Kronfeld Andrea, Rose Patrick, Baumgart Jan, Brockmann Carolin, Othman Ahmed E, Schweizer Bernd, Brockmann Marc Alexander
University Medical Center of the Johannes Gutenberg University Mainz, Department of Neuroradiology, Langenbeck 1, 55131, Mainz, Germany.
RheinMain University of Applied Sciences, Faculty of Engineering, Am Brückweg 26, 65428, Rüsselsheim am Main, Germany.
Heliyon. 2023 Dec 6;10(1):e23013. doi: 10.1016/j.heliyon.2023.e23013. eCollection 2024 Jan 15.
Emerging from the development of single-energy Computed Tomography (CT) and Dual-Energy Computed Tomography, Multi-Energy Computed Tomography (MECT) is a promising tool allowing advanced material and tissue decomposition and thereby enabling the use of multiple contrast materials in preclinical research. The scope of this work was to evaluate whether a usual preclinical micro-CT system is applicable for the decomposition of different materials using MECT together with a matrix-inversion method and how different changes of the measurement-environment affect the results. A matrix-inversion based algorithm to differentiate up to five materials (iodine, iron, barium, gadolinium, residual material) by applying four different acceleration voltages/energy levels was established. We carried out simulations using different ratios and concentrations (given in fractions of volume units, VU) of the four different materials (plus residual material) at different noise-levels for 30 keV, 40 keV, 50 keV, 60 keV, 80 keV and 100 keV (monochromatic). Our simulation results were then confirmed by using region of interest-based measurements in a phantom-study at corresponding acceleration voltages. Therefore, different mixtures of contrast materials were scanned using a micro-CT. Voxel wise evaluation of the phantom imaging data was conducted to confirm its usability for future imaging applications and to estimate the influence of varying noise-levels, scattering, artifacts and concentrations. The analysis of our simulations showed the smallest deviation of 0.01 (0.003-0.15) VU between given and calculated concentrations of the different contrast materials when using an energy-combination of 30 keV, 40 keV, 50 keV and 100 keV for MECT. Subsequent MECT phantom measurements, however, revealed a combination of acceleration voltages of 30 kV, 40 kV, 60 kV and 100 kV as most effective for performing material decomposition with a deviation of 0.28 (0-1.07) mg/ml. The feasibility of our voxelwise analyses using the proposed algorithm was then confirmed by the generation of phantom parameter-maps that matched the known contrast material concentrations. The results were mostly influenced by the noise-level and the concentrations used in the phantoms. MECT using a standard micro-CT combined with a matrix inversion method is feasible at four different imaging energies and allows the differentiation of mixtures of up to four contrast materials plus an additional residual material.
多能计算机断层扫描(MECT)是在单能计算机断层扫描(CT)和双能计算机断层扫描的发展基础上产生的,是一种很有前景的工具,可实现先进的材料和组织分解,从而能够在临床前研究中使用多种对比剂。本研究的目的是评估常规临床前微型CT系统是否适用于采用MECT和矩阵反演方法对不同材料进行分解,以及测量环境的不同变化如何影响结果。建立了一种基于矩阵反演的算法,通过应用四种不同的加速电压/能量水平来区分多达五种材料(碘、铁、钡、钆、残余材料)。我们针对30 keV、40 keV、50 keV、60 keV、80 keV和100 keV(单色),在不同噪声水平下,使用四种不同材料(加上残余材料)的不同比例和浓度(以体积单位分数,VU表示)进行了模拟。然后,通过在相应加速电压下的体模研究中基于感兴趣区域的测量,证实了我们的模拟结果。因此,使用微型CT扫描了不同的对比剂混合物。对体模成像数据进行了逐体素评估,以确认其在未来成像应用中的可用性,并估计不同噪声水平、散射、伪影和浓度的影响。我们的模拟分析表明,在MECT中使用30 keV、40 keV、50 keV和100 keV的能量组合时,不同对比剂的给定浓度和计算浓度之间的最小偏差为0.01(0.003 - 0.15)VU。然而,随后的MECT体模测量表明,30 kV、40 kV、60 kV和100 kV的加速电压组合对于进行材料分解最为有效,偏差为0.28(0 - 1.07)mg/ml。然后,通过生成与已知对比剂浓度匹配的体模参数图,证实了我们使用所提出算法进行逐体素分析的可行性。结果主要受噪声水平和体模中使用的浓度影响。使用标准微型CT结合矩阵反演方法的MECT在四种不同的成像能量下是可行的,并且能够区分多达四种对比剂加一种额外残余材料的混合物。