Texture analysis of cone‐beam computed tomography images assists the detection of furcal lesion
Bianca Costa Gonçalves, Elaine Cristina de Carvalho Beda Correa de Araújo, Amanda Drumstas Nussi, Naira Bechara, Dmitry José de Santana Sarmento, Márcia Silva de Oliveira, Mauro Pedrine Santamaría, André Luiz Ferreira Costa, Sérgio Lúcio Pereira de Castro Lopes
Abstract
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.