Opportunities and pitfalls in the quantification of fiber integrity: What can we gain from Q-ball imaging?
The quantification of fiber integrity is central to the clinical application of diffusion imaging. Compared to diffusion tensor imaging (DTI), Q-ball imaging (QBI) allows for the depiction of multiple fiber directions within a voxel. However, this advantage has not yet been shown to translate direct...
Gespeichert in:
Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2010-05, Vol.51 (1), p.242-251 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 251 |
---|---|
container_issue | 1 |
container_start_page | 242 |
container_title | NeuroImage (Orlando, Fla.) |
container_volume | 51 |
creator | Fritzsche, Klaus H. Laun, Frederik B. Meinzer, Hans-Peter Stieltjes, Bram |
description | The quantification of fiber integrity is central to the clinical application of diffusion imaging. Compared to diffusion tensor imaging (DTI), Q-ball imaging (QBI) allows for the depiction of multiple fiber directions within a voxel. However, this advantage has not yet been shown to translate directly to superior quantification of fiber integrity. Furthermore, recent developments in QBI reconstruction with solid angle consideration have led to sharper and intrinsically normalized orientation distribution functions. The implications of this technique on quantification are also unknown. To investigate this, the generalized fractional anisotropy (GFA) from the original and the more recent QBI reconstruction scheme and the DTI derived fractional anisotropy (FA) were evaluated comparatively using Monte Carlo simulations and real MRI measurements of crossing fiber phantoms. Contrast-to-noise ratio, accuracy, independence of the acquisition setup and the relation of single fiber anisotropies to measured anisotropy in crossings were assessed. In homogeneous single-fiber regions at b-values around 1000 s/mm2, the FA performed best. While the original QBI reconstruction does not show a clear advantage even at higher b-values and in crossing regions, the new reconstruction scheme yields superior properties and is recommended for quantification at higher b-values and especially in regions of heterogeneous fiber configuration. |
doi_str_mv | 10.1016/j.neuroimage.2010.02.007 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_746303080</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1053811910001552</els_id><sourcerecordid>746303080</sourcerecordid><originalsourceid>FETCH-LOGICAL-c499t-2c46fecedf8a62438ec3c98c8d2f273a9c58758ed04b3e7b18dc73e78ce02f623</originalsourceid><addsrcrecordid>eNqFkU2LFDEQhhtR3A_9CxLw4KnHykd3J17EXXQVFhZB8RjS6cpsmpmkN0kr--_NMKuClz2lSJ73rVS9TUMobCjQ_u28Cbim6PdmixsG9RrYBmB40pxSUF2ruoE9PdQdbyWl6qQ5y3kGAEWFfN6cVIlQclCnzXyzLDGVNfjiMRMTJrL44sxul4kPpNwiuVtNKN55a4qPgURHnB8x1eeC2-TL_Tvy49YUYk0gv5BsTdW5FPfkaztWH3L4pQ_b9y-aZ9U348uH87z5_unjt8vP7fXN1ZfLD9etFUqVllnRO7Q4OWl6JrhEy62SVk7MsYEbZTs5dBInECPHYaRyskMtpEVgrmf8vHlz9F1SvFsxF7332eJuZwLGNetB9Bw4SHic5LwXogNZydf_kXNcU6hjaNpBL3knFK-UPFI2xZwTOr2kOn261xT0ITg963_B6UNwGpiuwVXpq4cG67jH6a_wT1IVuDgCWFf302PS2XoMdU8-oS16iv7xLr8BI-CvJQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1506835493</pqid></control><display><type>article</type><title>Opportunities and pitfalls in the quantification of fiber integrity: What can we gain from Q-ball imaging?