Initial Performance Characterization of a Clinical Noise–Suppressing Reconstruction Algorithm for MDCT

OBJECTIVE: The number of CT examinations is increasing relatively dramatically, hence the radiation dose of the associated population. Thus, there is a need for efficient reconstruction methods with dose reduction potential that also maintain the image quality. In this article, we present the initial performance evaluation of such a reconstruction algorithm (iDose, Philips Healthcare). MATERIALS AND METHODS: iDose is a hybrid iterative reconstruction algorithm that provides enhanced image quality while reducing the radiation dose compared with the current clinical standard reconstruction. To quantify the advantages of this algorithm in image quality and dose reduction, we compared iDose with the conventional filtered back projection algorithm. Furthermore, we describe the performance of iDose with respect to several image quality metrics. RESULTS: The HU values remain stable while employing iDose. With iDose, the noise is significantly reduced. This is reflected by an improvement in the contrast-to-noise ratio and in the noise power spectrum compared with a standard reconstruction. The measurements of the modulation transfer function confirm that, with iDose, there is no decline in spatial resolution. CONCLUSION: We conclude that iDose is an important tool in the reduction of radiation dose in CT. However, continuous efforts to reduce radiation dose should be pursued.