Computational and phantom-based optimization of dc neuronal current imaging (dcNCI) with ultra-low-field nuclear magnetic resonance (ULF NMR)

• Applicant: Rainer Körber, Ph.D.
• Subject Area: Medical Physics, Biomedical Technology
• Term: from 2016 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 313526887

This project forms a vital part in the further development and potential first time in vivo demonstration of neuronal current imaging (NCI) using ultra-low-field nuclear magnetic resonance (ULF NMR) by means of optimized NMR sequences. NCI is a new modality for imaging brain function, complementary, in terms of both spatial and temporal resolution, to other existing functional tools such as functional Magnetic Resonance Imaging (fMRI) and Electro-or Magnetoencephalography (EEG or MEG). NCI measures directly the influence of weak and localized (<1mm) magnetic fields due to neuronal currents in the brain on NMR signals and hence does not suffer from non-uniqueness. The neuronal magnetic field with their spatial and temporal pattern will provide the natural contrast to localize neuronal activity.We focus on imaging long lasting brain activities (~s), coining the modality dcNCI, by using the latest generation of ULF-NMR instrumentation. The ULF-regime (~µT) is superior over the high field region (~T) as it eliminates susceptibility artefacts, a major obstacle in the demonstration of in vivo NCI. The dipole strength and position of somatosensory evoked, long lasting brain activities were estimated by MEG on volunteers and were reproduced with simplified phantoms containing a single current dipole. At PTB, the simplified phantom was used for initial NMR measurement using a 1D phase encoding scheme. This dcNCI feasibility study achieved the detection of small dipolar currents of about 150 nAm, about a factor 3 higher than the intensity of corresponding brain activities. This illustrated the need of substantial improvements in terms of Contrast-to-Noise ratio (CNR).Here, we will initially develop a framework based on computational electromagnetic models capable of simulating both the magnetic fields produced by the NMR coils and the phantom containing the single dipolar source. Numerical simulations of dcNCI using the 1D phase encoding scheme can be obtained by solving the Bloch equations using as input validated field distributions generated by both the NMR coil setup and the dipolar source. It is an integral part of this project to validate the computational model by MEG and ULF-NMR measurements.The second part of the project consists of the construction of more complex phantoms with additional dipolar sources and their associated validated computational electromagnetic models. With this framework we will be able to optimize the sequence for dcNCI with ULF NMR to obtain maximum CNR to improve the sensitivity with regard to the minimum detectable dipole strength. Moreover, due to the availability of computational models of the human body, optimized dcNCI sequences will be numerically tested against extended dipoles within realistic brain models.The output of this project will be a versatile and validated simulation tool usable for predicting and optimizing sequences for dcNCI with ULF NMR with the prospect of its first in vivo demonstration.

• DFG Programme: Research Grants
• International Connection: Switzerland
• Partner Organisation: Schweizerischer Nationalfonds (SNF)
• Co-Investigator: Professor Dr. Niels Kuster