Software comparison to analyze bone radiomics from high resolution CBCT scans of mandibular condyles.

Autor: Bianchi J; Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI, USA.; Department of Pediatric Dentistry, São Paulo State University (Unesp), School of Dentistry, Araraquara, SP, Brazil., Gonçalves JR; Department of Pediatric Dentistry, São Paulo State University (Unesp), School of Dentistry, Araraquara, SP, Brazil., Ruellas ACO; Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI, USA., Vimort JB; Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI, USA.; Kitware, Inc., Carrboro, NC, USA., Yatabe M; Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI, USA., Paniagua B; Kitware, Inc., Carrboro, NC, USA., Hernandez P; Kitware, Inc., Carrboro, NC, USA., Benavides E; Department of Periodontics and Oral Medicine, School of Dentistry, University of Michigan, Ann Arbor, MI, USA., Soki FN; Department of Periodontics and Oral Medicine, School of Dentistry, University of Michigan, Ann Arbor, MI, USA., Cevidanes LHS; Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI, USA.
Jazyk: angličtina
Zdroj: Dento maxillo facial radiology [Dentomaxillofac Radiol] 2019 Sep; Vol. 48 (6), pp. 20190049. Date of Electronic Publication: 2019 May 20.
DOI: 10.1259/dmfr.20190049
Abstrakt: Objectives: Radiomics refers to the extraction and analysis of advanced quantitative imaging from medical images to diagnose and/or predict diseases. In the dentistry field, the bone data from mandibular condyles could be computationally analyzed using the voxel information provided by high-resolution CBCT scans to increase the diagnostic power of temporomandibular joint (TMJ) conditions. However, such quantitative information demands innovative computational software, algorithm implementation, and validation. Our study's aim was to compare a newly developed BoneTexture application to two-consolidated software with previous applications in the medical field, Ibex and BoneJ, to extract bone morphometric and textural features from mandibular condyles.
Methods: We used an imaging database of HR-CBCT TMJs scans with an isotropic voxel size of 0.08 mm 3 . A single group with 66 distinct mandibular condyles composed the final sample. We calculated 18 variables for bone textural features and 5 for bone morphometric measurements using the Ibex, BoneJ and BoneTexture applications. Spearman correlation and Bland-Altman plot analyses were done to compare the agreement among software.
Results: The results showed a high Spearman correlation among the software applications ( r = 0.7-1), with statistical significance for all variables, except Grey Level Non-Uniformity and Short Run Emphasis. The Bland-Altman vertical axis showed, in general, good agreement between the software applications and the horizontal axis showed a narrow average distribution for Correlation, Long Run Emphasis and Long Run High Grey Level Emphasis.
Conclusions: Our data showed consistency among the three applications to analyze bone radiomics in high-resolution CBCT. Further studies are necessary to evaluate the applicability of those variables as new bone imaging biomarkers to diagnose bone diseases affecting TMJs.
Databáze: MEDLINE
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