MR biosignatures of uremia-induced tissue alterations in patients with chronic kidney disease and hemodialysis patients

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Chronic kidney disease (CKD) is a global health care burden with an increasing prevalence. CKD finally results in end-stage renal disease which requires renal replacement therapy such as hemodialysis or kidney transplantation. Patients with CKD face a very high risk of cardiovascular morbidity and mortality, often induced by severe electrolyte disturbance. Currently, diagnostic approaches to determine kidney disease severity are restricted to chemical analysis of body fluids (mainly blood and urine samples) together with the assessment of patient’s body weight, edema and blood pressure. Chronic alterations on the tissue level, e.g. electrolyte homeostasis, accumulation of uremic toxins, changes in tissue pH, and local edema therefore escape the clinical evaluation. MR-biosignatures might bridge this gap by revealing tissue specific MR “finger prints” caused by renal insufficiency. In our clinical study we intend to measure muscle as well as brain tissue in CKD patients and compare this data with age- and gender matched healthy controls. We intend to detect the pathophysiology of common complains, like muscle weakness or cognitive impairment frequently occurring in CKD patients. Additionally, we will measure patients on maintenance hemodialysis treatment before and after their regular dialysis procedure. The expected short-term changes in MR-biosignatures might explain symptoms such as severe muscle cramps or dizziness/nausea which occur during dialysis treatment. For this approach a combination of several MRI techniques will be developed in close cooperation with projects A1-A3, including: 23Na and 39K MRI, Chemical Exchange Saturation Transfer (CEST), Quantitative Susceptibility Mapping (QSM), and diffusion-weighted MRI. We plan to determine microstructural differences due to local edema, changes in fat-/ fluid content, alterations in electrolyte distribution as well as differing protein/ glycosaminoglycan (GAG) content or shifts in pH values in both tissues. This information will be analyzed in project S, also by means of artificial intelligence. We expect to find alterations in tissue specific MR-biosignatures of renal patients that differ from urine or blood analysis. In future this knowledge might help clinicians to determine the optimal time for initiating renal replacement therapy and might reduce HD associated symptoms by optimizing dialysis treatment regime.