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Research Group Translational Modelling

The research group “Translational Modeling” studies and develops methods and models for the quantification of functional and structural changes in vessels and nerve tissue and their extrapolation and integration into clinical routine. We use new techniques in magnetic resonance (MR) imaging such as vessel architectural imaging, arterial spin labeling, relaxometry and mapping techniques at 3 Tesla, 7 Tesla and 9.4 Tesla, as well as high-resolution multiphoton microscopy and light disk fluorescence microscopy in cooperation with the German Cancer Research Center. The resulting quantitative characterization of vascular networks and nerve tissue serves as the basis for the development of functional simulations that examine the changes in the MR signal under changing physiological conditions. The research group combines translational MR-physical basics, statistical image processing, preclinical disease models and clinical applications.

Vessel network acquisition and processing in a mouse model. (a) Schematic illustration of experimental procedures, including tumor cell and fluorescent marker injections, brain resection and clearing, with photographs of uncleared and cleared brains with cm scale, and Selective Plane Illumination Microscropy (SPIM). In the second row, an original image from a stack of a healthy mouse brain is presented on the right, with the binary segmentation overlay in red to the left. Below the brain segmentation image, an average intensity projection from a 200 μm thick section of a segmented, noise-filtered, and hole-filled image stack of a U87 glioblastoma is shown. To the right, the skeletonized version of the same dataset is presented, with branch voxels in orange and branching points in magenta. The vascular network quantifications on this post-processed data are illustrated in the last row. The vascular morphology assessment is clarified in a cube of 130 μm side length, marking a radius value r, length l and endpoint-separation d, as well as a segment’s surface area A. Using the vascular skeleton, the network topology can be studied, which is illustrated by a clustered graph, presenting the spatial distribution of vessel communities in a U87 glioblastoma. For details, see Hahn et al., Scientific Reports 2019.
Schematic flowchart of the numerical processing conducted on masked, segmented ultramicroscopy datasets of 3D vascular structure (left image). Each volume partition of the grid that lies within the mask was modeled as a virtual NMR voxel, containing the known microvasculature. Following a determination of the blood vessel induced off‐resonance frequency distribution within the virtual voxel (color‐coded in a 2D cut through a cubic voxel with 100 μm side length; third image), the extravascular water proton signal was numerically simulated in FID conditions. The magnetization decay accountable to spin dephasing was parametrized using different fit functions and a differentiation between short‐ and long‐time decay. For details, see Hahn et al., NMR Biomed 2020.
Tibial and peroneal parts of the sciatic nerve at the level of the thigh of a healthy test person (a, b) and a patient with severe diabetic polyneuropathy (c,d). In the T2-weighted image of the healthy test person (a), the nerve components are shown as hyperintense; the corresponding map of the fractional anisotropy (FA) from diffusion tensor imaging (b) shows high FA values. The patient with severe polyneuropathy, on the other hand, exhibits a loss of healthy nerve fibers with hypointense components in the T2 weighted image (c) and low FA values in diffusion tensor imaging (d).
VAI parameters in a patient with glioblastoma multiforme. (a) T1-weighted (T1w) imaging after administration of contrast agent with contrast-absorbing tumor parts in the right brain hemisphere. (b) FLAIR imaging of the same tumor with clearly hyperintense changes in and around the tumor area. (c) Map of the cerebral blood volume with increased blood volume in the tumor area with an affinity for contrast agent. The following VAI maps are shown: (d) slope length, (e) slope, (f) short axis, (g) distance map, (h) microvessel type indicator, (i) vascular-induced bolus peak-time shift, ( j) vessel size index, (k) Q as a measure of the microvascular density. For more details, see Zhang et al., Plos One 2019.
Sciatic nerve fiber tracts from diffusion tensor imaging with magnified views. (a) Female control, 67 years, neuropathy disability score (NDS) = 0. (b) Female prediabetes patient, 57 years, NDS = 3. (c) Male type 2 diabetes patient, 58 years, NDS = 7. For details, see Jende et al, Front Neurosci 2021.
  • Diffusion effects in MR imaging
  • Vascular network architecture and topology
  • Microstructural imaging
  • Quantitative MR imaging of peripheral nerves
  • Machine learning
  • Statistical modeling

Head

Portrait von Prof. Dr. Martin Bendszus
Prof. Dr. Martin Bendszus

Medical Director (Neuroradiologie)


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Team

Prof. Dr. rer. Nat. Dipl.-Phys. Sabine Heiland

Head of Division (Neuroradiologie)


Artur Hahn

PhD student (Neuroradiologie)

MSc (Doktorand Fakultät für Physik und Astronomie, Universität Heidelberg)


Portrait Christoph Mooshage

Dr. med. Christoph Mooshage

Resident physician (Neuroradiologie)


Portrait von Dr. med. Anja Hohmann
Dr. med. Anja Hohmann

Resident physician (Neurologie und Poliklinik)


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Yannis Seemann

Master's student (Neuroradiologie)

(Student – Master)


Myriam Keymling

Medical student (Neuroradiologie)

(cand. med.)


Dr. rer. nat. Volker Sturm

Physicist (Neuroradiologie)

(PhD)


  • German Cancer Research Center, Heidelberg (Research groups Experimental Neurooncology, Functional imaging, Pediatric Neurooncology, and Preclinical Imaging)
  • Jülich Research Center (Institute of Neuroscience and Medicine)
  • University Hospital Würzburg (Institute of Neuroradiology)
  • University Hospital Bern (Inselspital), Switzerland
  • Johns Hopkins Hospital, Baltimore, USA
  • National Institute on Ageing, National Institutes of Health, Bethesda, USA
  • Department of Radiology, Heidelberg University Hospital
  • Department of Endocrinology, Heidelberg University Hospital
  • Department of Paraplegiology, Heidelberg University Hospital
  • Department of Neurology, Heidelberg University Hospital
  • International Foundation for Research in Paraplegia research grant
  • DFG grant KU 3555/1-1
  • SFB 1158 A03
  • 2018 prize of the diffusion study group, International Society of Magnetic Resonance in Medicine
  • 2018 poster prize of the German Pain Society (Deutsche Schmerzgesellschaft)
  • 2017 Best selected lecture in “Neurodegeneration”, German Society of Neuroradiology (Deutsche Gesellschaft für Neuroradiologie)
  • 2014 Physician Scientist Fellowship of the Medical Faculty Heidelberg
  • 2014 Hoffmann-Klose-Foundation Stipend
  • 2014 Best selected lecture in “Multimodal imaging concepts”, German Society of Neuroradiology (Deutsche Gesellschaft für Neuroradiologie)
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