Multiobjective optimization framework for landmark measurement error correction in three-dimensional cephalometric tomography

Abstract

The purpose of this study is to minimize errors that occur when using a four vs six landmark superimpositioning method in the cranial base to define the co-ordinate system. Cone beam CT volumetric data from ten patients were used for this study. Co-ordinate system transformations were performed. A co-ordinate system was constructed using two planes defined by four anatomical landmarks located by an orthodontist. A second co-ordinate system was constructed using four anatomical landmarks that are corrected using a numerical optimization algorithm for any landmark location operator error using information from six landmarks. The optimization algorithm minimizes the relative distance and angle between the known fixed points in the two images to find the correction. Measurement errors and coordinates in all axes were obtained for each co-ordinate system. Significant improvement is observed after using the landmark correction algorithm to position the final co-ordinate system. The errors found in a previous study are significantly reduced. Errors found were between 1 mm and 2 mm. When analysing real patient data, it was found that the 6-point correction algorithm reduced errors between images and increased intrapoint reliability. A novel method of optimizing the overlay of three-dimensional images using a 6-point correction algorithm was introduced and examined. This method demonstrated greater reliability and reproducibility than the previous 4-point correction algorithm. Dentomaxillofacial Radiology (2013Radiology ( ) 42, 20130035. doi: 10.1259 Cite this article as: DeCesare A, Secanell M, Lagravère MO, Carey J. Multiobjective optimization framework for landmark measurement error correction in three-dimensional cephalometric tomography.

Reliability of three-dimensional anterior cranial base superimposition methods for assessment of overall hard tissue changes: A systematic review

“…Pre-and posttreatment images were registered on the anterior cranial base surface on all studies, 3,7,12,16,21,25 and one was also superimposed on the left zygomatic arch. 12 …”

“…DeCesare et al 7 assessed the six-landmark superimposition method when defining the coordinate system using data from 10 growing patients. The error reported was the absolute value of the difference in distances between the points calculated for the first image and the second image.…”

“…The application of this method has been widely 25 Cevidanes et al 16 Nada et al 12 DeCesare et al 7 Gkantidis et al 21 Weissheimer et al…”

“…1,4 However, two-dimensional (2D) cephalometric radiographs suffer from a number of inherent flaws, such as errors generated because of inadequate patient head position, alignment of the imaging device, inherent geometric distortions, and differential magnification created by projection distance and beam divergence. 1,[5][6][7][8][9] During the past decade, craniofacial three-dimensional (3D) digital records have become increasingly popular among orthodontists as the specialty progressed toward a 3D virtual representation of the patient for diagnosis, treatment planning, and surgical simulation. The advanced imaging capabilities of conebeam computed tomography (CBCT) are depicted through 3D cephalometric analysis, temporomandibular joint visualization, and 3D evaluation of dental anomalies, to name only a few.…”

“…[12][13][14] One of the main challenges of 3D superimposition of serial images is to understand that linear/angular measurements in 2D and 3D images are not directly comparable because of differences in size, shape, and relative spatial location of the skeletal, dental, and soft tissue between the two imaging systems. 4,15 The following three general methods of 3D cephalometric superimposition have been published and used for clinical diagnosis and assessment of orthodontic treatment outcomes: (1) voxel based, 3,4,[16][17][18][19] (2) landmark based, 7,20 and (3) surface based. 4,21 A review addressing the 3D CBCT superimposition methods was published in 2015.…”