Finding the peak velocity in a flow from its doppler spectrum

The signal backscattered by blood cells crossing a sample volume produces a Doppler power spectrum determined by the scatterers' velocity distribution. Because of intrinsic spectral broadening, the peak Doppler frequency observed does not correspond to the peak velocity in the flow. Several met...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on ultrasonics, ferroelectrics, and frequency control ferroelectrics, and frequency control, 2013-10, Vol.60 (10), p.2079-2088
Hauptverfasser: Vilkomerson, David, Ricci, Stefano, Tortoli, Piero
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 2088
container_issue 10
container_start_page 2079
container_title IEEE transactions on ultrasonics, ferroelectrics, and frequency control
container_volume 60
creator Vilkomerson, David
Ricci, Stefano
Tortoli, Piero
description The signal backscattered by blood cells crossing a sample volume produces a Doppler power spectrum determined by the scatterers' velocity distribution. Because of intrinsic spectral broadening, the peak Doppler frequency observed does not correspond to the peak velocity in the flow. Several methods have been proposed for estimating the maximum velocity component-an important clinical parameter-but these methods are approximate, based on heuristic thresholds that can be inaccurate and strongly affected by noise. Reported here is a method of modeling the Doppler power spectrum of a flow, and from that model, determining what Doppler frequency on the descending slope of the power spectrum corresponds to the peak velocity in the insonated flow. It is shown that, for a fully insonated flow with a parabolic velocity distribution, the peak velocity corresponds to the Doppler frequency at the half-power point on that slope. The method is demonstrated to be robust with regard to the effects of noise and valid for a wide range of acquisition parameters. Experimental maximum velocity measurements on steady flows with rates between 100 and 300 mL/min (peak velocity range 6.6 cm/s to 19.9 cm/s) show a mean bias error that is smaller than 1%.
doi_str_mv 10.1109/TUFFC.2013.2798
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_miscellaneous_1443381570</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6604539</ieee_id><sourcerecordid>1448722238</sourcerecordid><originalsourceid>FETCH-LOGICAL-c378t-223b24ebef47a256b530a08204314634948bd3266bc2043ce2dde6e9505f4d2a3</originalsourceid><addsrcrecordid>eNqNkTlPw0AQhVcIREKgpkBCK9HQOJm97HVBgSICSJFoktryMYYNvti1Qfn32CSkoKIaaeabN3rzCLlkMGUMwtlqvVjMpxyYmPIg1EdkzBRXng6VOiZj0Fp5AhiMyJlzGwAmZchPyYhL0Iwrf0zuFqbKTPVK2zekDcbv9BOLOjXtlpqKxjQv6i-a27qkpnU0q5umQEtdg2lru_KcnORx4fBiXydkvXhYzZ-85cvj8_x-6aUi0K3HuUi4xARzGcT92UQJiEFzkIJJX8hQ6iQT3PeTdOilyLMMfQwVqFxmPBYTcrvTbWz90aFro9K4FIsirrDuXNT70gHvz-j_oEJopgLo0Zs_6KbubNUbGSgmIGAwCM52VGpr5yzmUWNNGdttxCAaQoh-QoiGEKIhhH7jeq_bJSVmB_736z1wtQMMIh7Gvg9SiVB8Axsfh8A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1441307108</pqid></control><display><type>article</type><title>Finding the peak velocity in a flow from its doppler spectrum</title><source>IEEE Electronic Library (IEL)</source><creator>Vilkomerson, David ; Ricci, Stefano ; Tortoli, Piero</creator><creatorcontrib>Vilkomerson, David ; Ricci, Stefano ; Tortoli, Piero</creatorcontrib><description>The signal backscattered by blood cells crossing a sample volume produces a Doppler power spectrum determined by the scatterers' velocity distribution. Because of intrinsic spectral broadening, the peak Doppler frequency observed does not correspond to the peak velocity in the flow. Several methods have been proposed for estimating the maximum velocity component-an important clinical parameter-but these methods are approximate, based on heuristic thresholds that can be inaccurate and strongly affected by noise. Reported here is a method of modeling the Doppler power spectrum of a flow, and from that model, determining what Doppler frequency on the descending slope of the power spectrum corresponds to the peak velocity in the insonated flow. It is shown that, for a fully insonated flow with a parabolic velocity distribution, the peak velocity corresponds to the Doppler frequency at the half-power point on that slope. The method is demonstrated to be robust with regard to the effects of noise and valid for a wide range of acquisition parameters. Experimental maximum velocity measurements on steady flows with rates between 100 and 300 mL/min (peak velocity range 6.6 cm/s to 19.9 cm/s) show a mean bias error that is smaller than 1%.