Effects of five levels of noise reduction applied to indirect digital radiography on diagnostic accuracy of external apical root resorption

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background

Radiologic diagnosis of external apical root resorption (EARR) is clinically important. Noise might disrupt this diagnosis. Therefore, we assessed the efficacy of noise reduction on periapical indirect digital radiography.

Materials and Methods

in vitro this study as performed on 792 radiographs. A total of 66 single‑rooted premolars were inserted in dried hemimandibles of sheep and fixed with modeling wax. Digital images were obtained using the parallel technique. The storage phosphor plates were processed in the DIGORA Optime scanner. The resulting images were sent to a computer using the Scanora software for radiographic analysis. The teeth were removed from the mandible, and artificial EARR defects were simulated. Afterward, the indirect digital radiographs were obtained at the same condition of the baseline. Five levels of noise reduction were applied. All images were saved in Digital Imaging and Communications in Medicine format and monitored by two observers twice over 2 weeks. Data were analyzed statistically using Cochran and McNemar tests (α = 0.05).

Results

The highest sensitivity rate was found in the baseline group (0.99), and the lowest sensitivity was related to the “four‑time noise reduction” method (0.91). The highest specificity rate was in the “five‑times noise reduction” method (0.88) and the lowest specificity was associated with “one‑time noise reduction” method (0.71). There was no statistical difference between images with/without noise reduction enhancement with varied gradation levels in terms of diagnostic accuracies of EARR (P > 0.05).

Conclusion

Application of noise reduction procedure in Scanora software might have no effect on the accuracy of EARR diagnosis.

Language:
English
Published:
Dental Research Journal, Volume:17 Issue: 2, Mar Apr 2020
Pages:
125 to 133
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