| Comparing perfusion metrics obtained from a single compartment versus pharmacokinetic modeling methods using dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. | |
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MedLine Citation:
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PMID: 17032878 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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BACKGROUND AND PURPOSE: Numerous different parameters measured by perfusion MR imaging can be used for characterizing gliomas. Parameters derived from 3 different analyses were correlated with histopathologically confirmed grade in gliomas to determine which parameters best predict tumor grade. METHODS: Seventy-four patients with gliomas underwent dynamic susceptibility contrast-enhanced MR imaging (DSC MR imaging). Data were analyzed by 3 different algorithms. Analysis 1 estimated relative cerebral blood volume (rCBV) by using a single compartment model. Analysis 2 estimated fractional plasma volume (V(p)) and vascular transfer constant (K(trans)) by using a 2-compartment pharmacokinetic model. Analysis 3 estimated absolute cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) by using a single compartment model and an automated arterial input function. The Mann-Whitney U test was used make pairwise comparisons. Binary logistic regression was used to assess whether rCBV, V(p), K(trans), CBV, CBF, and MTT can discriminate high- from low-grade tumors. RESULTS: rCBV was the best discriminator of tumor grade ype, followed by CBF, CBV, and K(trans). Spearman rank correlation factors were the following: rCBV = 0.812 (P < .0001), CBF = 0.677 (P < .0001), CBV = 0.604 (P < .0001), K(trans) = 0.457 (P < .0001), V(p) = 0.301 (P =.009), and MTT = 0.089 (P = .448). rCBV was the best single predictor, and K(trans) with rCBV was the best set of predictors of high-grade glioma. CONCLUSION: rCBV, CBF, CBV K(trans), and V(p) measurements correlated well with histopathologic grade. rCBV was the best predictor of glioma grade, and the combination of rCBV with K(trans) was the best set of metrics to predict glioma grade. |
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Authors:
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M Law; R Young; J Babb; M Rad; T Sasaki; D Zagzag; G Johnson |
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Publication Detail:
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Type: Comparative Study; Journal Article; Research Support, N.I.H., Extramural |
Journal Detail:
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Title: AJNR. American journal of neuroradiology Volume: 27 ISSN: 0195-6108 ISO Abbreviation: AJNR Am J Neuroradiol Publication Date: 2006 Oct |
Date Detail:
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Created Date: 2006-10-11 Completed Date: 2007-01-12 Revised Date: 2008-02-14 |
Medline Journal Info:
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Nlm Unique ID: 8003708 Medline TA: AJNR Am J Neuroradiol Country: United States |
Other Details:
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Languages: eng Pagination: 1975-82 Citation Subset: IM |
Affiliation:
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Department of Radiology, NYU Medical Center, New York, NY 10016, USA. lawm01@med.nyu.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Adolescent Adult Aged Aged, 80 and over Blood Flow Velocity / physiology Blood Volume / physiology Brain / blood supply, pathology Brain Neoplasms / blood supply*, pathology Capillary Permeability / physiology Child Child, Preschool Contrast Media / administration & dosage, pharmacokinetics* Female Gadolinium DTPA / diagnostic use, pharmacokinetics* Glioma / blood supply*, pathology Humans Image Enhancement* Image Processing, Computer-Assisted* Magnetic Resonance Angiography* Magnetic Resonance Imaging* Male Middle Aged Neovascularization, Pathologic / diagnosis*, pathology Prognosis Regional Blood Flow / physiology Retrospective Studies Sensitivity and Specificity |
| Grant Support | |
ID/Acronym/Agency:
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R01CA093992/CA/NCI NIH HHS; R01CA100426/CA/NCI NIH HHS; R01CA111996/CA/NCI NIH HHS |
| Chemical | |
Reg. No./Substance:
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0/Contrast Media; 80529-93-7/Gadolinium DTPA |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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