Comparison of automated and manual protocols for magnetic resonance imaging assessment of liver iron concentration

Objective

To compare automated and manual magnetic resonance imaging protocols for estimating liver iron concentrations at 1.5 T.

Materials and Methods

Magnetic resonance imaging examination of the liver was performed in 53 patients with clinically suspected hepatic iron overload and in 21 control subjects. Liver iron concentrations were then estimated by two examiners who were blinded to the groups. The examiners employed automated T2* and T1 mapping, as well as manual T2* and signal-intensity-ratio method. We analyzed accuracy by using ROC curves. Interobserver and intraobserver agreement were analyzed by calculating two-way intraclass correlation coefficients.

Results

The area under the ROC curve (to discriminate between patients and controls) was 0.912 for automated T2* mapping, 0.934 for the signal-intensity-ratio method, 0.908 for manual T2*, and 0.80 for T1 mapping, the last method differing significantly from the other three. The level of interobserver and intraobserver agreement was good (intraclass correlation coefficient, 0.938-0.998; p < 0.05). Correlations involving T1 mapping, although still significant, were lower.

Conclusion

At 1.5 T, T2* mapping is a rapid tool that shows promise for the diagnosis of liver iron overload, whereas T1 mapping shows less accuracy. The performance of T1 mapping is poorer than is that of T2* methods.

Characterization of CD4+CD28null T cells in patients with coronary artery disease and individuals with risk factors for atherosclerosis

Risk factors for atherosclerosis may contribute to chronic low-grade inflammation. A highly cytotoxic and inflammatory CD4(+) cell subset (CD4(+)CD28(null) cells) has been associated with inflammatory diseases, including acute coronary syndromes (ACS). The aim of this study was to quantify and characterize CD4(+)CD28(null) cells in individuals with risk factors for atherosclerosis and patients with coronary artery disease (CAD). In order to achieve this goal, peripheral blood mononuclear cells (PBMCs) from individuals with risk factors for atherosclerosis and patients with CAD were analyzed using flow cytometry to detect cytotoxic molecules and evaluate the expression of homing receptors and inflammatory cytokines in CD4(+) cell subsets. The cells were evaluated ex vivo and after stimulation in culture. We found no differences in the proportions of CD4(+)CD28(null) cells among the groups. Compared with the CD4(+)CD28(+) population, the ex vivo CD4(+)CD28(null) subset from all groups expressed higher levels of granzymes A and B, perforin, granulysin and interferon-γ (IFN-γ). Individuals with risk factors and patients with ACS showed the highest levels of cytotoxic molecules. After stimulation, tumor necrosis factor-α (TNF-α) expression in the CD4(+)CD28(null) subset from these groups increased more than in the other groups. Stimulation with LPS decreased the expression of cytotoxic molecules by CD4(+)CD28(null) cells in all groups. In conclusion, our results show that risk factors for atherosclerosis may alter the CD4(+)CD28(null) cells phenotype, increasing their cytotoxic potential. Our findings also suggest that CD4(+)CD28(null) cells may participate in the early phases of atherosclerosis.

Platelet and leukocyte adhesion and activation in unstable angina and post-PTCA

BACKGROUND

Unstable atherosclerotic plaques activate blood cells which may adhere to the coronary endothelium causing vessel occlusion. However, it is unknown if different clinical syndromes associated with plaque rupture induce similar blood cell activation and adhesion to the endothelium.

METHODS

We studied changes in adhesion molecule expression of platelets (GPIIb/IIIa), neutrophils--CD18, CD11b and L-selectin--and monocytes (CD14) after interaction with active lesions of patients with stable angina subjected to PTCA and patients with unstable angina (UA). Generation of superoxide (SO) radicals from PMNs and PMN sequestration in the coronary circulation were also assessed. Blood samples were collected from the aorta (Ao) and coronary sinus (CS) before and 15 min after PTCA (n=13) and within the first 48 h of UA (n=12).

RESULTS

PTCA induced a marked up-regulation of CD18, CD11b, CD14 and GPIIb/IIIa with L-selectin shedding and reduced SO formation, whereas only minor L-selectin down-regulation and decreased SO production indicated activation in UA. However, a significant decrease in neutrophil count in the CS compared to the Ao was only observed in UA.

CONCLUSIONS

The magnitude of cellular activation depends on the underlying clinical setting and just partially contributes to cell adhesion to the endothelium which might be modulated by different extent of vascular occlusion and shear forces.