Andréanne Lapointe1, Arthur Lalonde1, Houda Bahig2,3, Jean-François Carrier1,2,3, Stéphane Bedwani1,2,3, Hugo Bouchard1,2,3. 1. Département de physique, Université de Montréal, 2900 boulevard Édouard-Montpetit, Montréal, QC, H3T 1J4, Canada. 2. Département de radio-oncologie, Centre hospitalier de l'Université de Montréal (CHUM), 1000 rue Saint-Denis, Montréal, Québec, H2X 0C1, Canada. 3. Centre de recherche du Centre hospitalier de l'Université de Montréal, 900 Rue Saint-Denis, Montréal, QC, H2X 0A9, Canada.
Abstract
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.
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.
Authors: Dominik Alexander Hering; Kai Kröger; Ralf W Bauer; Hans Theodor Eich; Uwe Haverkamp Journal: Br J Radiol Date: 2020-10-01 Impact factor: 3.039