TU-B-201B-01: Radiation Dose Reduction in Medical X-Ray CT Using Equally-Sloped Tomography

Abstract

Purpose: An exact Fourier‐based iterative reconstruction technique termed Equally‐Sloped Tomography (EST) has recently been developed to allow a reduction of radiation dose while maintaining image quality. Here we optimize this technique by incorporating a Gradient Descent algorithm with mathematical regularization constraints, including the Non‐Local Means Total Variation model. Using this technique, we conducted a series of comparative experiments to quantify the image quality, and explore radiation dose reduction in CT through reduction of X‐ray flux. Method and Materials: A standard quality control phantom containing multiple contrastvisibility and resolution inserts was imaged using a Siemens Somatom Sensation 64 scanner. The X‐ray flux was systematically lowered from 583mAs to 39mAs. All scans were performed under axial mode with constant tube current. Comparison reconstructions were produced by Filtered‐Back Projection (FBP) with a standard uncropped ramp filter. The resolution, signal‐to‐noise ratio (SNR) and contrast‐to‐noise ratio (CNR) were measured and compared as a function of flux. Results: Compared to the FBP reconstruction of 500mAs, the optimized EST reconstruction of 50mAs has comparable SNRs and CNRs. The low‐contrast regions of the phantom exhibit similar visibility. In addition, no resolution degradation is observed in the low‐dose EST reconstruction.Conclusion: As radiation dose is linearly proportional to the X‐ray flux, our results indicate that the optimized EST technique may potentially reduce the CT dose up to 90%, while producing comparable image resolution, quality and contrast as the full‐dose FBP reconstruction. The reasons that EST allows for significant reduction of the CT dose are because (i) an exact Fourier‐based iterative algorithm is used in the reconstruction where both physical and mathematical constraints can be naturally incorporated, (ii) the algorithm is guided towards a lowest‐possible noisy state, which is also strictly consistent with the measured data. Conflict of Interest: Research sponsored by UC Discovery / TomoSoft Technologies Grant #ITL07‐10166.