Prof. Jürgen Machann
Group Leader of Division "Metabolic Imaging""Setting standards for deeper understanding of the underlying mechanisms in the pathogenesis of metabolic diseases. Application of established MRI/MRS-techniques as well as promising new approaches for MR-based non-invasive phenotyping."
"Setting standards for deeper understanding of the underlying mechanisms in the pathogenesis of metabolic diseases. Application of established MRI/MRS-techniques as well as promising new approaches for MR-based non-invasive phenotyping."
Academic Pathway & Research Area
After the academic studies of Physics, Jürgen Machann started his professional career in the Section on Experimental Radiology at the University Hospital Tübingen (Leader: Prof. Dr. Dr. F. Schick) with the focus on magnetic resonance imaging (MRI) and spectroscopy (MR).
In cooperation with the Department of Diabetology, Endocrinology and Nephrology (Prof. Dr. H.-U. Häring) he was involved in the first approaches to investigate augmentation of lipids in muscle cells in the context of insulin resistance.
In a next step, he developed an MRI-based procedure for quantitative assessment of different adipose tissue compartments – e.g. visceral adipose tissue, subcutaneous adipose tissue – in the whole body with appropriate segmentation routines. Quantification of ectopic lipid accumulation in organs as liver or pancreas complete the portfolio of MR-based non-invasive phenotyping and the MR-techniques have been successfully established in a longitudinal lifestyle intervention study (TULIP).
With his broad knowledge and excellent experience, Jürgen Machann joined the Helmholtz Center Munich in 2012 as a scientific employee and his examination protocol serves as a fundamental basis for application in cross-sectional and interventional studies of the German Center for Diabetes Research (DZD).
As a designated expert, he is responsible for MR examinations in various national and international studies on metabolic research. Together with his group members he contributes to evaluation of epidemiological studies as KORA or GNC by applying state-of-the-art techniques based on deep-learning based segmentation.
His input allows a deeper understanding of individual metabolic risk and prognosis of success or failure of lifestyle intervention and is, thus, a key factor for insights in the pathogenesis of insulin resistance and type 2 diabetes.
Fields of Work and Expertise
Magnetic Resonance Imaging (MRI)Magnetic Resonance Spectroscopy (MRS)ObesityBig DataAdipose TissueSegmentationLiver
