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Radiomic features of Epicardial Adipose Tissue in AF progression
Session:
Comunicações Orais - Sessão 10 - Imagem em Cardiologia
Speaker:
Inês Amorim Cruz
Congress:
CPC 2024
Topic:
B. Imaging
Theme:
03. Imaging
Subtheme:
03.6 Cross-Modality and Multi-Modality Imaging Topics
Session Type:
Comunicações Orais
FP Number:
---
Authors:
Inês Amorim Cruz; Fábio Sousa-Nunes; Sílvia O. Diaz; João Pedrosa; Inês Neves; Rafael Teixeira; Francisca Saraiva; João Almeida; João Primo; Francisco Sampaio; António S. Barros; Ricardo Fontes-Carvalho
Abstract
<p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-size:10.5pt">Background:</span></strong><span style="font-size:10.5pt"> Obesity is </span><span style="font-size:10.5pt">an </span><span style="font-size:10.5pt">important risk </span><span style="font-size:10.5pt">factor</span><span style="font-size:10.5pt"> for atrial fibrillation (AF).</span> <span style="font-size:10.5pt">Improved</span><span style="font-size:10.5pt"> imaging </span><span style="font-size:10.5pt">methods now allow researchers to examine individual</span><span style="font-size:10.5pt"> adipose tissue </span><span style="font-size:10.5pt">storage sites in greater detail.</span> <span style="font-size:10.5pt">Epicardial adipose tissue (EAT) is a metabolically active tissue unique in its unobstructed proximity to the heart, which could influence the progression of AF.</span> <span style="font-size:10.5pt">Radiomics is a </span><span style="font-size:10.5pt">rapidly developing method of analyzing medical images that allows </span><span style="font-size:10.5pt">for </span><span style="font-size:10.5pt">noninvasive evaluation of </span><span style="font-size:10.5pt">tissue</span><span style="font-size:10.5pt">.</span> <span style="font-size:10.5pt">Our objective was to investigate the </span><span style="font-size:10.5pt">radiomic </span><span style="font-size:10.5pt">characteristics</span><span style="font-size:10.5pt"> of EAT</span><span style="font-size:10.5pt"> that </span><span style="font-size:10.5pt">could </span><span style="font-size:10.5pt">potentially distinguish</span><span style="font-size:10.5pt"> between paroxysmal and persistent AF.</span></span></span></span></p> <p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-size:10.5pt">Methods:</span></strong><span style="font-size:10.5pt"> We included all consecutive patients </span><span style="font-size:10.5pt">who underwent</span><span style="font-size:10.5pt"> AF ablation (2017-2021) who performed a CT scan prior to the procedure. </span><span style="font-size:10.5pt">The</span><span style="font-size:10.5pt"> EAT was segmented using a U-Net framework</span><span style="font-size:10.5pt">, which is</span><span style="font-size:10.5pt"> a </span><span style="font-size:10.5pt">type of convolutional neural network (CNN) designed specifically for image segmentation. This segmentation</span><span style="font-size:10.5pt"> was </span><span style="font-size:10.5pt">conducted without the use of contrast agents, and a total of 851 radiomic features were extracted </span><span style="font-size:10.5pt">using the Pyradiomics </span><span style="font-size:10.5pt">software. The radiomic </span><span style="font-size:10.5pt">features can be </span><span style="font-size:10.5pt">classified</span><span style="font-size:10.5pt"> into three main </span><span style="font-size:10.5pt">categories:</span><span style="font-size:10.5pt"> shape</span><span style="font-size:10.5pt">,</span><span style="font-size:10.5pt"> first</span><span style="font-size:10.5pt">-</span><span style="font-size:10.5pt">order (intensity</span><span style="font-size:10.5pt">),</span><span style="font-size:10.5pt"> and texture features. We </span><span style="font-size:10.5pt">conducted</span><span style="font-size:10.5pt"> an exploratory analysis</span><span style="font-size:10.5pt"> using</span><span style="font-size:10.5pt"> a univariate logistic regression model</span><span style="font-size:10.5pt">, while simultaneously adjusting for</span><span style="font-size:10.5pt"> age, </span><span style="font-size:10.5pt">sex</span><span style="font-size:10.5pt">, BMI, hypertension, diabetes</span><span style="font-size:10.5pt">,</span><span style="font-size:10.5pt"> and dilated LA</span><span style="font-size:10.5pt">. This analysis used </span><span style="font-size:10.5pt">non-transformed radiomic features.