分子影像学杂志2024，Vol.47Issue(6)：616-621,6.DOI:10.12122/j.issn.1674-4500.2024.06.10
人工智能诊断系统及CT无创血流储备分数在评估高海拔地区冠脉临界病变中的应用
Application of artificial intelligence diagnostic system and CT noninvasive blood flow reserve fraction in evaluating coronary critical lesion function at high altitude
摘要
Abstract
Objective To explore the application value of artificial intelligence (AI) diagnostic system based on coronary CT angiography and CT non-invasive blood flow reserve fraction (CT-FFR) in assessing the function of coronary artery critical lesions at high altitude. Methods A prospective collection was conducted on 164 patients with critical coronary artery disease at Qinghai University Affiliated Hospital from January 2022 to October 2023. They were grouped according to their residential altitude, with group A at 2000-3000 m(n=83)and group B at>3000 m(n=81). The two groups of patients were further divided into subgroups of 50％-60％(n=84)and 61％-70％(n=80)based on the degree of coronary stenosis. Import patient CCTA data into AI assisted diagnosis and CT-FFR measurement systems, and evaluate the application of AI and CT-FFR in the diagnosis of coronary critical lesions in high-altitude areas using coronary angiography and traditional coronary FFR as gold standards. Results Using FFR as the gold standard, the consistency between CT-FFR and FFR was 83.75％. The calcified and vulnerable plaques in group B were higher than those in group A (P=0.037, 0.020);The incidence of multi branch coronary artery disease and 61％-70％ stenosis degree in group B was higher than that in group (P<0.05); The incidence of calcified and vulnerable plaques in the 61％-70％subgroups of group A and group B was higher than that in the 50％-60％subgroups (P<0.05). The CT-FFR value of group B was significantly lower than that of group A (0.76 ± 0.04 vs 0.88 ± 0.05, P<0.01);The incidence of CT-FFR values ≤0.80 and <0.70 in the 61％-70％ subgroups of group B was higher than that in the 50％-60％ subgroups (P<0.05). Conclusion CT- FFR diagnostic system based on AI has a high consistency with FFR in evaluating coronary artery characteristics and hemodynamic changes in patients with critical coronary artery lesions at different altitudes,and has a high diagnostic sensitivity and specificity, which significantly improves the diagnostic efficiency.关键词
人工智能/冠状动脉/CT无创血流储备分数/CT血管成像/冠脉临界病变Key words
artificial intelligence/coronary artery/fractional flow reserve derived from computed tomography angiography/CT angiography/critical lesion引用本文复制引用
王雪燕,曹云太,韩千程,颜梅,韩玲,温生宝..人工智能诊断系统及CT无创血流储备分数在评估高海拔地区冠脉临界病变中的应用[J].分子影像学杂志,2024,47(6):616-621,6.基金项目
青海省医药卫生科技项目(2021-wjzdx-40) （2021-wjzdx-40）
