Kidney MRI Texture Analysis—A Universal Assessment of Kidney State and Function?

Introduction: Currently, chronic kidney disease (CKD) is detected based on glomerular filtration rate (GFR), proteinuria levels or kidney biopsy. However, the development of MRI techniques and AI algorithms gives hope to the assessment of CKD activity and kidney function with profound MRI image analysis. Methods: MRI images from healthy volunteers with no history of CKD were compared with those from CKD patients who had undergone both kidney MRI and kidney biopsy; the latter group was also divided into two subgroups based on CKD histopathological activity. Patients from both groups were scanned using either a 1.5 T or 3 T MRI scanner following sequential allocation (nine healthy controls and 28 CKD patients and 11 healthy volunteers and 43 CKD patients respectively for each scanner). Results: The final algorithm based on T1-weighted, T2-weighted and DWI images was able to distinguish patients with sensitivity ranging 77.78–87.50%, specificity 86.67–94.12% and precision 77.78–87.50%. Features of T1-weighted images and of T2-weighted images were found to correlate strongly with GFR with coefficients ranging from −0.5922 to −0.7090 and from 0.6126 to 0.6380, respectively. Conclusions: MRI image texture analysis may be suitable for assessing CKD activity, irrespective of the type of MRI scanner used. Furthermore, MRI image texture features correlate with eGFR values.