World of Phantoms: Reference Standards for Bench to Breast MRI

We have developed a method for making agar phantoms for MRI that mimic human tissue in terms of theirrelaxation pathways, including T1, T2, and T2*, and other magnetic interactions. Here, we describe a unique approach to developing air bubble-free phantoms that are sensitive to changes in scanner performance. Phantoms with varying concentrations of agar (0-3%) and Omniscan (0-1 mM) solutions were made, and the T1 and T2 values of these phantoms were determined. In addition, fat was suspended in an irregular pattern so that the phantom more accurately mimicked the breast. Here, we describe phantoms designed for two different applications. The first type of phantom can be used forperiodic quality assurance to evaluate overall scanner function. The second type is a unique soft phantom, and is designed for attachment to the breast or other areas of the body so that it can be scanned in the course of each clinical protocol

Patient-specific calibration for breast MRI: breast-coil insertable reference phantom

Abstract onl

The influence of temporal resolution in determining pharmacokinetic parameters from DCE-MRI data

We investigated the influence of the temporal resolution of dynamic contrast-enhanced MRI data on pharmacokinetic parameter estimation. Dynamic Gd-DTPA (Gadolinium-diethylene triamine pentaacetic acid) enhanced MRI data of implanted prostate tumors on rat hind limb were acquired at 4.7 T, with a temporal resolution of ~5 sec. The data were subsequently downsampled to temporal resolutions in the range of 15 sec to 85 sec, using a strategy that involves a recombination of k-space data. A basic two-compartment model was fit to the contrast agent uptake curves. The results demonstrated that as temporal resolution decreases, the volume transfer constant (Ktrans) is progressively underestimated (~4% to ~25%), and the fractional extravascular extracellular space (ve) is progressively overestimated (~1% to ~10%). The proposed downsampling strategy simulates the influence of temporal resolution more realistically than simply downsampling by removing samples. Magn Reson Med 63:811–816, 2010. © 2010 Wiley-Liss, Inc

The use of a reference tissue arterial input function with low-temporal-resolution DCE-MRI data

Pharmacokinetic modeling is a promising quantitative analysis technique for cancer diagnosis. However, diagnostic dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is commonly performed with low temporal resolution. This limits its clinical utility. We investigated for a range of temporal resolutions whether pharmacokinetic parameter estimation is impacted by the use of data-derived arterial input functions (AIFs), obtained via analysis of dynamic data from a reference tissue, as opposed to the use of a standard AIF, often obtained from the literature. We hypothesized that the first method allows the use of data at lower temporal resolutions than the second method. Test data were obtained by downsampling high-temporal-resolution rodent data via a k-space-based strategy. To fit the basic Tofts model, either the data-derived or the standard AIF was used. The resulting estimates of Ktrans and ve were compared with the standard estimates obtained by using the original data. The deviations in Ktrans and ve, introduced when lowering temporal resolution, were more modest using data-derived AIFs compared with using a standard AIF. Specifically, lowering the resolution from 5 to 60 s, the respective changes in Ktrans were 2% (non-significant) and 18% (significant). Extracting the AIF from a reference tissue enables accurate pharmacokinetic parameter estimation for low-temporal-resolution data

The influence of temporal resolution in determining pharmacokinetic parameters from DCE-MRI data

We investigated the influence of the temporal resolution of dynamic contrast-enhanced MRI data on pharmacokinetic parameter estimation. Dynamic Gd-DTPA (Gadolinium-diethylene triamine pentaacetic acid) enhanced MRI data of implanted prostate tumors on rat hind limb were acquired at 4.7 T, with a temporal resolution of ~5 sec. The data were subsequently downsampled to temporal resolutions in the range of 15 sec to 85 sec, using a strategy that involves a recombination of k-space data. A basic two-compartment model was fit to the contrast agent uptake curves. The results demonstrated that as temporal resolution decreases, the volume transfer constant (Ktrans) is progressively underestimated (~4% to ~25%), and the fractional extravascular extracellular space (ve) is progressively overestimated (~1% to ~10%). The proposed downsampling strategy simulates the influence of temporal resolution more realistically than simply downsampling by removing samples. Magn Reson Med 63:811–816, 2010. © 2010 Wiley-Liss, Inc

T1 Quantification: Variable Flip Angle Method vs Use of Reference Phantom

PURPOSE For standardized interpretation of DCEMRI curves, calculation of contrast agent (CA) concentration from signal intensity over time is desired. Accurate measurement of tissue T1 before and after CA administration is thus necessary. Current T1 measurement methods are time-consuming. We propose the use of the ‘reference tissue’ method [Medved et al. JMRI 20(1):122, 2004] for fast T1 measurements concurrent with DCEMRI data acquisition, but with use of a reference phantom

The role of temporal resolution in determining pharmacokinetic parameters from DCE-MR data

In DCE-MRI of the breast, a wide variety in parameter settings is possible. This especially holds for the temporal resolution of the dynamic series. Given thehigh expectations of pharmacokinetic modeling, it is crucial to analyze the effect of temporal resolution in determining pharmacokinetic parameters. Weinvestigated this issue by deriving low-temporal-resolution image-series from a high-temporal-resolution original via a reorganization of the k-space data. The initial experiment, as presented here, was performed on data from model tumors in rats. Fitting of the Kety two-compartment pharmacokinetic modeldemonstrated that with decreasing temporal resolution, Ktrans and ve get progressively under- and overestimated