Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score-First Results of a Photon-Counting CT.
Isabelle AyxHishan TharmaseelanAlexander HertelDominik NörenbergDaniel P OverhoffLukas T RotkopfPhilipp RiffelStefan O SchoenbergMatthias Frank FroelichPublished in: Diagnostics (Basel, Switzerland) (2022)
The coronary artery calcium score is an independent risk factor of the development of adverse cardiac events. The severity of coronary artery calcification may influence the myocardial texture. Due to higher spatial resolution and signal-to-noise ratio, new CT technologies such as PCCT may improve the detection of texture alterations depending on the severity of coronary artery calcification. In this retrospective, single-center, IRB-approved study, left ventricular myocardium was segmented and radiomics features were extracted using pyradiomics. The mean and standard deviation with the Pearson correlation coefficient for correlations of features were calculated and visualized as boxplots and heatmaps. Random forest feature selection was performed. Thirty patients (26.7% women, median age 58 years) were enrolled in the study. Patients were divided into two subgroups depending on the severity of coronary artery calcification (Agatston score 0 and Agatston score ≥ 100). Through random forest feature selection, a set of four higher-order features could be defined to discriminate myocardial texture between the two groups. When including the additional Agatston 1-99 groups as a validation, a severity-associated change in feature intensity was detected. A subset of radiomics features texture alterations of the left ventricular myocardium was associated with the severity of coronary artery calcification estimated by the Agatston score.
Keyphrases
- coronary artery
- left ventricular
- contrast enhanced
- pulmonary artery
- end stage renal disease
- chronic kidney disease
- ejection fraction
- magnetic resonance imaging
- computed tomography
- machine learning
- newly diagnosed
- aortic stenosis
- magnetic resonance
- heart failure
- acute myocardial infarction
- deep learning
- prognostic factors
- lymph node metastasis
- risk factors
- type diabetes
- emergency department
- pregnant women
- insulin resistance
- cross sectional
- patient reported
- patient reported outcomes
- positron emission tomography
- polycystic ovary syndrome
- quantum dots
- transcatheter aortic valve replacement
- neural network