</description><identifier>ISSN: 0885-3010</identifier><identifier>EISSN: 1525-8955</identifier><identifier>DOI: 10.1109/TUFFC.2013.2798</identifier><identifier>PMID: 24081256</identifier><identifier>CODEN: ITUCER</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Apertures ; Blood ; Blood cells ; Blood Flow Velocity ; Cells (biology) ; Computer Simulation ; Doppler ; Doppler effect ; Estimating ; Kinematics ; Mathematical model ; Models, Cardiovascular ; Noise ; Phantoms, Imaging ; Regional Blood Flow ; Spectra ; Steady flow ; Studies ; Transducers ; Ultrasonography, Doppler - methods ; Velocity distribution</subject><ispartof>IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2013-10, Vol.60 (10), p.2079-2088</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Oct 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c378t-223b24ebef47a256b530a08204314634948bd3266bc2043ce2dde6e9505f4d2a3</citedby><cites>FETCH-LOGICAL-c378t-223b24ebef47a256b530a08204314634948bd3266bc2043ce2dde6e9505f4d2a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6604539$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6604539$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24081256$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Vilkomerson, David</creatorcontrib><creatorcontrib>Ricci, Stefano</creatorcontrib><creatorcontrib>Tortoli, Piero</creatorcontrib><title>Finding the peak velocity in a flow from its doppler spectrum</title><title>IEEE transactions on ultrasonics, ferroelectrics, and frequency control</title><addtitle>T-UFFC</addtitle><addtitle>IEEE Trans Ultrason Ferroelectr Freq Control</addtitle><description>The signal backscattered by blood cells crossing a sample volume produces a Doppler power spectrum determined by the scatterers' velocity distribution. Because of intrinsic spectral broadening, the peak Doppler frequency observed does not correspond to the peak velocity in the flow. Several methods have been proposed for estimating the maximum velocity component-an important clinical parameter-but these methods are approximate, based on heuristic thresholds that can be inaccurate and strongly affected by noise. Reported here is a method of modeling the Doppler power spectrum of a flow, and from that model, determining what Doppler frequency on the descending slope of the power spectrum corresponds to the peak velocity in the insonated flow. It is shown that, for a fully insonated flow with a parabolic velocity distribution, the peak velocity corresponds to the Doppler frequency at the half-power point on that slope. The method is demonstrated to be robust with regard to the effects of noise and valid for a wide range of acquisition parameters. Experimental maximum velocity measurements on steady flows with rates between 100 and 300 mL/min (peak velocity range 6.6 cm/s to 19.9 cm/s) show a mean bias error that is smaller than 1%.</description><subject>Apertures</subject><subject>Blood</subject><subject>Blood cells</subject><subject>Blood Flow Velocity</subject><subject>Cells (biology)</subject><subject>Computer Simulation</subject><subject>Doppler</subject><subject>Doppler effect</subject><subject>Estimating</subject><subject>Kinematics</subject><subject>Mathematical model</subject><subject>Models, Cardiovascular</subject><subject>Noise</subject><subject>Phantoms, Imaging</subject><subject>Regional Blood Flow</subject><subject>Spectra</subject><subject>Steady flow</subject><subject>Studies</subject><subject>Transducers</subject><subject>Ultrasonography, Doppler - methods</subject><subject>Velocity distribution</subject><issn>0885-3010</issn><issn>1525-8955</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNqNkTlPw0AQhVcIREKgpkBCK9HQOJm97HVBgSICSJFoktryMYYNvti1Qfn32CSkoKIaaeabN3rzCLlkMGUMwtlqvVjMpxyYmPIg1EdkzBRXng6VOiZj0Fp5AhiMyJlzGwAmZchPyYhL0Iwrf0zuFqbKTPVK2zekDcbv9BOLOjXtlpqKxjQv6i-a27qkpnU0q5umQEtdg2lru_KcnORx4fBiXydkvXhYzZ-85cvj8_x-6aUi0K3HuUi4xARzGcT92UQJiEFzkIJJX8hQ6iQT3PeTdOilyLMMfQwVqFxmPBYTcrvTbWz90aFro9K4FIsirrDuXNT70gHvz-j_oEJopgLo0Zs_6KbubNUbGSgmIGAwCM52VGpr5yzmUWNNGdttxCAaQoh-QoiGEKIhhH7jeq_bJSVmB_736z1wtQMMIh7Gvg9SiVB8Axsfh8A</recordid><startdate>20131001</startdate><enddate>20131001</enddate><creator>Vilkomerson, David</creator><creator>Ricci, Stefano</creator><creator>Tortoli, Piero</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</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>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>L7M</scope><scope>7X8</scope></search><sort><creationdate>20131001</creationdate><title>Finding