</span></span></span></span></p> <p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-size:10.5pt">Results:</span></strong><span style="font-size:10.5pt"> A total of 533 patients were included, </span><span style="font-size:10.5pt">109 (20 %) </span><span style="font-size:10.5pt">of whom had persistent AF.</span> <span style="font-size:10.5pt">Compared to patients with paroxysmal AF, </span><span style="font-size:10.5pt">those </span><span style="font-size:10.5pt">with persistent AF had similar age, </span><span style="font-size:10.5pt">sex</span><span style="font-size:10.5pt">, diagnostic duration, and comorbidities, except for heart failure.</span> <span style="font-size:10.5pt">Patients with persistent AF exhibited greater </span><span style="font-size:10.5pt">shape-related features</span><span style="font-size:10.5pt">, including</span><span style="font-size:10.5pt"> EAT volume (Mesh Volume, </span><span style="font-size:10.5pt">OR</span><span style="font-size:10.5pt"> 1.38 [95% CI, 1.07-1.79</span><span style="font-size:10.5pt">],</span><span style="font-size:10.5pt"> p=0.015), maximum 3D diameter (</span><span style="font-size:10.5pt">OR</span><span style="font-size:10.5pt"> 1.32 [95% CI, 1.02-1.72</span><span style="font-size:10.5pt">],</span><span style="font-size:10.5pt"> p=0.034</span><span style="font-size:10.5pt">),</span><span style="font-size:10.5pt"> and the smallest axis length of</span><span style="font-size:10.5pt"> </span><span style="font-size:10.5pt">EAT (Least Axis Length, </span><span style="font-size:10.5pt">OR</span><span style="font-size:10.5pt"> 1.76 [95% CI, 1.35-2.33</span><span style="font-size:10.5pt">],</span><span style="font-size:10.5pt"> p<0.001). </span><span style="font-size:10.5pt">Additionally, the</span><span style="font-size:10.5pt"> texture heterogeneity of EAT was </span><span style="font-size:10.5pt">found to be </span><span style="font-size:10.5pt">higher in patients with persistent AF, </span><span style="font-size:10.5pt">characterized by </span><span style="font-size:10.5pt">dissimilar intensity gray-level values (Gray-Level Non-Uniformity). </span><span style="font-size:10.5pt">On the other hand, the</span><span style="font-size:10.5pt"> EAT coarseness, </span><span style="font-size:10.5pt">which signifies a</span><span style="font-size:10.5pt"> more uniform texture, was lower in patients with persistent AF (NGTDM-Coarseness, </span><span style="font-size:10.5pt">OR</span><span style="font-size:10.5pt"> 0.60 [95% CI, 0.41-0.84] p=0.005).</span> <span style="font-size:10.5pt">In addition</span><span style="font-size:10.5pt">, a higher magnitude of attenuation values (First-order-Total Energy, </span><span style="font-size:10.5pt">OR</span><span style="font-size:10.5pt"> 1.31 [95% CI, 1.02-1.68] <em>p</em>=0.037) was associated with persistent AF.</span></span></span></span></p> <p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-size:10.5pt">Conclusion:</span></strong> <span style="font-size:10.5pt">In this </span><span style="font-size:10.5pt">group</span><span style="font-size:10.5pt"> of patients with </span><span style="font-size:10.5pt">atrial fibrillation (</span><span style="font-size:10.5pt">AF</span><span style="font-size:10.5pt">) who received </span><span style="font-size:10.5pt">catheter ablation, </span><span style="font-size:10.5pt">it was found that </span><span style="font-size:10.5pt">both </span><span style="font-size:10.5pt">the</span><span style="font-size:10.5pt"> volume</span><span style="font-size:10.5pt"> of epicardial adipose tissue (EAT) and the</span><span style="font-size:10.5pt"> higher </span><span style="font-size:10.5pt">degree</span><span style="font-size:10.5pt"> of attenuation values </span><span style="font-size:10.5pt">within it, as well as the variability in</span><span style="font-size:10.5pt"> tissue </span><span style="font-size:10.5pt">composition</span><span style="font-size:10.5pt"> of</span><span style="font-size:10.5pt"> </span><span style="font-size:10.5pt">EAT</span><span style="font-size:10.5pt">,</span><span style="font-size:10.5pt"> were </span><span style="font-size:10.5pt">related to the persistence of</span><span style="font-size:10.5pt"> AF.</span></span></span></span></p>
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