Receptor modeling for use in computerized optimization of imaging systems

Inappropriate or poorly designed x-ray imaging systems can lead to inadequate image quality and/or excessive patient absorbed dose. To study this dilemma, we have developed a computer program, based on Monte Carlo methods, to model the imaging chain and to optimize the design of individual imaging system components. The Monte Carlo method is used to simulate the transport of x-ray photons through the patient and anti-scatter device and into the image receptor. Image quality is calculated in terms of contrast and signal-to-noise ratio (SNR) and patient risk in terms of mean absorbed dose. The model of the radiographic screen includes the statistics of x-ray to light conversion and diffusion of light photons and the spatial distribution of absorbed x rays. The optimal system was defined as that which, for a constant measure of image quality, results in the lowest mean absorbed dose in the patient. The results of the model agree with measured data. Examples are given for different measures of reducing the absorbed dose for constant SNR in a simulated lumbar spine examination. At the optimal tube potential, the dose reductions associated with using a thicker screen, a fiber-interspaced grid and an additional Cu-filtration are 53%, 42%, and 31%, respectively.