Thecentral nervous system (CNS) is our most complex organ system. Despite tremendousprogress in our understanding of the biochemical, electrical, and geneticregulation of CNS functioning and malfunctioning, many fundamental processesand diseases are still not fully understood. For example, axon growth patterns inthe developing brain can currently not be well-predicted based solely on thechemical landscape that neurons encounter, several CNS-related diseases cannotbe precisely diagnosed in living patients, and neuronal regeneration can stillnot be promoted after spinal cord injuries.
Duringmany developmental and pathological processes, neurons and glial cells aremotile. Fundamentally, motion is drivenby forces. Hence, CNS cells mechanicallyinteract with their surrounding tissue. They adhere to neighbouring cells and extracellular matrix using celladhesion molecules, which provide friction, and generate forces usingcytoskeletal proteins. These forces aretransmitted to the outside world not only to locomote but also to probe themechanical properties of the environment, which has a long overseen huge impacton cell function.
Onlyrecently, groups of several project leaders in this consortium, and a few other groupsworldwide, have discovered an important contribution of mechanical signalsto regulating CNS cell function. For example, they showed that brain tissuemechanics instructs axon growth and pathfinding in vivo, that mechanicalforces play an important role for cortical folding in the developing humanbrain, that the lack of remyelination in the aged brain is due to an increasein brain stiffness in vivo, and that many neurodegenerative diseases areaccompanied by changes in brain and spinal cord mechanics. These first insights strongly suggest thatmechanics contributes to many other aspects of CNS functioning, and it islikely that chemical and mechanical signals intensely interact at the cellularand tissue levels to regulate many diverse cellular processes.
The CRC 1540 EBM synergises the expertise of engineers, physicists,biologists, medical researchers, and clinicians in Erlangen to explore mechanicsas an important yet missing puzzle stone in our understanding of CNSdevelopment, homeostasis, and pathology. Our strongly multidisciplinary teamwith unique expertise in CNS mechanics integrates advanced invivo, in vitro, and in silico techniques across time(development, ageing, injury/disease) and length (cell, tissue, organ) scalesto uncover how mechanical forces and mechanical cell and tissue properties,such as stiffness and viscosity, affect CNS function. We especially focus on(A) cerebral, (B) spinal, and (C) cellular mechanics. Invivo and in vitro studies provide a basic understanding ofmechanics-regulated biological and biomedical processes in different regions ofthe CNS. In addition, they help identify key mechano-chemical factors forinclusion in in silico models and provide data for model calibration andvalidation. In silico models, in turn, allow us to test hypotheses without the need of excessive or even inaccessibleexperiments. In addition, they enable the transfer and comparison of mechanics data and findingsacross species and scales. They also empower us to optimise processparameters for the development of in vitro brain tissue-like matricesand in vivo manipulation of mechanical signals, and, eventually, pavethe way for personalised clinical predictions.
Insummary, we exploit mechanics-based approaches to advance ourunderstanding of CNS function and to provide the foundation for futureimprovement of diagnosis and treatment of neurological disorders.
My research is focused on magnetic resonance imaging, in particular on diffusion-weighted imaging and quantitative susceptibility mapping. We develop new pulse sequences, post processing schemes, but also focus on the underlying theory.
Research projects
Quantitative diffusionsgewichtete MRT und Suszeptibilitätskartierung zur Charakterisierung der Gewebemikrostruktur
(Third Party Funds Group – Sub project)
Term: 1. September 2023 - 31. August 2027
Funding source: DFG / Forschungsgruppe (FOR)
Dieses Projekt ist Teil der Forschungsgruppe (FOR) "Schnelle Kartierung von quantitativen MR bio-Signaturen bei ultrahohen Magnetfeldstärken". Es konzentriert sich auf die Erweiterung, Beschleunigung und Verbesserung der Diffusions- und quantitativen Suszeptibilitäts-Magnetresonanztomographie. Das Arbeitsprogramm ist in zwei Teile gegliedert. Im ersten Teil wird ein beschleunigtes Protokoll für die klinischen Projekte der FOR vorbereitet. Im zweiten Teil sollen eine weitere Beschleunigung sowie Qualitätsverbesserungen erreicht werden. Konkret werden wir eine lokal niedrigrangig regularisierte echoplanare Bildgebungssequenz für die diffusionsgewichtete Bildgebung implementieren. Sie nutzt Datenredundanzen bei Akquisitionen mit mehreren Diffusionskodierungen, um das Signal-Rausch-Verhältnis effektiv zu erhöhen und damit den Akquisitionsprozess zu beschleunigen. Die Sequenz wird im Wesentlichen beliebige Diffusionskodierungsmöglichkeiten ermöglichen (z.B. b-Tensor-Kodierung). In einem zweiten Schritt werden wir eine verschachtelte Mehrschuss-Version dieser Sequenz entwickeln, um Bildverzerrungen zu reduzieren, die bei der 7-Tesla echoplanaren Bildgebung störend sind. Für die quantitative Suszeptibilitätskartierung (QSM) werden wir eine Sequenz mit einer Stack-of-Stars-Aufnahmetrajektorie implementieren. Da die Magnitudenbilder von Gradientenechosequenzen, die zu unterschiedlichen Echozeiten akquiriert werden, Datenredundanzen aufweisen, die mit denen von diffusionskodierten Bildern vergleichbar sind, werden wir bei der Bildrekonstruktion ebenfalls eine lokale Regularisierung niedrigen Ranges verwenden. Die radialen Trajektorien dieser Sequenz sollten für eine unterabgetastete und damit beschleunigte Bildrekonstruktion gut geeignet sein. In einem zweiten Schritt werden wir die Fähigkeiten unserer Sequenz durch eine quasi-kontinuierliche Echozeit-Abtastung erweitern, bei dem jede Speiche ihre eigene optimierte Echozeit hat. Dies wird eine verbesserte Qualität der QSM ermöglichen, wenn Fett im Bild vorhanden ist, wie es häufig bei Muskeluntersuchungen und in der Brustbildgebung der Fall ist. Bezüglich der QSM-Rekonstruktion werden wir Verfahren des tiefen Lernens entwickeln, um eine qualitativ hochwertige Rekonstruktion mit einer geringeren Menge an Bilddaten als bei herkömmlichen Rekonstruktionsansätzen zu ermöglichen. Wir werden bestehende neuronale Netzwerke von niedrigeren Feldstärken auf 7 T anpassen und deren Fähigkeiten so erweitern, dass wir auch atemzyklusabhängige Feldkarten. Dieses Projekt wird parallele Sendemethoden (pTx) vom pTx-Projekt der FOR erhalten. Wir werden die entwickelten Sequenzen nach dem ersten Jahr an die klinischen Projekte der FOR liefern. Darüber hinaus werden wir wesentliche Auswerte- und Bildrekonstruktionsmethoden an die anderen Projekte der FOR transferieren.und quasi-kontinuierliche Echozeiten in die Rekonstruktion integrieren können.
Exploring Brain Mechanics (EBM): Understanding, engineering and exploiting mechanical properties and signals in central nervous system development, physiology and pathology
(Third Party Funds Group – Overall project)
Funding source: DFG / Sonderforschungsbereich / Transregio (SFB / TRR)
Thecentral nervous system (CNS) is our most complex organ system. Despite tremendousprogress in our understanding of the biochemical, electrical, and geneticregulation of CNS functioning and malfunctioning, many fundamental processesand diseases are still not fully understood. For example, axon growth patterns inthe developing brain can currently not be well-predicted based solely on thechemical landscape that neurons encounter, several CNS-related diseases cannotbe precisely diagnosed in living patients, and neuronal regeneration can stillnot be promoted after spinal cord injuries.
Duringmany developmental and pathological processes, neurons and glial cells aremotile. Fundamentally, motion is drivenby forces. Hence, CNS cells mechanicallyinteract with their surrounding tissue. They adhere to neighbouring cells and extracellular matrix using celladhesion molecules, which provide friction, and generate forces usingcytoskeletal proteins. These forces aretransmitted to the outside world not only to locomote but also to probe themechanical properties of the environment, which has a long overseen huge impacton cell function.
Onlyrecently, groups of several project leaders in this consortium, and a few other groupsworldwide, have discovered an important contribution of mechanical signalsto regulating CNS cell function. For example, they showed that brain tissuemechanics instructs axon growth and pathfinding in vivo, that mechanicalforces play an important role for cortical folding in the developing humanbrain, that the lack of remyelination in the aged brain is due to an increasein brain stiffness in vivo, and that many neurodegenerative diseases areaccompanied by changes in brain and spinal cord mechanics. These first insights strongly suggest thatmechanics contributes to many other aspects of CNS functioning, and it islikely that chemical and mechanical signals intensely interact at the cellularand tissue levels to regulate many diverse cellular processes.
The CRC 1540 EBM synergises the expertise of engineers, physicists,biologists, medical researchers, and clinicians in Erlangen to explore mechanicsas an important yet missing puzzle stone in our understanding of CNSdevelopment, homeostasis, and pathology. Our strongly multidisciplinary teamwith unique expertise in CNS mechanics integrates advanced invivo, in vitro, and in silico techniques across time(development, ageing, injury/disease) and length (cell, tissue, organ) scalesto uncover how mechanical forces and mechanical cell and tissue properties,such as stiffness and viscosity, affect CNS function. We especially focus on(A) cerebral, (B) spinal, and (C) cellular mechanics. Invivo and in vitro studies provide a basic understanding ofmechanics-regulated biological and biomedical processes in different regions ofthe CNS. In addition, they help identify key mechano-chemical factors forinclusion in in silico models and provide data for model calibration andvalidation. In silico models, in turn, allow us to test hypotheses without the need of excessive or even inaccessibleexperiments. In addition, they enable the transfer and comparison of mechanics data and findingsacross species and scales. They also empower us to optimise processparameters for the development of in vitro brain tissue-like matricesand in vivo manipulation of mechanical signals, and, eventually, pavethe way for personalised clinical predictions.
Insummary, we exploit mechanics-based approaches to advance ourunderstanding of CNS function and to provide the foundation for futureimprovement of diagnosis and treatment of neurological disorders.
2024
2023
2022
2021
2020
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