Hertel Alexander, Kuru Mustafa, Rink Johann S, Haag Florian, Vellala Abhinay, Papavassiliu Theano, Froelich Matthias F, Schoenberg Stefan O, Ayx Isabelle
Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany.
First Department of Medicine-Cardiology, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany.
Diagnostics (Basel). 2025 Jul 16;15(14):1796. doi: 10.3390/diagnostics15141796.
: Cardiovascular diseases are the leading cause of global mortality, with 80% of coronary heart disease in patients over 65. Understanding aging cardiovascular structures is crucial. Photon-counting computed tomography (PCCT) offers improved spatial and temporal resolution and better signal-to-noise ratio, enabling texture analysis in clinical routines. Detecting structural changes in aging left-ventricular myocardium may help predict cardiovascular risk. : In this retrospective, single-center, IRB-approved study, 90 patients underwent ECG-gated contrast-enhanced cardiac CT using dual-source PCCT (NAEOTOM Alpha, Siemens). Patients were divided into two age groups (50-60 years and 70-80 years). The left ventricular myocardium was segmented semi-automatically, and radiomics features were extracted using pyradiomics to compare myocardial texture features. Epicardial adipose tissue (EAT) density, thickness, and other clinical parameters were recorded. Statistical analysis was conducted with R and a Python-based random forest classifier. : The study assessed 90 patients (50-60 years, = 54, and 70-80 years, = 36) with a mean age of 63.6 years. No significant differences were found in mean Agatston score, gender distribution, or conditions like hypertension, diabetes, hypercholesterolemia, or nicotine abuse. EAT measurements showed no significant differences. The Random Forest Classifier achieved a training accuracy of 0.95 and a test accuracy of 0.74 for age group differentiation. Wavelet-HLH_glszm_GrayLevelNonUniformity was a key differentiator. : Radiomics texture features of the left ventricular myocardium outperformed conventional parameters like EAT density and thickness in differentiating age groups, offering a potential imaging biomarker for myocardial aging. Radiomics analysis of left ventricular myocardium offers a unique opportunity to visualize changes in myocardial texture during aging and could serve as a cardiac risk predictor.
心血管疾病是全球死亡的主要原因，65岁以上患者中80%患有冠心病。了解衰老的心血管结构至关重要。光子计数计算机断层扫描（PCCT）提供了更高的空间和时间分辨率以及更好的信噪比，能够在临床常规中进行纹理分析。检测衰老左心室心肌的结构变化可能有助于预测心血管风险。：在这项经机构审查委员会（IRB）批准的单中心回顾性研究中，90名患者使用双源PCCT（西门子NAEOTOM Alpha）进行了心电图门控对比增强心脏CT检查。患者分为两个年龄组（50 - 60岁和70 - 80岁）。左心室心肌进行半自动分割，并使用pyradiomics提取放射组学特征以比较心肌纹理特征。记录心包脂肪组织（EAT）密度、厚度和其他临床参数。使用R和基于Python的随机森林分类器进行统计分析。：该研究评估了90名患者（50 - 60岁，n = 54，70 - 80岁，n = 36），平均年龄为63.6岁。在平均阿加斯顿评分、性别分布或高血压、糖尿病、高胆固醇血症或尼古丁滥用等情况方面未发现显著差异。EAT测量结果无显著差异。随机森林分类器在年龄组区分方面的训练准确率为0.95，测试准确率为0.74。小波 - HLH_glszm_灰度级非均匀性是关键的区分因素。：左心室心肌的放射组学纹理特征在区分年龄组方面优于EAT密度和厚度等传统参数，为心肌衰老提供了一种潜在的成像生物标志物。左心室心肌的放射组学分析为可视化衰老过程中心肌纹理变化提供了独特机会，并且可以作为心脏风险预测指标。
