Quantitative Computed Tomography and image analysis for advanced muscle assessment

dc.contributorHáskólinn í Reykjavíken_US
dc.contributorReykjavik Universityen_US
dc.contributor.authorÁrnadóttir, Íris Dröfn
dc.contributor.authorPiccione, Francesco
dc.contributor.authorGargiulo, Paolo
dc.contributor.authorEdmunds, Kyle
dc.contributor.authorMagnús Gíslason
dc.contributor.authorMarcante, Andrea
dc.contributor.departmentInstitute of Biomedical and Neural Engineering (IBNE) (RU)en_US
dc.contributor.schoolTækni- og verkfræðideild (HR)en_US
dc.contributor.schoolSchool of Science and Engineering (RU)en_US
dc.date.accessioned2018-11-26T11:17:20Z
dc.date.available2018-11-26T11:17:20Z
dc.date.issued2016
dc.description.abstractMedical imaging is of particular interest in the field of translational myology, as extant literature describes the utilization of a wide variety of techniques to non-invasively recapitulate and quantity various internal and external tissue morphologies. In the clinical context, medical imaging remains a vital tool for diagnostics and investigative assessment. This review outlines the results from several investigations on the use of computed tomography (CT) and image analysis techniques to assess muscle conditions and degenerative process due to aging or pathological conditions. Herein, we detail the acquisition of spiral CT images and the use of advanced image analysis tools to characterize muscles in 2D and 3D. Results from these studies recapitulate changes in tissue composition within muscles, as visualized by the association of tissue types to specified Hounsfield Unit (HU) values for fat, loose connective tissue or atrophic muscle, and normal muscle, including fascia and tendon. We show how results from these analyses can be presented as both average HU values and compositions with respect to total muscle volumes, demonstrating the reliability of these tools to monitor, assess and characterize muscle degeneration.en_US
dc.description.sponsorshipThis research has been supported by the University Hospital Landspitali Scientific fund.en_US
dc.description.versionPeer revieweden_US
dc.format.extent93-100en_US
dc.identifier.citationEdmunds, K. J., Gislason, M. K., Arnadottir, I. D., Marcante, A., Piccione, F., & Gargiulo, P. (2016). Quantitative Computed Tomography and image analysis for advanced muscle assessment. European Journal of Translational Myology, 26(2), 93–100en_US
dc.identifier.doi10.4081/ejtm.2016.6015
dc.identifier.issn2037-7452
dc.identifier.issn2037-7460 (eISSN)
dc.identifier.journalEuropean Journal of Translational Myologyen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11815/920
dc.language.isoenen_US
dc.publisherPagepress Publ, Meditgroupen_US
dc.relation.ispartofseriesEuropean Journal of Translational Myology;26(2)
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectQuantitative computed tomographyen_US
dc.subjectImage analysisen_US
dc.subjectAdvanced muscle assessmenten_US
dc.subjectSneiðmyndatökuren_US
dc.subjectMyndgreining (læknisfræði)en_US
dc.subjectVöðvaren_US
dc.titleQuantitative Computed Tomography and image analysis for advanced muscle assessmenten_US
dc.typeinfo:eu-repo/semantics/articleen_US
dcterms.licenseThis article is distributed under the terms of the Creative Commons Attribution Noncommercial License (CC BY-NC 4.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.en_US

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