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目的:探讨基于人工智能技术的冠状动脉CT血流储备分数（FFRn CT）对左冠状动脉前降支纵深型心肌桥患者血流动力学改变的评估价值。n 方法:回顾性分析2017年1月至2019年12月同济大学附属同济医院放射科行冠状动脉CT血管造影（CCTA）检查诊断为左冠状动脉前降支纵深型心肌桥的113例患者资料。测量心肌桥的位置、长度、深度以及收缩期管腔狭窄率。利用基于人工智能技术的冠状动脉FFRn CT软件计算左冠状动脉前降支纵深型心肌桥的FFRn CT值。以0.80为界，将所有患者分为FFRn CT正常组（FFRn CT>0.80）及FFRn CT异常组（FFRn CT≤0.80），分析FFRn CT异常与左前降支纵深型心肌桥位置、长度、深度、收缩期狭窄率之间的关系。通过受试者工作特征（ROC）曲线分析心肌桥长度、深度及收缩期狭窄率预测FFRn CT异常的效能。n 结果:FFRn CT正常组（n n=79）和FFRn CT异常组（n n=34）两组患者间年龄、性别及高危因素差异均无统计学意义（均n P>0.05）。在临床症状中，FFRn CT正常组患者不稳定性心绞痛、无症状性心肌缺血、稳定性心绞痛占比分别约15.2%、41.8%、32.9%，FFRn CT异常组患者以上临床症状占比分别约32.4%、23.5%、35.3%，两组患者不稳定性心绞痛差异有统计学意义（n χ2=4.32，n P=0.038），无症状性心肌缺血、稳定性心绞痛差异无统计学意义（n χ2＝3.42、0.06，均n P>0.05）。FFRn CT正常组及FFRn CT异常组患者纵深型心肌桥长度分别约（36±5） mm、（44±5） mm，两者差异具有统计学意义（n t=-7.703，n P0.05). In terms of clinical symptoms, unstable angina, asymptomatic myocardial ischemia, stable angina in the FFRn CT normal group were 15.2%, 41.8%, 32.9%,respectively, while 32.4%, 23.5%, 35.3% in the FFRn CT abnormal group,respectively. Except for unstable angina (n χ2=4.32,n P=0.038), there were no significant differences in asymptomatic myocardial ischemia and stable angina between the two groups (n χ2=3.42, 0.06, n P>0.05). The length of deep MB was about (36±5) mm in the FFRn CT normal group and (44±5) mm in the FFRn CT abnormal group, respectively. The difference between the two groups was statistically significant (n t=-7.703, n 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%n CI:0.81-0.95, n P<0.001), and the accuracy rate of diagnosing FFRn CT ≤0.80 was 82.3%.n Conclusion:FFRn CT 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 FFRn CT value.n