Quantitative study and related factors analysis of sciatic neuropathy in type 2 diabetes mellitus patients by elastic...

The incidence of diabetic peripheral neuropathy (DPN) is increasing every year for type 2 diabetes mellitus (T2DM) patients, and diabetic polyneuropathy is a common type.

To quantify and analyze the factors associated with diabetic polyneuropathy using the virtual tissue imaging quantification (VTIQ) technique.

182 patients with T2DM, 137 patients with diabetic polyneuropathy, and 198 healthy volunteers were included in this retrospective cross-sectional diagnostic study. Sciatic neuropathy was evaluated through Doppler ultrasound examination with a VTIQ quantitative analysis system to acquire elastic modulus, cross-sectional area (CSA) and shear wave velocity (SWV). Nerve conduction velocity (NCV) was also evaluated via neurophysiological examination. Logistic regression was used to analyze odds ratios (OR) related diabetic polyneuropathy. The diagnostic accuracy of the VTIQ technique-acquired index on diabetic polyneuropathy was analyzed using the receiver operating characteristic (ROC) curve.

VTIQ technique-acquired indexes all differed significantly among three study groups, among which Elastic modulus and CSA were independently related to diabetic polyneuropathy risk according to the logistic regression analysis. NCV was also an independent risk factor for diabetic polyneuropathy. ROC analysis revealed that Elastic modulus, CSA and NCV can distinguish diabetic polyneuropathy patients from T2DM cases with the AUC of 0.797, 0.654 and 0.775 respectively. But their combination achieved the highest diagnostic value (AUC = 0.883). CSA and SWV of the sciatic nerve are positively correlated with visual analog scale (VAS) scores.

VTIQ technology contributes to the diagnosis of diabetic polyneuropathy, it can improve the diagnostic value of neurophysiological examination on sciatic neuropathy for T2DM patients.