PhD1 Sparsity sampling cardiac CT for perfusion quantification and dose reduction
PI Dewey, Co-PI Kutyniok, Associate-PI Kachelrieß
Application Area: Cardiovascular
Modality: CT
Background: Although CT accounts for only 7% of all radiological and nuclear medicine examinations, this technique is responsible for around 47% of all medical radiation exposure. While temporally resolved CT techniques are very promising for improving our understanding of tissue perfusion such as that of the myocardium in coronary artery disease, this comes at the cost of a further increase in radiation exposure.
Objective: To use compressed sensing combined with suitably chosen representation system to provide sparse approximations of key features of the given data for reducing ionizing radiation while at the same time enabling quantification of perfusion. We anticipate one particularly promising approach to be the use of dictionary learning techniques applied to test data for designing such a representation system. This has the potential to allow reduction of the effective radiation dose by a factor of 10-30.
→ see more details in PhD01.pdf

Requirements: Master’s or Diploma in Mathematics, Computer Science, or Physics, background in CT including registration and reconstruction would be preferable

PhD2 Compressed sensing MRI for 4D-cardiac flow quantification
PI Schulz-Menger, Co-PI Kutyniok, Associate-PI Kühne
Application Area: Cardiovascular
Modality: MRI
Background: 4D-flow MRI is of growing interest in different fields of cardiovascular medicine at all stages of life. Quantification of vessel wall injury by flow measurements may give insights into myocardial injury, e.g., in vascular disease. However, due to the high spatiotemporal resolution requirements accurate quantification of 4D cardiac flow remains a challenge especially when flow is accelerated.
Objective: To increase the temporal and spatial resolution in MRI by compressed sensing (CS), which we have recently adapted to sampling schemes based on random line structures with shearlet based reconstruction. In this project we aim at i) the development of shearlet-CS-based 4D-flow MRI, ii) construction of a “gold standard” pulsatile phantom, iii) validation of the new technique in this phantom and iv) application of the method in healthy volunteers and patients. Once established in pilot studies, shearlet-CS-based 4D-flow MRI will be used in long-term clinical trials to improve our understanding of the interaction between vessel and myocardial injury in vascular diseases.
→ see more details in PhD02.pdf

Requirements: Master’s in physics, engineering or related; training in Matlab and data processing, preferably with knowledge in C++; background in medical imaging desirable

PhD3 Quantitative characterization of tumor flow-metabolism mismatch by PET and MRI
PI Makowski, Co-PI Brenner, Associate-PI Abram
Application Area: Cancer

Modality: PET, MRI, PET-MR
Background: Simultaneous acquisition of PET and MRI with a PET-MRI hybrid system has the potential to improve the accuracy of detection and quantitative characterization of flow-metabolism mismatch, as simultaneous acquisition not only avoids spatial registration errors but also eliminates additional variance associated with consecutive imaging at different time points. Simultaneous PET-MRI also improves generation of image-derived input functions by accurate MRI-based delineation of large vessels and correction of patient motion by repeated MRI to track motion with sufficiently high temporal resolution. The project is centered on PET-MRI hybrid imaging for simultaneous acquisition of metabolism (by the PET component) and blood flow measures (by the MRI component). The project will comprise setup and optimization of acquisition protocols, image processing, tracer kinetic modeling, and multivariate image analysis.
Objective: WP1: Generation of the arterial input function for tracer kinetic modeling(2-5) of (dynamic) PET in simultaneously acquired PET/MRI data. This will build on MRI-based delineation and motion tracking of a large artery within the acquisition field-of-view. WP2: Optimization of simultaneous FDG-PET/ perfusion weighted MRI for generation of parametric maps of regional cerebral blood volume, regional cerebral blood flow and mean transit time. WP3: Identification of novel measures for quantitative characterization of flow-metabolism mismatch in tumors from the parametric maps generated in WP2 using machine learning tools such as multi-voxel pattern analysis.
→ see more details in PhD03.pdf

Requirements: This project is no longer available.

