Variables included in multiple regression model.

<p>Outliers outside 3 standard deviations are excluded in regression analysis, VIF: variance inflation factor.</p><p>Variables included in multiple regression model.</p

Reorientation error (RE) and factors influencing RE.

<p>Reorientation error (RE) and factors influencing RE.</p

Landmarks before reorientation.

<p>Landmarks before reorientation.</p

Reorientation axes.

<p>y and ź are lines parallel to y and z axis respectively.</p

Factors Influencing Superimposition Error of 3D Cephalometric Landmarks by Plane Orientation Method Using 4 Reference Points: 4 Point Superimposition Error Regression Model

<div><p>Superimposition has been used as a method to evaluate the changes of orthodontic or orthopedic treatment in the dental field. With the introduction of cone beam CT (CBCT), evaluating 3 dimensional changes after treatment became possible by superimposition. 4 point plane orientation is one of the simplest ways to achieve superimposition of 3 dimensional images. To find factors influencing superimposition error of cephalometric landmarks by 4 point plane orientation method and to evaluate the reproducibility of cephalometric landmarks for analyzing superimposition error, 20 patients were analyzed who had normal skeletal and occlusal relationship and took CBCT for diagnosis of temporomandibular disorder. The nasion, sella turcica, basion and midpoint between the left and the right most posterior point of the lesser wing of sphenoidal bone were used to define a three-dimensional (3D) anatomical reference co-ordinate system. Another 15 reference cephalometric points were also determined three times in the same image. Reorientation error of each landmark could be explained substantially (23%) by linear regression model, which consists of 3 factors describing position of each landmark towards reference axes and locating error. 4 point plane orientation system may produce an amount of reorientation error that may vary according to the perpendicular distance between the landmark and the x-axis; the reorientation error also increases as the locating error and shift of reference axes viewed from each landmark increases. Therefore, in order to reduce the reorientation error, accuracy of all landmarks including the reference points is important. Construction of the regression model using reference points of greater precision is required for the clinical application of this model.</p></div

Locating error (coordinate).

<p>Locating error (coordinate).</p

Locating error (coordinate).

<p>Locating error (coordinate).</p

Definition of the three spatial planes of the 19 points used in this study.

<p>Anteroposterior point(APP), Midpoint(MP), Posterior point(PP), Lowest Point(LP), Upper point(UP), Anterior-lower Point(ALP), Anterior-upper Point(AUP), Posterior-lower Point(PLP), Highest Point(HP), Inner Point(IP).</p><p>Definition of the three spatial planes of the 19 points used in this study.</p

A3r: Sum of angle errors (S, Na, Ba) from an averaged landmark.

<p>() α, β and γ represent angle errors viewed from an averaged landmark () respectively.</p

DX: Distance from X-axis to an averaged landmark.

<p>() The rotated arrow around X axis represents pitch rotation</p