Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging
Purpose To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI). Materials and Methods From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (M...
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creator | Tropine, Andrei Dellani, Paulo D. Glaser, Martin Bohl, Juergen Plöner, Till Vucurevic, Goran Perneczky, Axel Stoeter, Peter |
description | Purpose
To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI).
Materials and Methods
From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (MD) and fractional anisotropy (FA) maps as well as barycentric maps representing the geometrical shape of the tensors. The findings were compared to postoperative histology. The study was approved by the local ethics committee, and informed consent was given by the patients.
Results
According to one‐way analysis of variance (ANOVA), FA was the best parameter to differentiate between the subtypes (F = 32.2; p < 0.0001). Regarding tensor shape, endothelial meningiomas were represented by spherical tensors (80%) corresponding to isotropic diffusion, whereas the fibroblastic meningiomas showed a high percentage (43%) of nonspherical tensors, indicating planar or longitudinal diffusion. The difference was highly significant (F = 28.4; p < 0.0001) and may be due to the fascicular arrangement of long spindle‐shaped tumor cells and the high content of intra‐ and interfascicular fibers as shown in the histology. In addition, a capsule‐like rim of the in‐plane diffusion surrounded most meningiomas irrespective of their histological type.
Conclusion
If these results correlate to the intraoperative findings of meningioma consistency, DTI‐based measurement of FA and analysis of the shape of the diffusion tensor is a promising method to differentiate between fibroblastic and other subtypes of benign meningiomas in order to get information about their “hard” or “soft” consistency prior to removal. J. Magn. Reson. Imaging 2007. © 2007 Wiley‐Liss, Inc. |
doi_str_mv | 10.1002/jmri.20887 |
format | Article |
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To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI).
Materials and Methods
From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (MD) and fractional anisotropy (FA) maps as well as barycentric maps representing the geometrical shape of the tensors. The findings were compared to postoperative histology. The study was approved by the local ethics committee, and informed consent was given by the patients.
Results
According to one‐way analysis of variance (ANOVA), FA was the best parameter to differentiate between the subtypes (F = 32.2; p < 0.0001). Regarding tensor shape, endothelial meningiomas were represented by spherical tensors (80%) corresponding to isotropic diffusion, whereas the fibroblastic meningiomas showed a high percentage (43%) of nonspherical tensors, indicating planar or longitudinal diffusion. The difference was highly significant (F = 28.4; p < 0.0001) and may be due to the fascicular arrangement of long spindle‐shaped tumor cells and the high content of intra‐ and interfascicular fibers as shown in the histology. In addition, a capsule‐like rim of the in‐plane diffusion surrounded most meningiomas irrespective of their histological type.
Conclusion
If these results correlate to the intraoperative findings of meningioma consistency, DTI‐based measurement of FA and analysis of the shape of the diffusion tensor is a promising method to differentiate between fibroblastic and other subtypes of benign meningiomas in order to get information about their “hard” or “soft” consistency prior to removal. J. Magn. Reson. Imaging 2007. © 2007 Wiley‐Liss, Inc.</description><identifier>ISSN: 1053-1807</identifier><identifier>EISSN: 1522-2586</identifier><identifier>DOI: 10.1002/jmri.20887</identifier><identifier>PMID: 17345634</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Analysis of Variance ; Anisotropy ; barycentric maps ; Diagnosis, Differential ; Diffusion Magnetic Resonance Imaging ; diffusion tensor imaging ; Female ; Fibroblasts ; fractional anisotropy ; Humans ; Image Processing, Computer-Assisted ; Male ; Meningeal Neoplasms - diagnosis ; Meningeal Neoplasms - pathology ; Meningioma - diagnosis ; Meningioma - pathology ; meningioma subtypes ; Middle Aged ; Software ; tensor shape</subject><ispartof>Journal of magnetic resonance imaging, 2007-04, Vol.25 (4), p.703-708</ispartof><rights>Copyright © 2007 Wiley‐Liss, Inc.</rights><rights>Copyright (c) 2007 Wiley-Liss, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4987-ca5f9eb60594dd00044584b70c4e185d57b965c72fdcb0b1e7f10161ce2c3ab23</citedby><cites>FETCH-LOGICAL-c4987-ca5f9eb60594dd00044584b70c4e185d57b965c72fdcb0b1e7f10161ce2c3ab23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjmri.20887$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjmri.20887$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17345634$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tropine, Andrei</creatorcontrib><creatorcontrib>Dellani, Paulo D.</creatorcontrib><creatorcontrib>Glaser, Martin</creatorcontrib><creatorcontrib>Bohl, Juergen</creatorcontrib><creatorcontrib>Plöner, Till</creatorcontrib><creatorcontrib>Vucurevic, Goran</creatorcontrib><creatorcontrib>Perneczky, Axel</creatorcontrib><creatorcontrib>Stoeter, Peter</creatorcontrib><title>Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging</title><title>Journal of magnetic resonance imaging</title><addtitle>J. Magn. Reson. Imaging</addtitle><description>Purpose
To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI).