PhD4 Deep learning of MR perfusion for detection and grading of prostate cancer
PI Kutyniok/Dewey, Co-PI Schäffter
Application Area: Cancer
Modality: MR, US
Background: Prostate cancer is the most common malignancy in men worldwide and the incidence rates increased in nearly all countries. In routine clinical practice, the grading of prostate cancer is done using the Gleason score, which requires biopsies or prostatectomy specimen, and is based on rather subjective assessment with high interreader variability. Thus, there is great clinical need for quantitative grading of the aggressiveness of prostate cancer based on noninvasive imaging, e.g. by MR or US.
Objective: To develop novel methods for evaluation of prostate cancer that allow automatic detection and quantitative as well as reliable grading of tumor aggressiveness. Such methods are based on deep learning using convolutional neural networks and may involve other state-of-the-art approaches such as fractal analysis. Image data is derived from dynamic perfusion imaging obtained using MR. This data comes from our large database of 500 patients with 3T MR imaging and pathology correlation. Deep learning of perfusion using US will also be applied to selected cases prior to minimally invasive therapy providing a multimodal imaging perspective. The clinical impact will be non-invasive imaging tools for automatic detection and tumor grading to spare invasive biopsy or even prostatectomy in a large number of patients.
Requirements: This project is no longer available.


PhD5 Quantitative tissue characterization by multimodal imaging of tumor perfusion and effective-medium mechanical parameters in a preclinical model of lymphoma.
PI Laufer/Sack, Co-PI Fischer, Associate-PI Schmitt
Application Area: Cancer
Modality: MRI, US, PAT
Background: Quantitative 3D imaging of blood perfusion, blood volume and mechanical tissue parameters in lymphoma could help tumor staging and therapy monitoring.
Objective: To develop methods for quantitative 3D imaging of perfusion, blood volume and high-resolution elasticity maps in a preclinical small animal model of lymphoma. The time course of the change in the spatial distribution of haemoglobin or exogenous contrast agents, such as microbubbles, near-infrared fluorophores, iron oxide nanoparticles, or combinations thereof, will be measured using photoacoustic tomography (PAT), ultrasound imaging (US), and magnetic resonance imaging (MRI). Preclinical MRI elastography (MRE) will be developed towards tomoelastography in the mouse to depict the heterogeneity of intra-tumor stiffness by a high detail resolution. US and PAT measurements of perfusion will be correlated with MRE. Maps of the change in blood volume will be generated from 3D PAT images of the vasculature by determining the change in blood vessel diameter normalized by vessel density using, for example, vessel filtering techniques. While emphasis will be on the development of experimental methods such as high-resolution MRE of the mouse, the correlation of different biophysical parameters acquired by different modalities is also of interest due to the potential to better characterize tumors and to promote the translation of imaging methods to clinical applications.
→ see more details in PhD05.pdf

Requirements: Master’s in biology, bioengineering or related; training in Matlab and data processing, preferably with background in medical imaging or tissue mechanics

PhD6 Time-resolved quantification of myocardial microstructure by cardiac MR elastography.
PI Sack, Co-PI Schulz-Menger, Associate-PI Ittermann
Application Area: Cardiovascular
Modality: MRI
Background: Primary heart function is characterized by periodic changes in myocardial shear modulus.
Objective: To directly assess cardiac function by high-resolution quantitative mapping of myocardial elasticity in MRI. We capitalize on our experiences with steady-state cardiac MR elastography (MRE), which provides a relative measure of elasticity alteration between systole and diastole. This method will be extended towards wave-inversion based cardiac MRE for spatially resolved quantification of the myocardial shear modulus and complemented by other state-of-the art tissue characterization measurements including perfusion and diffusion MRI. Reference values will be acquired by experiments on tissue specimens and pulsating phantoms and will be compared to findings of ultrasound-based time harmonic cardiac elastography in healthy volunteers. In the follow-up of this PhD project, clinical pilot studies are envisioned to directly detect pathologically increased myocardial shear modulus values in patients with diastolic dysfunction and predefined focal scar tissue.
→ see more details in PhD06.pdf

