The role of Artificial intelligent-based FFRCT in assessing the hemodynamic relevance of deep myocardial bridge of the left anterior descending coronary artery

Abstract

Objective: To investigate the role of artificial intelligence-based coronary CT blood flow reserve score (FFRCT) in assessing hemodynamic relevance in patients with deep myocardial bridge (MB) of the left anterior descending coronary artery. Methods: A total of 113 patients diagnosed with deep MB of the left anterior descending coronary artery by coronary CT angiography (CCTA) at the Department of Radiology of Tongji Hospital Affiliated to Tongji University from January 2017 to December 2019 were retrospectively analyzed. The location, length, depth, and degree of systolic compression of the MB were measured. The artificial intelligence-based coronary FFRCT software was employed to calculate the FFRCT value of the deep MB of the left anterior descending coronary artery. With the boundary of 0.80, all patients were divided into FFRCT normal group (FFRCT>0.80) and FFRCT abnormal group (FFRCT≤0.80), and the relationship between FFRCT abnormality and the location, length, depth, and degree of systolic stenosis of the deep MB of the left anterior descending branch was analyzed. The effectiveness of the receiver operating characteristic (ROC) curve in predicting FFRCT abnormalities was measured by using ROC curve to analyze the length, depth, and degree of systolic stenosis of MB. Results: There were no significant differences in age, gender and high-risk factors between FFRCT normal group (n=79) and FFRCT abnormal group (n=34) (P>0.05). In terms of clinical symptoms, unstable angina, asymptomatic myocardial ischemia, stable angina in the FFRCT normal group were 15.2%, 41.8%, 32.9%,respectively, while 32.4%, 23.5%, 35.3% in the FFRCT abnormal group,respectively. Except for unstable angina (χ²=4.32,P=0.038), there were no significant differences in asymptomatic myocardial ischemia and stable angina between the two groups (χ²=3.42, 0.06, P>0.05). The length of deep MB was about (36±5) mm in the FFRCT normal group and (44±5) mm in the FFRCT abnormal group, respectively. The difference between the two groups was statistically significant (t=-7.703, P<0.001). The ROC curve showed that the optimal critical value of the length of the deep MB was 39.7 mm, the area under the curve was 0.88 (95%CI:0.81-0.95, P<0.001), and the accuracy rate of diagnosing FFRCT ≤0.80 was 82.3%. Conclusion: FFRCT value is of great value in the evaluation of hemodynamics in patients with deep myocardial bridge of left anterior descending coronary artery, and the length of deep myocardial bridge is an important factor affecting FFRCT value.