Modeling, simulation, and optimal initiation planning for needle insertion into the liver.
Identifieur interne : 000F20 ( PubMed/Checkpoint ); précédent : 000F19; suivant : 000F21Modeling, simulation, and optimal initiation planning for needle insertion into the liver.
Auteurs : R. Sharifi Sedeh [États-Unis] ; M T Ahmadian ; F. Janabi-SharifiSource :
- Journal of biomechanical engineering [ 1528-8951 ] ; 2010.
English descriptors
- KwdEn :
- MESH :
- instrumentation : Hepatectomy.
- methods : Biopsy, Needle, Hepatectomy, Prosthesis Implantation.
- physiology : Liver.
- surgery : Liver.
- Animals, Computer Simulation, Humans, Models, Biological, Needles.
Abstract
Needle insertion simulation and planning systems (SPSs) will play an important role in diminishing inappropriate insertions into soft tissues and resultant complications. Difficulties in SPS development are due in large part to the computational requirements of the extensive calculations in finite element (FE) models of tissue. For clinical feasibility, the computational speed of SPSs must be improved. At the same time, a realistic model of tissue properties that reflects large and velocity-dependent deformations must be employed. The purpose of this study is to address the aforementioned difficulties by presenting a cost-effective SPS platform for needle insertions into the liver. The study was constrained to planar (2D) cases, but can be extended to 3D insertions. To accommodate large and velocity-dependent deformations, a hyperviscoelastic model was devised to produce an FE model of liver tissue. Material constants were identified by a genetic algorithm applied to the experimental results of unconfined compressions of bovine liver. The approach for SPS involves B-spline interpolations of sample data generated from the FE model of liver. Two interpolation-based models are introduced to approximate puncture times and to approximate the coordinates of FE model nodes interacting with the needle tip as a function of the needle initiation pose; the latter was also a function of postpuncture time. A real-time simulation framework is provided, and its computational benefit is highlighted by comparing its performance with the FE method. A planning algorithm for optimal needle initiation was designed, and its effectiveness was evaluated by analyzing its accuracy in reaching a random set of targets at different resolutions of sampled data using the FE model. The proposed simulation framework can easily surpass haptic rates (>500 Hz), even with a high pose resolution level ( approximately 30). The computational time required to update the coordinates of the node at the needle tip in the provided example was reduced from 177 s to 0.8069 ms. The planning accuracy was acceptable even with moderate resolution levels: root-mean-square and maximum errors were 1 mm and 1.2 mm, respectively, for a pose and PPT resolution levels of 17 and 20, respectively. The proposed interpolation-based models significantly improve the computational speed of needle insertion simulation and planning, based on the discretized (FE) model of the liver and can be utilized to establish a cost-effective planning platform. This modeling approach can also be extended for use in other surgical simulations.
DOI: 10.1115/1.4000953
PubMed: 20387964
Affiliations:
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Sharifi Sedeh</name><affiliation wicri:level="2"><nlm:affiliation>Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. rsharifi@mit.edu</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139</wicri:regionArea><placeName><region type="state">Massachusetts</region></placeName></affiliation></author><author><name sortKey="Ahmadian, M T" sort="Ahmadian, M T" uniqKey="Ahmadian M" first="M T" last="Ahmadian">M T Ahmadian</name></author><author><name sortKey="Janabi Sharifi, F" sort="Janabi Sharifi, F" uniqKey="Janabi Sharifi F" first="F" last="Janabi-Sharifi">F. 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Sharifi Sedeh</name><affiliation wicri:level="2"><nlm:affiliation>Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. rsharifi@mit.edu</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139</wicri:regionArea><placeName><region type="state">Massachusetts</region></placeName></affiliation></author><author><name sortKey="Ahmadian, M T" sort="Ahmadian, M T" uniqKey="Ahmadian M" first="M T" last="Ahmadian">M T Ahmadian</name></author><author><name sortKey="Janabi Sharifi, F" sort="Janabi Sharifi, F" uniqKey="Janabi Sharifi F" first="F" last="Janabi-Sharifi">F. Janabi-Sharifi</name></author></analytic><series><title level="j">Journal of biomechanical engineering</title><idno type="eISSN">1528-8951</idno><imprint><date when="2010" type="published">2010</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Biopsy, Needle (methods)</term><term>Computer Simulation</term><term>Hepatectomy (instrumentation)</term><term>Hepatectomy (methods)</term><term>Humans</term><term>Liver (physiology)</term><term>Liver (surgery)</term><term>Models, Biological</term><term>Needles</term><term>Prosthesis Implantation (methods)</term></keywords><keywords scheme="MESH" qualifier="instrumentation" xml:lang="en"><term>Hepatectomy</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Biopsy, Needle</term><term>Hepatectomy</term><term>Prosthesis Implantation</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Liver</term></keywords><keywords scheme="MESH" qualifier="surgery" xml:lang="en"><term>Liver</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Computer Simulation</term><term>Humans</term><term>Models, Biological</term><term>Needles</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Needle insertion simulation and planning systems (SPSs) will play an important role in diminishing inappropriate insertions into soft tissues and resultant complications. Difficulties in SPS development are due in large part to the computational requirements of the extensive calculations in finite element (FE) models of tissue. For clinical feasibility, the computational speed of SPSs must be improved. At the same time, a realistic model of tissue properties that reflects large and velocity-dependent deformations must be employed. The purpose of this study is to address the aforementioned difficulties by presenting a cost-effective SPS platform for needle insertions into the liver. The study was constrained to planar (2D) cases, but can be extended to 3D insertions. To accommodate large and velocity-dependent deformations, a hyperviscoelastic model was devised to produce an FE model of liver tissue. Material constants were identified by a genetic algorithm applied to the experimental results of unconfined compressions of bovine liver. The approach for SPS involves B-spline interpolations of sample data generated from the FE model of liver. Two interpolation-based models are introduced to approximate puncture times and to approximate the coordinates of FE model nodes interacting with the needle tip as a function of the needle initiation pose; the latter was also