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Primary Colorectal Cancer: Use of Kinetic Modeling of Dynamic Contrast-enhanced CT Data to Predict Clinical Outcome.
MedLine Citation:
PMID:  23297334     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Purpose:To compare four different tracer kinetic models for the analysis of dynamic contrast material-enhanced computed tomographic (CT) data with respect to the prediction of 5-year overall survival in primary colorectal cancer.Materials and Methods:This study was approved by the ethical review board. Archival dynamic contrast-enhanced CT data from 46 patients with colorectal cancer, obtained as part of a research study, were analyzed retrospectively by using the distributed parameter, conventional compartmental, adiabatic tissue homogeneity, and generalized kinetic models. Blood flow, blood volume, mean transit time (MTT), permeability-surface area product, extraction fraction, extravascular extracellular volume (v(e)), and volume transfer constant (K(trans)) were compared by using the Friedman test, with statistical significance at 5%. Following receiver operating characteristic analysis, parameters of the different kinetic models and tumor stage were compared with respect to overall survival discrimination, with use of Kaplan Meier analysis and a univariate Cox proportional hazard model, with additional cross-validation and permutation testing.Results:Blood flow was lower with the distributed parameter model than with the conventional compartmental and adiabatic tissue homogeneity models (P < .0001), and blood flow values determined with the conventional compartmental and adiabatic tissue homogeneity models were similar. Conversely, MTT was longer with the distributed parameter model than with the conventional compartmental and adiabatic tissue homogeneity models (P < .0001). Blood volume, permeability-surface area product, and v(e) were higher with the conventional compartmental model than with the adiabatic tissue homogeneity, distributed parameter, or generalized kinetic models (P < .0001). The extraction fraction was higher with the distributed parameter model than with the adiabatic tissue homogeneity model. With respect to 5-year overall survival, only the distributed parameter model-derived v(e) was predictive of 5-year overall survival with a threshold value of 15.48 mL/100 mL after cross-validation and permutation testing.Conclusion:Parameter values differ significantly between models. Of the models investigated, the distributed parameter model was the best predictor of 5-year overall survival.© RSNA, 2013Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120186/-/DC1.
Authors:
Tong San Koh; Quan Sing Ng; Choon Hua Thng; Jin Wei Kwek; Robert Kozarski; Vicky Goh
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-7
Journal Detail:
Title:  Radiology     Volume:  -     ISSN:  1527-1315     ISO Abbreviation:  Radiology     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-8     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0401260     Medline TA:  Radiology     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Departments of Oncologic Imaging and Medical Oncology, National Cancer Centre Singapore, Singapore; School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore; CLiCR, University of Hertfordshire, Hatfield, England.
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