Possibilities of contrast-enhanced ultrasound in the early diagnosis of clinically significant angionephrosclerosis in patients with type 2 diabetes mellitus: a prospective study

INTRODUCTION: The instrumental methods currently used are either ionizing or invasive, which prevents their potential application in dynamic monitoring. Contrast-enhanced ultrasound (CEUS) can provide better assessment of renal blood flow.OBJECTIVE: Increasing the diagnostic and prognostic value of ultrasound using echo contrast in the early diagnosis of clinically significant angioedema in patients with type 2 diabetes mellitus.MATERIALS AND METHODS: From 2019 to 2023 On the basis of the Clinical Hospital No. 1 of Smolensk and the problem research laboratory «Diagnostic studies and minimally invasive technologies» of the Federal State Budgetary Educational Institution of Higher Education SSMU of the Ministry of Health of Russia, 166 people were examined (118 people — the main group (Group 1 — patients with type 2 diabetes without diabetic angioedema; group 2 — patients with type 2 diabetes with diabetic angioedema in the subcompensation stage; Group 3 — patients with type 2 diabetes with severe diabetic angioedema in the decompensation stage) and 48 people — the control group). All patients were examined according to a single diagnostic algorithm, which included 8 stages. Abstract methods — contrast-enhanced CT, dynamic nephroscintigraphy.DISCUSSION: Unlike CT and MRI, CEUS is not nephrotoxic, which allows it to be used in patients with reduced renal function, including for multiple dynamic monitoring. This is relevant for patients with type 2 diabetes, because as the disease progresses, it is important to assess preclinical signs of diabetic angioedema, namely, intrarenal blood flow. The use of CEUS in a comprehensive diagnostic algorithm for diabetic kidney disease makes it possible to identify preclinical changes in diabetic angioedema. CONCLUSION: Contrast-enhanced ultrasound is a reliable and safe method of diagnosing kidney pathology, which allows predicting the clinical course of the underlying disease.