Detection of Renal Fibrosis and Prediction of Kidney Function Decline

This study will investigate the ability of renal MRI to detect fibrosis, how this correlates to renal function and how well renal MRI biomarkers can predict decline in kidney function over time. We will also assess the correlation of renal MRI and kidney function to markers of renal ageing in blood, urine and tissue samples.

Chronic kidney disease (CKD) is an increasing health concern worldwide, with an estimated prevalence of 11% in the Norwegian population. Progression of CKD and development of end-stage kidney disease is closely related to the extent and progression of renal fibrosis. Traditionally the assessment of renal fibrosis is made by renal biopsy, which in addition to diagnostics also evaluates the degree of renal fibrosis.

However, the evaluation of fibrosis from a renal biopsy is limited by the risk of complications. Due to its invasive nature, clinicians often reserve a biopsy for situations where the anticipated yield will have therapeutic value. This means the fibrotic burden is often not assessed, and information on scar burden and kidney-prognosis is lost. Furthermore, we know that fibrosis may be unequally distributed throughout the kidney. Since a biopsy only samples a small portion of kidney tissue, it is inherently susceptible to sampling bias.

In contrast, Magnetic Resonance Imaging (MRI) techniques can assess whole organ fibrotic burden. Since it is a non-invasive procedure, MRI can evaluate renal fibrosis in patients not eligible for renal biopsy. Moreover, it can be performed at several time-points for temporal renal fibrosis assessments. Recent developments in MRI techniques have made it possible to assess renal fibrosis with MRI. These techniques rely on the different biological properties of fibrotic and non-fibrotic tissues, including reduced microcirculation, restriction of water motion and reduced oxygenation. From several MRI biomarkers currently available, five show particular promise in quantifying degree of renal fibrosis: Diffusion weighted MRI, T1-mapping and T2-mapping, T1-rho and arterial-spin labelling. A recently developed MRI-patch which combines these five techniques, makes it possible to perform a MRI-scan with simultaneous measurements whilst not prolonging examination time for the patient. We hypothesize that combining these MRI-techniques will give additional information, and thus provide a better correlation to histological-assessed fibrosis than any technique alone.

Markers of renal ageing may also predict development of renal fibrosis as accelerated renal ageing trough p16INK4a pathway activation, leading to cellular senescence, is involved in the development of renal fibrosis in CKD. Senescent cells are characterized by irreversible growth arrest and express a pro-inflammatory and pro-fibrotic senescent-associated secretory phenotype (SASP). This biochemical foot print can be detected by immunohistochemistry. We aim to assess the correlation between degree of renal fibrosis and markers of renal ageing, as well as to what extent decline in kidney function can be predicted by change in markers of renal ageing.

This study will be one of the first to evaluate correlation between multiparametric MRI and morphometric estimates of renal fibrosis. We will study whether activation of pathways involved in renal ageing are associated with progressive renal fibrosis and deterioration of renal function. Finally, we will evaluate the utility of temporal measurements of renal fibrosis for prediction of renal function deterioration with a non-invasive method.

Eligibility Criteria:
Inclusion Criteria:

- Patients over 18 years of age, who is scheduled for a kidney biopsy for diagnostic purposes at the Department of Nephrology, Akershus University Hospital will be invited to participate in the study.

Exclusion Criteria:

* Patients who are not able to understand information in order to give informed consent.
* Patients with claustrophobia.
* Patients with implanted metal devices which are not compatible with MRI.