Radiopacity quantification and spectroscopic characterization of OrthoMTA and RetroMTA.
Ekim Onur OrhanÖzgür IrmakEmine Zeynep BalZeliha DanacıFidan BabayevaEren OrhanBerk Can YücelPublished in: Microscopy research and technique (2020)
The aim of this article was to investigate the unknown radiopacity performances of OrthoMTA and RetroMTA via means of a contemporary image analyzing methods and energy dispersive X-ray spectroscopy. Three commercial hydraulic calcium silicate-based cements and a calcium hydroxide-based paste were used. Pure-grade zirconium oxide, bismuth oxide, zinc oxide, barium sulfate, and calcium hydroxide were as references. An energy-dispersive X-ray spectroscopy instrument was used for the elemental analysis. Radiographic image data was obtained according to the International Organization for Standardization 6876-2012 specifications. The region of interest was determined for each specimen. Mean (±SD) grey values of the X-ray image data was measured with an image analyzing software. The calibration curve was created by curve-plotting software and the mean grey-values were matched versus Al values (mm Al). Data were analyzed with one-way ANOVA followed by Tukey's multiple comparison test. Spectroscopic characterization of the commercial materials was shown with assigned Carbon, oxygen, aluminum, silicon, calcium, zinc, zirconium, barium, tungsten, bismuth, and sulfur elements. The major radiopacifier/s of OrthoMTA is Bi, of RetroMTA is Zr, of BioDentine are Ba and Zr, and of ProCal is Ba. The radiopacity values of all commercial materials are significantly different (p < .05). The rank of the radiopacity values: RetroMTA (3.36 ± 0.29mmAl) > OrthoMTA (2.56 ± 0.19mmAl) > BioDentine (2.02 ± 0.12mmAl) > ProCal (1.46 ± 0.60mmAl). The study reported that the radiopacity values and spectral characterization of RetroMTA and OrthoMTA cements. The pixel-based and reproducible method could be used universally to the quantification of the radiodensity of digitally collected X-ray data.
Keyphrases
- high resolution
- oxide nanoparticles
- electronic health record
- dual energy
- deep learning
- big data
- data analysis
- molecular docking
- ionic liquid
- white matter
- optical coherence tomography
- electron microscopy
- mass spectrometry
- magnetic resonance imaging
- single molecule
- solid phase extraction
- pet imaging
- magnetic resonance
- machine learning