Noninvasive Assessment of Kidney Injury by Combining Structure and Function Using Artificial Intelligence-Based Manganese-Enhanced Magnetic Resonance Imaging.
Journal:
ACS applied materials & interfaces
PMID:
38271189
Abstract
Contrast-enhanced magnetic resonance imaging (MRI) is seriously limited in kidney injury detection due to the nephrotoxicity of clinically used gadolinium-based contrast agents. Herein, we propose a noninvasive method for the assessment of kidney injury by combining structure and function information based on manganese (Mn)-enhanced MRI for the first time. As a proof of concept, the Mn-melanin nanoprobe with good biocompatibility and excellent T1 relaxivity is applied in MRI of a unilateral ureteral obstruction mice model. The abundant renal structure and function information is obtained through qualitative and quantitative analysis of MR images, and a brand new comprehensive assessment framework is proposed to precisely identify the degree of kidney injury successfully. Our study demonstrates that Mn-enhanced MRI is a promising approach for the highly sensitive and biosafe assessment of kidney injury in vivo.