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Epicardial and thoracic subcutaneous fat texture analysis in patients undergoing cardiac CT
INTRODUCTION: The aim of our study was to evaluate the feasibility of texture analysis of epicardial fat (EF) and thoracic subcutaneous fat (TSF) in patients undergoing cardiac CT (CCT). MATERIALS AND METHODS: We compared a consecutive population of 30 patients with BMI ≤25 kg/m(2) (Group A, 60.6 ± ...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196784/ https://www.ncbi.nlm.nih.gov/pubmed/37215845 http://dx.doi.org/10.1016/j.heliyon.2023.e15984 |
Sumario: | INTRODUCTION: The aim of our study was to evaluate the feasibility of texture analysis of epicardial fat (EF) and thoracic subcutaneous fat (TSF) in patients undergoing cardiac CT (CCT). MATERIALS AND METHODS: We compared a consecutive population of 30 patients with BMI ≤25 kg/m(2) (Group A, 60.6 ± 13.7 years) with a control population of 30 patients with BMI >25 kg/m(2) (Group B, 63.3 ± 11 years). A dedicated computer application for quantification of EF and a texture analysis application for the study of EF and TSF were employed. RESULTS: The volume of EF was higher in group B (mean 116.1 cm(3) vs. 86.3 cm(3), p = 0.014), despite no differences were found neither in terms of mean density (−69.5 ± 5 HU vs. −68 ± 5 HU, p = 0.28), nor in terms of quartiles distribution (Q1, p = 0.83; Q2, p = 0.22, Q3, p = 0.83, Q4, p = 0.34). The discriminating parameters of the histogram class were mean (p = 0.02), 0,1st (p = 0.001), 10(th) (p = 0.002), and 50(th) percentiles (p = 0.02). DifVarnc was the discriminating parameter of the co-occurrence matrix class (p = 0.007). The TSF thickness was 15 ± 6 mm in group A and 19.5 ± 5 mm in group B (p = 0.003). The TSF had a mean density of −97 ± 19 HU in group A and −95.8 ± 19 HU in group B (p = 0.75). The discriminating parameters of texture analysis were 10(th) (p = 0.03), 50(th) (p = 0.01), 90(th) percentiles (p = 0.04), S(0,1)SumAverg (p = 0.02), S(1,-1)SumOfSqs (p = 0.02), S(3,0)Contrast (p = 0.03), S(3,0)SumAverg (p = 0.02), S(4,0)SumAverg (p = 0.04), Horzl_RLNonUni (p = 0.02), and Vertl_LngREmph (p = 0.0005). CONCLUSIONS: Texture analysis provides distinctive radiomic parameters of EF and TSF. EF and TSF had different radiomic features as the BMI varies. |
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