Quantitative analysis of lung lesions using unenhanced chest computed tomography images.

INTRODUCTION: Chest radiograph and computed tomography (CT) scans can accidentally reveal pulmonary nodules. Malignant and benign pulmonary nodules can be difficult to distinguish without specific imaging features, such as calcification, necrosis, and contrast enhancement. However, these lesions may exhibit different image texture characteristics which cannot be assessed visually. Thus, a computer-assisted quantitative method like histogram analysis (HA) of Hounsfield unit (HU) values can improve diagnostic accuracy, reducing the need for invasive biopsy. METHODS: In this exploratory control study, nonenhanced chest CT images of 20 patients with benign (10) and cancerous (10) lesion were selected retrospectively. The appearances of benign and malignant lesions were very similar in chest CT images, and only pathology report was used to discriminate them. Free hand region of interest (ROI) was inserted inside the lesion for all slices of each lesion. Mean, minimum, maximum, and standard deviations of HU values were recorded and used to make HA. RESULTS: HA showed that the most malignant lesions have a mean HU value between 30 and 50, a maximum HU less than 150, and a minimum HU between -30 and 20. Lesions outside these ranges were mostly benign. CONCLUSION: Quantitative CT analysis may differentiate malignant from benign lesions without specific malignancy patterns on unenhanced chest CT image.

Dependence of the effective mass attenuation coefficient of gold nanoparticles on its radius.

PURPOSE: Several investigations are being carried since the past decade to use gold nanoparticles' (AuNP) suspensions as contrast agents (CA) for imaging in Computed Tomography. For this, the optimal size of AuNP has received considerable attention, which is addressed here. MATERIAL AND METHODS: In this theoretical study, effective attenuation coefficient for a single spherical shaped AuNP is first calculated from the first principles, as a function of the nanoparticle radius 'r', with µ(E) being the attenuation coefficient of the material for a given energy E. This result is extended to derive a formula for the attenuation coefficient and mass attenuation coefficient of a suspension of AuNP. RESULTS: It is seen that the effective mass attenuation coefficient of the nanoparticles is a decreasing function of α(E) = 2µ(E)r and falls inversely with α(E), for large values of α(E) ≫ 1, there being very little change for α ≤ 1. CONCLUSION: The paper shows that for nanoparticles, less than 100 nm in diameter the linear attenuation coefficient of the colloidal suspension has no dependence on the nanoparticles' size and depends only on the concentration of nanoparticle material present in the suspension.

Non-invasive characterization of coronary artery atherosclerotic plaque using dual energy CT: Explanation in ex-vivo samples.

PURPOSE: In this study non-calcified plaque composition is evaluated by Dual Energy CT (DECT). Energy Dispersive X-ray Spectroscopy (EDS) has been used to study the Plaque composition. An attempt has been made to explain the DECT results with EDS analysis. METHODS: Thirty-two ex-vivo human cadaver coronary artery samples were scanned by DECT and data was evaluated to calculate their effective atomic number and electron density (Zeff & ρe) by inversion method. Result of DECT was compared with pathology to assess their differentiating capability. The EDS study was used to explain DECT outcome. RESULTS: DECT study was able to differentiate vulnerable plaque from stable with 87% accuracy (area under the curve (AUC):0.85 [95% confidence interval {CI}:0.73-0.98}] and Kappa Coefficient (KC):0.75 with respect to pathology. EDS revealed significant compositional difference in vulnerable and stable plaque at p < .05. The weight percentage of higher atomic number elements like F, Na, Mg, S, Si, P, Cl, K and Ca was found to be slightly more in vulnerable plaques as compared to a stable plaque. EDS also revealed a significantly increased weight percentage of nitrogen in stable plaques. CONCLUSIONS: The EDS results were able to explain the outcomes of DECT study. This study conclusively explains the physics of DECT as a tool to assess the nature of non-calcified plaques as vulnerable and stable. The method proposed in this study allows for differentiation between vulnerable and stable plaque using DECT.

DECT evaluation of noncalcified coronary artery plaque.

PURPOSE: Composition of the coronary artery plaque is known to have critical role in heart attack. While calcified plaque can easily be diagnosed by conventional CT, it fails to distinguish between fibrous and lipid rich plaques. In the present paper, the authors discuss the experimental techniques and obtain a numerical algorithm by which the electron density (ρ(e)) and the effective atomic number (Z(eff)) can be obtained from the dual energy computed tomography (DECT) data. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques. METHODS: For the purpose of calibration of the CT machine, the authors prepare aqueous samples whose calculated values of (ρ(e), Z(eff)) lie in the range of (2.65 × 10(23) ≤ ρ(e) ≤ 3.64 × 10(23)/cm(3)) and (6.80 ≤ Z(eff) ≤ 8.90). The authors fill the phantom with these known samples and experimentally determine HU(V1) and HU(V2), with V1,V2 = 100 and 140 kVp, for the same pixels and thus determine the coefficients of inversion that allow us to determine (ρ(e), Z(eff)) from the DECT data. The HU(100) and HU(140) for the coronary artery plaque are obtained by filling the channel of the coronary artery with a viscous solution of methyl cellulose in water, containing 2% contrast. These (ρ(e), Z(eff)) values of the coronary artery plaque are used for their characterization on the basis of theoretical models of atomic compositions of the plaque materials. These results are compared with histopathological report. RESULTS: The authors find that the calibration gives ρ(e) with an accuracy of ±3.5% while Z(eff) is found within ±1% of the actual value, the confidence being 95%. The HU(100) and HU(140) are found to be considerably different for the same plaque at the same position and there is a linear trend between these two HU values. It is noted that pure lipid type plaques are practically nonexistent, and microcalcification, as observed in histopathology, has to be taken into account to explain the nature of the observed (ρ(e), Z(eff)) data. This also enables us to judge the composition of the plaque in terms of basic model which considers the plaque to be composed of fibres, lipids, and microcalcification. CONCLUSIONS: This simple and reliable method has the potential as an effective modality to investigate the composition of noncalcified coronary artery plaques and thus help in their characterization. In this inversion method, (ρ(e), Z(eff)) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (ρ(e), Ze(ff)) does not interfere with each other and the nature of the plaque can be identified in terms of a three component model.

X-ray attenuation coefficient of mixtures: inputs for dual-energy CT.

PURPOSE: The attenuation coefficient, µ(E) of substances, at any energy (E) of the x-ray photon, is known to depend on the electron density (ρ(e)) and the effective atomic number (Z(eff)) of the material. While the dependence on ρ(e) is known to be linear, that of Z(eff) is found to follow a power law (Z(eff))(x) which makes it very sensitive to the index "x". Several different values, lying between 3 and 4 have been suggested for the exponent x, in the existing literature. The purpose of the present investigations is to ascertain empirically the value that should be assigned to x. METHODS: This is done by measuring the HU value of different mixtures, having different values for ρ(e) and Z(eff) (calculated from their known chemical compositions) and thus determining the dependence of their attenuation coefficients (µ) on the above two quantities. RESULTS: The experimental results show the dependence of µ on Z(eff) to be of the power law type, [ρ(e)(Z(eff))(x)/E(y)], where y = 3.0669 but no single value for the index x, can be assigned to fit the observed data. It is seen in different mixtures that the value of x predominantly decreases as Z(eff) increases from 7.5 to 12. CONCLUSIONS: This result points out that very large errors can occur in calculating Z(eff) from the values of µ if a fixed value for x is used. The importance of this result to dual energy computed tomography is pointed out and it is concluded that the proper values for x are required to be incorporated in the inversion algorithms, for the different regimes of Z(eff).