Physics in medicine and biology
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This work investigates and compares two different phase-correction algorithms for Dixon fat-water separation and two different quality maps (QM) for region-growing: the original QM, based on phase gradients, and a QM based on phase uncertainty, proposed in this article. A spoiled dual-gradient-echo sequence was employed at 1.5 T to acquire in-phase and out-of-phase images of joints, parotid glands, abdomen and test objects. All 97 datasets were processed eight times each: with two different phase correction algorithms (original and hierarchical phase correction), with two different QM, and with/without removing linear component of the phase drifts associated with dual-echo acquisitions and bipolar readout gradient waveforms. ⋯ The hierarchic phase-correction algorithm outperformed the original phase-correction algorithm in all applications. The proposed phase-uncertainty QM provides a small performance improvement in clinical images, but can be vulnerable to flow-related phase shifts in bright vessels. Overall the most successful phase-correction technique employed phase-uncertainty QMs and hierarchic algorithms, with pre-processing to correct the linear phase drift associated with dual-echo acquisitions and bipolar readout gradient waveform.
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Comparative Study
A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer.
Quantitative analysis of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data requires the accurate determination of the arterial input function (AIF). A novel method for obtaining the AIF is presented here and pharmacokinetic parameters derived from individual and population-based AIFs are then compared. A Philips 3.0 T Achieva MR scanner was used to obtain 20 DCE-MRI data sets from ten breast cancer patients prior to and after one cycle of chemotherapy. ⋯ Regarding the kinetic parameters, the CCC values for K(trans), v(p) and v(e) as estimated by AIF(ind) and AIF(pop) are 0.65, 0.74 and 0.31, respectively, based on the region of interest analysis. The average CCC values for the voxel-by-voxel analysis are 0.76, 0.84 and 0.68 for K(trans), v(p) and v(e), respectively. This work indicates that K(trans) and v(p) show good agreement between AIF(pop) and AIF(ind) while there is a weak agreement on v(e).