Three commercial metal artifact reduction methods were evaluated for use in computed tomography (CT) imaging in the presence of clinically realistic metal implants: Philips O-MAR, GE's monochromatic Gemstone Spectral Imaging (GSI) using dual-energy CT, and GSI monochromatic imaging with metal artifact reduction software applied (MARs). Each method was evaluated according to CT number accuracy, metal size accuracy, and streak artifact severity reduction by using several phantoms, including three anthropomorphic phantoms containing metal implants (hip prosthesis, dental fillings, and spinal fixation rods). All three methods showed varying degrees of success for the hip prosthesis and spinal fixation rod cases, while none were particularly beneficial for dental artifacts. Limitations of the methods were also observed. MARs underestimated the size of metal implants and introduced new artifacts in imaging planes beyond the metal implant when applied to dental artifacts, and both the O-MAR and MARs algorithms induced artifacts for spinal fixation rods in a thoracic phantom. Our findings suggest that all three artifact mitigation methods may benefit patients with metal implants, though they should be used with caution in certain scenarios.

A streamlined scan protocol was developed to further investigate the effects of CTDIvol and rotation time while limiting data collection to the DEQC body phantom. Further data collection will be pursued to determine baseline values and statistically based failure thresholds for the validation of long-term DECT scanner performance.

Objectives Calcific and hemorrhagic intracranial lesions with attenuation levels of <100 Hounsfield Units (HU) cannot currently be reliably differentiated by single-energy computed tomography (SECT). The proper differentiation of these lesion types would have a multitude of clinical applications. A phantom model was used to test the ability of dual-energy CT (DECT) to differentiate such lesions. Materials and Methods Agar gel-bound ferric oxide and hydroxyapatite were used to model hemorrhage and calcification, respectively. Gel models were scanned using SECT and DECT and organized into SECT attenuation-matched pairs at 16 attenuation levels between 0 and 100 HU. DECT data were analyzed using 3D Gaussian mixture models (GMMs), as well as a simplified threshold plane metric derived from the 3D GMM, to assign voxels to hemorrhagic or calcific categories. Accuracy was calculated by comparing predicted voxel assignments with actual voxel identities. Results We measured 6,032 voxels from each gel model, for a total of 193,024 data points (16 matched model pairs). Both the 3D GMM and its more clinically implementable threshold plane derivative yielded similar results, with >90% accuracy at matched SECT attenuation levels ≥50 HU. Conclusions Hemorrhagic and calcific lesions with attenuation levels between 50 and 100 HU were differentiable using DECT in a clinically relevant phantom system with >90% accuracy. This method warrants further testing for potential clinical applications.

We have modeled and verified the relationship of the minimum detectable contrast to the patient size, the patient dose, and the lesion size from the images reconstructed with filtered backprojection. The findings can be useful for task-specific dose modulation on abdomen CT studies.