Harmonization of chest CT scans for different doses and reconstruction methods

Citation:

Vegas-Sánchez-Ferrero G, Ledesma-Carbayo MJ, Washko GR, San José Estépar R. Harmonization of chest CT scans for different doses and reconstruction methods. Med Phys. 2019.

Date Published:

2019 May 09

Abstract:

PURPOSE: To develop and validate a CT harmonization technique by combining noise-stabilization and autocalibration methodologies to provide reliable densitometry measurements in heterogeneous acquisition protocols. METHODS: We propose to reduce the effects of spatially-variant noise such as non-uniform patterns of noise and biases. The method combines the statistical characterization of the signal-to-noise relationship in the CT image intensities, which allows us to estimate both the signal and spatially-variant variance of noise, with an autocalibration technique that reduces the non-uniform biases caused by noise and reconstruction techniques. The method is firstly validated with anthropomorphic synthetic images that simulate CT acquisitions with variable scanning parameters: different dosage, non-homogeneous variance of noise, and various reconstruction methods. We finally evaluate these effects and the ability of our method to provide consistent densitometric measurements in a cohort of clinical chest CT scans from two vendors (Siemens, n=54 subjects; and GE, n=50 subjects) acquired with several reconstruction algorithms (filtered back-projection and iterative reconstructions) with high-dose and low-dose protocols. RESULTS: The harmonization reduces the effect of non-homogeneous noise without compromising the resolution of the images (25% RMSE reduction in both clinical datasets). An analysis through hierarchical linear models showed that the average biases induced by differences in dosage and reconstruction methods are also reduced up to 74:20%, enabling comparable results between highdose and low-dose reconstructions. We also assessed the statistical similarity between acquisitions obtaining increases of up to 30 percentage points and showing that the low-dose vs. high-dose comparisons of harmonized data obtain similar and even higher similarity than the observed for high-dose vs. high-dose comparisons of non-harmonized data. CONCLUSION: The proposed harmonization technique allows to compare measures of low-dose with high-dose acquisitions without using a specific reconstruction as a reference. Since the harmonization does not require a precalibration with a phantom, it can be applied to retrospective studies. This approach might be suitable for multicenter trials for which a reference reconstruction is not feasible or hard to define due to differences in vendors, models and reconstruction techniques. This article is protected by copyright. All rights reserved.