</title><source>MEDLINE</source><source>ScienceDirect Journals (5 years ago - present)</source><source>ProQuest Central UK/Ireland</source><creator>Fritzsche, Klaus H. ; Laun, Frederik B. ; Meinzer, Hans-Peter ; Stieltjes, Bram</creator><creatorcontrib>Fritzsche, Klaus H. ; Laun, Frederik B. ; Meinzer, Hans-Peter ; Stieltjes, Bram</creatorcontrib><description>The quantification of fiber integrity is central to the clinical application of diffusion imaging. Compared to diffusion tensor imaging (DTI), Q-ball imaging (QBI) allows for the depiction of multiple fiber directions within a voxel. However, this advantage has not yet been shown to translate directly to superior quantification of fiber integrity. Furthermore, recent developments in QBI reconstruction with solid angle consideration have led to sharper and intrinsically normalized orientation distribution functions. The implications of this technique on quantification are also unknown. To investigate this, the generalized fractional anisotropy (GFA) from the original and the more recent QBI reconstruction scheme and the DTI derived fractional anisotropy (FA) were evaluated comparatively using Monte Carlo simulations and real MRI measurements of crossing fiber phantoms. Contrast-to-noise ratio, accuracy, independence of the acquisition setup and the relation of single fiber anisotropies to measured anisotropy in crossings were assessed. In homogeneous single-fiber regions at b-values around 1000 s/mm2, the FA performed best. While the original QBI reconstruction does not show a clear advantage even at higher b-values and in crossing regions, the new reconstruction scheme yields superior properties and is recommended for quantification at higher b-values and especially in regions of heterogeneous fiber configuration.</description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2010.02.007</identifier><identifier>PMID: 20149879</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Accuracy ; Anisotropy ; Computer Simulation ; Contrast-to-noise ratio ; Diffusion anisotropy indices ; Diffusion Magnetic Resonance Imaging - instrumentation ; Diffusion Magnetic Resonance Imaging - methods ; Diffusion phantom ; Diffusion tensor imaging ; Diffusion Tensor Imaging - instrumentation ; Diffusion Tensor Imaging - methods ; Diffusion weighted imaging ; Fiber crossings ; Humans ; Models, Neurological ; Monte Carlo Method ; Neural Pathways - anatomy & histology ; Noise ; Phantoms, Imaging ; Q-ball imaging ; Quantification</subject><ispartof>NeuroImage (Orlando, Fla.), 2010-05, Vol.51 (1), p.242-251</ispartof><rights>2010 Elsevier Inc.</rights><rights>Copyright (c) 2010 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited May 15, 2010</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c499t-2c46fecedf8a62438ec3c98c8d2f273a9c58758ed04b3e7b18dc73e78ce02f623</citedby><cites>FETCH-LOGICAL-c499t-2c46fecedf8a62438ec3c98c8d2f273a9c58758ed04b3e7b18dc73e78ce02f623</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1506835493?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994,64384,64386,64388,72240</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20149879$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fritzsche, Klaus H.</creatorcontrib><creatorcontrib>Laun, Frederik B.</creatorcontrib><creatorcontrib>Meinzer, Hans-Peter</creatorcontrib><creatorcontrib>Stieltjes, Bram</creatorcontrib><title>Opportunities and pitfalls in the quantification of fiber integrity: What can we gain from Q-ball imaging?</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description>The quantification of fiber integrity is central to the clinical application of diffusion imaging. Compared to diffusion tensor imaging (DTI), Q-ball imaging (QBI) allows for the depiction of multiple fiber directions within a voxel. However, this advantage has not yet been shown to translate directly to superior quantification of fiber integrity. Furthermore, recent developments in QBI reconstruction with solid angle consideration have led to sharper and intrinsically normalized orientation distribution functions. The implications of this technique on quantification are also unknown. To investigate this, the generalized fractional anisotropy (GFA) from the original and the more recent QBI reconstruction scheme and the DTI derived fractional anisotropy (FA) were evaluated comparatively using Monte Carlo simulations and real MRI