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Investigation of a Logistic Model for T2* Dynamic Susceptibility Contrast Magnetic Resonance Imaging (dscMRI) Perfusion Studies.
MedLine Citation:
PMID:  22082544     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
ABSTRACT: There are a number of T1- and T2-based dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic modeling approaches to study cancer microvasculature. Alternatively, model-free approaches offer an easy, quantitative assessment of microcirculation. In this work, we investigate a 6-parameter model-free approach applied to a T2*-weighted echo-planar imaging bolus response curve. We tested this new approach on a small cohort of patients with clinically diagnosed primary rectal carcinoma before adjuvant chemoradiotherapy and surgical excision. Comparison with healthy muscle tissue shows that logistic parameters P1/P2, P4, and P5 offer good discrimination between tumor and healthy tissue. Bolus response logistic parameters P4 and P5 have been implicated in previous T1-based works as being important in the assessment of cancer malignancy. Further comparison of T2* parameters with signal attenuation amplitude (maximum signal drop) and percentage baseline signal loss also corroborates the models' ability to quantify the microenvironment.
Authors:
Graeme M Wardlaw; Raimond Wong; Colm Boylan; Ryan Rebello; Michael D Noseworthy
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of computer assisted tomography     Volume:  35     ISSN:  1532-3145     ISO Abbreviation:  J Comput Assist Tomogr     Publication Date:  2011 Nov 
Date Detail:
Created Date:  2011-11-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7703942     Medline TA:  J Comput Assist Tomogr     Country:  United States    
Other Details:
Languages:  eng     Pagination:  728-33     Citation Subset:  IM    
Affiliation:
From the *Medical Physics & Applied Radiation Sciences, McMaster University; †Brain-Body Institute, St. Joseph's Healthcare; ‡Department of Oncology, Medicine, McMaster University; §Department of Diagnostic Imaging, St. Joseph's Healthcare; and ∥Electrical & Computer Engineering and¶School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.
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