Development and validation methodology of the Nuss procedure surgical planner : Medical Simulation
Identifieur interne : 000164 ( PascalFrancis/Checkpoint ); précédent : 000163; suivant : 000165Development and validation methodology of the Nuss procedure surgical planner : Medical Simulation
Auteurs : Krzysztof J. Rechowicz [États-Unis] ; Frederic D. Mckenzie [États-Unis]Source :
- Simulation : (San Diego, Calif.) [ 0037-5497 ] ; 2013.
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Abstract
Surgical planners are used to achieve the optimal outcome for surgery. They are especially desired in procedures where a positive aesthetic outcome is the primary goal, such as the Nuss procedure which is a minimally invasive surgery for correcting pectus excavatum (PE) - a congenital chest wall deformity which is characterized by a deep depression of the sternum. The Nuss procedure consists of placement of a metal bar(s) underneath the sternum, thereby forcibly changing the geometry of the ribcage. Because of the prevalence of PE and the popularity of the Nuss procedure, the demand to perform this surgery is greater than ever. Therefore, a Nuss procedure surgical planner is an invaluable planning tool ensuring an optimal physiological and aesthetic outcome. We propose the development and validation of the Nuss procedure planner. First, a generic model of the ribcage is developed. Then, the computed tomography (CT) data collected from actual patients with PE is used to create a set of patient-specific finite element models (FEM). Based on finite element analyses (FEA) a force-displacement data set is created. This data is used to train an artificial neural network (ANN) to generalize the data set. In order to evaluate the planning process, a methodology which uses an average shape of the chest for comparison with results of the Nuss procedure planner is developed. Haptic feedback and inertial tracking is also implemented. The results show that it is possible to utilize this approximation of the force-displacement model for a Nuss procedure planner and trainer.
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Diego Calif.)</title><idno type="ISSN">0037-5497</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Aesthetics</term><term>Chest wall</term><term>Computerized tomography</term><term>Depression</term><term>Finite element method</term><term>Malformation</term><term>Minimally invasive surgery</term><term>Modeling</term><term>Neural network</term><term>Physiology</term><term>Planning</term><term>Tactile sensitivity</term><term>Tracking</term><term>Tracking(movable target)</term><term>User interface</term><term>Validation</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Chirurgie miniinvasive</term><term>Planification</term><term>Interface utilisateur</term><term>Pistage</term><term>Poursuite</term><term>Paroi thoracique</term><term>Esthétique</term><term>Etat dépressif</term><term>Malformation</term><term>Physiologie</term><term>Sensibilité tactile</term><term>Validation</term><term>Modélisation</term><term>Méthode élément fini</term><term>Réseau neuronal</term><term>Tomographie numérique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Surgical planners are used to achieve the optimal outcome for surgery. They are especially desired in procedures where a positive aesthetic outcome is the primary goal, such as the Nuss procedure which is a minimally invasive surgery for correcting pectus excavatum (PE) - a congenital chest wall deformity which is characterized by a deep depression of the sternum. The Nuss procedure consists of placement of a metal bar(s) underneath the sternum, thereby forcibly changing the geometry of the ribcage. Because of the prevalence of PE and the popularity of the Nuss procedure, the demand to perform this surgery is greater than ever. Therefore, a Nuss procedure surgical planner is an invaluable planning tool ensuring an optimal physiological and aesthetic outcome. We propose the development and validation of the Nuss procedure planner. First, a generic model of the ribcage is developed. Then, the computed tomography (CT) data collected from actual patients with PE is used to create a set of patient-specific finite element models (FEM). Based on finite element analyses (FEA) a force-displacement data set is created. This data is used to train an artificial neural network (ANN) to generalize the data set. In order to evaluate the planning process, a methodology which uses an average shape of the chest for comparison with results of the Nuss procedure planner is developed. Haptic feedback and inertial tracking is also implemented. The results show that it is possible to utilize this approximation of the force-displacement model for a Nuss procedure planner and trainer.</div></front></TEI><inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0037-5497</s0></fA01><fA03 i2="1"><s0>Simulation : (S. 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Rechowicz</name></region><name sortKey="Mckenzie, Frederic D" sort="Mckenzie, Frederic D" uniqKey="Mckenzie F" first="Frederic D." last="Mckenzie">Frederic D. Mckenzie</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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