Requirements: Master’s in physics or engineering or related; training in Matlab and data processing, preferably with knowledge in C++; background in medical imaging or tissue mechanics

PhD7 Time-harmonic elastography of the liver and spleen for quantification of portal hypertension
PI Fischer, Co-PI Sack, Associate-PI Duda
Application Area: Cardiovascular
Modality: US
Background: Hepatic blood flow is not regulated at the level of the portal vein, causing the hepatic vasculature to be highly susceptible to hypertension in subjects with diseases that affect the compliance of the hepatic vascular bed such as hepatic fibrosis and cirrhosis.
Objective: To measure pressure in the hepatosplenic hemodynamic system by time harmonic vibrations detected by real-time sonography. Our hypothesis is based on recent observations made by ultrasound and MRI elastography in liver tissue, which indicate that the shear modulus is sensitive to pressure changes in the vascular bed of the liver and spleen. Using novel ultrasound-based time harmonic elastography we can detect relative differences in shear moduli between liver and spleen and identify patients with elevated intrahepatic pressure gradients who need treatment with transjugular intrahepatic portosystemic shunt (TIPS). The noninvasively derived pressure parameters will be validated by pressure gradient data obtained during TIPS intervention and measured by compression-sensitive MR elastography.
→ see more details in PhD07.pdf

Requirements: This project is no longer available.

PhD8 CT quantification of poroelastic properties of the liver
PI Sack, Co-PI Dewey, Associate-PI Jöhrens
Application Area: Cancer
Modality: CT, MRI
Background: Hepatic fibrogenesis causes an increase of liver stiffness and is associated with risks of portal hypertension and liver cancer.
Objective: To generate CT and MRI maps of poroelastic parameters such as pressure, hydraulic permeability, density and compressibility of the liver derived from clinical scans obtained with either modality alone. Therefore, abdominal dynamic CT and image registration will be used to measure deformation fields of the liver induced by normal breathing in patients with liver tumors after contrast agent injection and compared to results obtained in specimens and phantoms. Poroelastic tissue properties are then extracted from deformation-dependent perfusion patterns and combined with MRI parameters obtained by compression-sensitive MR elastography in the same cohort in order to reveal alterations of microstructure and solid-fluid interactions in liver tissue due to tumor invasion and fibrogenesis. Mechanical ECM structure elements such as collagen and elastic fibers will be quantified by histological analyses.
→ see more details in PhD08.pdf

Requirements: Master’s in physics, bioengineering or related; training in Matlab and data processing, experimental skills; background in medical imaging or tissue mechanics

PhD9 Robust recovery strategies for the acoustic inverse scattering problem in anisotropic systems
PI Kutyniok, Co-PIs Laufer, Fischer, Associate-PI Hege
Application Area: Cardiovascular, Cancer
Modality: PAT, US, MRI
Background: Inverse scattering problems occur in medical imaging in various ways. Of particular importance is the acoustic inverse scattering problem, which models the reconstruction procedure from data generated by, for instance, PAT, US, and elastography.
Objective: We will introduce a mathematical model for 3D scatterers by accounting for anisotropic features prevalent in biological tissues such as connective tissue fibers, blood vessels, or lactiferous ducts. Given generalized geometrical features of self-similar 3D anisotropic networks in biological tissues, the model will provide an efficient mathematical treatment of highly complex scattering phenomena and enable us to invoke adapted regularization strategies such as the L1-norm of carefully chosen representation systems (e.g. shearlets) capable of sparsifying the model functions. Based on this approach, an optimal – in the sense of approximation accuracy – reconstruction scheme will be developed and analyzed with respect to realistic noise assumptions.
→ see more details in PhD09.pdf

Requirements: This project is no longer available.

