Análise de acurácia do diagnóstico assistido por computador no diagnóstico de lesões radiolucentes maxilofaciais - uma revisão sistemática e meta-análise

Objective: This study aimed to conduct a systematic review of the literature on the accuracy of computational image processing for the diagnosis of radiolucent maxillofacial lesions in comparison with histological biopsy diagnosis. Methods: A systematic review was conducted according to the statements of PRISMA- P and considering ten databases, including the grey literature. Protocol was registered in PROSPERO (CRD [Blinding]). The PICO strategy was used to define the eligibility criteria and only diagnostic test studies were included. Their risk of bias was assessed by the Joanna Briggs Institute Critical Appraisal tool. Random-effects model meta-analysis was performed and heterogeneity among the included studies was estimated using the I2 statistic. The GRADE tool assessed the quality of evidence and strength of recommendation across included studies. Results: Out of 715 identified citations, four papers, published between 2009 and 2017, fulfilled the criteria and were included in this systematic review. A total of 191 lesions, classified as periapical granuloma and cyst, dentigerous cyst, or keratocystic odontogenic tumor, were analyzed. All selected articles scored low risk of bias. The pooled accuracy estimation, regardless of the classification method used, was 88.75% (95% CI = 85.19-92.30). Heterogeneity test reached moderate values (I2 = 57.89%). According to the GRADE tool, the analyzed outcome was classified as having low level of certainty. Conclusions: The overall evaluation showed all studies presented high accuracy rates of computer-aided diagnosis systems in classifying radiolucent maxillofacial lesions compared to histopathological biopsy. However, due to the moderate heterogeneity found among the studies included in this meta-analysis, a pragmatic recommendation about the use of computer-assisted analysis is not possible.

Grantor dc:publisher

Universidade Federal do Rio Grande do Norte

Year dc:date.issued

2020

Author dc:creator

• Silva, Virgínia Kelma dos Santos

Advisor dc:contributor.advisor

• Galvão, Hebel Cavalcanti

• Processamento de imagem assistida por computador
• Diagnóstico assistido por computador
• Análise de imagem assistida por computador
• Cisto periapical
• Patologia maxilofacial

Statement dc:rights

• Acesso Aberto

Language dc:language

pt_BR

Repository record dc:identifier.uri

https://repositorio.ufrn.br/handle/123456789/44932

OAI identifier oai:identifier

oai:repositorio.ufrn.br:123456789/44932