| Automatic determination of arterial input function for dynamic contrast enhanced MRI in tumor assessment. | |
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MedLine Citation:
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PMID: 18979795 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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). |
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Authors:
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Jeremy Chen; Jianhua Yao; David Thomasson |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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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:
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Created Date: 2008-11-04 Completed Date: 2008-12-09 Revised Date: 2012-03-07 |
Medline Journal Info:
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Nlm Unique ID: 101249582 Medline TA: Med Image Comput Comput Assist Interv Country: Germany |
Other Details:
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Languages: eng Pagination: 594-601 Citation Subset: IM |
Affiliation:
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Diagnostic Radiology Department, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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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:
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Z99 CL999999/CL/CLC NIH HHS |
| Chemical | |
Reg. No./Substance:
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0/Contrast Media |
| Comments/Corrections | |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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