A laboratory feasibility study using a computer algorithm for anastomosis segmentation of epicardial ultrasonography images from distal coronary artery bypass anastomoses.

IF 1.5 4区 医学 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS
Alex Skovsbo Jørgensen, Martin Siemienski Andersen, Lasse Riis Østergaard, Samuel Emil Schmidt, Dorte Nøhr, Jan Jesper Andreasen
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引用次数: 0

Abstract

Background: The outcome of coronary artery bypass grafting (CABG) depends on several factors, including the quality of the distal anastomoses to the coronary arteries. Early graft failure may be caused by, e.g., technical suture failures, and such failures may be detected using intraoperative quality assessment. High-intensity epicardial ultrasonography (ECUS) allows anatomical visualization of the anastomoses during surgery, but currently, the images must be assessed manually. Here, we aim to describe an automatic quality assessment of distal coronary anastomoses using in-house software for vessel area and diameter extraction.

Methods: A postoperative, laboratory, investigational feasibility study comparing computer readings of longitudinal and transverse ultrasonographic images of distal coronary artery anastomoses with manual readings was performed, including ECUS images from 30 patients undergoing elective, isolated on-pump CABG. Vessel and anastomosis segmentation performance metrics from images obtained intraoperatively were compared to assess agreement between the manual and automatic segmentation methods. Scatter plots, the Dice coefficient and correlation analyses were used as measures of similarity between the two readings. p < 0.05 was considered significant.

Results: The number of dimensions of anastomotic vessel structures that are relevant for stenosis quantification and the Dice coefficient were 0.888 between the automatic and manual segmentations. The correlation coefficient between the manual and automatic stenotic rates was 0.674.

Conclusions: An anastomosis segmentation software for automatic and objective extraction of the anatomical dimensions of relevant distal coronary anastomotic structures from ECUS images obtained during CABG was developed. The framework allows for quantifying stenotic in the anastomotic structures and has the potential to assist surgeons during quality assessment of coronary anastomoses when the described segmentation of vessels and anastomoses is available for real-time epicardial ultrasonography use during surgery.

Trial registration: The study was registered on September 29, 2016, before enrolment of the first participant (ClinicalTrials.gov ID: NCT02919124).

应用计算机算法对冠状动脉远端搭桥吻合口心外膜超声图像进行吻合分割的可行性研究。
背景:冠状动脉旁路移植术(CABG)的结果取决于几个因素,包括远端冠状动脉吻合口的质量。早期移植物失败可能是由技术缝合失败引起的,这种失败可以通过术中质量评估来检测。高强度心外膜超声(ECUS)可以在手术过程中对吻合口进行解剖可视化,但目前,图像必须手工评估。在这里,我们的目的是描述一个自动质量评估远端冠状动脉吻合器使用内部软件血管面积和直径提取。方法:对30例选择性、孤立无泵搭桥患者的ECUS图像进行了术后、实验室、研究性可行性研究,比较了计算机读数的冠状动脉远端吻合口纵向和横向超声图像与手工读数。从术中获得的图像中比较血管和吻合的分割性能指标,以评估手动和自动分割方法之间的一致性。散点图、Dice系数和相关分析被用来衡量两个读数之间的相似性。p结果:自动和手动分割的吻合口血管结构与狭窄量化相关的尺寸数和Dice系数均为0.888。人工与自动狭窄率的相关系数为0.674。结论:开发了一种吻合口分割软件,可从冠脉搭桥术中获得的ECUS图像中自动、客观地提取相关冠状动脉远端吻合口结构的解剖尺寸。当所描述的血管和吻合口的分割可用于手术期间的实时心外膜超声检查时,该框架允许对吻合口结构中的狭窄进行量化,并有可能协助外科医生对冠状动脉吻合口进行质量评估。试验注册:该研究于2016年9月29日注册,在第一名受试者入组之前(ClinicalTrials.gov ID: NCT02919124)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Cardiothoracic Surgery
Journal of Cardiothoracic Surgery 医学-心血管系统
CiteScore
2.50
自引率
6.20%
发文量
286
审稿时长
4-8 weeks
期刊介绍: Journal of Cardiothoracic Surgery is an open access journal that encompasses all aspects of research in the field of Cardiology, and Cardiothoracic and Vascular Surgery. The journal publishes original scientific research documenting clinical and experimental advances in cardiac, vascular and thoracic surgery, and related fields. Topics of interest include surgical techniques, survival rates, surgical complications and their outcomes; along with basic sciences, pediatric conditions, transplantations and clinical trials. Journal of Cardiothoracic Surgery is of interest to cardiothoracic and vascular surgeons, cardiothoracic anaesthesiologists, cardiologists, chest physicians, and allied health professionals.
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