Quantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation procedures

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dc.contributor.authorRettmann, Maryam E.
dc.contributor.authorHolmes, David R.
dc.contributor.authorKwartowitz, David M.
dc.contributor.authorGunawan, Mia
dc.contributor.authorJohnson, Susan B.
dc.contributor.authorCamp, Jon J.
dc.contributor.authorCameron, Bruce M.
dc.contributor.authorDalegrave, Charles [UNIFESP]
dc.contributor.authorKolasa, Mark W.
dc.contributor.authorPacker, Douglas L.
dc.contributor.authorRobb, Richard A.
dc.contributor.institutionMayo Clin
dc.contributor.institutionClemson Univ
dc.contributor.institutionGeorgetown Univ
dc.contributor.institutionUniversidade Federal de São Paulo (UNIFESP)
dc.contributor.institutionDavid Grant Med Ctr
dc.date.accessioned2016-01-24T14:35:17Z
dc.date.available2016-01-24T14:35:17Z
dc.date.issued2014-02-01
dc.description.abstractPurpose: in cardiac ablation therapy, accurate anatomic guidance is necessary to create effective tissue lesions for elimination of left atrial fibrillation. While fluoroscopy, ultrasound, and electroanatomic maps are important guidance tools, they lack information regarding detailed patient anatomy which can be obtained from high resolution imaging techniques. for this reason, there has been significant effort in incorporating detailed, patient-specific models generated from preoperative imaging datasets into the procedure. Both clinical and animal studies have investigated registration and targeting accuracy when using preoperative models; however, the effect of various error sources on registration accuracy has not been quantitatively evaluated.Methods: Data from phantom, canine, and patient studies are used to model and evaluate registration accuracy. in the phantom studies, data are collected using a magnetically tracked catheter on a static phantom model. Monte Carlo simulation studies were run to evaluate both baseline errors as well as the effect of different sources of error that would be present in a dynamic in vivo setting. Error is simulated by varying the variance parameters on the landmark fiducial, physical target, and surface point locations in the phantom simulation studies. in vivo validation studies were undertaken in six canines in which metal clips were placed in the left atrium to serve as ground truth points. A small clinical evaluation was completed in three patients. Landmark-based and combined landmark and surface-based registration algorithms were evaluated in all studies. in the phantom and canine studies, both target registration error and point-to-surface error are used to assess accuracy. in the patient studies, no ground truth is available and registration accuracy is quantified using point-to-surface error only.Results: the phantom simulation studies demonstrated that combined landmark and surface-based registration improved landmark-only registration provided the noise in the surface points is not excessively high. Increased variability on the landmark fiducials resulted in increased registration errors; however, refinement of the initial landmark registration by the surface-based algorithm can compensate for small initial misalignments. the surface-based registration algorithm is quite robust to noise on the surface points and continues to improve landmark registration even at high levels of noise on the surface points. Both the canine and patient studies also demonstrate that combined landmark and surface registration has lower errors than landmark registration alone.Conclusions: in this work, we describe a model for evaluating the impact of noise variability on the input parameters of a registration algorithm in the context of cardiac ablation therapy. the model can be used to predict both registration error as well as assess which inputs have the largest effect on registration accuracy. (C) 2014 American Association of Physicists in Medicine.en
dc.description.affiliationMayo Clin, Coll Med, Rochester, MN 55905 USA
dc.description.affiliationClemson Univ, Dept Bioengn, Clemson, SC 29634 USA
dc.description.affiliationGeorgetown Univ, Dept Biochem & Mol & Cellular Biol, Washington, DC 20057 USA
dc.description.affiliationMayo Clin, Div Cardiovasc Dis, Rochester, MN 55905 USA
dc.description.affiliationUniversidade Federal de São Paulo, Div Cardiol, Hosp São Paulo, BR-04024002 São Paulo, Brazil
dc.description.affiliationDavid Grant Med Ctr, Fairfield, CA 94535 USA
dc.description.affiliationUnifespUniversidade Federal de São Paulo, Div Cardiol, Hosp São Paulo, BR-04024002 São Paulo, Brazil
dc.description.sourceWeb of Science
dc.description.sponsorshipNational Institutes of Health (NIH) from the National Institute of Biomedical Imaging and Bioengineering
dc.description.sponsorshipIDNational Institutes of Health (NIH) from the National Institute of Biomedical Imaging and Bioengineering: RO1EB002834
dc.format.extent11
dc.identifierhttp://dx.doi.org/10.1118/1.4861712
dc.identifier.citationMedical Physics. Melville: Amer Assoc Physicists Medicine Amer Inst Physics, v. 41, n. 2, 11 p., 2014.
dc.identifier.doi10.1118/1.4861712
dc.identifier.issn0094-2405
dc.identifier.urihttp://repositorio.unifesp.br/handle/11600/37416
dc.identifier.wosWOS:000331213300042
dc.language.isoeng
dc.publisherAmer Assoc Physicists Medicine Amer Inst Physics
dc.relation.ispartofMedical Physics
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectleft atriumen
dc.subjectcardiac ablationen
dc.subjectatrial fibrillationen
dc.subjectimage-guided interventionsen
dc.subjectregistrationen
dc.titleQuantitative modeling of the accuracy in registering preoperative patient-specific anatomic models into left atrial cardiac ablation proceduresen
dc.typeinfo:eu-repo/semantics/article
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