Magnetic resonance is a well established imaging technique that can still profit from contributions from physicists, both in terms of allowing its full exploitation in applicative contexts and in terms of improving its performances and from chemists, in terms of development of tracers.
This project plans to exploit the experience acquired by the participants on several physical and chemical aspects to the improvement of the impact of magnetic resonance imaging (MRI) on medical applications.
In particular, two are the lines of research that we intend to pursue:
- develop tools for the use of MRI in the assessment of the effectiveness of therapies, i.e. in the stadiation of tumors, in particular rectal cancer. We plan to use the expertise of data analysis, specifically machine learning, developed in high energy experiments to enhance the information extracted from images, in particular in the segmentation of the image.
- improve the quality of MRI with fluorine (19F) finalized to the determination of the biodistribution of tracers.
In this line, we plan to exploit the competences in data analysis of the components of the group to optimize the signal-to-noise ratio of the 19F images that suffer from a low signal and to exploit the competences in chemistry to develop innovative tracers for a particular clinical case, the enhancement of the effectiveness of neutron and/or proton therapy by enriching the tumor target with fluorinated and borated compounds.
MRI is a well established diagnostic technique and is of common use in the medical community. Radiologists, engineers and mathematicians are constantly active in the field, but there are still huge contributions that physicists and chemists can give to the field that can have a unique impact on the technique.
From the point of view of image analysis, the impact of experts of machine learning shouldering radiologists in the use of the most advanced neural networks can bring a significant impact on the use of MRI. In the particular medical aspects that we expect to face, automatic classification and prediction of tumoral response to neoadjuvant chemo-radiotherapy in rectal cancer, the development of the proposed techniques can significantly impact on the medical protocol, the expenses of the national health system (SSN) and the wellness of the patients. The proposed activity is the continuation of an existing work (already presented at the congress of the European Society of Radiology https://www.myesr.org/congress and the world congress on medical physics http://www.iupesm2018.org/ and soon published) and is based on solid grounds.
From the point of view of 19F-MRI, the present research project is highly multidisciplinary and will pave the way to the development of 19F-MRI producing new diagnostic tools and protocols. In the long term, this will have an impact both in the field of scientific progress, and a positive impact on the economic field, for the industries that produce and sell accessories for preclinical MRI scanners and for those that develop MRI software. Providing new insights and ideas for the development of new fluorinated tracers and MRI contrast agents, the results of the project will have a strong impact in the pharmaceutical industries. The planned studies can potentially lead to patentable ideas, like the development of new fluorinated carriers, the design of new MRI antennas, the optimization of the acquisition chain with new strategies to increase the SNR of MRI signal. There is indeed an explicit interest of Bruker, a multinational company producer of preclinical MRI scanners.