Developing a parametric ear model for auricular reconstruction: a new step towards patient-specific implants. Bos, E. J., Scholten, T., Song, Y., Verlinden, J. C., Wolff, J., Forouzanfar, T., Helder, M. N., & van Zuijlen, P. Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery, 43(3):390–395, April, 2015. doi abstract bibtex INTRODUCTION: Ear reconstruction is a tedious and demanding surgical procedure and the implant framework used is essential for the esthetic result. The outcome of a reconstructed ear, however, is not necessarily limited to the implant shape but rather to the available options of transplantable tissue for coverage. Apart from the visual aesthetics, ear reconstruction subsequently also requires implant dimensions to be adapted to the surgical possibilities. In this article, we have brought different disciplines together to develop a customizable ear model for 3D printing of ear implants. MATERIAL AND METHODS: Computed tomography (CT) scans were made of 4 human cadaver ears before and after soft tissue dissection using a Discovery 750 High Definition Freedom Edition scanner (GE, Milwaukee, WI, USA) and subsequently converted into an STL data set using Mimics Software (Materialise, Leuven, Belgium). These scans were then used to develop a fully adjustable parametric model based on the essential ear anatomy using Rhinoceros and Grasshopper software. RESULTS: To determine the quality of the developed models, directed Hausdorff distance (DHD) was applied as the basis for measuring the similarity between the parametric model and the ear cartilage scanning data. Two methods were used. The mean directed Haussdorff distance (MDHD) was calculated based on the distribution of point sets showing an average similarity of 0.8 mm (+/-0.05 mm). The mean similarity coefficient (SC) of the model and scan surfaces was 94% with a 2-mm threshold. CONCLUSION: This study shows that a parametric standard model could be used as a feasible method to generate custom implants based on existing ear images.
@article{bos_developing_2015,
title = {Developing a parametric ear model for auricular reconstruction: a new step towards patient-specific implants.},
volume = {43},
copyright = {Copyright (c) 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.},
issn = {1878-4119 1010-5182},
doi = {10.1016/j.jcms.2014.12.016},
abstract = {INTRODUCTION: Ear reconstruction is a tedious and demanding surgical procedure and the implant framework used is essential for the esthetic result. The outcome of a reconstructed ear, however, is not necessarily limited to the implant shape but rather to the available options of transplantable tissue for coverage. Apart from the visual aesthetics, ear reconstruction subsequently also requires implant dimensions to be adapted to the surgical possibilities. In this article, we have brought different disciplines together to develop a customizable ear model for 3D printing of ear implants. MATERIAL AND METHODS: Computed tomography (CT) scans were made of 4 human cadaver ears before and after soft tissue dissection using a Discovery 750 High Definition Freedom Edition scanner (GE, Milwaukee, WI, USA) and subsequently converted into an STL data set using Mimics Software (Materialise, Leuven, Belgium). These scans were then used to develop a fully adjustable parametric model based on the essential ear anatomy using Rhinoceros and Grasshopper software. RESULTS: To determine the quality of the developed models, directed Hausdorff distance (DHD) was applied as the basis for measuring the similarity between the parametric model and the ear cartilage scanning data. Two methods were used. The mean directed Haussdorff distance (MDHD) was calculated based on the distribution of point sets showing an average similarity of 0.8 mm (+/-0.05 mm). The mean similarity coefficient (SC) of the model and scan surfaces was 94\% with a 2-mm threshold. CONCLUSION: This study shows that a parametric standard model could be used as a feasible method to generate custom implants based on existing ear images.},
language = {eng},
number = {3},
journal = {Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery},
author = {Bos, E. J. and Scholten, T. and Song, Y. and Verlinden, J. C. and Wolff, J. and Forouzanfar, T. and Helder, M. N. and van Zuijlen, P.},
month = apr,
year = {2015},
pmid = {25703503},
keywords = {*Patient-Specific Modeling, Algorithms, Cadaver, Computer-Aided Design, Ear, Ear, External/*anatomy \& histology/surgery, Feasibility Studies, Humans, Image Processing, Computer-Assisted/methods, Implant, Model, Parametric, Personalized, Printing, Three-Dimensional, Prostheses and Implants, Prosthesis Design, Reconstruction, Reconstructive Surgical Procedures/*methods, Tomography, X-Ray Computed/methods},
pages = {390--395},
}