the peak velocity in a flow from its doppler spectrum</title><author>Vilkomerson, David ; Ricci, Stefano ; Tortoli, Piero</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c378t-223b24ebef47a256b530a08204314634948bd3266bc2043ce2dde6e9505f4d2a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Apertures</topic><topic>Blood</topic><topic>Blood cells</topic><topic>Blood Flow Velocity</topic><topic>Cells (biology)</topic><topic>Computer Simulation</topic><topic>Doppler</topic><topic>Doppler effect</topic><topic>Estimating</topic><topic>Kinematics</topic><topic>Mathematical model</topic><topic>Models, Cardiovascular</topic><topic>Noise</topic><topic>Phantoms, Imaging</topic><topic>Regional Blood Flow</topic><topic>Spectra</topic><topic>Steady flow</topic><topic>Studies</topic><topic>Transducers</topic><topic>Ultrasonography, Doppler - methods</topic><topic>Velocity distribution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vilkomerson, David</creatorcontrib><creatorcontrib>Ricci, Stefano</creatorcontrib><creatorcontrib>Tortoli, Piero</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE transactions on ultrasonics, ferroelectrics, and frequency control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Vilkomerson, David</au><au>Ricci, Stefano</au><au>Tortoli, Piero</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Finding the peak velocity in a flow from its doppler spectrum</atitle><jtitle>IEEE transactions on ultrasonics, ferroelectrics, and frequency control</jtitle><stitle>T-UFFC</stitle><addtitle>IEEE Trans Ultrason Ferroelectr Freq Control</addtitle><date>2013-10-01</date><risdate>2013</risdate><volume>60</volume><issue>10</issue><spage>2079</spage><epage>2088</epage><pages>2079-2088</pages><issn>0885-3010</issn><eissn>1525-8955</eissn><coden>ITUCER</coden><abstract>The signal backscattered by blood cells crossing a sample volume produces a Doppler power spectrum determined by the scatterers' velocity distribution. Because of intrinsic spectral broadening, the peak Doppler frequency observed does not correspond to the peak velocity in the flow. Several methods have been proposed for estimating the maximum velocity component-an important clinical parameter-but these methods are approximate, based on heuristic thresholds that can be inaccurate and strongly affected by noise. Reported here is a method of modeling the Doppler power spectrum of a flow, and from that model, determining what Doppler frequency on the descending slope of the power spectrum corresponds to the peak velocity in the insonated flow. It is shown that, for a fully insonated flow with a parabolic velocity distribution, the peak velocity corresponds to the Doppler frequency at the half-power point on that slope. The method is demonstrated to be robust with regard to the effects of noise and valid for a wide range of acquisition parameters. Experimental maximum velocity measurements on steady flows with rates between 100 and 300 mL/min (peak velocity range 6.6 cm/s to 19.9 cm/s) show a mean bias error that is smaller than 1%.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>24081256</pmid><doi>10.1109/TUFFC.2013.2798</doi><tpages>10</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0885-3010
ispartof IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2013-10, Vol.60 (10), p.2079-2088
issn 0885-3010
1525-8955
language eng
recordid cdi_proquest_miscellaneous_1443381570
source IEEE Electronic Library (IEL)
subjects Apertures
Blood
Blood cells
Blood Flow Velocity
Cells (biology)
Computer Simulation
Doppler
Doppler effect
Estimating
Kinematics
Mathematical model
Models, Cardiovascular
Noise
Phantoms, Imaging
Regional Blood Flow
Spectra
Steady flow
Studies
Transducers
Ultrasonography, Doppler - methods
Velocity distribution
title Finding the peak velocity in a flow from its doppler spectrum
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-02T04%3A18%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Finding%20the%20peak%20velocity%20in%20a%20flow%20from%20its%20doppler%20spectrum&rft.jtitle=IEEE%20transactions%20on%20ultrasonics,%20ferroelectrics,%20and%20frequency%20control&rft.au=Vilkomerson,%20David&rft.date=2013-10-01&rft.volume=60&rft.issue=10&rft.spage=2079&rft.epage=2088&rft.pages=2079-2088&rft.issn=0885-3010&rft.eissn=1525-8955&rft.coden=ITUCER&rft_id=info:doi/10.1109/TUFFC.2013.2798&rft_dat=%3Cproquest_RIE%3E1448722238%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1441307108&rft_id=info:pmid/24081256&rft_ieee_id=6604539&rfr_iscdi=true