Document Detail


Automatic determination of arterial input function for dynamic contrast enhanced MRI in tumor assessment.
MedLine Citation:
PMID:  18979795     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Dynamic Contrast Enhanced MRI (DCE-MRI) is today one of the most popular methods for tumor assessment. Several pharmacokinetic models have been proposed to analyze DCE-MRI. Most of them depend on an accurate arterial input function (AIF). We propose an automatic and versatile method to determine the AIF. The method has two stages, detection and segmentation, incorporating knowledge about artery structure, fluid kinetics, and the dynamic temporal property of DCE-MRI. We have applied our method in DCE-MRIs of four different body parts: breast, brain, liver and prostate. The results show that we achieve average 89.5% success rate for 40 cases. The pharmacokinetic parameters computed from the automatic AIF are highly agreeable with those from a manually derived AIF (R2 = 0.89, P (T <=t) = 0.19) and a semiautomatic AIF (R2 = 0.98, P(T <=t) = 0.01).
Authors:
Jeremy Chen; Jianhua Yao; David Thomasson
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention     Volume:  11     ISSN:  -     ISO Abbreviation:  Med Image Comput Comput Assist Interv     Publication Date:  2008  
Date Detail:
Created Date:  2008-11-04     Completed Date:  2008-12-09     Revised Date:  2012-03-07    
Medline Journal Info:
Nlm Unique ID:  101249582     Medline TA:  Med Image Comput Comput Assist Interv     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  594-601     Citation Subset:  IM    
Affiliation:
Diagnostic Radiology Department, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Arteries / metabolism
Artificial Intelligence
Breast Neoplasms / diagnosis*,  metabolism*
Computer Simulation
Contrast Media / pharmacokinetics*
Female
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Magnetic Resonance Imaging / methods*
Models, Biological
Models, Statistical
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Grant Support
ID/Acronym/Agency:
Z99 CL999999/CL/CLC NIH HHS
Chemical
Reg. No./Substance:
0/Contrast Media
Comments/Corrections

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


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