@Article{RSM:Bay2012,
  author =       "J.D. Bayer and R.C. Blake and G. Plank and N.A. Trayanova",
  title =        "A novel rule-based algorithm for assigning myocardial
                 fiber orientation to computational heart models.",
  journal =      j-ABE,
  year =         "2012",
  month =        "Oct",
  volume =       "40",
  number =       "10",
  pages =        "2243--2254",
  robnote =      "Electrical waves traveling throughout the myocardium
                 elicit muscle contractions responsible for pumping blood
                 throughout the body. The shape and direction of these
                 waves depend on the spatial arrangement of ventricular
                 myocytes, termed fiber orientation. In computational
                 studies simulating electrical wave propagation or
                 mechanical contraction in the heart, accurately
                 representing fiber orientation is critical so that model
                 predictions corroborate with experimental data. Typically,
                 fiber orientation is assigned to heart models based on
                 Diffusion Tensor Imaging (DTI) data, yet few alternative
                 methodologies exist if DTI data is noisy or absent. Here
                 we present a novel Laplace-Dirichlet Rule-Based (LDRB)
                 algorithm to perform this task with speed, precision, and
                 high usability. We demonstrate the application of the LDRB
                 algorithm in an image-based computational model of the
                 canine ventricles. Simulations of electrical activation in
                 this model are compared to those in the same geometrical
                 model but with DTI-derived fiber orientation. The results
                 demonstrate that activation patterns from simulations with
                 LDRB and DTI-derived fiber orientations are nearly
                 indistinguishable, with relative differences </=6\%,
                 absolute mean differences in activation times </=3.15 ms,
                 and positive correlations >/=0.99. These results
                 convincingly show that the LDRB algorithm is a robust
                 alternative to DTI for assigning fiber orientation to
                 computational heart models.",
  bibdate =      "Sat Nov 24 14:41:52 2012",
}

{"_id":"gK5X48hKv7hpZCvJD","bibbaseid":"bayer-blake-plank-trayanova-anovelrulebasedalgorithmforassigningmyocardialfiberorientationtocomputationalheartmodels-2012","downloads":0,"creationDate":"2016-07-01T21:38:29.900Z","title":"A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models.","author_short":["Bayer, J.","Blake, R.","Plank, G.","Trayanova, N."],"year":2012,"bibtype":"article","biburl":"http://www.sci.utah.edu/~macleod/Bibtex/biglit.bib","bibdata":{"bibtype":"article","type":"article","author":[{"firstnames":["J.D."],"propositions":[],"lastnames":["Bayer"],"suffixes":[]},{"firstnames":["R.C."],"propositions":[],"lastnames":["Blake"],"suffixes":[]},{"firstnames":["G."],"propositions":[],"lastnames":["Plank"],"suffixes":[]},{"firstnames":["N.A."],"propositions":[],"lastnames":["Trayanova"],"suffixes":[]}],"title":"A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models.","journal":"j-ABE","year":"2012","month":"Oct","volume":"40","number":"10","pages":"2243–2254","robnote":"Electrical waves traveling throughout the myocardium elicit muscle contractions responsible for pumping blood throughout the body. The shape and direction of these waves depend on the spatial arrangement of ventricular myocytes, termed fiber orientation. In computational studies simulating electrical wave propagation or mechanical contraction in the heart, accurately representing fiber orientation is critical so that model predictions corroborate with experimental data. Typically, fiber orientation is assigned to heart models based on Diffusion Tensor Imaging (DTI) data, yet few alternative methodologies exist if DTI data is noisy or absent. Here we present a novel Laplace-Dirichlet Rule-Based (LDRB) algorithm to perform this task with speed, precision, and high usability. We demonstrate the application of the LDRB algorithm in an image-based computational model of the canine ventricles. Simulations of electrical activation in this model are compared to those in the same geometrical model but with DTI-derived fiber orientation. The results demonstrate that activation patterns from simulations with LDRB and DTI-derived fiber orientations are nearly indistinguishable, with relative differences </=6%, absolute mean differences in activation times </=3.15 ms, and positive correlations >/=0.99. These results convincingly show that the LDRB algorithm is a robust alternative to DTI for assigning fiber orientation to computational heart models.","bibdate":"Sat Nov 24 14:41:52 2012","bibtex":"@Article{RSM:Bay2012,\n author = \"J.D. Bayer and R.C. Blake and G. Plank and N.A. Trayanova\",\n title = \"A novel rule-based algorithm for assigning myocardial\n fiber orientation to computational heart models.\",\n journal = j-ABE,\n year = \"2012\",\n month = \"Oct\",\n volume = \"40\",\n number = \"10\",\n pages = \"2243--2254\",\n robnote = \"Electrical waves traveling throughout the myocardium\n elicit muscle contractions responsible for pumping blood\n throughout the body. The shape and direction of these\n waves depend on the spatial arrangement of ventricular\n myocytes, termed fiber orientation. In computational\n studies simulating electrical wave propagation or\n mechanical contraction in the heart, accurately\n representing fiber orientation is critical so that model\n predictions corroborate with experimental data. Typically,\n fiber orientation is assigned to heart models based on\n Diffusion Tensor Imaging (DTI) data, yet few alternative\n methodologies exist if DTI data is noisy or absent. Here\n we present a novel Laplace-Dirichlet Rule-Based (LDRB)\n algorithm to perform this task with speed, precision, and\n high usability. We demonstrate the application of the LDRB\n algorithm in an image-based computational model of the\n canine ventricles. Simulations of electrical activation in\n this model are compared to those in the same geometrical\n model but with DTI-derived fiber orientation. The results\n demonstrate that activation patterns from simulations with\n LDRB and DTI-derived fiber orientations are nearly\n indistinguishable, with relative differences </=6\\%,\n absolute mean differences in activation times </=3.15 ms,\n and positive correlations >/=0.99. These results\n convincingly show that the LDRB algorithm is a robust\n alternative to DTI for assigning fiber orientation to\n computational heart models.\",\n bibdate = \"Sat Nov 24 14:41:52 2012\",\n}\n\n","author_short":["Bayer, J.","Blake, R.","Plank, G.","Trayanova, N."],"key":"RSM:Bay2012","id":"RSM:Bay2012","bibbaseid":"bayer-blake-plank-trayanova-anovelrulebasedalgorithmforassigningmyocardialfiberorientationtocomputationalheartmodels-2012","role":"author","urls":{},"metadata":{"authorlinks":{}},"downloads":0,"html":""},"search_terms":["novel","rule","based","algorithm","assigning","myocardial","fiber","orientation","computational","heart","models","bayer","blake","plank","trayanova"],"keywords":[],"authorIDs":[],"dataSources":["5HG3Kp8zRwDd7FotB"]}