Materials and Methods
From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (MD) and fractional anisotropy (FA) maps as well as barycentric maps representing the geometrical shape of the tensors. The findings were compared to postoperative histology. The study was approved by the local ethics committee, and informed consent was given by the patients.
Results
According to one‐way analysis of variance (ANOVA), FA was the best parameter to differentiate between the subtypes (F = 32.2; p < 0.0001). Regarding tensor shape, endothelial meningiomas were represented by spherical tensors (80%) corresponding to isotropic diffusion, whereas the fibroblastic meningiomas showed a high percentage (43%) of nonspherical tensors, indicating planar or longitudinal diffusion. The difference was highly significant (F = 28.4; p < 0.0001) and may be due to the fascicular arrangement of long spindle‐shaped tumor cells and the high content of intra‐ and interfascicular fibers as shown in the histology. In addition, a capsule‐like rim of the in‐plane diffusion surrounded most meningiomas irrespective of their histological type.
Conclusion
If these results correlate to the intraoperative findings of meningioma consistency, DTI‐based measurement of FA and analysis of the shape of the diffusion tensor is a promising method to differentiate between fibroblastic and other subtypes of benign meningiomas in order to get information about their “hard” or “soft” consistency prior to removal. J. Magn. Reson. Imaging 2007. © 2007 Wiley‐Liss, Inc.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Analysis of Variance</subject><subject>Anisotropy</subject><subject>barycentric maps</subject><subject>Diagnosis, Differential</subject><subject>Diffusion Magnetic Resonance Imaging</subject><subject>diffusion tensor imaging</subject><subject>Female</subject><subject>Fibroblasts</subject><subject>fractional anisotropy</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted</subject><subject>Male</subject><subject>Meningeal Neoplasms - diagnosis</subject><subject>Meningeal Neoplasms - pathology</subject><subject>Meningioma - diagnosis</subject><subject>Meningioma - pathology</subject><subject>meningioma subtypes</subject><subject>Middle Aged</subject><subject>Software</subject><subject>tensor shape</subject><issn>1053-1807</issn><issn>1522-2586</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkEtv1TAQRi1ERR-w4Qcgr1ggpfgZO0toobQqDyEQ3Vm2M764JPHFTkTvv8ftvYUdrDzynDma-RB6SskxJYS9vB5zPGZEa_UAHVDJWMOkbh_WmkjeUE3UPjos5ZoQ0nVCPkL7VHEhWy4OEJzGECDDNEc7xzThFHCILic32DJHj0eY4rSKabQFh5xGnObvkLGr36sJl8XNmzUUvJRK4b7KalU1M0wlZRxHu6qNx2gv2KHAk917hL6-ffPl5F1z-fHs_OTVZeNFp1XjrQwduJbITvR9XVcIqYVTxAugWvZSua6VXrHQe0ccBRUooS31wDy3jvEj9HzrXef0c4EymzEWD8NgJ0hLMYpwxiQn_wVp13ZasK6CL7agz6mUDMGscz0qbwwl5jZ9c5u-uUu_ws921sWN0P9Fd3FXgG6BX3GAzT9U5uL95_N7abOdiWWGmz8zNv8wreJKmm8fzoz6dKpfX6krw_hvYZmg1Q</recordid><startdate>200704</startdate><enddate>200704</enddate><creator>Tropine, Andrei</creator><creator>Dellani, Paulo D.</creator><creator>Glaser, Martin</creator><creator>Bohl, Juergen</creator><creator>Plöner, Till</creator><creator>Vucurevic, Goran</creator><creator>Perneczky, Axel</creator><creator>Stoeter, Peter</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>200704</creationdate><title>Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging</title><author>Tropine, Andrei ; Dellani, Paulo D. ; Glaser, Martin ; Bohl, Juergen ; Plöner, Till ; Vucurevic, Goran ; Perneczky, Axel ; Stoeter, Peter</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4987-ca5f9eb60594dd00044584b70c4e185d57b965c72fdcb0b1e7f10161ce2c3ab23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Analysis of Variance</topic><topic>Anisotropy</topic><topic>barycentric maps</topic><topic>Diagnosis, Differential</topic><topic>Diffusion Magnetic Resonance