Removing limiting factors for Leeds Test Object TO.10 usage

Abstract

The Leeds Test Object TO.10 is routinely used to provide a subjective estimate of Signal to Noise Ratio (SNR) as a measure of overall image quality. Currently, calibrated contrast values are provided for a limited set of discrete peak voltage (65, 70, 75, 80 kVp) and copper filtration thickness (1.0, 1.5, 2.0 mm Cu) combinations. However, it can be challenging to attain these exact settings on modern interventional imaging systems incorporating Automatic Dose Rate Controls (ADRC) and varying amounts of additional copper filtration. These limit the accuracy of results obtained thus representing significant limiting factors for the TO.10. We describe two methods of removing these limiting factors: a three-dimensional (3D) Matlab interpolation and extrapolation algorithm, and a multivariate-polynomial function, the coefficients of which can be stored in Excel. Both methods make use of the available contrast values to generate contrast curves for any kVp and mm Cu combination. Results obtained from both methods are presented as Threshold Index (H_T(A)) curves modelled by best fit log-polynomials. Their accuracies are evaluated through comparison with H_T(A) curves obtained under calibrated conditions. Both methods are found to produce more accurate estimates of detail contrasts for non-standard kVp and mm Cu combinations. Although an inherent error of approximately 15% is associated with this type of contrast detail analysis, the ability to analyse TO.10 data for non-standard kVp and mm Cu combinations offered by modern systems increases the accuracy of calculated H_T(A)’s. These methods further reduce the time required for image quality tests and room downtime.