a function of postpuncture time. A real-time simulation framework is provided, and its computational benefit is highlighted by comparing its performance with the FE method. A planning algorithm for optimal needle initiation was designed, and its effectiveness was evaluated by analyzing its accuracy in reaching a random set of targets at different resolutions of sampled data using the FE model. The proposed simulation framework can easily surpass haptic rates (>500 Hz), even with a high pose resolution level ( approximately 30). The computational time required to update the coordinates of the node at the needle tip in the provided example was reduced from 177 s to 0.8069 ms. The planning accuracy was acceptable even with moderate resolution levels: root-mean-square and maximum errors were 1 mm and 1.2 mm, respectively, for a pose and PPT resolution levels of 17 and 20, respectively. The proposed interpolation-based models significantly improve the computational speed of needle insertion simulation and planning, based on the discretized (FE) model of the liver and can be utilized to establish a cost-effective planning platform. This modeling approach can also be extended for use in other surgical simulations.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">20387964</PMID><DateCreated><Year>2010</Year><Month>04</Month><Day>14</Day></DateCreated><DateCompleted><Year>2010</Year><Month>07</Month><Day>21</Day></DateCompleted><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1528-8951</ISSN><JournalIssue CitedMedium="Internet"><Volume>132</Volume><Issue>4</Issue><PubDate><Year>2010</Year><Month>Apr</Month></PubDate></JournalIssue><Title>Journal of biomechanical engineering</Title><ISOAbbreviation>J Biomech Eng</ISOAbbreviation></Journal><ArticleTitle>Modeling, simulation, and optimal initiation planning for needle insertion into the liver.</ArticleTitle><Pagination><MedlinePgn>041001</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1115/1.4000953</ELocationID><Abstract><AbstractText>Needle insertion simulation and planning systems (SPSs) will play an important role in diminishing inappropriate insertions into soft tissues and resultant complications. Difficulties in SPS development are due in large part to the computational requirements of the extensive calculations in finite element (FE) models of tissue. For clinical feasibility, the computational speed of SPSs must be improved. At the same time, a realistic model of tissue properties that reflects large and velocity-dependent deformations must be employed. The purpose of this study is to address the aforementioned difficulties by presenting a cost-effective SPS platform for needle insertions into the liver. The study was constrained to planar (2D) cases, but can be extended to 3D insertions. To accommodate large and velocity-dependent deformations, a hyperviscoelastic model was devised to produce an FE model of liver tissue. Material constants were identified by a genetic algorithm applied to the experimental results of unconfined compressions of bovine liver. The approach for SPS involves B-spline interpolations of sample data generated from the FE model of liver. Two interpolation-based models are introduced to approximate puncture times and to approximate the coordinates of FE model nodes interacting with the needle tip as a function of the needle initiation pose; the latter was also a function of postpuncture time. A real-time simulation framework is provided, and its computational benefit is highlighted by comparing its performance with the FE method. A planning algorithm for optimal needle initiation was designed, and its effectiveness was evaluated by analyzing its accuracy in reaching a random set of targets at different resolutions of sampled data using the FE model. The proposed simulation framework can easily surpass haptic rates (>500 Hz), even with a high pose resolution level ( approximately 30). The computational time required to update the coordinates of the node at the needle tip in the provided example was reduced from 177 s to 0.8069 ms. The planning accuracy was acceptable even with moderate resolution levels: root-mean-square and maximum errors were 1 mm and 1.2 mm, respectively, for a pose and PPT resolution levels of 17 and 20, respectively. The proposed interpolation-based models significantly improve the computational speed of needle insertion simulation and planning, based on the discretized (FE) model of the liver and can be utilized to establish a cost-effective planning platform. This modeling approach can also be extended for use in other surgical simulations.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Sharifi Sedeh</LastName><ForeName>R</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. rsharifi@mit.edu</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ahmadian</LastName><ForeName>M T</ForeName><Initials>MT</Initials></Author><Author ValidYN="Y"><LastName>Janabi-Sharifi</LastName><ForeName>F</ForeName><Initials>F</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>J Biomech Eng</MedlineTA><NlmUniqueID>7909584</NlmUniqueID><ISSNLinking>0148-0731</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="N" UI="D000818">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D001707">Biopsy, Needle</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003198">Computer Simulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006498">Hepatectomy</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000295">instrumentation</QualifierName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006801">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D008099">Liver</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName><QualifierName MajorTopicYN="Y" UI="Q000601">surgery</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D008954">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D009339">Needles</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D019919">Prosthesis Implantation</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000379">methods</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2010</Year><Month>4</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2010</Year><Month>4</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2010</Year><Month>7</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="doi">10.1115/1.4000953</ArticleId><ArticleId IdType="pubmed">20387964</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Massachusetts</li></region></list><tree><noCountry><name sortKey="Ahmadian, M T" sort="Ahmadian, M T" uniqKey="Ahmadian M" first="M T" last="Ahmadian">M T Ahmadian</name><name sortKey="Janabi Sharifi, F" sort="Janabi Sharifi, F" uniqKey="Janabi Sharifi F" first="F" last="Janabi-Sharifi">F. Janabi-Sharifi</name></noCountry><country name="États-Unis"><region name="Massachusetts"><name sortKey="Sharifi Sedeh, R" sort="Sharifi Sedeh, R" uniqKey="Sharifi Sedeh R" first="R" last="Sharifi Sedeh">R. Sharifi Sedeh</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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