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A fluorinated, air-stable cobalt(ii) complex serves as a turn-on 19 F magnetic resonance imaging (MRI) tracer for reactive oxygen species including H 2 O 2 . Upon oxidation with H 2 O 2 , the complex converts from paramagnetic high spin Co II to diamagnetic low spin Co III resulting in a chemical shift change and enhancement in 19 F NMR signal. Further, the oxidation can be reversed in the presence of reductant Na 2 S 2 O 4 . The turn-on response is demonstrated by 19 F MRI, characterized by a ∼2-3 fold enhancement in signal.

Introduction: This pilot study developed techniques to perform Magnetic Resonance Imaging (MRI) of specific fat deposition in 18 children (age 18 months to 4 years)., Methods: The children engaged in a series of practice tests to become acclimated to the scanner noises, reduce claustrophobia, and rehearse holding still for a set time. The practice tests assessed if the child could remain still for two minutes while watching a video, first while lying on a blanket, second, on the blanket with headphones, and third, in the mock scanner. The children who passed the three practice tests were then scanned with a 3T Siemens Skyra magnet. Abdominal fat distribution (region of interest (ROI) from the top of the ileac crest to the bottom of the ribcage) volume was measured using 2-point DIXON technique. This region was chosen to give an indication of the body composition around the liver., Results: Twelve out of eighteen participants successfully completed the actual MRI scan. Chi-squared test showed no significant difference between male and female pass-fail rates. The median age of completed scans was 36 months, whereas the median age for children unable to complete a scan was 28 months. The average total trunk fat was 240.9±85.2mL and the average total VAT was 37.7±25.9mLand liver fat was not quantifiable due to physiological motion. Several strategies (modeling, videos, and incentives) were identified to improve pediatric imaging in different age ranges., Conclusion: Using an age-specific and tailored protocol, we were able to successfully use MRI for fat imaging in a majority of young children. Development of such protocols enables researchers to better understand the etiology of fat deposition in young children, which can be used to aid in the prevention and treatment of adiposity.

Models have been developed for the analysis of dynamic contrast-enhanced MRI (DCE-MRI) data that do not require direct measurements of the arterial input function; such methods are referred to as reference region models. These models typically return estimates of the volume transfer constant (K(trans)) and the extravascular extracellular volume fraction (v(e)). To date such models have assumed a linear relationship between the measured R(1) ( identical with 1/T(1)) and the concentration of contrast agent, a transformation referred to as the fast exchange limit, but this assumption is not valid for all concentrations of an agent. A theory for DCE-MRI reference region models which accounts for water exchange is presented, evaluated in simulations, and applied in tumor-bearing mice. Using reasonable parameter values, simulations show that the assumption of fast exchange can underestimate K(trans) and v(e) by up to 82% and 46%, respectively. By analyzing a large region of interest and a single voxel the new model can return parameters within approximately +/-10% and +/-25%, respectively, of their true values. Analysis of experimental data shows that the new approach returns K(trans) and v(e) values that are up to 90% and 73%, respectively, greater than conventional fast exchange analyses., ((c) 2008 Wiley-Liss, Inc.)

Purpose: To test the repeatability of a reference region (RR) model for the analysis of dynamic contrast-enhanced MRI (DCE-MRI) in a mouse model of cancer at high field., Materials and Methods: Seven mice were injected with 10(6) 4T1 mammary carcinoma cells and imaged eight to 10 days later on a Varian 7.0T scanner. Two DCE-MRI studies were performed for each mouse (separated by 2.5 hours). The RR model was used to analyze the data, and returned estimates on the perfusion-permeability index (Ktrans) for the RR and the tissue of interest (TOI), as well as the extravascular extracellular volume fraction (ve) for the TOI., Results: When the first injection was compared with the second injection, all parameters tested were highly correlated (r2=0.90, 0.62, 0.82 for the RR Ktrans, TOI Ktrans, and TOI ve, respectively, with P<0.001 for all). To observe a statistically significant change (at the 5% level) in a treatment study with seven animals in each group, log10 changes of 0.084 and 0.077 in the tumor Ktrans and ve, respectively, are required., Conclusion: If a reliable arterial input function (AIF) is unavailable, the RR model is a reasonable alternative to measuring MRI contrast-agent (CA) kinetics in mouse models of cancer at high field., (Copyright (c) 2006 Wiley-Liss, Inc.)

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess tumor perfusion, microvascular vessel wall permeability and extravascular-extracellular volume fraction. Analysis of DCE-MRI data is usually based on indicator dilution theory that requires knowledge of the concentration of the contrast agent in the blood plasma, the arterial input function (AIF). A method is presented that compares the tissues of interest (TOI) curve shape to that of a reference region (RR), thereby eliminating the need for direct AIF measurement. By assigning literature values for Ktrans (the blood perfusion-vessel permeability product) and v(e) (extravascular-extracellular volume fraction) in a reference tissue, it is possible to extract the Ktrans and v(e) values for a TOI without knowledge of the AIF. The operational RR equation for DCE-MRI analysis is derived, and its sensitivity to noise and incorrect assignment of the RR parameters is tested via simulations. The method is robust at noise levels of 10%, returning accurate (+/-20% in the worst case) and precise (+/-15% in the worst case) values. Errors in the TOI Ktrans and v(e) values scale approximately linearly with the errors in the assigned RR Ktrans and v(e) values. The methodology is then applied to a Lewis Lung Carcinoma mouse tumor model. A slowly enhancing TOI yielded Ktrans=0.039+/-0.002 min-1 and v(e)=0.46+/-0.01, while a rapidly enhancing region yielded Ktrans=0.35+/-0.05 min-1 and v(e)=0.31+/-0.01. Parametric Ktrans and v(e) mappings manifested a tumor periphery with elevated Ktrans (>0.30 min-1) and v(e) (>0.30) values. The main advantage of the RR approach is that it allows for quantitative assessment of tissue properties without having to obtain high temporal resolution images to characterize an AIF. This allows for acquiring images with higher spatial resolution and/or SNR, and therefore, increased ability to probe tissue heterogeneity.