Imaging</topic><topic>diffusion tensor imaging</topic><topic>Female</topic><topic>Fibroblasts</topic><topic>fractional anisotropy</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted</topic><topic>Male</topic><topic>Meningeal Neoplasms - diagnosis</topic><topic>Meningeal Neoplasms - pathology</topic><topic>Meningioma - diagnosis</topic><topic>Meningioma - pathology</topic><topic>meningioma subtypes</topic><topic>Middle Aged</topic><topic>Software</topic><topic>tensor shape</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tropine, Andrei</creatorcontrib><creatorcontrib>Dellani, Paulo D.</creatorcontrib><creatorcontrib>Glaser, Martin</creatorcontrib><creatorcontrib>Bohl, Juergen</creatorcontrib><creatorcontrib>Plöner, Till</creatorcontrib><creatorcontrib>Vucurevic, Goran</creatorcontrib><creatorcontrib>Perneczky, Axel</creatorcontrib><creatorcontrib>Stoeter, Peter</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of magnetic resonance imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tropine, Andrei</au><au>Dellani, Paulo D.</au><au>Glaser, Martin</au><au>Bohl, Juergen</au><au>Plöner, Till</au><au>Vucurevic, Goran</au><au>Perneczky, Axel</au><au>Stoeter, Peter</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging</atitle><jtitle>Journal of magnetic resonance imaging</jtitle><addtitle>J. Magn. Reson. Imaging</addtitle><date>2007-04</date><risdate>2007</risdate><volume>25</volume><issue>4</issue><spage>703</spage><epage>708</epage><pages>703-708</pages><issn>1053-1807</issn><eissn>1522-2586</eissn><abstract>Purpose
To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI).
Materials and Methods
From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (MD) and fractional anisotropy (FA) maps as well as barycentric maps representing the geometrical shape of the tensors. The findings were compared to postoperative histology. The study was approved by the local ethics committee, and informed consent was given by the patients.
Results
According to one‐way analysis of variance (ANOVA), FA was the best parameter to differentiate between the subtypes (F = 32.2; p < 0.0001). Regarding tensor shape, endothelial meningiomas were represented by spherical tensors (80%) corresponding to isotropic diffusion, whereas the fibroblastic meningiomas showed a high percentage (43%) of nonspherical tensors, indicating planar or longitudinal diffusion. The difference was highly significant (F = 28.4; p < 0.0001) and may be due to the fascicular arrangement of long spindle‐shaped tumor cells and the high content of intra‐ and interfascicular fibers as shown in the histology. In addition, a capsule‐like rim of the in‐plane diffusion surrounded most meningiomas irrespective of their histological type.
Conclusion
If these results correlate to the intraoperative findings of meningioma consistency, DTI‐based measurement of FA and analysis of the shape of the diffusion tensor is a promising method to differentiate between fibroblastic and other subtypes of benign meningiomas in order to get information about their “hard” or “soft” consistency prior to removal. J. Magn. Reson. Imaging 2007. © 2007 Wiley‐Liss, Inc.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>17345634</pmid><doi>10.1002/jmri.20887</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Aged Aged, 80 and over Analysis of Variance Anisotropy barycentric maps Diagnosis, Differential Diffusion Magnetic Resonance Imaging diffusion tensor imaging Female Fibroblasts fractional anisotropy Humans Image Processing, Computer-Assisted Male Meningeal Neoplasms - diagnosis Meningeal Neoplasms - pathology Meningioma - diagnosis Meningioma - pathology meningioma subtypes Middle Aged Software tensor shape |
title | Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging |
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