| Determination of Grade and Subtype of Meningiomas by Using Histogram Analysis of Diffusion-Tensor Imaging Metrics. | |
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MedLine Citation:
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PMID: 22084207 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Purpose:To determine whether histogram analysis of diffusion-tensor (DT) magnetic resonance (MR) imaging metrics, including tensor shape measurements, can help determine the grades and subtypes of meningiomas.Materials and Methods:The institutional review board approved this HIPAA-compliant study. Nine atypical, three anaplastic, and 39 typical meningiomas were retrospectively studied. The 39 typical meningiomas included one secretory meningioma and 11 fibroblastic, 11 transitional, 14 meningothelial, and two angiomatous meningiomas. DT imaging metrics, including fractional anisotropy, mean diffusivity, linear anisotropy coefficient, planar anisotropy coefficient (CP), spherical anisotropy coefficient (CS), and eigenvalue skewness (SK), as well as normalized signal intensity from contrast-enhanced T1- and T2-weighted images, were measured from the enhancing region of the tumor. Mean, variance, skewness, and kurtosis were extracted from the histograms. A two-level decision tree was designed, and a multivariate logistic regression analysis was used at each level to determine the best model for classification.Results:Histogram skewness of SK and kurtosis of SK were significantly higher in atypical and anaplastic meningiomas than in typical meningiomas (P < .01). Among typical meningiomas, significant differences in histogram measures of CP and CS between fibroblastic meningiomas and other subtypes were observed (P < .01). The best model for differentiating atypical and anaplastic meningiomas from typical meningiomas consisted of mean and skewness of SK and kurtosis of T1 signal intensity, with an area under the receiver operating characteristic curve (AUC) of 0.946. The best model for differentiating fibroblastic meningiomas from other subtypes consisted of skewness of T2 signal intensity and kurtosis of CP (AUC, 0.970).Conclusion:Histogram analysis of DT imaging metrics can help determine the grades and subtypes of meningiomas, which can better assist in surgical planning.© RSNA, 2011Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11110576/-/DC1. |
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Authors:
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Sumei Wang; Sungheon Kim; Yu Zhang; Lu Wang; Edward B Lee; Peter Syre; Harish Poptani; Elias R Melhem; John Y K Lee |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-11-14 |
Journal Detail:
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Title: Radiology Volume: - ISSN: 1527-1315 ISO Abbreviation: - Publication Date: 2011 Nov |
Date Detail:
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Created Date: 2011-11-15 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0401260 Medline TA: Radiology Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Radiology, Division of Neuroradiology, Department of Pathology and Laboratory Medicine, and Department of Neurosurgery, Hospital of the University of Pennsylvania, 3400 Spruce St, 219 Dulles Bldg, Philadelphia, PA 19104. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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