Evidence map›Paper›PMID 41816070›Full record

ArticleQuantitative imaging in medicine and surgery2026

Association between CT-based adrenal gland volume and 10-year cardiovascular disease risk in patients with diabetes mellitus.

Caihong Li, Xiangjun Chen, Yi Li, Shumin Yang, Jinbo Hu, Haiqin Deng, Xue Mo, Yun Mao

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Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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8 authors.

Caihong Li *Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xiangjun Chen *Department of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yi Li *Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Shumin YangDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jinbo HuDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Haiqin DengDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xue MoDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yun MaoDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0000-0002-3326-4729

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hyperactivity of the hypothalamic-pituitary-adrenal (HPA) axis is an independent risk factor for cardiovascular disease (CVD). Adrenal gland volume reflects disturbances in glucose-lipid metabolism and HPA axis activity, but its relationship with CVD risk remains unclear. This study aimed to investigate the association between adrenal gland volume and estimated 10-year CVD risk in patients with diabetes mellitus (DM). Methods: A total of 223 patients with DM (30-74 years) without prior CVD were retrospectively included. Adrenal gland volume was measured from non-contrast computed tomography (CT) images using a three-dimensional no new U-net (nnU)-Net deep learning algorithm. The 10-year CVD risk was estimated using the Framingham Risk Score (FRS) and categorized into low-to-intermediate risk (<20%) and high risk (≥20%) groups. Spearman correlation and multivariable linear regression were used to assess the associations of volume with metabolic parameters and the FRS, whereas multivariable binary logistic regression evaluated its association with high CVD risk. Receiver operating characteristic (ROC) curve analysis determined the predictive performance of volume for high CVD risk. Results: In multivariable linear regression, total volume was positively associated with male sex (P=0.036), waist circumference (P=0.044), and hypertension (P=0.012), and negatively associated with high-density lipoprotein cholesterol (HDL-C; P=0.020). After adjustment for confounders, total volume remained significantly correlated with FRS [β=0.085, 95% confidence interval (CI): 0.003-0.168, P=0.042]. Volume was significantly larger in the high risk group compared to the low-to-intermediate risk group (P<0.001). Moreover, volume was independently associated with high CVD risk [left: odds ratio (OR) =1.777, 95% CI: 1.179-2.959; right: OR =2.053, 95% CI: 1.239-3.899; total: OR =1.467, 95% CI: 1.139-2.021]. The area under the curve (AUC) for total volume in predicting high CVD risk was 0.713 (95% CI: 0.643-0.783). At the optimal cut-off value of 9.04 cm3, the sensitivity and specificity were 70.3% and 61.3%, respectively. Conclusions: Adrenal gland volume is independently associated with high estimated 10-year CVD risk in patients with diabetes and may potentially provide imaging-based support for the early identification of high-risk individuals.

Indexed as

Adrenal gland volumecardiovascular disease risk (CVD risk)diabetes mellitus (DM)fully automated segmentation

Identifiers

PMID41816070
PMCPMC12971375

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