TOWARDS QUANTIFICATION OF KIDNEY STONES USING X-RAY DARK-FIELD TOMOGRAPHY

Kidney stones is a renal disease with high prevalence and one of the major reasons for emergency room visits. The prevalence of kidney stones is increasing, and the lifetime recurrence rate is estimated as almost 50%. Thus, treatment of kidney stones becomes an increasingly important topic. However, different types of kidney stones require specific treatments, which creates the need for accurate diagnosis of the stone type prior to the intervention. Imaging techniques that are commonly used for the detection of kidney stones, such as X-ray CT and ultrasound, are insufficient to differentiate the types of kidney stones. In this paper, we present a proof-of-concept study for differentiating kidney stones using X-ray dark-field tomography. The most important advantage of this method is its ability to image non-homogeneous kidney stones, i.e., to localize and identify the individual components of mixed-material kidney stones. We use a weighted total-variation regularized reconstruction method to compute the ratio of dark-field over absorption signal (DA Ratio) from noisy projections. We evaluate the performance of the proposed approach on two kidney stones of homogeneous composition, and one well-defined numerical phantom with known ground truth for mixed types of stones. We illustrate that the DA Ratio is significantly distinguished for different materials from the experiments. Reconstruction of phantom data recovers voxel-wise material information with high accuracy. We show that X-ray dark-field tomography has a significant potential in selective characterization of kidney stones.