{"title":"基于CMR成像的患者特异性左心房几何重构","authors":"S. Teo, Xiaodan Zhao, R. Tan, L. Zhong, Yi Su","doi":"10.22489/CinC.2018.169","DOIUrl":null,"url":null,"abstract":"Clinical quantification of left atrial (LA) volumes is currently performed using either the biplane area-length method or the method of discs (Simpson‘s method) on 2-D cardiac images or 3D echocardiography. However, these methods tend to underestimate LA volumes as compared to cardiovascular magnetic resonance (CMR) imaging. In this paper, we propose a geometry-based reconstruction algorithm for computing the LA volume automatically for the entire cardiac cycle by combining information from both the short- and long-axis from CMR imaging. The inputs to our reconstruction algorithm are as follows: (i) a set of segmented short-axis contours and (ii) a set of segmented long-axis contours from the standard 2-chamber and 4-chamber views. Our approach consists of a series of iterative steps where the most basal short-axis contour is projected in the atrial direction and subsequently morph to the patient-specific LA shape using the long-axis contours as guide. These series of morphing generate a left heart comprising both the LV and LA geometries with a planar basal surface. To reconstruct the LA cap, this planar basal surface is morphed into a hemisphere representing the closed surface of the LA using the long-axis contours as guide, thereby allowing us to reconstruct the closed LA shape and to calculate its volume.","PeriodicalId":215521,"journal":{"name":"2018 Computing in Cardiology Conference (CinC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconstruction of Patient-Specific Left Atrial Geometry from CMR Imaging\",\"authors\":\"S. Teo, Xiaodan Zhao, R. Tan, L. Zhong, Yi Su\",\"doi\":\"10.22489/CinC.2018.169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Clinical quantification of left atrial (LA) volumes is currently performed using either the biplane area-length method or the method of discs (Simpson‘s method) on 2-D cardiac images or 3D echocardiography. However, these methods tend to underestimate LA volumes as compared to cardiovascular magnetic resonance (CMR) imaging. In this paper, we propose a geometry-based reconstruction algorithm for computing the LA volume automatically for the entire cardiac cycle by combining information from both the short- and long-axis from CMR imaging. The inputs to our reconstruction algorithm are as follows: (i) a set of segmented short-axis contours and (ii) a set of segmented long-axis contours from the standard 2-chamber and 4-chamber views. Our approach consists of a series of iterative steps where the most basal short-axis contour is projected in the atrial direction and subsequently morph to the patient-specific LA shape using the long-axis contours as guide. These series of morphing generate a left heart comprising both the LV and LA geometries with a planar basal surface. To reconstruct the LA cap, this planar basal surface is morphed into a hemisphere representing the closed surface of the LA using the long-axis contours as guide, thereby allowing us to reconstruct the closed LA shape and to calculate its volume.\",\"PeriodicalId\":215521,\"journal\":{\"name\":\"2018 Computing in Cardiology Conference (CinC)\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Computing in Cardiology Conference (CinC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22489/CinC.2018.169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Computing in Cardiology Conference (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22489/CinC.2018.169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconstruction of Patient-Specific Left Atrial Geometry from CMR Imaging
Clinical quantification of left atrial (LA) volumes is currently performed using either the biplane area-length method or the method of discs (Simpson‘s method) on 2-D cardiac images or 3D echocardiography. However, these methods tend to underestimate LA volumes as compared to cardiovascular magnetic resonance (CMR) imaging. In this paper, we propose a geometry-based reconstruction algorithm for computing the LA volume automatically for the entire cardiac cycle by combining information from both the short- and long-axis from CMR imaging. The inputs to our reconstruction algorithm are as follows: (i) a set of segmented short-axis contours and (ii) a set of segmented long-axis contours from the standard 2-chamber and 4-chamber views. Our approach consists of a series of iterative steps where the most basal short-axis contour is projected in the atrial direction and subsequently morph to the patient-specific LA shape using the long-axis contours as guide. These series of morphing generate a left heart comprising both the LV and LA geometries with a planar basal surface. To reconstruct the LA cap, this planar basal surface is morphed into a hemisphere representing the closed surface of the LA using the long-axis contours as guide, thereby allowing us to reconstruct the closed LA shape and to calculate its volume.