DocumentCode
710819
Title
Generalized Q-space MRI reveals macroscopic patterns of tumor architecture in vivo
Author
Taylor, Erik N. ; Yao Ding ; Lin, Leon ; Aninwene, George E. ; Hoffman, Matthew P. ; Fuller, Clifton D. ; Gilbert, Richard J.
Author_Institution
Chem. & Chem. Biol., Northeastern Univ., Boston, MA, USA
fYear
2015
fDate
17-19 April 2015
Firstpage
1
Lastpage
2
Abstract
Current approaches for studying tumor activity in patients involve molecular characterization in excised tissue or biopsied samples. Recognizing that tumors are composed of heterogeneous arrays of cells and their environment, there is a compelling rationale to explore the macroscopic organization of tumor tissue. We present a novel methodology for probing the micro-structural constituents of tumors in vivo utilizing generalized Q-space MRI. This approach employs varying magnetic field gradients and diffusion sensitivities to yield voxel-scale probability distribution functions of proton diffusivity, and then maps multi-voxel cellular alignment with tractography. Using this methodology, we describe the presence of macroscopic organizational features in patients with head and neck cancers, specifically depicting regional differences between the geometrically coherent periphery and incoherent core region. Such methods may comprise a method for assessing attributes of tumor biology in vivo and for predicting the response of such tumors to various drugs and interventions.
Keywords
biodiffusion; biomedical MRI; cancer; cellular biophysics; drugs; medical image processing; probability; tumours; biopsied samples; generalized Q-space MRI; geometrically coherent periphery; head-neck cancers; heterogeneous cell arrays; incoherent core region; macroscopic organization; macroscopic organizational features; macroscopic patterns; magnetic field gradients; microstructural constituents; molecular characterization; multivoxel cellular alignment; proton diffusivity; tractography; tumor architecture in vivo; tumor biology in vivo; tumor tissue; voxel-scale probability distribution functions; Biology; Cancer; Computer architecture; Magnetic resonance imaging; Organizations; Tumors; Q-space imaging; Tumor organization; biological connectivity; diffusion-weighted magnetic resonance imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering Conference (NEBEC), 2015 41st Annual Northeast
Conference_Location
Troy, NY
Print_ISBN
978-1-4799-8358-2
Type
conf
DOI
10.1109/NEBEC.2015.7117057
Filename
7117057
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