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.
Humans
Male
Female
Diabetes Mellitus, Type 2
/ complications
Pericardium
/ diagnostic imaging
Middle Aged
Deep Learning
Adipose Tissue
/ diagnostic imaging
Aged
Vascular Calcification
/ diagnostic imaging
Coronary Artery Disease
/ diagnostic imaging
Predictive Value of Tests
Automation
Diabetic Angiopathies
/ diagnostic imaging
Risk Assessment
Radiographic Image Interpretation, Computer-Assisted
Computed Tomography Angiography
Adiposity
Coronary Angiography
Risk Factors
Reproducibility of Results
Prognosis
Epicardial Adipose Tissue
CAC score
Cardiac computed tomography
Deep learning
Epicardial adipose tissue
Type 2 diabetes
Journal
Cardiovascular diabetology
ISSN: 1475-2840
Titre abrégé: Cardiovasc Diabetol
Pays: England
ID NLM: 101147637
Informations de publication
Date de publication:
03 Sep 2024
03 Sep 2024
Historique:
received:
01
07
2024
accepted:
19
08
2024
medline:
4
9
2024
pubmed:
4
9
2024
entrez:
3
9
2024
Statut:
epublish
Résumé
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). 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. 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. Fully-automated EAT volume quantification could provide useful information about the risk of both renal and macrovascular complications in T2D patients.
Sections du résumé
BACKGROUND
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
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
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
CONCLUSIONS
Fully-automated EAT volume quantification could provide useful information about the risk of both renal and macrovascular complications in T2D patients.
Identifiants
pubmed: 39227844
doi: 10.1186/s12933-024-02411-y
pii: 10.1186/s12933-024-02411-y
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
328Informations de copyright
© 2024. The Author(s).
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