Abstract
This study assessed whether the use of digital image filters influences the detection of temporomandibular joint (TMJ) bone changes on cone beam computed tomography (CBCT). Two radiologists evaluated the TMJ images of CBCT scans to verify the presence of osteophytes, erosions, pseudocysts, bone sclerosis and flattening, using the software XoranCAT®; each image of the TMJ was assessed with and without the use of the following filters: Angio Sharpen 3x3 and Angio Sharpen 5x5. Kruskal-Wallis’ test was used to assess whether the application of filters influenced the scores assigned to the degenerative bone changes in the condyle. Flattening was present in 15 cases (51.72%), followed by osteophytes in six cases (20.69%), sclerosis in three cases (10.34%), and erosion in three cases (10.34%), with pseudocyst found in two cases (6.90%). No statistically significant difference was found in the scores (P = 0.786) regarding the original images and those treated with both filters. Digital image filters used in our study did not influence the diagnosis of degenerative bone changes in the TMJ on CBCT images.
Highlights
Degenerative bone changes, known as osteoarthrosis, are a deteriorating, progressive, chronic condition defined as being a gradual deterioration of the bone surface, affecting more women and elderly individuals
The sample size was defined based on the total of cone beam computed tomography (CBCT) available in a private clinic, all taken for evaluation of the temporomandibular joint (TMJ) in both men and women
The CBCT images used in this work belonged to 91 patients, where 17 were male (18.7%) and 74 female (81.3%)
Summary
Degenerative bone changes, known as osteoarthrosis, are a deteriorating, progressive, chronic condition defined as being a gradual deterioration of the bone surface, affecting more women and elderly individuals. Digital filters for image enhancement are an alternative approach used to improve images, facilitating the evaluation of temporomandibular joint (TMJ) changes, in which specific software allows several valuable image manipulations for soft or bony tissues. The application of these filters can strongly influence the image quality depending on the type of filter used, as one can reduce artifacts, reduce image noise, soften gray tones and detect and increase edges (Carvalho et al, 2017; Eliášová & Dostálová, 2017). Other factors such as voxel size, tension peak, milliamperage, exposure time, FOV size, and rotation degree are involved
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