A novel CT acquisition and analysis technique for breathing motion modeling
To report on a novel technique for providing artifact-free quantitative four-dimensional computed tomography (4DCT) image datasets for breathing motion modeling. Commercial clinical 4DCT methods have difficulty managing irregular breathing. The resulting images contain motion-induced artifacts that...
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Veröffentlicht in: | Physics in medicine & biology 2013-06, Vol.58 (11), p.L31-L36 |
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creator | Low, Daniel A White, Benjamin M Lee, Percy P Thomas, David H Gaudio, Sergio Jani, Shyam S Wu, Xiao Lamb, James M |
description | To report on a novel technique for providing artifact-free quantitative four-dimensional computed tomography (4DCT) image datasets for breathing motion modeling. Commercial clinical 4DCT methods have difficulty managing irregular breathing. The resulting images contain motion-induced artifacts that can distort structures and inaccurately characterize breathing motion. We have developed a novel scanning and analysis method for motion-correlated CT that utilizes standard repeated fast helical acquisitions, a simultaneous breathing surrogate measurement, deformable image registration, and a published breathing motion model. The motion model differs from the CT-measured motion by an average of 0.65 mm, indicating the precision of the motion model. The integral of the divergence of one of the motion model parameters is predicted to be a constant 1.11 and is found in this case to be 1.09, indicating the accuracy of the motion model. The proposed technique shows promise for providing motion-artifact free images at user-selected breathing phases, accurate Hounsfield units, and noise characteristics similar to non-4D CT techniques, at a patient dose similar to or less than current 4DCT techniques. |
doi_str_mv | 10.1088/0031-9155/58/11/L31 |
format | Article |
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Commercial clinical 4DCT methods have difficulty managing irregular breathing. The resulting images contain motion-induced artifacts that can distort structures and inaccurately characterize breathing motion. We have developed a novel scanning and analysis method for motion-correlated CT that utilizes standard repeated fast helical acquisitions, a simultaneous breathing surrogate measurement, deformable image registration, and a published breathing motion model. The motion model differs from the CT-measured motion by an average of 0.65 mm, indicating the precision of the motion model. The integral of the divergence of one of the motion model parameters is predicted to be a constant 1.11 and is found in this case to be 1.09, indicating the accuracy of the motion model. The proposed technique shows promise for providing motion-artifact free images at user-selected breathing phases, accurate Hounsfield units, and noise characteristics similar to non-4D CT techniques, at a patient dose similar to or less than current 4DCT techniques.</description><identifier>ISSN: 0031-9155</identifier><identifier>EISSN: 1361-6560</identifier><identifier>DOI: 10.1088/0031-9155/58/11/L31</identifier><identifier>PMID: 23640212</identifier><identifier>CODEN: PHMBA7</identifier><language>eng</language><publisher>England: IOP Publishing</publisher><subject>4DCT ; breathing motion modeling ; Four-Dimensional Computed Tomography - methods ; Humans ; Models, Biological ; Movement ; radiation therapy ; Respiration</subject><ispartof>Physics in medicine & biology, 2013-06, Vol.58 (11), p.L31-L36</ispartof><rights>2013 Institute of Physics and Engineering in Medicine</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c511t-ce55f13f44a6e5861b6f94e4d663d7ae9a900f7821f8731ed522c4f8623d7d5b3</citedby><cites>FETCH-LOGICAL-c511t-ce55f13f44a6e5861b6f94e4d663d7ae9a900f7821f8731ed522c4f8623d7d5b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/0031-9155/58/11/L31/pdf$$EPDF$$P50$$Giop$$H</linktopdf><link.rule.ids>230,315,782,786,887,27931,27932,53853,53900</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23640212$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Low, Daniel A</creatorcontrib><creatorcontrib>White, Benjamin M</creatorcontrib><creatorcontrib>Lee, Percy P</creatorcontrib><creatorcontrib>Thomas, David H</creatorcontrib><creatorcontrib>Gaudio, Sergio</creatorcontrib><creatorcontrib>Jani, Shyam S</creatorcontrib><creatorcontrib>Wu, Xiao</creatorcontrib><creatorcontrib>Lamb, James M</creatorcontrib><title>A novel CT acquisition and analysis technique for breathing motion modeling</title><title>Physics in medicine & biology</title><addtitle>PMB</addtitle><addtitle>Phys. Med. Biol</addtitle><description>To report on a novel technique for providing artifact-free quantitative four-dimensional computed tomography (4DCT) image datasets for breathing motion modeling. Commercial clinical 4DCT methods have difficulty managing irregular breathing. The resulting images contain motion-induced artifacts that can distort structures and inaccurately characterize breathing motion. We have developed a novel scanning and analysis method for motion-correlated CT that utilizes standard repeated fast helical acquisitions, a simultaneous breathing surrogate measurement, deformable image registration, and a published breathing motion model. The motion model differs from the CT-measured motion by an average of 0.65 mm, indicating the precision of the motion model. The integral of the divergence of one of the motion model parameters is predicted to be a constant 1.11 and is found in this case to be 1.09, indicating the accuracy of the motion model. The proposed technique shows promise for providing motion-artifact free images at user-selected breathing phases, accurate Hounsfield units, and noise characteristics similar to non-4D CT techniques, at a patient dose similar to or less than current 4DCT techniques.