In recent decades, there have been important developments in temporomandibular joint (TMJ) imaging. New techniques complement preexisting methods, and each modality is indicated for specific conditions in accordance with the clinical diagnosis. The aim of this review is to give an overview of conventional and new techniques in TMJ imaging. The literature review includes studies published between 1976 and 2009 that appear in the Medline database. Magnetic resonance imaging remains the ''gold standard'' modality for TMJ analysis. It allows structures to be visualized without radiation whether or not they are mineralized; however, it is costly and complex. Ultrasonography, an alternative method with increasing importance in TMJ analysis, is a simple, noninvasive, and low-cost technique that allows for the visualization of the position of the disk; however, it does not detect condylar abnormalities. Reconstructions in three-dimensions can be obtained with computed tomography, magnetic resonance imaging, and ultrasonography and can be used to obtain rapid prototyping biomodels. Health professionals performing TMJ imaging exams should consider clinical history and findings, exam cost, radiation exposure, results of previous exams, and whether the current result will influence diagnosis and treatment planning.
Background This study aimed to search for scientific evidence concerning the accuracy of computer-assisted analysis for diagnosing odontogenic cysts. Material and Methods A systematic review was conducted according to the PRISMA statements and considering eleven databases, including the grey literature. Protocol was registered in PROSPERO (CRD 42020189349). The PECO strategy was used to define the eligibility criteria and only studies involving diagnostic accuracy were included. Their risk of bias was investigated using the Joanna Briggs Institute Critical Appraisal tool. Results Out of 437 identified citations, five papers, published between 2006 and 2019, fulfilled the criteria and were included in this systematic review. A total of 5,264 images from 508 lesions, classified as radicular cyst, odontogenic keratocyst, lateral periodontal cyst, glandular odontogenic cyst, or dentigerous cyst, were analyzed. All selected articles scored low risk of bias. In three studies, the best performances were achieved when the two subtypes of odontogenic keratocysts (solitary or syndromic) were pooled together, the case-wise analysis showing a success rate of 100% for odontogenic keratocysts and radicular cysts, in one of them. In two studies, the dentigerous cyst was associated with the majority of misclassifications, and its omission from the dataset improved significantly the classification rates. Conclusions The overall evaluation showed all studies presented high accuracy rates of computer-aided systems in classifying odontogenic cysts in digital images of histological tissue sections. However, due to the heterogeneity of the studies, a meta-analysis evaluating the outcomes of interest was not performed and a pragmatic recommendation about their use is not possible. Key words: Computer-assisted diagnosis, computer-assisted image analysis, computer-assisted image processing, odontogenic cysts, keratocysts, radicular cysts.
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