In vivo resting state MRI of the kidney predicts the development of fibrosis after acute kidney injury, and correlates with nephron number

Motivation: Current clinical tools are insensitive to detect early changes in kidney structure and function during chronic kidney disease (CKD) progression. Goal(s): Resting state MRI (rsMRI) has been proposed to detect and map spontaneous physiological fluctuations in the kidney. Here, we show rsMRI predicts CKD progression after acute kidney injury (AKI) and investigate its physiological mechanisms. Approach: We compared rsMRI spectra with clinical metrics and pathologic assessment following mild AKI. We demonstrate that rsMRI is specifically sensitive to tubuloglomerular feedback and directly correlates with nephron number in healthy rats. Results: rsMRI predicts CKD progression after AKI and reflects nephron number in vivo. Impact: rsMRI of the kidney provides novel physiological biomarkers that may facilitate early detection of risk and progression of chronic kidney disease (CKD) after acute kidney injury (AKI).