Affiliation:
1. Capital Medical University
2. Shukun (Beijing) Technology Company Ltd
Abstract
Abstract
Objective
To evaluate the performance of a fully automatic algorithm for labeling coronary arteries in CCTA images using deep learning based on the two 3-dimensional (3D) U-Net architectures for myocardium structure extraction.
Methods
In total, 157 patients who underwent CCTA scanning were retrospectively included. An automatic coronary artery labeling algorithm based on the distance transformation algorithm was proposed to identify the anatomical segments of the centerlines extracted from CCTA images. Sixteen segments were identified and labeled. The results obtained via the algorithm were recorded and reviewed by three experts. The performance of segment detection and labeling of each segment was evaluated, and the proportion of agreement between the two experts on the manually labeled segments was also calculated.
Results
Compared with the labels of the experts, 117 labels (5.4%) (2180 segments) from the algorithm needed to be changed or removed. The overall accuracy of label presence was 96.2%. The average overlap between the expert reference and algorithm labels was 94.0%. The average agreement between the two experts was 95.0%.
Conclusions
The proposed deep learning algorithm provided a high accuracy of the automatic labeling with respect to the labels from the clinical experts. This method is promising for labeling coronary arteries automatically and alleviating the workload of radiologists in the near future.
Publisher
Research Square Platform LLC
Reference18 articles.
1. The Challenge of Effectively Reporting Coronary Angiography Results From Computed Tomography;Arbab-Zadeh A;JACC Cardiovasc Imaging,2018
2. SCCT guidelines for the interpretation and reporting of coronary CT angiography: A report of the Society of Cardiovascular Computed Tomography Guidelines Committee;Leipsic J;Journal of Cardiovascular Computed Tomography,2014
3. 2014 SCCT guidelines for the interpretation and reporting of coronary CT angiography: a report of the Society of Cardiovascular Computed Tomography Guidelines Committee;Wu FZ;J Cardiovasc Comput Tomogr,2015
4. Difference between Outcome of Left Circumflex Artery and Right Coronary Artery Related Acute Inferior Wall Myocardial Infarction in Patients Undergoing Adjunctive Angioplasty;Sohrabi B;after Fibrinolysis,2014
5. Akinyemi A, Murphy S, Poole I, Roberts C. Automatic labelling of coronary arteries. In:european signal processing conference, 2009; 1562–1566