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基于深度学习的上腺体体积计用于预测糖尿病

Eu Jeong Ku^1,2, Soon Ho Yoon³, Seung Shin Park^2,4

¹Department of Internal Medicine, Seoul National University Hospital Healthcare System Gangnam Center, Korea.

Endocrinology and metabolism (Seoul, Korea)

|June 18, 2025

概括

深度学习准确地测量上腺体体积 (AGV),将较大的体积与2型糖尿病 (T2D) 联系起来. 提升的AGV预测了未来T2D的发展,提供了一个新的预测标记.

科学领域:

内分泌学在内分泌学.
放射学放射学是一门学科.
人工智能的人工智能

背景情况:

上腺体体积 (AGV) 和2型糖尿病 (T2D) 之间的关系需要进一步阐明.
之前的研究还没有充分探索先进的成像技术的实用性,以评估这种关联.

研究的目的:

确定深度学习衍生的AGV与当前血糖状况之间的关联.
调查AGV对于发生的2型糖尿病 (T2D) 的预测价值.

主要方法:

利用来自健康检查队列 (n=9708) 的腹腔皮层CT扫描进行观察性分析.
采用3D nnU-Net深度学习算法用于自动上腺细分和体积测量 (AGV).
使用统计建模评估了AGV和T2D之间的横截面和纵向关联.

主要成果:

深度学习模型在上腺细分方面取得了高精度 (迪斯系数0.71±0.11).
与对照组相比,患有T2D的参与者表现出明显更大的AGV (男性:7.3厘米3vs6.7厘米3;女性:6.3厘米3vs5.5厘米3).
较高的AGV独立地与在中位数7.0年随访期间患T2D的风险增加有关 (aHR,1.27).

结论:

基于深度学习的AGV测量是评估上腺体大小的可靠方法.
AGV与当前的血糖状况有显著的关联,并作为发生型2糖尿病的强有力的预测因素.

关键词:

上腺腺体是什么?深度学习是一种深度学习.糖尿病,第二类糖尿病.射线图像解释,计算机辅助的计算机图像解释.

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