Jørgensen Alex Skovsbo, Andersen Martin Siemienski, Østergaard Lasse Riis, Schmidt Samuel Emil, Nøhr Dorte, Andreasen Jan Jesper
Department of Health Science and Technology, Aalborg University, Selma Lagerløfs Vej 249, Gistrup, 9260, Denmark.
Department of Cardiothoracic Surgery, Aalborg University Hospital, Hobrovej 18-22, Aalborg, 9000, Denmark.
J Cardiothorac Surg. 2025 Jan 6;20(1):34. doi: 10.1186/s13019-024-03187-8.
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.
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.
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.
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.
The study was registered on September 29, 2016, before enrolment of the first participant (ClinicalTrials.gov ID: NCT02919124).
冠状动脉旁路移植术（CABG）的结果取决于多种因素，包括冠状动脉远端吻合口的质量。早期移植失败可能由技术缝合失败等原因引起，此类失败可通过术中质量评估检测出来。高强度心外膜超声检查（ECUS）可在手术过程中对吻合口进行解剖可视化，但目前，图像必须手动评估。在此，我们旨在描述一种使用内部软件自动评估冠状动脉远端吻合口质量的方法，该软件可提取血管面积和直径。
进行了一项术后实验室研究，比较计算机对冠状动脉远端吻合口纵向和横向超声图像的读数与手动读数，研究对象包括30例行择期、单纯体外循环CABG患者的ECUS图像。比较术中获得图像的血管和吻合口分割性能指标，以评估手动和自动分割方法之间的一致性。散点图、Dice系数和相关性分析用作两种读数之间相似性的度量。p < 0.05被认为具有统计学意义。
与狭窄量化相关的吻合血管结构维度数量以及自动和手动分割之间的Dice系数为0.888。手动和自动狭窄率之间的相关系数为0.674。
开发了一种吻合口分割软件，可从CABG期间获得的ECUS图像中自动、客观地提取相关冠状动脉远端吻合结构的解剖维度。该框架能够量化吻合结构中的狭窄情况，并且当所述血管和吻合口分割可用于手术期间的心外膜实时超声检查时，有可能在冠状动脉吻合口质量评估期间协助外科医生。
该研究于2016年9月29日在招募第一名参与者之前进行了注册（ClinicalTrials.gov标识符：NCT02919124）。
