Differentiation Between Solitary Pulmonary Inflammatory Lesions and Solitary Cancer Using Gemstone Spectral Imaging.

BACKGROUND: The distinction between solitary inflammatory lesion and solitary lung cancer remains a challenge because of their considerable overlapping computed tomography (CT) imaging features. PURPOSE: This study aimed to verify whether spectral CT parameters can differentiate solitary lung cancer from solitary inflammatory lesions and to find their correlations with lesion size. METHODS: A total of 78 patients with solitary lung lesions were included in our study. All of them underwent enhanced CT scans with Gemstone Spectral Imaging (GSI) mode, which was one of the dual-energy imaging technologies. According to maximum diameter (Dmax) of the lesion, regions of interest were collected and divided into inflammatory (group I: <3 cm [IA], n = 17; ≥3 cm [IB], n = 14) and cancer groups (group II: <3 cm [IIA], n = 20; ≥3 cm [IIB], n = 27). Computed tomography values (HU40keV, HU70keV), effective atomic number (Zeff), iodine concentration (IC), normalized IC (NIC), and spectral curve slopes (λ30, λ40) of each region of interest were calculated. The NIC was defined as the IC ratio of the lesion to the descending aorta. Mann-Whitney U test was used for intergroup (I vs II, IA vs IIA, IB vs IIB) and intragroup (IA vs IB, IIA vs IIB) comparisons, and receiver operating characteristic curve analysis was performed. Correlation analysis was applied to find the relationship between Dmax and GSI parameters. RESULTS: No significant correlation was found between GSI parameters and Dmax in the inflammatory group, whereas inverse correlations were found in the cancer group. Gemstone spectral imaging parameters (except HU70keV) of group IIA were significantly higher than those of group IIB. There were significant differences in HU40keV, IC, NIC, λ30, and λ40 between groups IB and IIB under both arterial and venous phase (P values < 0.05), whereas the area under the curve for λ30 under venous phase was largest, and sensitivity and specificity were 96.32% and 85.71%, respectively. However, only HU40keV and HU70keV values under the arterial phase of IIA were significantly higher than those of IA. CONCLUSIONS: Quantitative parameters of GSI demonstrated an inverse correlation with the lesion size of solitary lung cancer, and GSI parameters can be new ways to differentiate solitary lung cancer from solitary inflammatory lesions.

Diffusion kurtosis imaging of microstructural changes in brain tissue affected by acute ischemic stroke in different locations.

The location of an acute ischemic stroke is associated with its prognosis. The widely used Gaussian model-based parameter, apparent diffusion coefficient (ADC), cannot reveal microstructural changes in different locations or the degree of infarction. This prospective observational study was reviewed and approved by the Institutional Review Board of Xiamen Second Hospital, China (approval No. 2014002).Diffusion kurtosis imaging (DKI) was used to detect 199 lesions in 156 patients with acute ischemic stroke (61 males and 95 females), mean age 63.15 ± 12.34 years. A total of 199 lesions were located in the periventricular white matter (n = 52), corpus callosum (n = 14), cerebellum (n = 29), basal ganglia and thalamus (n = 21), brainstem (n = 21) and gray-white matter junctions (n = 62). Percentage changes of apparent diffusion coefficient (ΔADC) and DKI-derived indices (fractional anisotropy [ΔFA], mean diffusivity [ΔMD], axial diffusivity [ΔDa], radial diffusivity ΔDr, mean kurtosis [ΔMK], axial kurtosis [ΔKa], and radial kurtosis [ΔKr]) of each lesion were computed relative to the normal contralateral region. The results showed that (1) there was no significant difference in ΔADC, ΔMD, ΔDa or ΔDr among almost all locations. (2) There was significant difference in ΔMK among almost all locations (except basal ganglia and thalamus vs. brain stem; basal ganglia and thalamus vs. gray-white matter junctions; and brainstem vs. gray-white matter junctions. (3) The degree of change in diffusional kurtosis in descending order was as follows: corpus callosum > periventricular white matter > brainstem > gray-white matter junctions > basal ganglia and thalamus > cerebellum. In conclusion, DKI could reveal the differences in microstructure changes among various locations affected by acute ischemic stroke, and performed better than diffusivity among all groups.