Computational modeling and real-time control of patient-specific laser treatment of cancer.
Identifieur interne : 000069 ( PubMed/Corpus ); précédent : 000068; suivant : 000070Computational modeling and real-time control of patient-specific laser treatment of cancer.
Auteurs : D. Fuentes ; J T Oden ; K R Diller ; J D Hazle ; A. Elliott ; A. Shetty ; R J StaffordSource :
- Annals of biomedical engineering [ 1573-9686 ] ; 2009.
English descriptors
- KwdEn :
- Algorithms, Animals, Biomedical Engineering (methods), Calibration, Computational Biology (methods), Computer Simulation, Computer Systems, Dogs, Feedback, Forecasting, Hot Temperature, Humans, Hyperthermia, Induced, Image Processing, Computer-Assisted, Laser Therapy, Magnetic Resonance Imaging (methods), Male, Models, Biological, Phantoms, Imaging, Prostatic Neoplasms (therapy), Reproducibility of Results, Software, Therapy, Computer-Assisted.
- MESH :
- methods : Biomedical Engineering, Computational Biology, Magnetic Resonance Imaging.
- therapy : Prostatic Neoplasms.
- Algorithms, Animals, Calibration, Computer Simulation, Computer Systems, Dogs, Feedback, Forecasting, Hot Temperature, Humans, Hyperthermia, Induced, Image Processing, Computer-Assisted, Laser Therapy, Male, Models, Biological, Phantoms, Imaging, Reproducibility of Results, Software, Therapy, Computer-Assisted.
Abstract
An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.
DOI: 10.1007/s10439-008-9631-8
PubMed: 19148754
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pubmed:19148754Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Computational modeling and real-time control of patient-specific laser treatment of cancer.</title><author><name sortKey="Fuentes, D" sort="Fuentes, D" uniqKey="Fuentes D" first="D" last="Fuentes">D. Fuentes</name><affiliation><nlm:affiliation>Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA. fuentes@ices.utexas.edu</nlm:affiliation></affiliation></author><author><name sortKey="Oden, J T" sort="Oden, J T" uniqKey="Oden J" first="J T" last="Oden">J T Oden</name></author><author><name sortKey="Diller, K R" sort="Diller, K R" uniqKey="Diller K" first="K R" last="Diller">K R Diller</name></author><author><name sortKey="Hazle, J D" sort="Hazle, J D" uniqKey="Hazle J" first="J D" last="Hazle">J D Hazle</name></author><author><name sortKey="Elliott, A" sort="Elliott, A" uniqKey="Elliott A" first="A" last="Elliott">A. Elliott</name></author><author><name sortKey="Shetty, A" sort="Shetty, A" uniqKey="Shetty A" first="A" last="Shetty">A. Shetty</name></author><author><name sortKey="Stafford, R J" sort="Stafford, R J" uniqKey="Stafford R" first="R J" last="Stafford">R J Stafford</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2009">2009</date><idno type="doi">10.1007/s10439-008-9631-8</idno><idno type="RBID">pubmed:19148754</idno><idno type="pmid">19148754</idno><idno type="wicri:Area/PubMed/Corpus">000069</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Computational modeling and real-time control of patient-specific laser treatment of cancer.</title><author><name sortKey="Fuentes, D" sort="Fuentes, D" uniqKey="Fuentes D" first="D" last="Fuentes">D. Fuentes</name><affiliation><nlm:affiliation>Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA. fuentes@ices.utexas.edu</nlm:affiliation></affiliation></author><author><name sortKey="Oden, J T" sort="Oden, J T" uniqKey="Oden J" first="J T" last="Oden">J T Oden</name></author><author><name sortKey="Diller, K R" sort="Diller, K R" uniqKey="Diller K" first="K R" last="Diller">K R Diller</name></author><author><name sortKey="Hazle, J D" sort="Hazle, J D" uniqKey="Hazle J" first="J D" last="Hazle">J D Hazle</name></author><author><name sortKey="Elliott, A" sort="Elliott, A" uniqKey="Elliott A" first="A" last="Elliott">A. Elliott</name></author><author><name sortKey="Shetty, A" sort="Shetty, A" uniqKey="Shetty A" first="A" last="Shetty">A. Shetty</name></author><author><name sortKey="Stafford, R J" sort="Stafford, R J" uniqKey="Stafford R" first="R J" last="Stafford">R J Stafford</name></author></analytic><series><title level="j">Annals of biomedical engineering</title><idno type="eISSN">1573-9686</idno><imprint><date when="2009" type="published">2009</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Animals</term><term>Biomedical Engineering (methods)</term><term>Calibration</term><term>Computational Biology (methods)</term><term>Computer Simulation</term><term>Computer Systems</term><term>Dogs</term><term>Feedback</term><term>Forecasting</term><term>Hot Temperature</term><term>Humans</term><term>Hyperthermia, Induced</term><term>Image Processing, Computer-Assisted</term><term>Laser Therapy</term><term>Magnetic Resonance Imaging (methods)</term><term>Male</term><term>Models, Biological</term><term>Phantoms, Imaging</term><term>Prostatic Neoplasms (therapy)</term><term>Reproducibility of Results</term><term>Software</term><term>Therapy, Computer-Assisted</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Biomedical Engineering</term><term>Computational Biology</term><term>Magnetic Resonance Imaging</term></keywords><keywords scheme="MESH" qualifier="therapy" xml:lang="en"><term>Prostatic Neoplasms</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Animals</term><term>Calibration</term><term>Computer Simulation</term><term>Computer Systems</term><term>Dogs</term><term>Feedback</term><term>Forecasting</term><term>Hot Temperature</term><term>Humans</term><term>Hyperthermia, Induced</term><term>Image Processing, Computer-Assisted</term><term>Laser Therapy</term><term>Male</term><term>Models, Biological</term><term>Phantoms, Imaging</term><term>Reproducibility of Results</term><term>Software</term><term>Therapy, Computer-Assisted</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">19148754</PMID><DateCreated><Year>2009</Year><Month>03</Month><Day>16</Day></DateCreated><DateCompleted><Year>2009</Year><Month>05</Month><Day>12</Day></DateCompleted><DateRevised><Year>2014</Year><Month>09</Month><Day>01</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1573-9686</ISSN><JournalIssue CitedMedium="Internet"><Volume>37</Volume><Issue>4</Issue><PubDate><Year>2009</Year><Month>Apr</Month></PubDate></JournalIssue><Title>Annals of biomedical engineering</Title><ISOAbbreviation>Ann Biomed Eng</ISOAbbreviation></Journal><ArticleTitle>Computational modeling and real-time control of patient-specific laser treatment of cancer.</ArticleTitle><Pagination><MedlinePgn>763-82</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s10439-008-9631-8</ELocationID><Abstract><AbstractText>An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Fuentes</LastName><ForeName>D</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA. fuentes@ices.utexas.edu</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Oden</LastName><ForeName>J T</ForeName><Initials>JT</Initials></Author><Author ValidYN="Y"><LastName>Diller</LastName><ForeName>K R</ForeName><Initials>KR</Initials></Author><Author ValidYN="Y"><LastName>Hazle</LastName><ForeName>J D</ForeName><Initials>JD</Initials></Author><Author ValidYN="Y"><LastName>Elliott</LastName><ForeName>A</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Shetty</LastName><ForeName>A</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Stafford</LastName><ForeName>R J</ForeName><Initials>RJ</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>GM074258</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>P20RR0206475</GrantID><Acronym>RR</Acronym><Agency>NCRR NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>P30 CA016672</GrantID><Acronym>CA</Acronym><Agency>NCI NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate 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