Cheng S H, Ni J, Liu J, Huang F, Wang P J
Department of Radiology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China.
Zhonghua Yi Xue Za Zhi. 2021 Feb 23;101(7):464-469. doi: 10.3760/cma.j.cn112137-20200924-02709.
To investigate the role of artificial intelligence-based coronary CT blood flow reserve score (FFR) in assessing hemodynamic relevance in patients with deep myocardial bridge (MB) of the left anterior descending coronary artery. 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 FFR software was employed to calculate the FFR value of the deep MB of the left anterior descending coronary artery. With the boundary of 0.80, all patients were divided into FFR normal group (FFR>0.80) and FFR abnormal group (FFR≤0.80), and the relationship between FFR 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 FFR abnormalities was measured by using ROC curve to analyze the length, depth, and degree of systolic stenosis of MB. There were no significant differences in age, gender and high-risk factors between FFR normal group (=79) and FFR abnormal group (=34) (>0.05). In terms of clinical symptoms, unstable angina, asymptomatic myocardial ischemia, stable angina in the FFR normal group were 15.2%, 41.8%, 32.9%,respectively, while 32.4%, 23.5%, 35.3% in the FFR abnormal group,respectively. Except for unstable angina (=4.32,=0.038), there were no significant differences in asymptomatic myocardial ischemia and stable angina between the two groups (=3.42, 0.06, >0.05). The length of deep MB was about (36±5) mm in the FFR normal group and (44±5) mm in the FFR abnormal group, respectively. The difference between the two groups was statistically significant (=-7.703, 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%:0.81-0.95, <0.001), and the accuracy rate of diagnosing FFR ≤0.80 was 82.3%. FFR 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 FFR value.
探讨基于人工智能的冠状动脉CT血流储备分数（FFR）在评估左前降支冠状动脉深层心肌桥（MB）患者血流动力学相关性中的作用。回顾性分析了2017年1月至2019年12月在同济大学附属同济医院放射科经冠状动脉CT血管造影（CCTA）诊断为左前降支冠状动脉深层MB的113例患者。测量了MB的位置、长度、深度和收缩期压迫程度。采用基于人工智能的冠状动脉FFR软件计算左前降支冠状动脉深层MB的FFR值。以0.80为界值，将所有患者分为FFR正常组（FFR>0.80）和FFR异常组（FFR≤0.80），分析FFR异常与左前降支深层MB的位置、长度、深度和收缩期狭窄程度之间的关系。通过ROC曲线分析MB的长度、深度和收缩期狭窄程度，测量ROC曲线预测FFR异常的有效性。FFR正常组（n = 79）和FFR异常组（n = 34）在年龄、性别和高危因素方面无显著差异（P>0.05）。在临床症状方面，FFR正常组中不稳定型心绞痛、无症状心肌缺血、稳定型心绞痛分别为15.2%、41.8%、32.9%，而FFR异常组分别为32.4%、23.5%、35.3%。除不稳定型心绞痛（P = 4.32，P = 0.038）外，两组无症状心肌缺血和稳定型心绞痛差异无统计学意义（P = 3.42，P = 0.06，P>0.05）。FFR正常组深层MB长度约为（36±5）mm，FFR异常组约为（44±5）mm。两组差异有统计学意义（t = -7.703，P = 0.001）。ROC曲线显示，深层MB长度的最佳临界值为39.7 mm，曲线下面积为0.88（95%CI：0.81 - 0.95，P<0.001），诊断FFR≤0.80的准确率为82.3%。FFR值在评估左前降支冠状动脉深层心肌桥患者血流动力学方面具有重要价值，深层心肌桥长度是影响FFR值的重要因素。
