Document Detail


Region of interest and pixel-by-pixel analysis of dynamic contrast enhanced magnetic resonance imaging parameters and time-intensity curve shapes: a comparison in chondroid tumors.
MedLine Citation:
PMID:  18619754     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Dynamic contrast enhanced (DCE) MRI is widely acknowledged to be a helpful tool in the diagnosis and differentiation of tumors. In common clinical settings, the dynamic changes described by the time-intensity curves (TICs) are evaluated to find patterns of atypical tissue behavior, i.e., areas characterized by rapid contrast wash-in and wash-out. Despite the ease of this approach, there is no consensus about the specificity of the TIC shapes in discriminating tumor grades. We explore a new way of looking at TICs, where these are not averaged over a selected region of interest (ROI), but rendered pixel-by-pixel. In this way, the characteristic of the tissue is not given as a single TIC classification but as a distribution of the different TIC patterns. We applied this method in a group of patients with chondroid tumors and compared its outcome with the outcome of the standard ROI-based averaged TIC analysis. Furthermore, we focused on the problem of ROI selection in these tumors and how this affects the outcome of the TIC analysis. Finally, we investigated what relationship exists between the "standard" DCE-MRI parameter maximum enhancement (ME) and the TIC shape. CONCLUSIONS: We demonstrate that, where the ROI approach fails to show the presence of areas of rapid contrast wash-in and wash-out, the pixel-by-pixel approach reveals the coexistence of a heterogeneous pattern of TIC shapes. Secondly, we point out the differences in the DCE MRI parameters and tumor volume that can result when selecting the tumor based on DCE parameter maps or post-contrast T1-weighted images. Finally, we show that ME maps and TIC shape maps highlight different tissue areas and, therefore, the use of the ME maps is not appropriate for the correct identification of areas of atypical TICs.
Authors:
Cristina Lavini; Branko P Pikaart; Milko C de Jonge; Gerard R Schaap; Mario Maas
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, Non-U.S. Gov't     Date:  2008-07-11
Journal Detail:
Title:  Magnetic resonance imaging     Volume:  27     ISSN:  0730-725X     ISO Abbreviation:  Magn Reson Imaging     Publication Date:  2009 Jan 
Date Detail:
Created Date:  2008-12-09     Completed Date:  2009-04-16     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8214883     Medline TA:  Magn Reson Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  62-8     Citation Subset:  IM    
Affiliation:
Department of Radiology, Academic Medical Center (AMC), 1105 AZ Amsterdam, The Netherlands. c.lavini@amc.uva.nl
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MeSH Terms
Descriptor/Qualifier:
Adult
Aged
Bone Neoplasms / pathology*
Chondrosarcoma / pathology*
Contrast Media
Female
Humans
Image Interpretation, Computer-Assisted / methods*
Knee Joint / pathology*
Magnetic Resonance Imaging / methods*
Male
Middle Aged
Chemical
Reg. No./Substance:
0/Contrast Media

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


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