Harmonization of chest CT scans for different doses and reconstruction methods

Vegas Sánchez-Ferrero, Gonzalo and Ledesma Carbayo, Maria Jesus and Washko, George R. and San José Estépar, Raúl (2019). Harmonization of chest CT scans for different doses and reconstruction methods. "Medical Physics", v. 46 (n. 7); pp. 3117-3132. ISSN 0094-2405. https://doi.org/10.1002/mp.13578.


Title: Harmonization of chest CT scans for different doses and reconstruction methods
  • Vegas Sánchez-Ferrero, Gonzalo
  • Ledesma Carbayo, Maria Jesus
  • Washko, George R.
  • San José Estépar, Raúl
Item Type: Article
Título de Revista/Publicación: Medical Physics
Date: July 2019
ISSN: 0094-2405
Volume: 46
Freetext Keywords: CT scanner; calibration; Hounsfield Unit correction; lung density; quantitative imaging; COPD
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Purpose: To develop and validate a computed tomography (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 nonuniform 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 nonuniform 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, nonhomogeneous 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 nonhomogeneous 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 high-dose and low-dose reconstructions. We also assessed the statistical similarity between acquisitions obtaining increases of up to 30% 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 nonharmonized 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.

Funding Projects

Government of SpainRTI2018-098682-B-I00UnspecifiedUnspecifiedUnspecified

More information

Item ID: 64275
DC Identifier: https://oa.upm.es/64275/
OAI Identifier: oai:oa.upm.es:64275
DOI: 10.1002/mp.13578
Official URL: https://pubmed.ncbi.nlm.nih.gov/31069809/
Deposited by: Memoria Investigacion
Deposited on: 16 Dec 2020 16:06
Last Modified: 01 Jul 2021 22:30
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