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There is increasing recognition that oral health affects overall health andsystemic diseases. Nonetheless it remains challenging to rapidly screen patientbiopsies for signs of inflammation or the pathogens or foreign materials thatelicit the immune response. This is especially true in conditions such asforeign body gingivitis (FBG), where the foreign particles are often difficultto detect. Our long term goal is to establish a method to determine if theinflammation of the gingival tissue is due to the presence of a metal oxide,with emphasis on elements that were previously reported in FBG biopsies, suchas silicon dioxide, silica, and titanium dioxide whose persistent presence canbe carcinogenic. In this paper, we proposed to use multiple energy X-rayprojection imaging to detect and to differentiate different metal oxideparticles embedded inside gingival tissues. To simulate the performance of theimaging system, we have used GATE simulation software to mimic the proposedsystem and to obtain images with different systematic parameters. The simulatedparameters include the X-ray tube anode metal, the X-ray spectra bandwidth, theX-ray focal spot size, the X-ray photon number, and the X-ray dector pixel. Wehave also applied the de-noising algorithm to obtain better Contrast-to-noiseratio (CNR). Our results indicate that it is feasible to detect metal particlesas small as 0.5 micrometer in diameter when we use a Chromium anode target withan energy bandwidth of 5 keV, an X-ray photon number of 10^8, and an X-raydetector with a pixel size of 0.5 micrometer and 100 by 100 pixels. We havealso found that different metal particles could be differentiated from the CNRat four different X-ray anodes and spectra. These encouraging initial resultswill guide our future imaging system design.

X-ray projection imaging of metal oxide particles inside gingival tissues