measurements of crossing fiber phantoms. Contrast-to-noise ratio, accuracy, independence of the acquisition setup and the relation of single fiber anisotropies to measured anisotropy in crossings were assessed. In homogeneous single-fiber regions at b-values around 1000 s/mm2, the FA performed best. While the original QBI reconstruction does not show a clear advantage even at higher b-values and in crossing regions, the new reconstruction scheme yields superior properties and is recommended for quantification at higher b-values and especially in regions of heterogeneous fiber configuration.</description><subject>Accuracy</subject><subject>Anisotropy</subject><subject>Computer Simulation</subject><subject>Contrast-to-noise ratio</subject><subject>Diffusion anisotropy indices</subject><subject>Diffusion Magnetic Resonance Imaging - instrumentation</subject><subject>Diffusion Magnetic Resonance Imaging - methods</subject><subject>Diffusion phantom</subject><subject>Diffusion tensor imaging</subject><subject>Diffusion Tensor Imaging - instrumentation</subject><subject>Diffusion Tensor Imaging - methods</subject><subject>Diffusion weighted imaging</subject><subject>Fiber crossings</subject><subject>Humans</subject><subject>Models, Neurological</subject><subject>Monte Carlo Method</subject><subject>Neural Pathways - anatomy & histology</subject><subject>Noise</subject><subject>Phantoms, Imaging</subject><subject>Q-ball imaging</subject><subject>Quantification</subject><issn>1053-8119</issn><issn>1095-9572</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkU2LFDEQhhtR3A_9CxLw4KnHykd3J17EXXQVFhZB8RjS6cpsmpmkN0kr--_NMKuClz2lSJ73rVS9TUMobCjQ_u28Cbim6PdmixsG9RrYBmB40pxSUF2ruoE9PdQdbyWl6qQ5y3kGAEWFfN6cVIlQclCnzXyzLDGVNfjiMRMTJrL44sxul4kPpNwiuVtNKN55a4qPgURHnB8x1eeC2-TL_Tvy49YUYk0gv5BsTdW5FPfkaztWH3L4pQ_b9y-aZ9U348uH87z5_unjt8vP7fXN1ZfLD9etFUqVllnRO7Q4OWl6JrhEy62SVk7MsYEbZTs5dBInECPHYaRyskMtpEVgrmf8vHlz9F1SvFsxF7332eJuZwLGNetB9Bw4SHic5LwXogNZydf_kXNcU6hjaNpBL3knFK-UPFI2xZwTOr2kOn261xT0ITg963_B6UNwGpiuwVXpq4cG67jH6a_wT1IVuDgCWFf302PS2XoMdU8-oS16iv7xLr8BI-CvJQ</recordid><startdate>20100515</startdate><enddate>20100515</enddate><creator>Fritzsche, Klaus H.</creator><creator>Laun, Frederik B.</creator><creator>Meinzer, Hans-Peter</creator><creator>Stieltjes, Bram</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><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>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>7QO</scope></search><sort><creationdate>20100515</creationdate><title>Opportunities and pitfalls in the quantification of fiber integrity: What can we gain from Q-ball imaging?</title><author>Fritzsche, Klaus H. ; Laun, Frederik B. ; Meinzer, Hans-Peter ; Stieltjes, Bram</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c499t-2c46fecedf8a62438ec3c98c8d2f273a9c58758ed04b3e7b18dc73e78ce02f623</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Accuracy</topic><topic>Anisotropy</topic><topic>Computer Simulation</topic><topic>Contrast-to-noise ratio</topic><topic>Diffusion anisotropy indices</topic><topic>Diffusion Magnetic Resonance Imaging - instrumentation</topic><topic>Diffusion Magnetic Resonance Imaging - methods</topic><topic>Diffusion phantom</topic><topic>Diffusion tensor imaging</topic><topic>Diffusion Tensor Imaging - instrumentation</topic><topic>Diffusion Tensor Imaging - methods</topic><topic>Diffusion weighted imaging</topic><topic>Fiber crossings</topic><topic>Humans</topic><topic>Models, Neurological</topic><topic>Monte Carlo Method</topic><topic>Neural Pathways - anatomy & histology</topic><topic>Noise</topic><topic>Phantoms, Imaging</topic><topic>Q-ball imaging</topic><topic>Quantification</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fritzsche, Klaus H.</creatorcontrib><creatorcontrib>Laun, Frederik B.