ZusammenfassungReduced kidney function and chronic kidney disease (CKD) are associated with significant morbidity and mortality, but established markers of early renal function impairment are currently lacking. Furthermore, our current understanding of the complex interplay between lifestyle, inherited and environmental factors governing physiological renal function is rather limited. MRI-derived imaging biomarkers of the kidney could be potentially informative with respect to physiological renal function or as indicators of early kidney function decline. Therefore, the immediate goal of this proposal is to develop an accurate and automated method for the quantification of renal parameters from MR images. Once these renal MRI markers are derived, we plan to subsequently describe their distribution among all NAKO participants with available MRI data, as well as in a healthy subsample, and aim to identify relevant clinical, subclinical and biochemical correlates of the derived imaging biomarkers and to evaluate specifically their association with established biochemical renal markers in serum and urine. Even later, once NAKO follow-up data become available, we plan to assess whether the derived MRI biomarkers predict kidney function decline and incident CKD, independent of established biochemical markers of kidney function and potential covariates. If required, we can submit a separate proposal once the follow-up data are available. In summary, the proposed analyses will develop an automated algorithm for renal segmentation and for the readout of novel imaging biomarkers of kidney function and disease. Subsequently, these novel MRI biomarkers of renal structure and function will be systematically evaluated for their epidemiological correlates.

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EinrichtungenUniklinik Freiburg, Universitätsmedizin Greifswald, Universität Regensburg, Universität Leipzig, Magnetic Resonance Development and Application Center, Universitätsklinikum Freiburg, Universität Kiel