Theoretical Comparison of a Dual Energy System and Photon Counting Silicon Detector Used for Material Quantification in Spectral CT

Abstract

Any method using dual energy computed tomography (CT) has to make prior assumptions in order to quantify k-edge contrast agents. This work estimates the mean square error (MSE) in contrast agent quantification employing a method based on assigning each reconstructed voxel a ratio of soft tissue and fat using dual energy CT. The results are compared to the MSE using a photon counting silicon detector with multiple bins. The square root of the MSEs of the quantifications of iodine and gadolinium for an object consisting of soft tissue and fat using the silicon detector and dual energy CT range from below 2% and 1% of the contrast agent content for 100 mg/cm(3) of iodine and gadolinium, up to approximately 10% and 13%, and 6% and 4%, for 5 mg/cm(3) of iodine and gadolinium, respectively. When adding bone with a voxel volume fraction of 2.2%, the square root of the MSEs of the quantifications of iodine and gadolinium using dual energy CT increases to 25% and 6%, respectively, for 5 mg/cm(3) of contrast agent. In conclusion, results indicate that the noise levels of the material quantification using the silicon detector are higher than the noise levels using a dual energy CT when the composition of the object is known. However, using a dual energy CT increases the risk of model specification error and subsequently a large bias in contrast agent quantification, a problem which does not exist when using a multi-bin CT where the number of energy bins is larger than two.

Photon-counting CT: Technical Principles and Clinical Prospects

“…Although clinical photon-counting CT scanners are not yet commercially available, several groups and manufacturers dual-energy CT) therefore must build on assumptions about the tissue composition (52). If these assumptions are wrong, for example, if there is calcium in the same voxel, the measurement will be inaccurate (53). Photon-counting CT will likely allow more accurate measurement of iodine concentrations (23).…”

A framework for performance characterization of energy‐resolving photon‐counting detectors

“…Also, the detectability for specific tasks with both spectral and spatial dependence has been studied by Fredenberg et al ,. Yveborg et al . and Chen et al …”

“…Richard and Siewerdsen 29 used linear-systems theory to study the performance of a dual-energy system. Also, the detectability for specific tasks with both spectral and spatial dependence has been studied by Fredenberg et al 30 , Yveborg et al 31 and Chen et al 32 A common way to combine information from several spectral channels is to make a weighted sum of the energy-selective images, with weights chosen to be optimal for the considered imaging task. 11,12,33 A good measure of the performance of an energy-resolving detector should, therefore, take optimal weighting into account.…”

Photon counting x‐ray imaging with K‐edge filtered x‐rays: A simulation study

“…For comparison, the energy separation factors between the low and high energy bins used for DE subtraction were 0.64 and 0.52 for Gd and Cu filters, respectively. The major problem with three-material decomposition using three-bin data is strongly decreased SNR (by a factor of [10][11][12][13][14][15][16][17][18][19][20], as compared to two-material decomposition with two-bin data. On the other hand, three-material decomposition can also be performed using two-bin data and approximate decomposition methods such as volume and mass conservation methods.…”