Moen T et al, 2018: Robustness of Textural Features to Predict Stone Fragility Across Computed Tomography Acquisition and Reconstruction Parameters.
Moen T, Ferrero A, McCollough C.
Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905.
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 (3mm) images, two different reconstruction kernels, and iterative reconstruction at two strengths. Fragilityof 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.
Acad Radiol. 2018 Oct 1. pii: S1076-6332(18)30405-7. doi: 10.1016/j.acra.2018.08.010. [Epub ahead of print]
Prediction of treatment efforts is considered clinically important for any medical disease. But there are few fields of medicine in which this problem so frequently has been addressed clinically and experimentally. This report describes such an approach.
Basically different parameters from NCCT examinations with single- or double energy sources were used to classify 67 stones obtained from stone patients. A comparison between morphological characteristics and stone fragility was carried out. The fragility was determined in terms of time to stone disintegration.
It is of note, however, that 15 of the stones were composed of pure uric acid whereas apparently another 28 stones were mixtures containing uric acid (?) and only 24 stones were of non-uric acid type.
Different CT-recorded parameters were used for predicting fragility: stone volume, porosity and various estimates of the stone morphology. A formula was presented in which the fragility (comminution time) was predicted from porosity, stone uniformity and mean curvature of the stone surface.
It is not mentioned how the stones were disintegrated but from Figure 2 my conclusion is that this step was accomplished with ultrasound.
The important technical notation in order to minimize misclassification of stone fragility was that the CT-slice thickness should not exceed 1 mm.
Different modalities for stone disintegration (ultrasound HoYAG laser and SWL) are difficult to compare and the applicability of the formula mentioned above can vary considerably. Only future clinical experience will tell how useful this predictive method is. Nevertheless the finings in this report correspond well with other observations on stone morphology.