Xiong Qing-Feng, Fu Xiao-Rong, Chen Yi-Ju, Zheng Ya-Bo, Wang Liu, Zhang Wen-Sheng
Image Center, Hainan Enhance International Medical Center, 571437 Boao, Hainan, China.
Image Center, Wuhan Asia Heart Hospital, 430022 Wuhan, Hubei, China.
Rev Cardiovasc Med. 2024 Aug 12;25(8):284. doi: 10.31083/j.rcm2508284. eCollection 2024 Aug.
Using fluid dynamic modeling, noninvasive fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA) data provides better anatomic and functional information than CCTA, with a high diagnostic and discriminatory value for diagnosing hemodynamically significant lesions. Myocardial blood flow index (MBFI) based on CCTA is a physiological parameter that reflects myocardial ischemia. Thus, exploring the relationship between computed tomography derived fractional flow reserve (CT-FFR) and MBFI could be clinically significant. This study aimed to investigate the relationship between CT-FFR and MBFI and to analyze the feasibility of MBFI differing from CT-FFR in diagnosing suspected coronary artery disease (CAD).
Data from 61 patients (35 males, mean age: 59.2 10.02 years) with suspected CAD were retrospectively analyzed, including the imaging data of CCTA, CT-FFR, and data of invasive coronary angiography performed within one week after hospitalization. CT-FFR and MBFI were calculated, and the correlation between MBFI or CT-FFR and invasive coronary angiography (ICA) was evaluated. Using ICA (value 0.70) as the gold standard and determining the optimal cutoff value via a diagnostic test, the diagnostic performance of MBFI or CT-FFR was evaluated.
MBFI and CT-FFR were negatively correlated with ICA ( = -0.3670 and -0.4922, = 0.0036 and 0.0001, respectively). Using ICA (value of 0.70) the gold standard, the optimal cutoff value was 0.115 for MBFI, and the area under the curve (AUC) was 0.833 (95% confidence interval [CI]: 0.716-0.916, Z = 5.357, 0.0001); using ICA (value of 0.70) the gold standard, the optimal cutoff value was 0.80 for CT-FFR, and the area under the curve (AUC) was 0.759 (95% CI: 0.632-0.859, Z = 3.665, = 0.0002). No significant difference was observed between the AUCs of CT-FFR and MBFI (Z = 0.786, = 0.4316).
MBFI based on CCTA can be used to evaluate myocardial ischemia similar to CT-FFR in suspected CAD; however, it should be noted that CT-FFR is a functional index based on the anatomical stenosis of the coronary artery, whereas MBFI is a physiological index reflecting myocardial mass remodeling.
利用流体动力学建模，从冠状动脉计算机断层扫描血管造影（CCTA）数据得出的无创血流储备分数（FFR）比CCTA能提供更好的解剖和功能信息，对诊断血流动力学显著病变具有较高的诊断和鉴别价值。基于CCTA的心肌血流指数（MBFI）是反映心肌缺血的生理参数。因此，探索计算机断层扫描衍生的血流储备分数（CT-FFR）与MBFI之间的关系可能具有临床意义。本研究旨在调查CT-FFR与MBFI之间的关系，并分析MBFI与CT-FFR在诊断疑似冠状动脉疾病（CAD）方面的差异及可行性。
回顾性分析61例疑似CAD患者（35例男性，平均年龄：59.2±10.02岁）的数据，包括CCTA、CT-FFR的影像数据以及住院后一周内进行的有创冠状动脉造影数据。计算CT-FFR和MBFI，并评估MBFI或CT-FFR与有创冠状动脉造影（ICA）之间的相关性。以ICA（值≤0.70）为金标准，通过诊断试验确定最佳截断值，评估MBFI或CT-FFR的诊断性能。
MBFI和CT-FFR与ICA呈负相关（分别为r=-0.3670和-0.4922，P=0.0036和0.0001）。以ICA（值≤0.70）为金标准，MBFI的最佳截断值为0.115，曲线下面积（AUC）为0.833（95%置信区间[CI]：0.716-0.916，Z=5.357，P<0.0001）；以ICA（值≤0.70）为金标准，CT-FFR的最佳截断值为0.80，曲线下面积（AUC）为0.759（95%CI：0.632-0.859，Z=3.
