Robustness of Textural Features to Predict Stone Fragility Across Computed Tomography Acquisition and Reconstruction Parameters.

Published on Jul 1, 2019in Academic Radiology2.488
· DOI :10.1016/J.ACRA.2018.08.010
Taylor R. Moen1
Estimated H-index: 1
(Mayo Clinic),
Andrea Ferrero8
Estimated H-index: 8
(Mayo Clinic),
Cynthia H. McCollough76
Estimated H-index: 76
(Mayo Clinic)
Sources
Abstract
Rationale and Objectives Previous studies have demonstrated that quantitative relationships exist between stone fragility at lithotripsy and morphological features extracted from computed tomography (CT) scans. The goal of this study was to determine if variations in scanner model, patient size, radiation dose, or reconstruction parameters impact the accuracy of the prediction of renal stone fragility in an in vitro model. Materials and Methods Sixty-seven kidney stones were scanned using routine single and dual energy stone protocols, mimicking average, and large patient habitus. Low dose scans were also performed. Each scan was reconstructed with routine protocol parameters, and with thinner (0.6 mm) or thicker (3 mm) images, two different reconstruction kernels, and iterative reconstruction at two strengths. Fragility of each stone was measured in a controlled ex vivo experiment. A single predictive model was developed from a reference CT protocol configuration and applied to data from each CT acquisition and reconstruction parameter tested to obtain estimated stone comminution times. Results None of the investigated protocols showed a significant variation in the accuracy of stone fragility classification, except for the ones with the most aggressive iterative reconstruction and/or with thicker images. In these protocols, a number of stone fragility assessments changed from fragile to hard (or vice versa), compared to their ground truth measurement. Conclusion Prediction accuracy of stone fragility models developed from CT data is robust to expected variations in CT stone protocols used for quantification tasks. This finding facilitates their future adoption to different clinical practices.
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