Analysis of Epicardial Adipose Tissue Texture in Relation to Coronary Artery Calcification in PCCT: The EAT Signature!
Peter MundtAlexander HertelHishan TharmaseelanDominik NörenbergTheano PapavassiliuStefan O SchoenbergMatthias Frank FroelichIsabelle AyxPublished in: Diagnostics (Basel, Switzerland) (2024)
(1) Background: Epicardial adipose tissue influences cardiac biology in physiological and pathological terms. As it is suspected to be linked to coronary artery calcification, identifying improved methods of diagnostics for these patients is important. The use of radiomics and the new Photon-Counting computed tomography (PCCT) may offer a feasible step toward improved diagnostics in these patients. (2) Methods: In this retrospective single-centre study epicardial adipose tissue was segmented manually on axial unenhanced images. Patients were divided into three groups, depending on the severity of coronary artery calcification. Features were extracted using pyradiomics. Mean and standard deviation were calculated with the Pearson correlation coefficient for feature correlation. Random Forest classification was applied for feature selection and ANOVA was performed for group comparison. (3) Results: A total of 53 patients (32 male, 21 female, mean age 57, range from 21 to 80 years) were enrolled in this study and scanned on the novel PCCT. "Original_glrlm_LongRunEmphasis", "original_glrlm_RunVariance", "original_glszm_HighGrayLevelZoneEmphasis", and "original_glszm_SizeZoneNonUniformity" were found to show significant differences between patients with coronary artery calcification (Agatston score 1-99/≥100) and those without. (4) Conclusions: Four texture features of epicardial adipose tissue are associated with coronary artery calcification and may reflect inflammatory reactions of epicardial adipose tissue, offering a potential imaging biomarker for atherosclerosis detection.
Keyphrases
- coronary artery
- adipose tissue
- end stage renal disease
- chronic kidney disease
- ejection fraction
- computed tomography
- newly diagnosed
- pulmonary artery
- insulin resistance
- peritoneal dialysis
- machine learning
- oxidative stress
- deep learning
- high fat diet
- magnetic resonance imaging
- type diabetes
- mass spectrometry
- magnetic resonance
- high resolution
- risk assessment
- pulmonary embolism
- image quality