Characterisation of urinary stones in the presence of iodinated contrast medium using dual-energy CT: a phantom study

Abstract

Objective

To develop a dual-energy CT (DECT) method for differentiating uric acid (UA) from non-UA stones in the presence of iodinated contrast medium.

Methods

Thirty UA and 45 non-UA stones were selected after infra-red spectroscopic analysis and independently placed in a 1.5-ml vial, which was filled first with saline and then with increasing concentrations of iodine. For each condition, tubes were put in a 35-cm water phantom and examined using a dual-source CT system at 100 and 140 kV. Virtual unenhanced images created from CT data sets of the stones in iodine-containing solutions provided position and volume information. This map was used to calculate a CT number ratio to differentiate stone type. A region-growing method was developed to improve the ability to differentiate between UA and non-UA stones with iodinated contrast medium.

Results

The sensitivity for detecting UA stones was 100 % for unenhanced images but fell to 18 % with 20 mgI/ml iodine solution and 0 % for higher concentrations. With region growing, the sensitivity for detecting UA stones was increased to 100 %, 82 %, 57 %, 50 % and 21 % for iodine solutions of 20, 40, 60, 80 and 100 mgI/ml.

Conclusion

The region-growing method improves differentiation of UA from non-UA stones on contrast-enhanced DECT urograms.

Key Points

• Computed tomography is widely used to assess renal tract calculi

• Dual-energy CT can assess stone composition and provide virtual unenhanced images

• However, iodinated contrast medium affects the volume estimation for urinary stones.

• CTR of stones is altered by the surrounding iodine in CT urograms.

• The region-growing method improves the identification of uric acid stones.

Appendix

After the stone was segmented from the background soft tissue structures using the commercial virtual unenhanced technique, a binary map of stone position was applied to the CTR image (CTR = CT_low kV/CT_high kV). For each stone, the centre slice along the z direction was used to determine the starting point of the region-growing iterative process (Fig. A1a). First, an internal region was acquired by performing a four-pixel by four-pixel area of erosion on the CTR map of the centre slice. Then, the pixel with the closest CTR value to the average CTR of the internal region was chosen as the starting point (the seed). Starting from the seed, the nearest 26 neighbouring pixels were searched (Fig. A1b) in an iterative process (Fig. A2) to find all pixels that had CTR values within a certain range relative to the mean CTR of the stone. The width of the range is the only parameter to be defined before the iteration. Here 0.2 (± 0.1) was used for all stones at all five iodine concentrations. As shown in Fig. A2, the mean CTR was updated at each iteration and, as more pixels were included, it was expected to approach the true CTR of the stone, with those pixels affected by iodinated contrast medium (far away from the centre) excluded.

Fig. A1

a A CTR map of a uric acid stone immersed in iodine solution. The red dot in the centre represents the starting point of the region-growing iterative process. b The 26 neighbouring pixels of the starting point

Fig. A2

The iterated steps of the region-growing method