Kolossváry Márton, Lin Andrew, Kwiecinski Jacek, Cadet Sebastien, Slomka Piotr J, Newby David E, Dweck Marc R, Williams Michelle C, Dey Damini
Gottsegen National Cardiovascular Center, Budapest, Hungary; Physiological Controls Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.
Monash Victorian Heart Institute and Monash Health Heart, Victorian Heart Hospital, Monash University, Victoria, Australia.
JACC Cardiovasc Imaging. 2025 Mar;18(3):308-319. doi: 10.1016/j.jcmg.2024.08.012. Epub 2024 Oct 30.
Coronary computed tomography (CT) angiography-derived attenuation-based plaque burden assessments can identify patients at risk of myocardial infarction.
This study sought to assess whether more detailed plaque morphology assessment using patient-based radiomic characterization could further enhance the identification of patients at risk of myocardial infarction during long-term follow-up.
Post hoc analysis of coronary CT angiography was performed within the SCOT-HEART (Scottish Computed Tomography of the HEART) clinical trial. Coronary plaque segmentations were used to calculate plaque burdens and eigen radiomic features that described plaque morphology. Univariable and multivariable Cox proportional hazard models were used to evaluate the association between clinical and image-based features and fatal or nonfatal myocardial infarction, whereas Harrell's C-statistic and cumulative/dynamic area under the curve (AUC) values with cross-validation were used to evaluate prognostic performance.
Scans from 1,750 patients (aged 58 ± 9 years; 56% male) were analyzed. Over a median of 8.6 years of follow-up, 82 patients had a fatal or nonfatal myocardial infarction. Among the eigen radiomic features, 15 were associated with myocardial infarction in univariable analysis, and 8 features retained their association following adjustment for cardiovascular risk score and plaque burden metrics. Adding plaque burden metrics to a clinical model incorporating cardiovascular risk score, Agatston score and presence of obstructive coronary artery disease had similar prediction performance (C-statistic 0.70 vs 0.70), whereas further addition of eigen radiomic features improved model performance (C-statistic 0.74). In temporal analysis, the model including eigen radiomic features had higher cumulative/dynamic AUC values following the fifth year of follow-up.
Radiomics-based precision phenotyping of coronary plaque morphology provided improvements to long-term prediction of myocardial infarction by CT angiography over and above clinical factors and plaque burden. (Scottish Computed Tomography of the HEART [SCOT-HEART]; NCT01149590).
基于冠状动脉计算机断层扫描(CT)血管造影得出的基于衰减的斑块负荷评估可识别出有心肌梗死风险的患者。
本研究旨在评估使用基于患者的放射组学特征进行更详细的斑块形态评估是否能在长期随访期间进一步提高对有心肌梗死风险患者的识别能力。
在SCOT-HEART(苏格兰心脏计算机断层扫描)临床试验中对冠状动脉CT血管造影进行事后分析。冠状动脉斑块分割用于计算斑块负荷和描述斑块形态的特征放射组学特征。单变量和多变量Cox比例风险模型用于评估临床和基于图像的特征与致命或非致命心肌梗死之间的关联,而使用Harrell's C统计量以及交叉验证的曲线下累积/动态面积(AUC)值来评估预后性能。
分析了1750例患者(年龄58±9岁;56%为男性)的扫描结果。在中位8.6年的随访期内,82例患者发生了致命或非致命心肌梗死。在特征放射组学特征中,单变量分析有15个与心肌梗死相关,在调整心血管风险评分和斑块负荷指标后,8个特征仍保持其相关性。将斑块负荷指标添加到包含心血管风险评分、阿加斯顿评分和阻塞性冠状动脉疾病存在情况的临床模型中,预测性能相似(C统计量0.70对0.70),而进一步添加特征放射组学特征可改善模型性能(C统计量0.74)。在时间分析中,包含特征放射组学特征的模型在随访第五年后具有更高的累积/动态AUC值。
基于放射组学的冠状动脉斑块形态精准表型分析在临床因素和斑块负荷之外,通过CT血管造影改善了心肌梗死的长期预测。(苏格兰心脏计算机断层扫描[SCOT-HEART];NCT01149590)