Development and validation of a 3D anthropomorphic phantom for dental CBCT imaging research

Author:

Merken Karen1,Monnens Janne1,Marshall Nicholas1,Johan Nuyts2,Brasil Danieli Moura3,Santaella Gustavo Machado3,Politis Constantinus4,Jacobs Reinhilde45,Bosmans Hilde1

Affiliation:

1. Department of Imaging and Pathology Division of Medical Physics & Quality Assessment KU Leuven Leuven Belgium

2. Department of Imaging and Pathology Division of Nuclear Medicine & Molecular Imaging KU Leuven Leuven Belgium

3. Department of Diagnosis and Oral Health School of Dentistry University of Louisville Louisville Kentucky USA

4. Department of Imaging and Pathology Division of Oral and Maxillofacial Surgery KU Leuven Leuven Belgium

5. Department of Dental Medicine Karolinska Institutet Huddinge Sweden

Abstract

AbstractBackgroundOptimization of dental cone beam computed tomography (CBCT) imaging is still in a preliminary stage and should be addressed using task‐based methods. Dedicated models containing relevant clinical tasks for image quality studies have yet to be developed.PurposeTo present a methodology to develop and validate a virtual adult anthropomorphic voxel phantom for use in task‐based image quality optimization studies in dental CBCT imaging research, focusing on root fracture (RF) detection tasks in the presence of metal artefacts.MethodsThe phantom was developed from a CBCT scan with an isotropic voxel size of 0.2 mm, from which the main dental structures, mandible and maxilla were segmented. The missing large anatomical structures, including the spine, skull and remaining soft tissues, were segmented from a lower resolution full skull scan. Anatomical abnormalities were absent in the areas of interest. Fine detailed dental structures, that could not be segmented due to the limited resolution and noise in the clinical data, were modelled using a‐priori anatomical knowledge. Model resolution of the teeth was therefore increased to 0.05 mm. Models of RFs as well as dental restorations to create the artefacts, were developed, and could be inserted in the phantom in any desired configuration. Simulated CBCT images of the models were generated using a newly developed multi‐resolution simulation framework that incorporated the geometry, beam quality, noise and spatial resolution characteristics of a real dental CBCT scanner. Ray‐tracing and Monte Carlo techniques were used to create the projection images, which were reconstructed using the classical FDK algorithm. Validation of the models was assessed by measurements of different tooth lengths, the pulp volume and the mandible, and comparison with reference values. Additionally, the simulated images were used in a reader study in which two oral radiologists had to score the realism level of the model's normal anatomy, as well as the modelled RFs and restorations.ResultsA model of an adult head, as well as models of RFs and different types of dental restorations were created. Anatomical measurements were consistent with ranges reported in literature. For the tooth length measurements, the deviations from the mean reference values were less than 20%. In 77% of all the measurements, the deviations were within 10.1%. The pulp volumes, and mandible measurements were within one standard deviation of the reference values. Regarding the normal anatomy, both readers considered the realism level of the dental structures to be good. Background structures received a lower realism score due to the lack of detailed enough trabecular bone structure, which was expected but not the focus of this study. All modelled RFs were scored at least adequate by at least one of the readers, both in appearance and position. The realism level of the modelled restorations was considered to be good.ConclusionsA methodology was proposed to develop and validate an anthropomorphic voxel phantom for image quality optimization studies in dental CBCT imaging, with a main focus on RF detection tasks. The methodology can be extended further to create more models representative of the clinical population.

Publisher

Wiley

Subject

General Medicine

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