Mandibular asymmetry characterization using generalized tensor-based morphometry

Quantitative assessment of facial asymmetry is crucial for successful planning of corrective surgery. We propose a tensor-based morphometry (TBM) framework to locate and quantify asymmetry using 3D CBCT images. To this end, we compute a rigid transformation between the mandible segmentation and its mirror image, which yields global rotation and translation with respect to the cranial base to guide the surgery's first stage. Next, we nonrigidly register the rigidly aligned images and use TBM methods to locally analyze the deformation field. This yields data on the location, amount and direction of “growth” (or “shrinkage”) between the left and right sides. We visualize this data in a volumetric manner and via scalar and vector maps on the mandibular surface to provide the surgeon with optimal understanding of the patient's anatomy. We illustrate the feasibility and strength of our technique on 3 representative patients with a wide range of facial asymmetries.

[1]  Colin Studholme,et al.  Measures for Characterizing Directionality Specific Volume Changes in TBM of Brain Growth , 2010, MICCAI.

[2]  P. Pirttiniemi,et al.  3-D analysis of facial asymmetry in children with hip dysplasia. , 2010, The Angle orthodontist.

[3]  Alan C. Evans,et al.  Cerebral asymmetries in 12-week-old C57Bl/6J mice measured by magnetic resonance imaging , 2010, NeuroImage.

[4]  S. Bartlett,et al.  Mandibular Deformities: Single-Vector Distraction Techniques for a Multivector Problem , 2009, The Journal of craniofacial surgery.

[5]  Paul M. Thompson,et al.  Generalized Tensor-Based Morphometry of HIV/AIDS Using Multivariate Statistics on Deformation Tensors , 2008, IEEE Transactions on Medical Imaging.

[6]  S. Schendel,et al.  Computer Simulation of Curvilinear Mandibular Distraction: Accuracy and Predictability , 2007, Plastic and reconstructive surgery.

[7]  Paul M. Thompson,et al.  Mean Template for Tensor-Based Morphometry Using Deformation Tensors , 2007, MICCAI.

[8]  P. Pirttiniemi,et al.  Management of facial asymmetry. , 2007, Oral and maxillofacial surgery clinics of North America.

[9]  Torsten Rohlfing,et al.  Deformation-based brain morphometry to track the course of alcoholism: Differences between intra-subject and inter-subject analysis , 2006, Psychiatry Research: Neuroimaging.

[10]  Michael W. Weiner,et al.  Chronic active heavy drinking and family history of problem drinking modulate regional brain tissue volumes , 2005, Psychiatry Research: Neuroimaging.

[11]  Norbert Schuff,et al.  Deformation tensor morphometry of semantic dementia with quantitative validation , 2004, NeuroImage.

[12]  Seiji Haraguchi,et al.  Facial asymmetry in subjects with skeletal Class III deformity. , 2009, The Angle orthodontist.

[13]  Mark Meyer,et al.  Discrete Differential-Geometry Operators for Triangulated 2-Manifolds , 2002, VisMath.

[14]  Alan C. Evans,et al.  A Unified Statistical Approach to Deformation-Based Morphometry , 2001, NeuroImage.

[15]  O M Antonyshyn,et al.  Facial asymmetry: three-dimensional analysis using laser surface scanning. , 1999, Plastic and reconstructive surgery.

[16]  S. Kiebel,et al.  Detecting Structural Changes in Whole Brain Based on Nonlinear Deformations—Application to Schizophrenia Research , 1999, NeuroImage.

[17]  U. Grenander,et al.  Computational anatomy: an emerging discipline , 1998 .

[18]  James C. Gee,et al.  Atlas warping for brain morphometry , 1998, Medical Imaging.

[19]  Michael I. Miller,et al.  Deformable templates using large deformation kinematics , 1996, IEEE Trans. Image Process..

[20]  Jerry L Prince,et al.  A computerized approach for morphological analysis of the corpus callosum. , 1996, Journal of computer assisted tomography.