PhD position on MRI based electrical conductivity imaging
Innovative PhD project using MRI to measure tissue conductivity for earlier, non-invasive cancer diagnosis and treatment monitoring, with a focus on brain imaging and development of clinically applicable techniques.
Magnetic Resonance Imaging (MRI) is central in the journey of oncological patients, from diagnosis to guidance of radiotherapy. Nevertheless, clinical MRIs can only image late-stage macroscopic changes like tumor volume. Early-stage changes due to cancer and radiotherapy are visible at the metabolic level. These changes lead to altered electrolyte concentrations, following cell-membrane pump failures, affecting cellular viability. However, these can only be imaged with highly-specialized techniques and MRI systems, limiting their availability and clinical use.
This project develops a new MRI technology to measure the electrical conductivity of human tissues. The electrical conductivity differs between healthy and cancer tissues and changes rapidly during treatment, making it a promising indicator for non-invasive cancer diagnosis and monitoring treatment response.
This research focuses on developing this technology for clinical MRI machines for brain, breast, and prostate cancer, three of the most common cancer types worldwide. This work will support personalized, effective cancer care improving (cost) efficiency, while creating open-access tools and data to help hospitals and researchers accelerate adoption in clinical practice.
Your work will focus on the development of this technology for brain, from image acquisition, to reconstructions involving AI, development and testing it in phantoms, volunteers and brain tumor patients. The work will also extend beyond conductivity imaging, including e.g., quantitative MRI.
You will be working at the internationally renowned Center for Image Sciences at the UMC Utrecht, within the Imaging and Oncology Division. You will collaborate with a multi-disciplinary team of scientists, PhD candidates, post-docs, (medical) physicists, radiologists, and radiation oncologists. You will be part of the Computational Imaging Group (https://cig-utrecht.org/).
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