Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Department of Cardiology, The George Washington University School of Medicine, Washington, DC, USA.
J Cardiovasc Comput Tomogr. 2023 Nov-Dec;17(6):407-412. doi: 10.1016/j.jcct.2023.08.012. Epub 2023 Oct 3.
Non-obstructing small coronary plaques may not be well recognized by expert readers during coronary computed tomography angiography (CCTA) evaluation. Recent developments in atherosclerosis imaging quantitative computed tomography (AI-QCT) enabled by machine learning allow for whole-heart coronary phenotyping of atherosclerosis, but its diagnostic role for detection of small plaques on CCTA is unknown.
We performed AI-QCT in patients who underwent serial CCTA in the multinational PARADIGM study. AI-QCT results were verified by a level III experienced reader, who was blinded to baseline and follow-up status of CCTA. This retrospective analysis aimed to characterize small plaques on baseline CCTA and evaluate their serial changes on follow-up imaging. Small plaques were defined as a total plaque volume <50 mm.
A total of 99 patients with 502 small plaques were included. The median total plaque volume was 6.8 mm (IQR 3.5-13.9 mm), most of which was non-calcified (median 6.2 mm; 2.9-12.3 mm). The median age at the time of baseline CCTA was 61 years old and 63% were male. The mean interscan period was 3.8 ± 1.6 years. On follow-up CCTA, 437 (87%) plaques were present at the same location as small plaques on baseline CCTA; 72% were larger and 15% decreased in volume. The median total plaque volume and non-calcified plaque volume increased to 18.9 mm (IQR 8.3-45.2 mm) and 13.8 mm (IQR 5.7-33.4 mm), respectively, among plaques that persisted on follow-up CCTA. Small plaques no longer visualized on follow-up CCTA were significantly more likely to be of lower volume, shorter in length, non-calcified, and more distal in the coronary artery, as compared with plaques that persisted at follow-up.
In this retrospective analysis from the PARADIGM study, small plaques (<50 mm) identified by AI-QCT persisted at the same location and were often larger on follow-up CCTA.
在冠状动脉计算机断层扫描血管造影(CCTA)评估中,非阻塞性小冠状动脉斑块可能无法被专家读者很好地识别。基于机器学习的动脉粥样硬化成像定量计算机断层扫描(AI-QCT)的最新发展使得能够对冠状动脉粥样硬化进行全心脏表型分析,但它在检测 CCTA 上的小斑块方面的诊断作用尚不清楚。
我们在多国 PARADIGM 研究中进行了接受连续 CCTA 检查的患者的 AI-QCT。AI-QCT 结果由一位具有 III 级经验的读者进行验证,该读者对 CCTA 的基线和随访状态不知情。这项回顾性分析旨在描述基线 CCTA 上的小斑块,并评估其在随访成像上的连续变化。小斑块定义为总斑块体积<50mm。
共纳入 99 例患者的 502 个小斑块。总斑块体积中位数为 6.8mm(IQR 3.5-13.9mm),其中大部分为非钙化斑块(中位数 6.2mm;2.9-12.3mm)。基线 CCTA 时的中位年龄为 61 岁,63%为男性。平均两次扫描间隔为 3.8±1.6 年。在随访 CCTA 中,437(87%)个斑块位于基线 CCTA 中小斑块的相同位置;72%的斑块较大,15%的斑块体积减小。在随访 CCTA 中持续存在的斑块中,总斑块体积和非钙化斑块体积中位数分别增加至 18.9mm(IQR 8.3-45.2mm)和 13.8mm(IQR 5.7-33.4mm)。在随访 CCTA 中不再可见的小斑块体积较小、长度较短、非钙化且位于冠状动脉的更远端的可能性显著更高。
在来自 PARADIGM 研究的这项回顾性分析中,AI-QCT 识别的小斑块(<50mm)在相同位置持续存在,并且在随访 CCTA 中通常更大。