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Abstract #4884

Diffusion tensor distribution imaging of breast tumors: Initial findings

Isaac Damiel1, Daniel Topgaard2,3, Karin Bryske2, Sunitha Thakur1, and Katja Pinker-Domenig1
1Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Random Walk Imaging, Lund, Sweden, 3Lund University, Lund, Sweden

Diffusion tensor distribution (DTD) imaging was applied in a pilot study to investigate the potential for breast tumor grading in a clinical setting. The method relies on advanced gradient waveforms to encode the signal with information about cell densities, shapes, and orientations, and quantify tissue composition as a probability distribution in a space with dimensions analogous to the cellular ones. Five patients with ductal carcinoma underwent a <4 min DTD protocol giving voxel-resolved distributions and parameter maps with microstructural information not accessible with conventional methods, thereby encouraging future studies with larger patient groups and comparison with current gold standards.

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