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DOI 10.1016/j.heliyon.2020.e05194

Медицинская библиотека · Heliyon · 2020

Differentiation of periapical granuloma from radicular cyst using cone beam computed tomography images texture analysis.

De Rosa Catharina Simioni, Bergamini Mariana Lobo, Palmieri Michelle, Sarmento Dmitry José de Santana, de Carvalho Marcia Oliveira, Ricardo Ana Lúcia Franco, Hasseus Bengt, Jonasson Peter, Braz-Silva Paulo Henrique, Ferreira Costa Andre Luiz

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Аннотация

OBJECTIVE

This study aimed to investigate the use of texture analysis for characterization of radicular cysts and periapical granulomas and to assess its efficacy to differentiate between both lesions with histological diagnosis.

METHODS

Cone beam computed tomography (CBCT) images were obtained from 19 patients with 25 periapical lesions (14 radicular cysts and 11 periapical granulomas) confirmed by biopsy. Regions of interest were created in the lesions from which 11 texture parameters were calculated. Spearman's correlation analysis was performed and adjusted with Benjamini-Hochberg false discovery rate procedure (FDR <0.005).

RESULTS

The texture parameters used to differentiate the lesions were assessed by using a receiver operating characteristic analysis. Five texture parameters were predictive of lesion differentiation for eight positions: angular second moment; sum of squares; sum of average; contrast; correlation.

CONCLUSION

Texture analysis of CBCT scans distinguishes radicular cysts from periapical granulomas and can be a promising diagnostic tool for periapical lesions.

CLINICAL SIGNIFICANCE: Texture analysis can be used in diagnostic and treatment monitoring to provide supplementary information.

Для цитирования: De Rosa Catharina Simioni, Bergamini Mariana Lobo, Palmieri Michelle, Sarmento Dmitry José de Santana, de Carvalho Marcia Oliveira, Ricardo Ana Lúcia Franco, Hasseus Bengt, Jonasson Peter, Braz-Silva Paulo Henrique, Ferreira Costa Andre Luiz. Differentiation of periapical granuloma from radicular cyst using cone beam computed tomography images texture analysis.. Heliyon. 2020. DOI: 10.1016/j.heliyon.2020.e05194.
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