Implementation of PROPELLER MRI method for Diffusion Tensor Reconstruction A. Cheryauka 1, J. Lee 1, A. Samsonov 2, M. Defrise 3, and G. Gullberg 4 1 – MIRL, University of Utah 2 – SCI, University of Utah, 3 – Free University, Brussels 4 – Lawrence Berkeley National Lab

Objectives Magnetic Resonance Imaging To obtain images of good quality at appropriate speeds of acquisition and reconstruction for efficient clinical evaluation PROPELLER method - High-resolution imaging with promising capabilities, - Motion reduction, - Optimized for diffusion tensor imaging Our work - Explore the potential of PROPELLER - Develop image reconstruction & processing tools - Implement Diffusion Tensor PROPELLER

MRI acquisition schemes Rectangular 256x256 Radial 256x406 PROPELLER 256x32x12 K-spaces

Diffusion-weighted image Blade B  Low-resolution image from blade ( MR signal p  (k) of region B  support   - proton density b - attenuation constant D - diffusion tensor  - direction of diffusion gradient PROPELLER* (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction )

MIRL imageGE image Proton Density Reconstruction ( GE scanner ) Agar phantom

Head Imaging ( Picker scanner ) Acquisition parameters: 24 cm FOV 5 mm slice TE/TR= 135/800 msec no attenuation (b=0) 256x24x16 k-space

Diffusion Tensor Imaging Objective: estimate an effective diffusion tensor (DT) in each voxel from series of diffusion-weighted images Motivation: DWI sensitivity to alternation of local fluid mobility or space geometry (epilepsy, myocardial ischemia, spinal lesion). PROPELLER vs EPI: combines the advantages of FSE, navigator echoes, and projection reconstruction into a single technique.

Tensor Measurements Encoding DTT MRI with rotated gradients ( Gullberg, 1999 ) - directions of gradients are the same for each blade in local coordinate system Stationary gradients ( Basser, 1994) - directions of gradients are the same for all blades in global coordinate system Partially rotated gradients (Defrise, 2002) - several gradient directions in global coordinate system 2 -D

DW Image Reconstruction DT Tomography MRI with rotated gradients goes with iterative optimization solver Conventional DT MRI with stationary gradients uses “mapping + 2D FFT” scheme. L – objective functional p’,p – measured & predicted data m – model parameters L prior – stabilizing functional  - regularization parameter W d, W m - weighing matrices

DT imaging (1) ( 2-D, stationary gradients ) Proton density ‘Two-bottles’ numerical phantom, 5 % random noise Eigenvalues & eigenvectors

DT imaging (2) ( 2-D, partially rotated gradients ) Proton density ‘Two-bottles’ numerical phantom, 5 % random noise Eigenvalues & eigenvectors

DT imaging (3) ( 3-D, stationary gradients ) ‘Gel – celery – agar’ phantom Proton density DT components

Conclusions Identified ways and strategies Built new acquisition sequences (Picker scanner) Developed image reconstruction and processing tools Tested on a variety of synthetic and real data …