Open PhD position

Funded PhD position – CSF dynamics, traumatic brain injury

The Project in a Nutshell:

Acute traumatic spinal cord injury (SCI) caused by mechanical trauma results in paralysis, impaired sensation, and autonomic dysfunction. Degenerative cervical myelopathy (DCM) can show similar symptoms and is related to chronic progressive narrowing of the spinal canal (stenosis). The resulting lifelong deficits associated with paralysis and sensory loss have a substantial effect on individuals, caregivers, and society. The question of timing and sufficient opening of the stenosis (surgical decompression) is a critical objective with many pre-clinical and clinical studies. However, quantifying the degree of cord compression and providing intraoperative guidance in decompression surgery remains a challenge. New diagnostic approaches are needed to improve treatment decisions. The analysis of flow and pressure signals in the fluid that surrounds the spinal cord (cerebrospinal fluid, CSF) are seen as a potential new approach to reduce these diagnostic gaps. In this project, such signals acquired in patients and large animals will be analyzed using both the latest machine learning and classical system identification methods. As part of an international translational-clinical network, this cutting-edge research aims to improve care for patients with SCI and DCM.

The Project in Detail:

Increased resistance to CSF flow through spinal stenosis and spinal cord compression in SCI and DCM results in different CSF pressure dynamics down- and upstream of the narrowed section. Our previous work indicates that downstream pressure dynamics could provide a quantitative measure for the degree of spinal cord compression. The ultimate goal of the research is to evaluate the value of CSF pressure indices as a preoperative diagnostic and perioperative monitoring approach. Intraoperatively, we will investigate the CSF pressure waveform and decompression-related changes. Additionally, all patients will be characterized with neurological examinations, magnetic resonance imaging (MRI) and electrodiagnostic studies, allowing correlation to CSF parameters. In the large-animal model, CSF pressure will be acquired continuously before and after CSF space ligation and correlated to velocities acquired with phase-contrast MRI.

The core task of the PhD student will be the development of a computational model of CSF dynamics and spinal cord compression. This will be based upon the collected data in patients and animals, as well as established physical and physiological concepts CSF fluid dynamics and CSF space obstruction. The PhD student will be trained in the relevant clinical and physiological areas, and mentored in computational modeling. The student will also participate in the data acquisition in large animals (adapting the data acquisition software for the new measurements (LabView), surgical assistance, animal handling) and in clinical data acquisition (assisting with signal monitoring in the operating theatre). This project has the potential to elucidate entirely novel avenues to improve the diagnosis and monitoring of spinal cord disease.

The Research Team:

Our team consists of the Spinal Cord Injury Center Group at Balgrist University Hospital (https://www.sci-research.uzh.ch/en/aboutus.html) and The Interface Group at the University of Zurich (interfacegroup.ch). The Spinal Cord Injury Center provides highly specialized treatment for spinal cord injury patients by an interdisciplinary team of surgeons and neurologists. The Interface Group provides a creative, cross-disciplinary international work environment with outstanding infrastructure for computational research in biomedicine, physiology and biophysics. This unique constellation of clinical and basic sciences enables fast translation of research findings to benefit patients.

The Applicant:

Your goal is to have an immediate impact on the lives of patients. You are intrigued by the potential of combining neuroimaging and biomechanical proxies for evaluating spinal cord compression. You have a background in (biomedical) engineering, in physiology with strong technical expertise in data acquisition and analysis, or a comparable background. You are comfortable with working alongside medical doctors in the operating theater, with veterinarians for data acquisition on large animals, and in collaboration with engineers on the analysis of image and signal analysis. You are open to spending part of your PhD with our collaborators in the United Kingdom and Australia.

To Apply:

Please send your motivation letter, CV, and transcripts by e-mail to Dr. Carl Zipser Zipser: carl.zipser@balgrist.ch.