基础医学与临床 ›› 2025, Vol. 45 ›› Issue (2): 229-233.doi: 10.16352/j.issn.1001-6325.2025.02.0229

• 临床研究 • 上一篇    下一篇

剪切波弹性成像在糖尿病周围神经病变诊断中的应用

余玲1, 王曦2, 黄薪儒1, 陈燕1, 陶莉1, 刘红梅1, 徐晴1, 肖蓉1*   

  1. 西藏自治区人民政府驻成都办事处医院 1.超声医学科;
    2.内分泌科,四川 成都 610041
  • 收稿日期:2024-08-28 修回日期:2024-11-25 出版日期:2025-02-05 发布日期:2025-01-17
  • 通讯作者: *anicesummer2324@126.com
  • 基金资助:
    成都市医学科研项目(2022501, 2022460);西藏自治区自然科学基金(XZ202201ZR0031G, XZ202401ZR0066)

Application of shear wave elastography in the diagnosis of diabetes with peripheral neuropathy

YU Ling1, WANG Xi2, HUANG Xinru1, CHEN Yan1, TAO Li1, LIU Hongmei1, XU Qing1, XIAO Rong1*   

  1. 1. Department of Ultrasound Medicine;
    2. Department of Endocrinology,Chengdu Office Hospital of People's Government of Tibetan Autonomous Region,Chengdu 610041, China
  • Received:2024-08-28 Revised:2024-11-25 Online:2025-02-05 Published:2025-01-17
  • Contact: *anicesummer2324@126.com

摘要: 目的 探讨剪切波弹性成像(SWE)技术在糖尿病患者周围神经病变诊断中的应用价值。方法 选取西藏自治区人民政府驻成都办事处医院85例2型糖尿病(T2DM)患者,其中伴周围神经病变(DPN)患者46例,不伴周围神经病变(NDPN)患者39例。比较两组患者临床资料(性别、年龄、病程)、高频超声检测正中神经的横截面积(CSA)及剪切波弹性成像参数:平均杨氏模量值(Emean)、剪切波速度(SWV)。将上述组间比较有统计学差异的指标进行多因素Logistic回归分析,筛选出在诊断糖尿病周围神经病变中的独立预测因子,并构建组合模型。使用受试者操作特征曲线下面积(AUC)、敏感度、特异度指标来评估临床资料、高频超声及SWE所测的定量参数(CSA、Emean、SWV)单一模型及组合模型在诊断糖尿病患者周围神经病变中的的诊断效能。结果 年龄、病程、Emean、SWV及CSA在诊断糖尿病患者周围神经病变中均有统计学意义(P<0.05),AUC分别为0.658、0.754、0.839、0.822、0.736。基于病程、CSA及SWV构建的组合模型的诊断效能最高,其AUC、敏感度、特异度分别为0.887(0.800~0.946)、80.43%,84.62%。结论 基于病程、CSA、SWV构建的组合模型,在糖尿病患者周围神经病变的诊断效能较高,在临床上有良好的应用价值。

关键词: 超声, 剪切波弹性成像, 周围神经病变, 糖尿病, 正中神经

Abstract: Objective To evaluate the application of shear wave elastography (SWE) in the diagnosis of peripheral neuropathy in patients with diabetes. Methods Totally 85 patients with type 2 diabetes (T2DM) were selected from the Chengdu Office Hospital of People's Government of Tibetan Autonomous Region, including 46 patients with peripheral neuropathy (DPN) and 39 patients without peripheral neuropathy (NDPN). Compared for clinical data (gender, age, disease duration), cross-sectional area of the median nerve measured by high-frequency ultrasound (CSA) and shear wave elastography (SWE) parameters (mean Young's modulus value, Emean) and shear wave velocity (SWV) between two groups of patients. Multifactor Logistic regression analysis was carried out on the indicators between the above groups to screen independent predictors in the diagnosis of peripheral neuropathy in diabetes patients, and a combined model was constructed. The area under the operating characteristic curve(AUC), sensitivity and specificity of the subjects were used to evaluate the diagnostic efficacy of the single model and combined model of the quantitative parameters (CSA, Emean, SWV) measured by clinical data, high-frequency ultrasound and SWE in the diagnosis of peripheral neuropathy in diabetes patients. Results Age, course of disease, Emean, SWV and CSA were statistically significant in the diagnosis of peripheral neuropathy in diabetes patients(all P<0.05). AUC was 0.658, 0.754, 0.839, 0.822 and 0.736, respectively. The combination model based on disease course, CSA and SWV showed the highest diagnostic efficiency, with AUC, sensitivity, and specificity of 0.887(0.800-0.946), 80.43%, and 84.62%, respectively. Conclusions The combined model based on the course of disease, CSA and SWV have a high diagnostic efficiency in peripheral neuropathy of diabetes patients, and has good clinical application value.

Key words: ultrasound, shear wave elastography, peripheral neuropathy, diabetes, median nerve

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