Texture analysis of cone-beam computed tomography images assists the detection of furcal lesion

• Autor(a) principal: Gonçalves, Bianca C. [UNESP]
• Data de Publicação: 2020
• Outros Autores: de Araújo, Elaine C. [UNESP], Nussi, Amanda D., Bechara, Naira [UNESP], Sarmento, Dmitry, Oliveira, Marcia S., Santamaria, Mauro P. [UNESP], Costa, Andre Luiz F., Lopes, Sérgio [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1002/JPER.19-0477; http://hdl.handle.net/11449/199384
• topic: aggressive periodontitis; diagnostic imaging; periodontal diseases; texture analysis

Background: The aim of this study was to apply texture analysis (TA) to cone-beam computed tomography (CBCT) scans of patients with grade C periodontitis for detection of non-visible changes in the image. Methods: TA was performed on CBCT scans of 34 patients with grade C periodontitis. Axial sections of CBCT were divided into three groups as follows: Group L (lesion) in which there is a furcal lesion with periodontal bone loss; Group I (intermediate) in which the border of the furcal lesion has normal characteristics; and Group C (control) in which the area is healthy. Eleven texture parameters were extracted from the region of interest. Mann-Whitney U test was used to assess the differences in the texture between the three groups as follows: L versus I; L versus C, and I versus C. Results: Statistically significant differences (P <0.05) were observed in almost all parameters in the intergroup analyses (i.e., L versus I and L versus C). However, statistical differences were smaller in groups I versus C in which only entropy of sum, entropy of difference, mean of sum, and variance of difference were statistically different (P < 0.05). Conclusion: TA can potentially provide prognostic information to improve the diagnostic accuracy in the grading of the tissue around the furcal lesion, thus potentially accelerating the treatment decision-making process.