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相关概念视频

Synthesis and Regulation of Thyroid Hormones01:20

Synthesis and Regulation of Thyroid Hormones

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Low blood levels of the thyroid hormones — triiodothyronine (T3) and thyroxine (T4) — signal the hypothalamus to release the thyrotropin-releasing hormone (TRH). TRH then reaches the pituitary gland and stimulates the release of thyroid-stimulating hormone(TSH) into the bloodstream.
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The Thyroid Gland01:23

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The thyroid gland is a small, butterfly-shaped gland located in the neck and covers the anterior surface of the trachea. The gland has two lateral lobes connected by a thin tissue mass called the isthmus. Internally, each lobe comprises many small spherical structures known as thyroid follicles, surrounded by a network of blood vessels.
The follicles have a central cavity lined by simple cuboidal to squamous epithelial cells called follicular cells. These cells produce the glycoprotein...
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Functions of Thyroid Hormones01:18

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The thyroid hormone (TH) plays a pivotal role in the intricate orchestration of physiological processes, exerting profound effects on development, metabolism, and homeostasis throughout different life stages.
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相关实验视频

Updated: Sep 14, 2025

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
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多维预测模型用于评估甲状腺眼病的临床活性.

Yang Li1,2,3, Guang-Hong Zhang1,3,4, Man Tian1,2,3

  • 1Thyroid Center of Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan, China.

Frontiers in medicine
|July 23, 2025
PubMed
概括

结合临床数据,SPECT/CT成像和生物标志物的新多维模型显著改善了对甲状腺眼病 (TED) 活动的评估,优于目前的方法.

关键词:
在SPECT/CT测试中,临床活动得分临床活动得分.多维模型是一个多维模型.血清中的生物标志物甲状腺眼睛疾病 甲状腺眼睛疾病

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科学领域:

  • 眼科医生 眼科 眼科
  • 内分泌学 在内分泌学.
  • 核医学是一种核医学.

背景情况:

  • 甲状腺眼病 (TED) 是一种具有复杂炎症的自身免疫性疾病.
  • 目前的评估方法,如临床活动评分 (CAS),缺乏客观性和全面性.
  • 准确的TED活动评估对于有效的管理至关重要.

研究的目的:

  • 为TED活动评估开发一个多维预测模型.
  • 为了整合临床参数,SPECT/CT成像数据和血清生物标志物.
  • 为了提高TED活动评估的准确性和全面性.

主要方法:

  • 36名TED患者 (72只眼睛) 的回顾性研究.
  • 使用临床活动得分 (CAS) 进行活动评估.
  • 采用贝叶斯收缩回归 (BSR) 和LASSO进行变量选择.
  • 使用ROC曲线,DCA和校准曲线评估的模型.

主要成果:

  • 一个综合模型结合了临床,成像 (EX,URmax) 和生物标志物 (TRAb,RBC) 实现了91.18%的AUC.
  • 关键预测因素包括男性性别,TRAb,EX,URmax和红细胞计数.
  • 从SPECT/CT获得的URmax与疾病活性有很强的相关性;生物标志物补充成像.

结论:

  • 多维数据集成显著改善了TED活动评估,而不是单一的模式.
  • 与传统方法相比,开发的模型提供了更高的诊断准确性.
  • 建议TED管理采用整体方法,整合多样化的数据.