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Head motion during cone-beam computed tomography: Analysis of frequency and influence on image quality

Imaging Science in Dentistry 2020³â 50±Ç 3È£ p.227 ~ 236
Moratin Julius, Berger Moritz, Ruckschloss Thomas, Metzger Karl, Berger Hannah, Gottsauner Maximilian, Engel Michael, Hoffmann Jurgen, Freudlsperger Christian, Ristow Oliver,
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 ( Moratin Julius ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery
 ( Berger Moritz ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery
 ( Ruckschloss Thomas ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery
 ( Metzger Karl ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery
 ( Berger Hannah ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery
 ( Gottsauner Maximilian ) - University Hospital Regensburg Department of Oral and Maxillofacial Surgery
 ( Engel Michael ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery
 ( Hoffmann Jurgen ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery
 ( Freudlsperger Christian ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery
 ( Ristow Oliver ) - University Hospital Heidelberg Department of Oral and Maxillofacial Surgery

Abstract


Purpose: Image artifacts caused by patient motion cause problems in cone-beam computed tomography (CBCT) because they lead to distortion of the 3-dimensional reconstruction. This prospective study was performed to quantify patient movement during CBCT acquisition and its influence on image quality.

Materials and Methods: In total, 412 patients receiving CBCT imaging were equipped with a wireless head sensor system that detected inertial, gyroscopic, and magnetometric movements with 6 dimensions of freedom. The type and amplitude of movements during CBCT acquisition were evaluated and image quality was rated in 7 different anatomical regions of interest. For continuous variables, significance was calculated using the Student t-test. A linear regression model was applied to identify associations of the type and extent of motion with image quality scores. Kappa statistics were used to assess intra- and inter-rater agreement. Chi-square testing was used to analyze the impact of age and sex on head movement.

Results: All CBCT images were acquired in a 10-month period. In 24% of the investigations, movement was recorded (acceleration: >0.10 [m/s2]; angular velocity: >0.018 [¡Æ/s]). In all examined regions of interest, head motion during CBCT acquisition resulted in significant impairment of image quality (P<0.001). Movement in the horizontal and vertical axes was most relevant for image quality (R2>0.7).

Conclusion: Relevant head motions during CBCT imaging were frequently detected, leading to image quality loss and potentially impairing diagnosis and therapy planning. The presented data illustrate the need for digital correction algorithms and hardware to minimize motion artefacts in CBCT imaging.

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Cone-Beam Computed Tomography; Diagnostic Imaging; Motion; Artifacts

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