</creatorcontrib><creatorcontrib>Meinzer, Hans-Peter</creatorcontrib><creatorcontrib>Stieltjes, Bram</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><jtitle>NeuroImage (Orlando, Fla.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fritzsche, Klaus H.</au><au>Laun, Frederik B.</au><au>Meinzer, Hans-Peter</au><au>Stieltjes, Bram</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Opportunities and pitfalls in the quantification of fiber integrity: What can we gain from Q-ball imaging?</atitle><jtitle>NeuroImage (Orlando, Fla.)</jtitle><addtitle>Neuroimage</addtitle><date>2010-05-15</date><risdate>2010</risdate><volume>51</volume><issue>1</issue><spage>242</spage><epage>251</epage><pages>242-251</pages><issn>1053-8119</issn><eissn>1095-9572</eissn><abstract>The quantification of fiber integrity is central to the clinical application of diffusion imaging. Compared to diffusion tensor imaging (DTI), Q-ball imaging (QBI) allows for the depiction of multiple fiber directions within a voxel. However, this advantage has not yet been shown to translate directly to superior quantification of fiber integrity. Furthermore, recent developments in QBI reconstruction with solid angle consideration have led to sharper and intrinsically normalized orientation distribution functions. The implications of this technique on quantification are also unknown. To investigate this, the generalized fractional anisotropy (GFA) from the original and the more recent QBI reconstruction scheme and the DTI derived fractional anisotropy (FA) were evaluated comparatively using Monte Carlo simulations and real MRI measurements of crossing fiber phantoms. Contrast-to-noise ratio, accuracy, independence of the acquisition setup and the relation of single fiber anisotropies to measured anisotropy in crossings were assessed. In homogeneous single-fiber regions at b-values around 1000 s/mm2, the FA performed best. While the original QBI reconstruction does not show a clear advantage even at higher b-values and in crossing regions, the new reconstruction scheme yields superior properties and is recommended for quantification at higher b-values and especially in regions of heterogeneous fiber configuration.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>20149879</pmid><doi>10.1016/j.neuroimage.2010.02.007</doi><tpages>10</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1053-8119 |
ispartof | NeuroImage (Orlando, Fla.), 2010-05, Vol.51 (1), p.242-251 |
issn | 1053-8119 1095-9572 |
language | eng |
recordid | cdi_proquest_miscellaneous_746303080 |
source | MEDLINE; ScienceDirect Journals (5 years ago - present); ProQuest Central UK/Ireland |
subjects | Accuracy Anisotropy Computer Simulation Contrast-to-noise ratio Diffusion anisotropy indices Diffusion Magnetic Resonance Imaging - instrumentation Diffusion Magnetic Resonance Imaging - methods Diffusion phantom Diffusion tensor imaging Diffusion Tensor Imaging - instrumentation Diffusion Tensor Imaging - methods Diffusion weighted imaging Fiber crossings Humans Models, Neurological Monte Carlo Method Neural Pathways - anatomy & histology Noise Phantoms, Imaging Q-ball imaging Quantification |
title | Opportunities and pitfalls in the quantification of fiber integrity: What can we gain from Q-ball imaging? |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T23%3A13%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Opportunities%20and%20pitfalls%20in%20the%20quantification%20of%20fiber%20integrity:%20What%20can%20we%20gain%20from%20Q-ball%20imaging?&rft.jtitle=NeuroImage%20(Orlando,%20Fla.)&rft.au=Fritzsche,%20Klaus%20H.&rft.date=2010-05-15&rft.volume=51&rft.issue=1&rft.spage=242&rft.epage=251&rft.pages=242-251&rft.issn=1053-8119&rft.eissn=1095-9572&rft_id=info:doi/10.1016/j.neuroimage.2010.02.007&rft_dat=%3Cproquest_cross%3E746303080%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1506835493&rft_id=info:pmid/20149879&rft_els_id=S1053811910001552&rfr_iscdi=true |