Six-week project Lauren Villemaire MBP 3970Z Department of Medical Biophysics University of Western Ontario

Outline Introduction MRI Imaging at high magnetic fields Phantoms Objective Methods Results Discussion Conclusion Acknowledgements References 2

Introduction to MRI Uses nuclear magnetic resonance of protons to produce proton density images Magnetism - proton spin Larmor Frequency - rate of precession The 7T MRI at Robarts Research Institute. 3

The primary magnet - main magnetic field - the tesla The gradient magnet - alters magnetic field - focuses magnetic field The RF coil - alters direction of proton spin - detects precession energy T1 and T2 relaxation times - characteristic of tissues - image contrast 4

Imaging at ultra high magnetic fields Advantages SNR Spatial Resolution Tissue Contrast Disadvantages RF heterogeneities Magnetic susceptibility artifacts Specific Absorption Rate (SAR) 5

Brain images at 7T have shading and bright spots that compromise image homogeneity. 6 Human hippocampus 1.5 T 7 T Images at 7T have much higher spatial resolution and SNR than at 1.5T

What are phantoms? An artificial object of known size and composition that is imaged to test, adjust or monitor an MRI system’s - homogeneity - imaging performance - orientation aspects. 7

Objective To develop a brain-mimicking phantom for use in the 7T MRI with the following characteristics in common with the brain: - Grey matter/white matter T1 and T2 relaxation times - Electrical and wave properties - Anatomical structure and size (not symmetrical) 8

Method The relaxivity of varying concentrations of GdCl3 and agarose were measured A concentric phantom was fabricated Coil loading was measured and B1+ effects were empirically determined 9 T1 and T2 values that match average human grey matter and white matter values were determined via measurements done by MRI CSF was mimicked by a 50-mM NaCl solution Grey matterWhite matter CSF

Axial images of brain slices were obtained from Brain Web – Simulated Brain Database. These images represent the standard size and structure of the human brain. Number of slices  36 Modality  T1 Slice thickness  5mm Noise  0% Intensity non-uniformity (RF)  0% 10

14 brain slices, each 1cm apart, were selected Images were, then, modified using Image J to sharpen and enhance contrast between grey matter, white matter, and CSF. 11

Each image was manually outlined to distinguish between the different compartments. 12

Tracings were scanned and made binary using ImageJ and then converted to SAT using Solid Works. 13 jpg pdf dxf  sat

Images were then formatted to open in the MasterCam Mill 9 program where they were modified. 14

Results An agarose gel and saline solution phantom was developed to mimic properties of the human brain for imaging at 7T. Tissue Target T1 (ms) Target T2 (ms) % agarose [GdCl3] (uM) Grey matter %8 White matter %22 15

T1W MP RAGE images of the same slice of the phantom with different inversion times. 16 TI = 500ms T1 = 1400ms to null GM T1 = 900ms to null WM

Comparison of RF interference patterns. Single element transmitting (located at back of head) All elements transmitting with random phases to produce interferences. 17

Now that each brain slice is compartmentalized into MasterCam, they can be milled out of plastic and eventually filled with the appropriate brain mimicking substances. 18

Discussion The phantom exhibits very similar dielectric properties (conductivity and permittivity) to the human brain The phantom is the same size and shape of the average brain The phantom has similar anatomical structure to the average brain The phantom has grey matter/ white matter contrast with the same T1 and T2 relaxation times as human brain tissue imaged at 7T I’ve successfully designed a head-mimicking phantom for use in the 7T MRI. 19

Conclusion Such a phantom is unique. It would... (1) allow the ability to instrument the phantom and measure RF power deposition (SAR) and (2) optimize RF shimming techniques using multiple transmitters. Both of these are major challenges currently. 20

Acknowledgements Supervisor: Dr. Ravi S. Menon Post-doctoral student: Kyle Gilbert Graduate student: Andrew Curtis 21

References Brain Web: Simulated Brain Database Rooney WD, et al. Magn Reson Med 2007; 57: Wright PJ et al. MAGMA 2008; 21: Yoshida A et al. Int J Hyperthermia 2004; 20: