Student: Elisa Roccia
Simultaneous PET/MRI scanners have recently been introduced into clinical practice with the great promise that a hybrid approach might overcome specific limitations of morphologic and molecular imaging to yield a comprehensive characterization of cancer. However, studies to date have not exploited simultaneity innovatively and it is still unknown whether these hybrid systems, compared with MRI or PET (in PET/CT) performed separately, will indeed hold the promise of improving clinical imaging.
This project will develop a novel method for multi-modality cancer imaging: A single-scan multi-parametric MR sequence to replace the current multi-sequence approach to cancer MRI. The key innovation is that this MRI method will enable true integration of simultaneous PET/MR in a simple “push-button” exam. The parallel nature of the acquisition method will result in co-registered multi-parametric images. Integrated motion correction will further improve image quality. These are key developments towards clinical standardisation. The technological advances may represent a paradigm shift towards truly simultaneous PET/MR for comprehensive cancer imaging.
This PhD project joins expertise in imaging methodology of MRI and PET and clinical application in cancer imaging. The PhD student will work closely with MRI scientists with background in image acquisition and reconstruction as well as clinical researchers to translate the developments into a clinical setting. In the emerging field of hybrid PET/MR it requires a new generation of researchers, basic scientists and clinicians, trained in both modalities to address methodological challenges and conceive new research at the interface of both modalities. This proposal will train the student in state-of-the-art simultaneous PET/MRI methodology and because all methods are developed on a clinical system in close collaboration with clinical scientists, it will also provide the student with insight into clinical research. This project also has a strong translational aspect. The student will work closely with our industry partner, Siemens Healthcare, to develop methodology directly within the clinical PET/MR system software to enable rapid clinical translation.