Kahmann Jannik, Nörenberg Dominik, Papavassiliu Theano, Dar Salman Ul Hassan, Engelhardt Sandy, Schoenberg Stefan O, Froelich Matthias F, Ayx Isabelle
Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany.
First Department of Internal Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim, University of Heidelberg, 68167, Mannheim, Germany.
Insights Imaging. 2024 Jul 6;15(1):170. doi: 10.1186/s13244-024-01759-9.
This study aims to investigate how radiomics analysis can help understand the association between plaque texture, epicardial adipose tissue (EAT), and cardiovascular risk. Working with a Photon-counting CT, which exhibits enhanced feature stability, offers the potential to advance radiomics analysis and enable its integration into clinical routines.
Coronary plaques were manually segmented in this retrospective, single-centre study and radiomic features were extracted using pyradiomics. The study population was divided into groups according to the presence of high-risk plaques (HRP), plaques with at least 50% stenosis, plaques with at least 70% stenosis, or triple-vessel disease. A combined group with patients exhibiting at least one of these risk factors was formed. Random forest feature selection identified differentiating features for the groups. EAT thickness and density were measured and compared with feature selection results.
A total number of 306 plaques from 61 patients (mean age 61 years +/- 8.85 [standard deviation], 13 female) were analysed. Plaques of patients with HRP features or relevant stenosis demonstrated a higher presence of texture heterogeneity through various radiomics features compared to patients with only an intermediate stenosis degree. While EAT thickness did not significantly differ, affected patients showed significantly higher mean densities in the 50%, HRP, and combined groups, and insignificantly higher densities in the 70% and triple-vessel groups.
The combination of a higher EAT density and a more heterogeneous plaque texture might offer an additional tool in identifying patients with an elevated risk of cardiovascular events.
Cardiovascular disease is the leading cause of mortality globally. Plaque composition and changes in the EAT are connected to cardiac risk. A better understanding of the interrelation of these risk indicators can lead to improved cardiac risk prediction.
Cardiac plaque composition and changes in the EAT are connected to cardiac risk. Higher EAT density and more heterogeneous plaque texture are related to traditional risk indicators. Radiomics texture analysis conducted on PCCT scans can help identify patients with elevated cardiac risk.
本研究旨在探讨放射组学分析如何有助于理解斑块纹理、心外膜脂肪组织（EAT）与心血管风险之间的关联。使用具有增强特征稳定性的光子计数CT进行研究，有望推进放射组学分析并使其融入临床常规。
在这项回顾性单中心研究中，对冠状动脉斑块进行手动分割，并使用pyradiomics提取放射组学特征。根据高危斑块（HRP）的存在、至少50%狭窄的斑块、至少70%狭窄的斑块或三支血管病变，将研究人群分组。形成了具有至少一种这些危险因素的患者的组合组。随机森林特征选择确定了各组的区分特征。测量EAT厚度和密度，并与特征选择结果进行比较。
共分析了61例患者（平均年龄61岁±8.85[标准差]，13例女性）的306个斑块。与仅具有中度狭窄程度的患者相比，具有HRP特征或相关狭窄的患者的斑块通过各种放射组学特征表现出更高的纹理异质性。虽然EAT厚度没有显著差异，但受影响的患者在50%、HRP和组合组中显示出显著更高的平均密度，在70%和三支血管组中显示出略高的密度。
较高的EAT密度和更不均匀的斑块纹理的组合可能为识别心血管事件风险升高的患者提供额外的工具。
心血管疾病是全球死亡的主要原因。斑块组成和EAT的变化与心脏风险相关。更好地理解这些风险指标之间的相互关系可以改善心脏风险预测。
心脏斑块组成和EAT的变化与心脏风险相关。较高的EAT密度和更不均匀的斑块纹理与传统风险指标相关。在光子计数CT扫描上进行的放射组学纹理分析可以帮助识别心脏风险升高的患者。
