Document Detail


Toward local arterial input functions in dynamic contrast-enhanced MRI.
MedLine Citation:
PMID:  20882623     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
PURPOSE: To present a method for estimating the local arterial input function (AIF) within a dynamic contrast-enhanced MRI scan, based on the alternating minimization with model (AMM) method.
MATERIALS AND METHODS: This method clusters a subset of data into representative curves, which are then input to the AMM algorithm to return a parameterized AIF and pharmacokinetic parameters. Computer simulations are used to investigate the accuracy with which the AMM is able to estimate the true AIF as a function of the input tissue curves.
RESULTS: Simulations show that a power law relates uncertainty in kinetic parameters and SNR and heterogeneity of the input. Kinetic parameters calculated with the measured AIF are significantly different from those calculated with either a global (P < 0.005) or a local input function (P = 0.0). The use of local AIFs instead of measured AIFs yield mean lesion-averaged parameter changes: K(trans): +24% [+15%, +70%], k(ep): +13% [-36%, +300%]. Globally estimated input functions yield mean lesion-averaged changes: K(trans): +9% [-38%, +65%], k(ep): +13% [-100%, +400%]. The observed improvement in fit quality with local AIFs was found to be significant when additional free parameters were accounted for using the Akaike information criterion.
CONCLUSION: Local AIFs result in significantly different kinetic parameter values. The statistically significant improvement in fit quality suggests that changes in parameter estimates using local AIFs reflect differences in underlying tissue physiology.
Authors:
Jacob U Fluckiger; Matthias C Schabel; Edward V R DiBella
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of magnetic resonance imaging : JMRI     Volume:  32     ISSN:  1522-2586     ISO Abbreviation:  J Magn Reson Imaging     Publication Date:  2010 Oct 
Date Detail:
Created Date:  2010-09-30     Completed Date:  2011-02-02     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9105850     Medline TA:  J Magn Reson Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  924-34     Citation Subset:  IM    
Affiliation:
Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, Utah, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Arteries / pathology*
Brain Neoplasms / diagnosis,  pathology
Computer Simulation
Contrast Media / pharmacology*
Humans
Image Processing, Computer-Assisted / methods
Kinetics
Magnetic Resonance Imaging / methods*
Models, Statistical
Normal Distribution
Perfusion Imaging / methods
Reproducibility of Results
Sarcoma / diagnosis,  pathology
Grant Support
ID/Acronym/Agency:
K25 E005077//PHS HHS; R01 EB000177/EB/NIBIB NIH HHS
Chemical
Reg. No./Substance:
0/Contrast Media

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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