何付权 李亚飞 杨嘉 刘晓强 朱磊

【摘要】 目的：探究人工智能（AI）辅助冠脉CT血管成像（CTA）“双低”成像诊断冠状动脉病变的可行性。方法：选取2022年7月—2023年6月于上海交通大学附属第一人民医院就诊的116例疑似冠状动脉病变患者，所有患者均行冠脉CTA“双低”成像诊断，图像均经医生诊断和AI辅助诊断，比较两种方式的诊断时间及对图像质量评估结果，以选择性冠状动脉造影术（CAG）结果为金标准，比较两种方式对冠状动脉病变的诊断价值。以医生诊断结果为标准，采用Kappa检验分析AI辅助诊断与医生诊断对冠状动脉狭窄程度、冠状动脉斑块诊断的一致性。结果：AI组诊断时间短于医生组，图像评优率高于医生组（P<0.05）；医生组和AI组诊断对冠状动脉病变的准确率分为93.97%、93.10%，敏感度分别为95.33%、94.39%，特异度分别为77.78%、77.78%，差异均无统计学意义（P>0.05）；Kappa检验结果显示，医生组与AI组对冠状动脉狭窄程度、冠状动脉斑块诊断的Kappa值分别为0.954、0.922，具有高度一致性。结论：AI辅助冠脉CTA“双低”成像对冠状动脉病变有较高的诊断价值，能显著缩短冠状动脉病变的诊断时间，可作为医生诊断冠状动脉病变的有效辅助工具。

【关键词】 冠状动脉病变 人工智能 冠脉CT血管成像 辅助诊断 可行性

Feasibility Study of Artificial Intelligence-assisted Coronary CTA Imaging under "Double Low Scheme" in the Diagnosis of Coronary Artery Lesion/HE Fuquan， LI Yafei， YANG Jia， LIU Xiaoqiang， ZHU Lei. //Medical Innovation of China， 2024， 21（13）： -134

[Abstract] Objective： To explore the feasibility of artificial intelligence （AI）-assisted coronary CT angiography （CTA） imaging under "double low scheme" in the diagnosis of coronary artery lesion. Method： A total of 116 patients with suspected coronary artery lesion in the First People's Hospital Affiliated to Shanghai Jiao Tong University from July 2022 to June 2023 were selected. All patients underwent coronary CTA imaging diagnosis under "double low scheme". The images were diagnosed by doctors and AI-assisted diagnosis. The diagnosis time and image quality assessment results of the two methods were compared. Selective coronary angiography （CAG） result was used as the gold standard to compare the diagnostic value of the two methods on coronary artery disease. Based on the doctor's diagnosis result， Kappa test was used to analyze the consistency of AI-assisted diagnosis and doctor's diagnosis in the diagnosis of coronary artery stenosis degree and coronary plaque. Result： The diagnosis time in AI group was shorter than that in doctor group， and the rate of excellent image assessment was higher than that in doctor group （P<0.05）. The accuracy rates of diagnosis of coronary artery disease in doctor group and AI group were 93.97% and 93.10%， the sensitivities were 95.33% and 94.39%， and the specificities were 77.78% and 77.78% respectively， the differences were no significant differences （P>0.05）. Kappa test results showed that the Kappa values of doctor group and AI group for the diagnosis of coronary artery stenosis degree and coronary plaque were 0.954 and 0.922 respectively， with high consistency. Conclusion： AI-assisted coronary CTA imaging under "double low scheme" has a high diagnostic value on coronary artery lesion， and it can significantly shorten the diagnosis time of coronary artery lesion and can be used as an effective auxiliary tool for doctors to diagnose coronary artery lesion.

[Key words] Coronary artery lesion Artificial intelligence Coronary CT angiography Assisted diagnosis Feasibility

First-author's address： Department of Radiology， the First People's Hospital Affiliated to Shanghai Jiao Tong University， Shanghai 201620， China

doi：10.3969/j.issn.1674-4985.2024.13.030

冠状动脉病变是指冠状动脉供血不足或阻塞的疾病，其病因主要是动脉粥样硬化，即血管壁内脂质沉积形成斑块，逐渐增大堵塞血管腔[1]。冠状动脉病变临床表现为胸痛、气短、胸闷、心悸、乏力等，发病通常与高血脂、高血压、糖尿病、吸烟、肥胖、炎症反应和家族遗传等因素有关，近年来，其发病率和病死率上升，且呈年轻化趋势发展，因此，早期诊断和临床干预极其重要[2-3]。……