Bénédicte Gaborit, Jean Baptiste Julla, Joris Fournel, Patricia Ancel, Astrid Soghomonian, Camille Deprade, Adèle Lasbleiz, Marie Houssays, Badih Ghattas, Pierre Gascon, Maud Righini, Frédéric Matonti, Nicolas Venteclef, Louis Potier, Jean François Gautier, Noémie Resseguier, Axel Bartoli, Florian Mourre, Patrice Darmon, Alexis Jacquier, Anne Dutour
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Patients included who had undergone cardiac CT for CAC (Coronary Artery Calcium) scoring after inclusion (n = 1253) were tested with a validated deep learning segmentation pipeline for EAT volume quantification.</p><p><strong>Results: </strong>Median age of the study population was 61 [54;67], with a majority of men (57%) a median duration of the disease 11 years [5;18] and a mean HbA1c of7.8 ± 1.4%. EAT was significantly associated with all traditional CV risk factors. EAT volume significantly increased with chronic kidney disease (CKD vs no CKD: 87.8 [63.5;118.6] vs 82.7 mL [58.8;110.8], p = 0.008), coronary artery disease (CAD vs no CAD: 112.2 [82.7;133.3] vs 83.8 mL [59.4;112.1], p = 0.0004, peripheral arterial disease (PAD vs no PAD: 107 [76.2;141] vs 84.6 mL[59.2; 114], p = 0.0005 and elevated CAC score (> 100 vs < 100 AU: 96.8 mL [69.1;130] vs 77.9 mL [53.8;107.7], p < 0.0001). By contrast, EAT volume was neither associated with DR, nor with peripheral neuropathy. We further evidenced a subgroup of patients with high EAT volume and a null CAC score. Interestingly, this group were more likely to be composed of young women with a high BMI, a lower duration of T2D, a lower prevalence of microvascular complications, and a higher inflammatory profile.</p><p><strong>Conclusions: </strong>Fully-automated EAT volume quantification could provide useful information about the risk of both renal and macrovascular complications in T2D patients.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":null,"pages":null},"PeriodicalIF":8.5000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373274/pdf/","citationCount":"0","resultStr":"{\"title\":\"Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.\",\"authors\":\"Bénédicte Gaborit, Jean Baptiste Julla, Joris Fournel, Patricia Ancel, Astrid Soghomonian, Camille Deprade, Adèle Lasbleiz, Marie Houssays, Badih Ghattas, Pierre Gascon, Maud Righini, Frédéric Matonti, Nicolas Venteclef, Louis Potier, Jean François Gautier, Noémie Resseguier, Axel Bartoli, Florian Mourre, Patrice Darmon, Alexis Jacquier, Anne Dutour\",\"doi\":\"10.1186/s12933-024-02411-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).</p><p><strong>Methods: </strong>EPIDIAB is a post hoc analysis from the AngioSafe T2D study, which is a multicentric study aimed at determining the safety of antihyperglycemic drugs on retina and including patients with T2D screened for diabetic retinopathy (DR) (n = 7200) and deeply phenotyped for MVC. 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引用次数: 0
摘要
研究背景本研究（EPIDIAB）旨在评估心外膜脂肪组织（EAT）与2型糖尿病（T2D）微血管和大血管并发症（MVC）之间的关系：该研究是一项多中心研究，旨在确定降糖药物对视网膜的安全性，研究对象包括筛查出糖尿病视网膜病变（DR）的 2 型糖尿病患者（n = 7200），并对 MVC 进行了深入的表型分析。对纳入后接受心脏 CT 进行 CAC（冠状动脉钙化）评分的患者（n = 1253）进行了测试，并使用经过验证的深度学习分割管道对 EAT 体积进行量化：研究人群的中位年龄为 61 [54;67]，男性占多数（57%），中位病程为 11 年 [5;18]，平均 HbA1c 为 7.8 ± 1.4%。EAT 与所有传统的冠心病风险因素都有明显关联。慢性肾脏病（CKD vs 无 CKD：87.8 [63.5;118.6] vs 82.7 mL [58.8;110.8], p = 0.008）、冠状动脉疾病（CAD vs 无 CAD：112.2 [82.7;133.3] vs 83.8 mL [59.4;112.1]，p = 0.0004；外周动脉疾病（PAD vs 无 PAD：107 [76.2;141] vs 84.6 mL[59.2;114]，p = 0.0005）；CAC 评分升高（> 100 vs 结论：CAC 评分升高可能是由于外周动脉疾病所致）：全自动 EAT 容量定量可提供有关 T2D 患者肾脏和大血管并发症风险的有用信息。
Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.
Background: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).
Methods: EPIDIAB is a post hoc analysis from the AngioSafe T2D study, which is a multicentric study aimed at determining the safety of antihyperglycemic drugs on retina and including patients with T2D screened for diabetic retinopathy (DR) (n = 7200) and deeply phenotyped for MVC. Patients included who had undergone cardiac CT for CAC (Coronary Artery Calcium) scoring after inclusion (n = 1253) were tested with a validated deep learning segmentation pipeline for EAT volume quantification.
Results: Median age of the study population was 61 [54;67], with a majority of men (57%) a median duration of the disease 11 years [5;18] and a mean HbA1c of7.8 ± 1.4%. EAT was significantly associated with all traditional CV risk factors. EAT volume significantly increased with chronic kidney disease (CKD vs no CKD: 87.8 [63.5;118.6] vs 82.7 mL [58.8;110.8], p = 0.008), coronary artery disease (CAD vs no CAD: 112.2 [82.7;133.3] vs 83.8 mL [59.4;112.1], p = 0.0004, peripheral arterial disease (PAD vs no PAD: 107 [76.2;141] vs 84.6 mL[59.2; 114], p = 0.0005 and elevated CAC score (> 100 vs < 100 AU: 96.8 mL [69.1;130] vs 77.9 mL [53.8;107.7], p < 0.0001). By contrast, EAT volume was neither associated with DR, nor with peripheral neuropathy. We further evidenced a subgroup of patients with high EAT volume and a null CAC score. Interestingly, this group were more likely to be composed of young women with a high BMI, a lower duration of T2D, a lower prevalence of microvascular complications, and a higher inflammatory profile.
Conclusions: Fully-automated EAT volume quantification could provide useful information about the risk of both renal and macrovascular complications in T2D patients.
期刊介绍：
Cardiovascular Diabetology is a journal that welcomes manuscripts exploring various aspects of the relationship between diabetes, cardiovascular health, and the metabolic syndrome. We invite submissions related to clinical studies, genetic investigations, experimental research, pharmacological studies, epidemiological analyses, and molecular biology research in this field.
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