An Image-Domain Contrast Material Extraction Method for Dual-Energy Computed Tomography

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Abstract

Objectives

Conventional material decomposition techniques for dual-energy computed tomography (CT) assume mass or volume conservation, where the CT number of each voxel is fully assigned to predefined materials. We present an image-domain contrast material extraction process (CMEP) method that preferentially extracts contrast-producing materials while leaving the remaining image intact.

Materials and Methods

Image processing freeware (Fiji) is used to perform consecutive arithmetic operations on a dual-energy ratio map to generate masks, which are then applied to the original images to generate material-specific images. First, a low-energy image is divided by a high-energy image to generate a ratio map. The ratio map is then split into material-specific masks. Ratio intervals known to correspond to particular materials (eg, iodine, calcium) are assigned a multiplier of 1, whereas ratio values in between these intervals are assigned linear gradients from 0 to 1. The masks are then multiplied by an original CT image to produce material-specific images. The method was tested quantitatively at dual-source CT and rapid kVp-switching CT (RSCT) with phantoms using pure and mixed formulations of tungsten, calcium, and iodine. Errors were evaluated by comparing the known material concentrations with those derived from the CMEP material-specific images. Further qualitative evaluation was performed in vivo at RSCT with a rabbit model using identical CMEP parameters to the phantom. Orally administered tungsten, vascularly administered iodine, and skeletal calcium were used as the 3 contrast materials.

Results

All 5 material combinations—tungsten, iodine, and calcium, and mixtures of tungsten-calcium and iodine-calcium—showed distinct dual-energy ratios, largely independent of material concentration at both dual-source CT and RSCT. The CMEP was successful in both phantoms and in vivo. For pure contrast materials in the phantom, the maximum error between the known and CMEP-derived material concentrations was 0.9 mg/mL, 24.9 mg/mL, and 0.4 mg/mL for iodine, calcium, and tungsten respectively. Mixtures of iodine and calcium showed the highest discrepancies, which reflected the sensitivity of iodine to the image-type chosen for the extraction of the final material-specific image. The rabbit model was able to clearly show the 3 extracted material phases, vascular iodine, oral tungsten, and skeletal calcium. Some skeletal calcium was misassigned to the extracted iodine image; however, this did not impede the depiction of the vasculature.

Conclusions

The CMEP is a straightforward, image-domain approach to extract material signal at dual-energy CT. It has particular value for separation of experimental high-Z contrast elements from conventional iodine contrast or calcium, even when the exact attenuation coefficient profiles of desired contrast materials may be unknown. The CMEP is readily implemented in the image-domain within freeware, and can be adapted for use with images from multiple vendors.

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