Spectral ρZ-Projection Method for Characterization of Body Fluids in Computed Tomography. Ex Vivo Experiments1
Department of Diagnostic Radiology and Applied Medical Engineering, Helmholtz Institute, RWTH Aachen University, Pauwelsstrasse 30, D 52074, Aachen, Germany. Academic radiology
(Impact Factor: 1.75).
07/2009; 16(6):763-9. DOI: 10.1016/j.acra.2009.01.002
The identification of body fluids in computed tomography poses a major diagnostic challenge. The chemical composition of body fluids deviates only slightly from water with very similar computed tomographic (CT) values, which typically range from 0 to 100 HU. The aim of this study was to assess physical and chemical properties of different body fluids in an ex vivo setting.
A total of 44 samples of blood, blood mixed with pus, pus, bile, and urine obtained during diagnostic and therapeutic punctures were scanned at 80 and 140 kV. Data was quantitatively assessed using the spectral rhoZ-projection algorithm, which converts dual-energy CT scans into mass density (rho) and effective atomic number (Z(eff.)) information.
Attenuation values measured at 80 and 140 kV were largely overlapping. CT values allowed, to some degree, for the differentiation of bile or pus from blood or the blood/pus mixture. By applying the rhoZ-projection, most substances, except for urine, were distinguishable with only small standard deviations ranging between 0.003 and 0.007 g/cm(3) for mass density and between 0.020 and 0.043 for Z(eff.).
The rhoZ-projection method is suited to quantitatively assess mass density and effective atomic number of ex vivo body fluid samples. In clinical routine, this technique might be useful for identifying unclear fluid collections even in unenhanced computed tomography.
Available from: Frank Verhaegen
- "The correction reduces errors on Z cor to ±1%, except for lung tissue (Z eff = 7.60). This level of accuracy is within the 0.1 to 0.2 (in units of Z) requirement suggested by Mahnken et al (2009) for soft tissue identification. Similar agreement is found for the relative electron density. "
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ABSTRACT: This work compares Monte Carlo (MC) dose calculations for (125)I and (103)Pd low-dose rate (LDR) brachytherapy sources performed in virtual phantoms containing a series of human soft tissues of interest for brachytherapy. The geometries are segmented (tissue type and density assignment) based on simulated single energy computed tomography (SECT) and dual energy (DECT) images, as well as the all-water TG-43 approach. Accuracy is evaluated by comparison to a reference MC dose calculation performed in the same phantoms, where each voxel's material properties are assigned with exactly known values. The objective is to assess potential dose calculation accuracy gains from DECT. A CT imaging simulation package, ImaSim, is used to generate CT images of calibration and dose calculation phantoms at 80, 120, and 140 kVp. From the high and low energy images electron density ρ(e) and atomic number Z are obtained using a DECT algorithm. Following a correction derived from scans of the calibration phantom, accuracy on Z and ρ(e) of ±1% is obtained for all soft tissues with atomic number Z ∊ [6,8] except lung. GEANT4 MC dose calculations based on DECT segmentation agreed with the reference within ±4% for (103)Pd, the most sensitive source to tissue misassignments. SECT segmentation with three tissue bins as well as the TG-43 approach showed inferior accuracy with errors of up to 20%. Using seven tissue bins in our SECT segmentation brought errors within ±10% for (103)Pd. In general (125)I dose calculations showed higher accuracy than (103)Pd. Simulated image noise was found to decrease DECT accuracy by 3-4%. Our findings suggest that DECT-based segmentation yields improved accuracy when compared to SECT segmentation with seven tissue bins in LDR brachytherapy dose calculation for the specific case of our non-anthropomorphic phantom. The validity of our conclusions for clinical geometry as well as the importance of image noise in the tissue segmentation procedure deserves further experimental investigation.
Physics in Medicine and Biology 09/2011; 56(19):6257-78. DOI:10.1088/0031-9155/56/19/007 · 2.76 Impact Factor
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ABSTRACT: Recent technological advances in multidetector computed tomography (CT) have led to the introduction of dual-source CT, which allows acquisition of CT data at the same energy or at 2 distinct tube voltage settings during a single acquisition. The advantage of the former is improvement of temporal resolution, whereas the latter offers new options for CT imaging, allowing tissue characterization and functional analysis with morphologic evaluation. The most investigated application has been iodine mapping at pulmonary CT angiography. The material decomposition achievable opens up new options for recognizing substances poorly characterized by single-energy CT. Although it is too early to draw definitive conclusions on dual-energy CT applications, this article reviews the results already reported with the first generation of dual-source CT systems.
Radiologic Clinics of North America 01/2010; 48(1):193-205. DOI:10.1016/j.rcl.2009.08.013 · 1.98 Impact Factor
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ABSTRACT: The development of atherosclerotic plaques occurs slowly over decades. This provides an opportunity for diagnostic imaging
to identify patients before clinical events occur. Computed tomography (CT) is an important imaging technique that is rountinely
used for the noninvasive imaging of the arteries throughout the body. One of the most recent innovations in CT is the use
of two tubes with different energy, which is called dual-energy CT. This technique has the potential to improve the abilities
to differentiate various body tissues with CT, and to increase the inherently low contrast of single-energy CT. This chapter
reviews the current status and potential future role of dual-energy CT to detect, characterize and differentiate atherosclerotic
01/2011: pages 73-79;
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