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<p>To evaluate the diagnostic value of the combined model constructed by viscosity imaging (Vi), shear wave elastography (SWE) and high-frequency ultrasound (HFUS) for various clinical stages of diabetic peripheral neuropathy (DPN). A prospective study was conducted between January 2025 and March 2026, including 102 patients with type 2 diabetes mellitus (T2DM) and 60 healthy volunteers as controls. Patients were divided into four groups: Group I, confirmed DPN, with peripheral nerve‑related symptoms and signs and abnormal nerve conduction study (NCS) results; Group II, subclinical DPN, without DPN‑related symptoms or signs but with abnormalities detected only by NCS or small fiber nerve function tests; Group III, T2DM patients with normal nerve conduction studies; and Group IV, healthy controls. HFUS was used to measure the cross‑sectional area (CSA) of the tibial nerve; SWE was performed to evaluate shear wave velocity (Cs, m/s); and Vi was applied to obtain viscosity parameters (Vi, Pa·s). Intergroup differences in these parameters were compared, and seven diagnostic models were constructed based on CSA, Csmean, and Vimean, respectively. The diagnostic value of each model for grading the severity of DPN was assessed. The diagnostic performance of individual parameters and combined models was evaluated through receiver operating characteristic curve (ROC curve) analysis, and the differences in the area under the curve were compared using the DeLong test. In the diagnosis of subclinical DPN, Vimean showed the highest diagnostic value among all single parameters. The combined model incorporating Vimean exhibited diagnostic performance comparable to Vimean alone and superior to CSA or Csmean alone. Vimean and Csmean showed similar diagnostic efficacy in the diagnosis of definite diabetic peripheral neuropathy, both being significantly better than CSA. Comprehensive diagnostic models demonstrated superior overall diagnostic value compared with single‑parameter models. The three‑parameter combination of CSA, Vimean, and Csmean achieved the highest diagnostic efficacy for confirmed DPN. Vimean shows relatively promising diagnostic performance for subclinical DPN and may serve as a potential screening indicator for this high-risk population. For confirmed DPN, multiparameter models incorporating CSA may potentially improve diagnostic efficacy. Among these models, the combined model of CSA, Csmean and Vimean appears to yield relatively better overall diagnostic value.</p>

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Ultrasound viscosity imaging for stratified diagnosis of diabetic peripheral neuropathy: A prospective clinical study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月15日

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  • Siqi Zhang,
  • Qing Xiao,
  • Yuhao Jia,
  • Lijun Zhou,
  • Xin Luo,
  • Hailin Shao

摘要

To evaluate the diagnostic value of the combined model constructed by viscosity imaging (Vi), shear wave elastography (SWE) and high-frequency ultrasound (HFUS) for various clinical stages of diabetic peripheral neuropathy (DPN). A prospective study was conducted between January 2025 and March 2026, including 102 patients with type 2 diabetes mellitus (T2DM) and 60 healthy volunteers as controls. Patients were divided into four groups: Group I, confirmed DPN, with peripheral nerve‑related symptoms and signs and abnormal nerve conduction study (NCS) results; Group II, subclinical DPN, without DPN‑related symptoms or signs but with abnormalities detected only by NCS or small fiber nerve function tests; Group III, T2DM patients with normal nerve conduction studies; and Group IV, healthy controls. HFUS was used to measure the cross‑sectional area (CSA) of the tibial nerve; SWE was performed to evaluate shear wave velocity (Cs, m/s); and Vi was applied to obtain viscosity parameters (Vi, Pa·s). Intergroup differences in these parameters were compared, and seven diagnostic models were constructed based on CSA, Csmean, and Vimean, respectively. The diagnostic value of each model for grading the severity of DPN was assessed. The diagnostic performance of individual parameters and combined models was evaluated through receiver operating characteristic curve (ROC curve) analysis, and the differences in the area under the curve were compared using the DeLong test. In the diagnosis of subclinical DPN, Vimean showed the highest diagnostic value among all single parameters. The combined model incorporating Vimean exhibited diagnostic performance comparable to Vimean alone and superior to CSA or Csmean alone. Vimean and Csmean showed similar diagnostic efficacy in the diagnosis of definite diabetic peripheral neuropathy, both being significantly better than CSA. Comprehensive diagnostic models demonstrated superior overall diagnostic value compared with single‑parameter models. The three‑parameter combination of CSA, Vimean, and Csmean achieved the highest diagnostic efficacy for confirmed DPN. Vimean shows relatively promising diagnostic performance for subclinical DPN and may serve as a potential screening indicator for this high-risk population. For confirmed DPN, multiparameter models incorporating CSA may potentially improve diagnostic efficacy. Among these models, the combined model of CSA, Csmean and Vimean appears to yield relatively better overall diagnostic value.