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Robust quantitative contrast‐enhanced dual‐energy CT for radiotherapy applications
Author(s) -
Lapointe Andréanne,
Lalonde Arthur,
Bahig Houda,
Carrier JeanFrançois,
Bedwani Stéphane,
Bouchard Hugo
Publication year - 2018
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.12934
Subject(s) - a priori and a posteriori , robustness (evolution) , computer science , contrast (vision) , calibration , medical imaging , context (archaeology) , decomposition , biological system , biological tissue , materials science , algorithm , biomedical engineering , artificial intelligence , mathematics , chemistry , medicine , statistics , paleontology , organic chemistry , epistemology , biology , gene , philosophy , biochemistry
Purpose The purpose of this study was to develop and validate accurate methods for determining iodine content and virtual noncontrast maps of physical parameters, such as electron density, in the context of radiotherapy. Methods A simulation environment is developed to compare three methods allowing extracting iodine content and virtual noncontrast composition: (a) two‐material decomposition, (b) three‐material decomposition with the conservation of volume constraint, and (c) eigentissue decomposition. The simulation allows comparing the performance of the methods using iodine‐based contrast agent contents in tissues from a reference dataset with variable density and elemental composition. The comparison is performed in two ways: (a) with a priori knowledge on the composition of the targeted tissue, and (b) without a priori knowledge on the base tissue. The three methods are tested with patient images scanned with dual‐energy CT and iodine‐based contrast agent. An experimental calibration adapted to the presence of iodine is performed by imaging tissue equivalent materials and diluted contrast agent solutions with known atomic composition. Results Results show that in the case of known a priori on the composition of the targeted tissue, the two‐material decomposition is robust to variable densities and atomic compositions without biasing the results. In the absence of a priori knowledge on the target tissue composition, the eigentissue decomposition method yields minimal bias and higher robustness to variations. Results from the experimental calibration and the images of two patients show that the extracted quantities are accurate and the bias is negligible for both methods with respect to clinical applications in their respective scope of use. For the patient imaged with a contrast agent, virtual noncontrast electron densities are found in good agreement with values extracted from the scan without contrast agent. Conclusion This study identifies two accurate methods to quantify iodine‐based contrast agents and virtual noncontrast composition images with dual‐energy CT. One is the two‐material decomposition with a priori knowledge of the constituent components focused on organ‐specific applications, such as kidney or lung function assessment. The other method is the eigentissue decomposition and is useful for general radiotherapy applications, such as treatment planning where accurate dose calculations are needed in the absence of contrast agent.