</description><subject>4DCT</subject><subject>breathing motion modeling</subject><subject>Four-Dimensional Computed Tomography - methods</subject><subject>Humans</subject><subject>Models, Biological</subject><subject>Movement</subject><subject>radiation therapy</subject><subject>Respiration</subject><issn>0031-9155</issn><issn>1361-6560</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kUtLAzEUhYMoWh-_QJBZuhknN6-mG6EUX1hwU9chnUnalJlJTWYK_ntTW4tuXIQQznfPvTkXoWvAd4ClLDCmkI-A84LLAqCYUjhCA6ACcsEFPkaDA3GGzmNcYQwgCTtFZ4QKhgmQAXodZ63fmDqbzDJdfvQuus75NtNtlY6uP6OLWWfKZes-epNZH7J5MLpbunaRNf6bbXxl6vS-RCdW19Fc7e8L9P74MJs859O3p5fJeJqXHKDLS8O5BWoZ08JwKWAu7IgZVglBq6E2Iz3C2A4lASuHFEzFCSmZlYIkueJzeoHud77rft6YqjRtF3St1sE1Onwqr536q7RuqRZ-o6iQnEmcDG73BsGnX8VONS6Wpq51a3wfFVBOMeMEeELpDi2DjzEYe2gDWG3XoLYhq23IiksFoNIaUtXN7wkPNT-5J6DYAc6v1cr3IUUd_7X8AlcIkgg</recordid><startdate>20130607</startdate><enddate>20130607</enddate><creator>Low, Daniel A</creator><creator>White, Benjamin M</creator><creator>Lee, Percy P</creator><creator>Thomas, David H</creator><creator>Gaudio, Sergio</creator><creator>Jani, Shyam S</creator><creator>Wu, Xiao</creator><creator>Lamb, James M</creator><general>IOP Publishing</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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20130607</creationdate><title>A novel CT acquisition and analysis technique for breathing motion modeling</title><author>Low, Daniel A ; White, Benjamin M ; Lee, Percy P ; Thomas, David H ; Gaudio, Sergio ; Jani, Shyam S ; Wu, Xiao ; Lamb, James M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c511t-ce55f13f44a6e5861b6f94e4d663d7ae9a900f7821f8731ed522c4f8623d7d5b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>4DCT</topic><topic>breathing motion modeling</topic><topic>Four-Dimensional Computed Tomography - methods</topic><topic>Humans</topic><topic>Models, Biological</topic><topic>Movement</topic><topic>radiation therapy</topic><topic>Respiration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Low, Daniel A</creatorcontrib><creatorcontrib>White, Benjamin M</creatorcontrib><creatorcontrib>Lee, Percy P</creatorcontrib><creatorcontrib>Thomas, David H</creatorcontrib><creatorcontrib>Gaudio, Sergio</creatorcontrib><creatorcontrib>Jani, Shyam S</creatorcontrib><creatorcontrib>Wu, Xiao</creatorcontrib><creatorcontrib>Lamb, James M</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Physics in medicine & biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Low, Daniel A</au><au>White, Benjamin M</au><au>Lee, Percy P</au><au>Thomas, David H</au><au>Gaudio, Sergio</au><au>Jani, Shyam S</au><au>Wu, Xiao</au><au>Lamb, James M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A novel CT acquisition and analysis technique for breathing motion modeling</atitle><jtitle>Physics in medicine & biology</jtitle><stitle>PMB</stitle><addtitle>Phys. Med. Biol</addtitle><date>2013-06-07</date><risdate>2013</risdate><volume>58</volume><issue>11</issue><spage>L31</spage><epage>L36</epage><pages>L31-L36</pages><issn>0031-9155</issn><eissn>1361-6560</eissn><coden>PHMBA7</coden><abstract>To report on a novel technique for providing artifact-free quantitative four-dimensional computed tomography (4DCT) image datasets for breathing motion modeling. Commercial clinical 4DCT methods have difficulty managing irregular breathing. The resulting images contain motion-induced artifacts that can distort structures and inaccurately characterize breathing motion. We have developed a novel scanning and analysis method for motion-correlated CT that utilizes standard repeated fast helical acquisitions, a simultaneous breathing surrogate measurement, deformable image registration, and a published breathing motion model. The motion model differs from the CT-measured motion by an average of 0.65 mm, indicating the precision of the motion model. The integral of the divergence of one of the motion model parameters is predicted to be a constant 1.11 and is found in this case to be 1.09, indicating the accuracy of the motion model. The proposed technique shows promise for providing motion-artifact free images at user-selected breathing phases, accurate Hounsfield units, and noise characteristics similar to non-4D CT techniques, at a patient dose similar to or less than current 4DCT techniques.</abstract><cop>England</cop><pub>IOP Publishing</pub><pmid>23640212</pmid><doi>10.1088/0031-9155/58/11/L31</doi><oa>free_for_read</oa></addata></record> |
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subjects | 4DCT breathing motion modeling Four-Dimensional Computed Tomography - methods Humans Models, Biological Movement radiation therapy Respiration |
title | A novel CT acquisition and analysis technique for breathing motion modeling |
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