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Purpose To evaluate the effect of different methods to convert MR signal intensity (SI) to gadolinium concentration ([Gd]) on estimation and reproducibility of model-free and modeled hepatic perfusion parameters measured with DCE-MRI. Materials and Methods In this IRB-approved prospective study, 23 DCE-MRI examinations of the liver were performed on 17 patients. SI was converted to [Gd] using linearity vs. non linearity assumptions (using SPGR signal equations). [Gd] vs. time curves were analyzed using model-free parameters and a dual-input single compartment model. Perfusion parameters obtained with the two conversion methods were compared using paired Wilcoxon test. Test-retest and inter-observer reproducibility of perfusion parameters were assessed in 6 patients. Results There were significant differences between the two conversion methods for the following parameters: AUC60 (area under the curve at 60 seconds, p <0.001), peak gadolinium concentration (Cpeak, p <0.001), upslope (p <0.001), Fp (portal flow, p=0.04), total hepatic flow (Ft, p=0.007), and MTT (mean transit time, p <0.001). Our preliminary results showed acceptable to good reproducibility for all model-free parameters for both methods [mean coefficient of variation (CV) range, 11.87–23.7%], except for upslope (CV = 37%). Among modeled parameters, DV (distribution volume) had CV <22% with both methods, PV and MTT showed CV <21% and <29% using SPGR equations, respectively. Other modeled parameters had CV >30% with both methods. Conclusion Linearity assumption is acceptable for quantification of model-free hepatic perfusion parameters while the use of SPGR equations and T1 mapping may be recommended for the quantification of modeled hepatic perfusion parameters.

Naïve T-cells divide and mature, both functionally and phenotypically, upon stimulation through the T-cell receptor. Although much is known about the overall changes that occur in naïve cells upon TCR stimulation, and the different memory/effector populations that arise following stimulation, the relationship between cell division and functional and phenotypical changes that occur after activation is poorly understood. Here, we examine the early stages of human naïve and antigen-experienced T-cell activation, and the relationship between cell division and acquisition of effector function during the transition from resting antigen-experienced or naïve T-cells into effector cells. Stimulated naïve T-cells proliferate prior to acquisition of effector function, as measured by cytokine production and expression of effector-associated cell surface molecules. Additionally, we show that interlukin-7 (IL-7) can drive proliferation of naïve T-cells without TCR:MHC peptide interactions. IL-7 alone does not, however, drive the proliferation of antigen-experienced T-cells. Memory T-cells will divide in response to exogenous IL-7 but only in the presence of naïve T-cells and IL-2. This study contributes to the current understanding of the mechanistic differences between naïve and memory T-cell responses by defining the functional and phenotypic changes that occur to T-cells after stimulation.

To monitor and better understand the immunoinflammatory sequelae in sepsis and septic shock, systemic and monocyte-related cytokine responses were evaluated in baboons with experimental peritonitis induced by an E. coli-laden fibrin clot. Despite similar bacterial inocula, considerable interindividual variability in clinical manifestation and outcome of infection was observed. Because monocytes and macrophages are a key component of innate immunity, we hypothesized that early polarization of distinct activation programs in circulating monocytes that culminates in the emergence of either classically (M1) or alternatively (M2) activated monocytes may underlie the observed susceptibility or resistance to infection. To test our hypothesis, we analyzed infection-induced expression of cytokine mRNAs in monocytes isolated from surviving and dead animals. Our data show that resistance to E. coli sepsis may well be associated with a mixed M1/M2 activation state of circulating monocytes, whereas M1 phenotype appeared to be prevailing in monocytes from animals that died. Together with data on systemic cytokine responses, the latter findings indicate that morbidity and mortality of animals with gram-negative sepsis may well result from an overwhelming proinflammatory response. Collectively, our data contribute to a better understanding of cytokine networking in the immunoinflammatory response to microbial infection and suggest M1/M2 immunophenotypic profiling of readily available circulatory monocytes for early prognosis of severe infections.