Assessment of peripheral tissue perfusion by optical dynamic fluorescence imaging and nonlinear regression modeling

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dc.contributor.authorKang, Y.ko
dc.contributor.authorLee, J.ko
dc.contributor.authorKwon, K.ko
dc.contributor.authorChoi, Chulheeko
dc.date.accessioned2013-03-11T16:22:59Z-
dc.date.available2013-03-11T16:22:59Z-
dc.date.created2012-04-04-
dc.date.created2012-04-04-
dc.date.issued2010-
dc.identifier.citationPROGRESS IN BIOMEDICAL OPTICS AND IMAGING - PROCEEDINGS OF SPIE , v.7548, no.0, pp.0 - 0-
dc.identifier.issn1605-7422-
dc.identifier.urihttp://hdl.handle.net/10203/99589-
dc.description.abstractThe purpose of this study is to examine the peripheral tissue perfusion rates by time-series analysis of distribution and elimination kinetics of a clinically proven NIR fluorescence probe, indocyanine green (ICG). We developed a new method, dynamic ICG perfusion imaging technique to evaluate peripheral tissue perfusion that employs planar imaging with a CCD digital imaging system and time-series analysis of the spatiotemporal dynamics (150s) of intravenously injected ICG by using nonlinear regression and differential evolution methods. Six parameters (α, β, s, d, m; parameters which depend on an arterial input function (AIF) into a lower extremity and p; perfusion rates in the lower extremity) were estimated by the nonlinear regression modeling method. We have confirmed the validity of our new method by applying the method to a normal control and a patient with peripheral arterial occlusion disease (PAOD). PAOD patient showed a unique AIF curve pattern, which was caused by collateral blood flow bypassing the occluded major artery. The lower extremity tissue perfusion rate of the PAOD patient was estimated as about 35% of those of normal values. These results indicate that ICG perfusion imaging method is sensitive enough to diagnose PAOD and capable of diagnosing functional arterial diseases. © 2010 Copyright SPIE - The International Society for Optical Engineering.-
dc.languageEnglish-
dc.publisherSPIE-
dc.titleAssessment of peripheral tissue perfusion by optical dynamic fluorescence imaging and nonlinear regression modeling-
dc.typeArticle-
dc.identifier.scopusid2-s2.0-78249270821-
dc.type.rimsART-
dc.citation.volume7548-
dc.citation.issue0-
dc.citation.beginningpage0-
dc.citation.endingpage0-
dc.citation.publicationnamePROGRESS IN BIOMEDICAL OPTICS AND IMAGING - PROCEEDINGS OF SPIE-
dc.identifier.doi10.1117/12.841620-
dc.contributor.localauthorChoi, Chulhee-
dc.contributor.nonIdAuthorKang, Y.-
dc.contributor.nonIdAuthorLee, J.-
dc.contributor.nonIdAuthorKwon, K.-
dc.subject.keywordAuthordifferential evolution-
dc.subject.keywordAuthorIndicator dilution curve-
dc.subject.keywordAuthormathematical modeling-
dc.subject.keywordAuthorNIR fluorescence imaging-
dc.subject.keywordAuthornon-linear regression-
dc.subject.keywordAuthorperipheral arterial occlusive disease-
dc.subject.keywordAuthortissue perfusion-
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