Texture analysis of cone‐beam computed tomography images assists the detection of furcal lesion. Issue 9 (26th February 2020)

• Record Type: Journal Article
• Authors: Gonçalves, Bianca C.; de Araújo, Elaine C.; Nussi, Amanda D.; Bechara, Naira; Sarmento, Dmitry; Oliveira, Marcia S.; Santamaria, Mauro P.; Costa, Andre Luiz F.; Lopes, Sérgio
• Is Part Of: Journal of periodontology. Volume 91:Issue 9(2020)
• Page Start: 1159
• Page End: 1166
• Publication Date: 2020-02-26
• Subjects: aggressive periodontitis -- diagnostic imaging -- periodontal diseases -- texture analysis; Periodontics -- Periodicals; 617.632
• DOI: 10.1002/JPER.19-0477
• Languages: English
• ISSNs: 0022-3492

Abstract

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.