PhD10 Quantitative MRI for assessment of myocardial fat infiltration at ultra-high field strength
PI Schäffter, Co-PI Schulz-Menger, Associate-PI Niendorf
Application Area: Cardiovascular
Modality: MRI
The concept of fatty myocardium has received attention because of its role in cardiomyopathy and obesity. Furthermore, a relationship between severity of atrial fibrillation and epicardial fat and myocardial fat infiltration has recently been reported. MR spectroscopy and water-fat MRI have been employed to measure fat deposition in humans. However, quantification is still challenging as it requires advanced techniques to correct for T2* and T1 effects. Furthermore, long acquisition times are often a limiting factor.
Objective: Fast quantitative water-fat sensitive MRI will be developed and used for tissue characterization in cardiomyopathy at ultra-high magnetic field strength.
→ see more details in PhD10.pdf

Requirements: Master’s in Physics, Electrical/Biomedical Engineering or similar, training in Matlab and data processing; background in medical imaging and biology is a plus

PhD11 Magnetic imaging markers for quantification of inflammation beyond macrophage targeting
PI Taupitz, Co-PI Abram, Associate-PI Makowski
Application Area: Cardiovascular
Modality: MRI
Background: Detection of inflammation by magnetic nanoparticle (MNP)-based MRI usually exploits the fact that inflammatory processes such as atherosclerosis, arthritis or bacterial infection are associated with an accumulation of phagocytic cells in the affected tissue region. However, inflammatory processes also cause major tissue structure alterations including accumulation of sugar-based components of the ECM (proteoglycans and GAGs), which can be targeted by electrostatically stabilized MNP (ES-MNP). While targeting of phagocytic cells takes hours to days, targeting of sugar-based ECM components occurs on the order of minutes, which potentially reduces side-effects and increases the accuracy of the quantification method.
Objective: This project aims at i) quantitative correlation of the degree of inflammation with the accumulation of ES-MNP, ii) determination of the local kinetics of the ES-MNP after in-vivo injection in animal models of inflammation using MRI and MPI, and iii) in-vivo and ex-vivo examinations for quantification of particle accumulation and inflammation-induced structural changes by radiolabeling techniques, immunohistochemistry and BIOQIC-available expertise in biophysical and mechanical tissue characterization.
→ see more details in PhD11.pdf

Requirements: This project is no longer available.

PhD12 Sensors for quantification of tumor-induced tissue structure alterations by enzyme-activated Xe-MRI contrast
PI Schröder, Co-PI Taupitz, Associate-PI Schmitt
Application Area: Cancer
Modality: MRI
Background: Matrix metalloproteinases (MMP) play a pivotal role in tumor growth, invasion and metastasis, including proteolytic degradation of ECM and alteration of cell-cell/ECM interactions.
Objective: To localize and quantify MMP-related structural changes in vivo by Xe-biosensor MRI, which has the potential to detect internalized compounds at nanomolar concentrations. Such sensors can generate a contrast which is switched on and off through the MRI pulse sequence (hyper-CEST) and is – other than in relaxation-based methods – not masked by the background MRI signal. Based on our expertise in designing Xe-biosensors and by using novel hyper-CEST methods we will develop a smart sensor activated by MMP-induced hairpin cleavage for the exposure of cell-penetrating peptides. Focus will be laid on basal membrane digestion and the related migration of metastatic cells in an animal model of pancreatic cancer. Quantification of ECM structural changes will be correlated to histology and biophysical methods available within BIOQIC such as elastography, atomic force microscopy and optical stretcher experiments.
→ see more details in PhD12.pdf

Requirements: This project is no longer available.

