Abstract: Ultra-low field magnetic resonance imaging has become an emerging field in imaging due to extensive development over the past few decades. Reducing the magnetic field strength for imaging purposes entails promising advantages for use in proton therapy. Proton therapy has substantial advantages over conventional radiation therapy with electrons or photons in the treatment of cancer, but it has not yet been able to establish itself clinically due to significantly higher treatment costs [1]. This work is part of a project to democratize access to proton therapy by developing a fixed beam facility. In addition to low costs, ULF MRI results in low proton beam deflection and the ability to dynamically position patients in the beam through an open MRI design. In the first part of this work a novel coil optimization method is presented. This enabled the investigation of the feasiblity of an integrated hybrid proton therapy system. With this method breast coils were optimized, designed and built. The applied algorithm has lead to improved image qualities. Comparing the optimized coils to the non-optimized ones, a higher B1 homogeneity, a better signal-to-noise ratio and a stronger signal in the chest wall could be achieved. As a result, all structures larger than 5 mm were resolved in a NIST breast phantom and the various tissue mimics in the images obtained could be distinguished. Imaging was performed on volunteers in both the prone and sitting position. In addition to structures in the breast, the ribs, the musculus pectoralis major and the subcostal muscles could also be displayed. Especially organs at risk in the chest wall (e.g. the heart) could be made visible through the optimization. Finally, it is shown how the future layout of hybrid systems can be carried out using monte carlo-based simulations.

[1] Michael Baumann, Mechthild Krause, Jens Overgaard, Jürgen Debus, Søren M Bentzen, Juliane Daartz, Christian Richter, Daniel Zips, and Thomas Bortfeld. Radiation oncology in the era of precision medicine.  Nature Reviews Cancer, 16(4):234–249, 2016.