Due to an increase in regulatory scrutiny and medical facility accreditation requirements to monitor patient radiation dose from diagnostic imaging procedures, there is a growing necessity to determine and record accurate patient radiation dose from diagnostic medical imaging procedures. Current methods of patient dosimetry in diagnostic imaging are both extremely difficult and time consuming, require large computing resources (such as Monte Carlo computations), or lack accuracy due to using data based on homogeneous materials and “standard-man sized” anthropomorphic models.
This dissertation provides an algorithm that calculates a more accurate dose using patient-specific projection radiographic images. The algorithm includes measurements acquired during routine physics testing of the x-ray unit, data from two-view (Anterior-Posterior and Lateral chest) radiographic images, and accounts for patient specific and body habitus.
The algorithm developed in this work uses formulas for calculating entrance and exit dose utilizing a new dose correction factor. The dose correction factor is based on the exposure index and average grayscale from radiographic images specific to the subject and shows improved accuracy of traditional calculation methods for entrance and exit dose calculations.
Measurements using optically stimulated luminescent dosimeters, physics measurements on radiographic equipment, and Monte Carlo simulations were used to test and develop the algorithm. This new algorithm uses the mean radiographic image grayscale value over the region of interest and the reported Exposure Index to create a correction factor to correct patient dose calculations. The final product is an algorithm for calculating patient specific dose from AP and lateral chest radiographs that is more accurate with less associated uncertainty than current traditional dose calculation methods.
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Sandoval, Daniel J.. "Patient Specific Radiation Doses From Projection Radiography Images: Improving the Accuracy of Low Dose Radiation Calculations." (2018). https://digitalrepository.unm.edu/ne_etds/70