PhD13 Bioconjugation kits for multimetal use and multiorgan targeting
PI Abram, Co-PI Brenner, Associate-PI Buchert
Application Area: Cardiovascular, Cancer
Modality: SPECT, PET
Background: Using biochemical and biophysical-structural information, as outlined in RA3, classical radiopharmaceuticals for organ imaging have usually been developed and optimized for one specific nuclide and one target organ. For optimizing diagnostic yield, however, the combination of various imaging techniques is desired.
Objective: Based on the bioconjugation approach for labeling, labeling kits will be developed, which allow the coupling of arbitrary target-seeking biomolecules to one unique chelator system via peptide coupling or ‘click chemistry’. The chelator system will be designed in a way to make it suitable for the formation of stable complexes with various radioactive isotopes of the SPECT and PET nuclide families. Combining radioactive ‘imaging nuclides’ with nuclides for therapy in a single chelating system we aim at real-time theragnostics based on a single labeling kit.
→ see more details in PhD13.pdf

Requirements: This project is no longer available.

PhD14 Quantitative assessment of coronary plaques by motion-compensated PET-MRI 
PI Schäffter, Co-PI Brenner, Associated PI Makowski
Application Area: Cancer
Modality: PET, MRI, PET-MRI
Background: MRI yields both high-resolution 3D coronary angiography images and respiratory and cardiac motion information, which can be used to improve the quality of both MRI and simultaneously acquired PET images. However, quantification of PET-tracer uptake from blood into the plaque (kinetic) is challenging. One of the main issues is physiological motion of the heart due to breathing and beating of the heart. The size of coronaries is below three millimeters, and therefore already small motion amplitudes lead to a significant decrease in detected plaque signals and strongly impair the diagnostic value of PET images. Therefore, quantification is challenging and severely degraded by motion.
Objective: The project is divided into four work packages. WP1: Implementation of a 3D whole-heart coronary MR sequence which allows for the reconstruction of images showing the coronary artery at different cardiac and respiratory motion states. WP2:  Evaluation of different image registration and MR motion compensation algorithms for varying breathing patterns and heart rates. WP3: Develop a numerical simulation environment which allows for the simulation of different motion types and which can be used to study the effect of physiological motion and motion compensation on the quantification of coronary plaque using 18F-NaF PET. WP4: Extend the MR-based motion compensation techniques to simultaneous PET-MR to improve the reliability and robustness of 18F-NaF PET for the quantification of coronary plaque.
→ see more details in PhD14.pdf

Requirements: This project is no longer available

PhD15 Towards quantitative structure-sensitive MPI: Application to sentinel lymph node detection.
PI Taupitz, Co-PI Schäffter, Associate-PI Käs
Application Area: Cancer
Modality: MPI, MRI
Background: The novel MPI modality detects and localizes magnetic nanoparticles (MNP) in vivo, quantitatively and across multiple time scales from milliseconds to hours. For these reasons, MPI is ideally suited for studying the interaction of MNP with the local physiologic environment in soft tissues and to detect disease-related structural changes by medical imaging. Interactions between MNP and soft tissue environment include the adhesion of MNP to macromolecular, ECM, and cell surface components as well as internalization and intracellular compartmentalization of MNP by phagocytosing cells.
Objective: To study these processes in models of interstitial lymphography including in vitro assays, cultured cells, ex vivo organs of healthy rats such as lymph nodes as well as in vivo rats. The MPI signals will be correlated to histology based on light microscopy, nanomenchanical tests, transmission electron microscopy and radioactive labeling as well as to magnetic tissue characterization. In particular, we will perform a thorough characterization of the physical properties of the particles in tissue by employing various measurement techniques, e.g. magnetic particle spectroscopy, magnetorelaxometry, Moessbauer spectroscopy, and static and dynamic light scattering. In this way, we aim at understanding the influence of physiologic processes on quantitative MPI signal detection. In addition we will compare MPI results with quantitative MRI techniquesfor the quantification of MNPs in lymph nodes.
→ see more details in PhD15.pdf

Requirements: Master’s in Physics, Electrical/Biomedical Engineering or related, training in Matlab and data processing; background in medical imaging and biology is a plus