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
Link To Document :
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