Project Details
Projekt
Identification of non-invasive biomarkers for CKD transitions with super-resolution ultrasound
Subject Area
Nephrology
Term
since 2025
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 445703531
We are currently investigating and validating non-invasive, microbubble contrast based super-resolution ultrasound imaging (motion model ultrasound localization microscopy, mULM)), for experimental and clinical nephrology. We optimized mULM foreground/background separation using phantoms and mouse models to improve tracking and localization of microbubbles in mouse kidneys. This allowed the visualization of kidney microvasculature and assessment of microvessel density and tortuosity. We optimized image acquisition and post-processing in kidney transplants, enabling the visualization and characterization of kidney microvasculature also in patients. Currently, challenges remain in adapting the protocol for native kidneys, which have much higher motion and are located deeper, and the visualization of glomeruli. The importance of microvasculature and its rarefaction in kidney disease progression is described, but the non-invasive assessment approaches are lacking. We hypothesize that further optimization of mULM will enable a detailed characterization of kidney microvasculature in patients, including the enumeration of glomeruli, facilitating the understanding and monitoring of kidney disease transitions. To achieve this, we will combine complementary expertise in nephrology and clinical sonography (Fleig), experimental imaging and data analysis (Kiessling) and ultrasound physics (Schmitz). In WP1, we will improve our microbubble tracking to visualize the microvasculature including the glomeruli in healthy and CKD mice and correlate complementary imaging (Klinkhammer, P6) and histology (Boor, P4). In WP2, we will identify image-based parameters for progressive kidney disease and renal fibrosis in preclinical models. We will use a combination of mULM, photoacoustics, and delta radiomics, i.e., quantitative image analysis between different imaging time points. Preclinical models will allow us to correlate radiomics with pathomics (with P4). In WP3, we will acquire mULM data from contrast ultrasound data of patients with acute or chronic kidney disease, who are hospitalized for or underwent kidney biopsy (Nephrology, UK Aachen) and are followed as outpatients (e.g., IgAN-cohort Seikrit (P8)), to quantitatively characterize kidney microvasculature with respect to cortex volume and eGFR. We will optimize image acquisition in native kidneys and post-processing approaches to overcome breathing motion artefacts and visualize functional nephrons non-invasively. In summary, advancement of mULM will enable non-invasive, quantitative assessment of kidney microvasculature, including the glomeruli, thereby providing a novel complementary clinical readout of kidney health. As mULM can be implemented on clinically used ultrasound devices, the technology can be readily established clinically to improve our understanding of disease progression, define potential clinical endpoints and serve as a diagnostic tool for (early) detection and monitoring of kidney disease.
DFG Programme
Clinical Research Units