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The outcome of a reconstructed ear, however, is not necessarily limited to the implant shape but rather to the available options of transplantable tissue for coverage. Apart from the visual aesthetics, ear reconstruction subsequently also requires implant dimensions to be adapted to the surgical possibilities. In this article, we have brought different disciplines together to develop a customizable ear model for 3D printing of ear implants. MATERIAL AND METHODS: Computed tomography (CT) scans were made of 4 human cadaver ears before and after soft tissue dissection using a Discovery 750 High Definition Freedom Edition scanner (GE, Milwaukee, WI, USA) and subsequently converted into an STL data set using Mimics Software (Materialise, Leuven, Belgium). These scans were then used to develop a fully adjustable parametric model based on the essential ear anatomy using Rhinoceros and Grasshopper software. RESULTS: To determine the quality of the developed models, directed Hausdorff distance (DHD) was applied as the basis for measuring the similarity between the parametric model and the ear cartilage scanning data. Two methods were used. The mean directed Haussdorff distance (MDHD) was calculated based on the distribution of point sets showing an average similarity of 0.8 mm (+/-0.05 mm). The mean similarity coefficient (SC) of the model and scan surfaces was 94% with a 2-mm threshold. CONCLUSION: This study shows that a parametric standard model could be used as a feasible method to generate custom implants based on existing ear images.","language":"eng","number":"3","journal":"Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery","author":[{"propositions":[],"lastnames":["Bos"],"firstnames":["E.","J."],"suffixes":[]},{"propositions":[],"lastnames":["Scholten"],"firstnames":["T."],"suffixes":[]},{"propositions":[],"lastnames":["Song"],"firstnames":["Y."],"suffixes":[]},{"propositions":[],"lastnames":["Verlinden"],"firstnames":["J.","C."],"suffixes":[]},{"propositions":[],"lastnames":["Wolff"],"firstnames":["J."],"suffixes":[]},{"propositions":[],"lastnames":["Forouzanfar"],"firstnames":["T."],"suffixes":[]},{"propositions":[],"lastnames":["Helder"],"firstnames":["M.","N."],"suffixes":[]},{"propositions":["van"],"lastnames":["Zuijlen"],"firstnames":["P."],"suffixes":[]}],"month":"April","year":"2015","pmid":"25703503","keywords":"*Patient-Specific Modeling, Algorithms, Cadaver, Computer-Aided Design, Ear, Ear, External/*anatomy & histology/surgery, Feasibility Studies, Humans, Image Processing, Computer-Assisted/methods, Implant, Model, Parametric, Personalized, Printing, Three-Dimensional, Prostheses and Implants, Prosthesis Design, Reconstruction, Reconstructive Surgical Procedures/*methods, Tomography, X-Ray Computed/methods","pages":"390–395","bibtex":"@article{bos_developing_2015,\n\ttitle = {Developing a parametric ear model for auricular reconstruction: a new step towards patient-specific implants.},\n\tvolume = {43},\n\tcopyright = {Copyright (c) 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.},\n\tissn = {1878-4119 1010-5182},\n\tdoi = {10.1016/j.jcms.2014.12.016},\n\tabstract = {INTRODUCTION: Ear reconstruction is a tedious and demanding surgical procedure and the implant framework used is essential for the esthetic result. The outcome of a reconstructed ear, however, is not necessarily limited to the implant shape but rather to the available options of transplantable tissue for coverage. Apart from the visual aesthetics, ear reconstruction subsequently also requires implant dimensions to be adapted to the surgical possibilities. In this article, we have brought different disciplines together to develop a customizable ear model for 3D printing of ear implants. MATERIAL AND METHODS: Computed tomography (CT) scans were made of 4 human cadaver ears before and after soft tissue dissection using a Discovery 750 High Definition Freedom Edition scanner (GE, Milwaukee, WI, USA) and subsequently converted into an STL data set using Mimics Software (Materialise, Leuven, Belgium). These scans were then used to develop a fully adjustable parametric model based on the essential ear anatomy using Rhinoceros and Grasshopper software. RESULTS: To determine the quality of the developed models, directed Hausdorff distance (DHD) was applied as the basis for measuring the similarity between the parametric model and the ear cartilage scanning data. Two methods were used. The mean directed Haussdorff distance (MDHD) was calculated based on the distribution of point sets showing an average similarity of 0.8 mm (+/-0.05 mm). The mean similarity coefficient (SC) of the model and scan surfaces was 94\\% with a 2-mm threshold. 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