Evaluation of feline permanent canine tooth mineral density using micro-computed tomography

• Published in: Veterinary sciences 2023-03, Vol.10 (3), p.1-10
• Main Authors: Silva, Graça, Babo, Pedro Miguel Sousa, Azevedo, Jorge, Gomes, Manuela E., Viegas, Carlos, Requicha, João F.
• Format: Article
• Language: English
• Subjects: Canine teeth; Canine tooth; Cat; Cementum; Computed tomography; CT imaging; Dental enamel; Dental pulp; Dentin; Dentistry; Diagnosis; Disease; Enamel; Endodontics; Hydroxyapatite; micro-computed tomography; Mineral density; Pathology; Radiation; Radiography; Science & Technology; Teeth; Tomography; Veterinary medicine
• ISSN: 2306-7381; 2306-7381
• DOI: 10.3390/vetsci10030217

The tooth is made up of three mineralized tissues, enamel, dentin, and cementum, which surround a non-mineralized tissue called the dental pulp. Micro-computed tomography (mCT) is an imaging technology based on X-rays that allows non-invasive visualization of objects at a microscopic scale, according to their radiopacity and in three dimensions (3D). Likewise, it allows the subsequent execution of morphological and quantitative analysis of the objects, such as, for example, the determination of the relative mineral density (MD). The present work aimed to describe the MD of feline teeth using mCT. The studied sample consisted of four European Shorthair cats, from which nine canine teeth were extracted per medical indication. These teeth were evaluated through dental radiography before and after their extraction. Using mCT and the CTAn software, the values of the relative mineral density of the root of each tooth and of specific segments corresponding to the coronal, middle, and apical thirds of the root were determined. Mean MD of root tissues was 1.374 ± 0040 g·cm −3 , and of hard root, tissues was 1.402 ± 0.035 g·cm −3 . Through mCT, it was possible to determine the mean MD values of feline canine teeth. The study of MD could become an ancillary method for the diagnosis and characterization of dental pathology. This work was funded by national funds through FCT—Foundation for Science and Technology, I.P., under the Scientific Employment Stimulus—Institutional Call-CEECINS/00127/2018 (J.F. Requicha) and supported by the projects UIDB/CVT/00772/2020 and LA/P/0059/2020.