破裂,粘膜不规则和壁层破坏(κ:0.595–0.419)。我们的算法以81.4%的诊断准确性提高了评估者之间协议的强度。我们根据IDUS特征的可识别性提出了一种算法,内镜医师可以使用它来评估这些特征并确定胆道阻塞的原因。

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