Wang Huaijun, Schmieder Anne, Watkins Mary, Wang Pengjun, Mitchell Joshua, Qamer S Zyad, Lanza Gregory
United Imaging Healthcare, Houston, TX 77054, United States.
Division of Cardiology, Washington University in Saint Louis, Saint Louis, MO 63108, United States.
World J Cardiol. 2025 Jul 26;17(7):108745. doi: 10.4330/wjc.v17.i7.108745.
A key cardiac magnetic resonance (CMR) challenge is breath-holding duration, difficult for cardiac patients.
To evaluate whether artificial intelligence-assisted compressed sensing CINE (AI-CS-CINE) reduces image acquisition time of CMR compared to conventional CINE (C-CINE).
Cardio-oncology patients ( = 60) and healthy volunteers ( = 29) underwent sequential C-CINE and AI-CS-CINE with a 1.5-T scanner. Acquisition time, visual image quality assessment, and biventricular metrics (end-diastolic volume, end-systolic volume, stroke volume, ejection fraction, left ventricular mass, and wall thickness) were analyzed and compared between C-CINE and AI-CS-CINE with Bland-Altman analysis, and calculation of intraclass coefficient (ICC).
In 89 participants (58.5 ± 16.8 years, 42 males, 47 females), total AI-CS-CINE acquisition and reconstruction time (37 seconds) was 84% faster than C-CINE (238 seconds). C-CINE required repeats in 23% (20/89) of cases (approximately 8 minutes lost), while AI-CS-CINE only needed one repeat (1%; 2 seconds lost). AI-CS-CINE had slightly lower contrast but preserved structural clarity. Bland-Altman plots and ICC (0.73 ≤ ≤ 0.98) showed strong agreement for left ventricle (LV) and right ventricle (RV) metrics, including those in the cardiac amyloidosis subgroup ( = 31). AI-CS-CINE enabled faster, easier imaging in patients with claustrophobia, dyspnea, arrhythmias, or restlessness. Motion-artifacted C-CINE images were reliably interpreted from AI-CS-CINE.
AI-CS-CINE accelerated CMR image acquisition and reconstruction, preserved anatomical detail, and diminished impact of patient-related motion. Quantitative AI-CS-CINE metrics agreed closely with C-CINE in cardio-oncology patients, including the cardiac amyloidosis cohort, as well as healthy volunteers regardless of left and right ventricular size and function. AI-CS-CINE significantly enhanced CMR workflow, particularly in challenging cases. The strong analytical concordance underscores reliability and robustness of AI-CS-CINE as a valuable tool.
心脏磁共振成像(CMR)的一个关键挑战是屏气时间,这对心脏病患者来说很困难。
评估与传统电影磁共振成像(C-CINE)相比,人工智能辅助的压缩感知电影磁共振成像(AI-CS-CINE)是否能减少CMR的图像采集时间。
心脏肿瘤患者(n = 60)和健康志愿者(n = 29)使用1.5-T扫描仪依次进行C-CINE和AI-CS-CINE检查。采用Bland-Altman分析和组内相关系数(ICC)计算,对C-CINE和AI-CS-CINE之间的采集时间、视觉图像质量评估以及双心室指标(舒张末期容积、收缩末期容积、每搏输出量、射血分数、左心室质量和壁厚)进行分析和比较。
在89名参与者(年龄58.5±16.8岁,男性42名,女性47名)中,AI-CS-CINE的总采集和重建时间(37秒)比C-CINE(238秒)快84%。C-CINE在23%(20/89)的病例中需要重复检查(大约损失8分钟),而AI-CS-CINE只需要一次重复检查(1%;损失2秒)。AI-CS-CINE的对比度略低,但保留了结构清晰度。Bland-Altman图和ICC(0.73≤ICC≤0.98)显示左心室(LV)和右心室(RV)指标,包括心脏淀粉样变性亚组(n = 31)中的指标,具有高度一致性。AI-CS-CINE能够在幽闭恐惧症、呼吸困难、心律失常或烦躁不安的患者中更快、更轻松地成像。运动伪影的C-CINE图像可以从AI-CS-CINE中可靠地解读出来。
AI-CS-CINE加速了CMR图像的采集和重建,保留了解剖细节,并减少了患者相关运动的影响。在心脏肿瘤患者,包括心脏淀粉样变性队列以及健康志愿者中,无论左、右心室大小和功能如何,AI-CS-CINE的定量指标与C-CINE密切一致。AI-CS-CINE显著增强了CMR工作流程,尤其是在具有挑战性的病例中。强大的分析一致性强调了AI-CS-CINE作为一种有价值工具的可靠性和稳健性。