Journal of Dental Medicine

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Nowadays, bone mass estimation, through imaging methods, is widely used in metabolic diseases diagnosis and treatment. One of these methods is called "optical densitometry" which estimates bone density by measuring the intensity of the transmitted light on different parts of a radiographic image. Digital radiography systems act similarly by determining grey levels of the image. The aim of this study is comparing two different methods of optical densitometry and a digital system densitometry known as radiovisiography. 45 samples, containing urografin with three different concentrations, were imaged, by both radiovisiogrphy (RVG) and conventional film systems. To determine the densitometry of films and radiovisiography images, optical densitometry and bone densitometry option of the RVG software, were applied respectively. Data were analyzed and compared for their reliability (repeatability) and correlations with concentration. In RVG densitometry system, the correlation with concentration is moderate (r=0.42) and intra samples and intra group reliability are 97.68% and 88.19%. Moreover, in conventional optical film densitometry, correlation with concentration (r=0.987) is high, intra samples and intra group reliability is high, intra samples and intra group reliability are 99.97% and 99.84%, respectively. According to the results, it is suggested that conventional film optical densitometry is more precise and reliable than RVG densitometry.

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  Background and Aims Bone density is frequently used in medical diagnosis and research. The current methods for determining bone density are expensive and not easily available in dental clinics. The aim of this study was to design and evaluate the accuracy of a digital method for hard tissue densitometry which could be applied on personal computers.

  Materials and Methods: An aluminum step wedge was constructed. 50 E-speed Kodak films were exposed. Exposure time varied from 0.05s to 0.5 s with 0.05 s interval. Films were developed with automatic developer and fixer and digitized with 1240U photo Epson scanner. Images were cropped at 10 × 10mm size with Microsoft Office Picture Manager. By running the algorithm designed in MATLAB software, the mean pixel value of pictures was calculated.

  Results: Finding of this study showed that by increasing the exposure time, the mean pixel value was decreased and at step 12, a significant discrimination was seen between the two subsequent times(P<0.001). By increasing the thickness of object, algorithm could define the density changes from step 4 in 0.3 s and 5 in 0.5 s, and it could determine the differences in the mean pixel value between the same steps of 0.3 s and 0.5 s from step 4.

  Conclusion: By increasing the object thickness and exposure time, the accuracy of the algorithm for recognizing changes in density was increased. This software was able to determine the radiographic density changes of aluminum step wedge with at least 4mm thickness at exposure time of 0.3 s and 5 mm at 0.5 s.