Daniel Prochnow | PubMed Health

PubMed2006

Solid-state NMR studies of 17O-enriched pyrophosphates.

For the first time, 17O NMR studies were performed on 17O-enriched crystalline pyrophosphates (magnesium-, sodium- and barium-pyrophosphate) by means of triple-quantum magic-angle spinning (3QMAS) and double-rotation (DOR) in the high external field of 17.6 T. Oxygen atoms in bridging positions (P-OB-P) exhibit a significant higher quadrupole coupling constant compared to oxygen atoms in terminal positions (P-OT). With increasing cationic radius a higher value of the chemical shift of the terminal oxygen atoms is observed.

Journal Article↗

PubMed2005

Implementation of a rapid inversion-prepared dual-contrast gradient echo sequence for quantitative dynamic contrast-enhanced magnetic resonance imaging of the human prostate.

The first step in quantitative pharmacokinetic modeling is to determine the arterial input function (AIF) by deriving the contrast medium (CM) concentration from an appropriate imaging sequence by monitoring changes in either the amplitude or the phase signal of an accommodative artery. The bolus passage is best detected on T2- or T2*-weighted images, while extravasation is best assessed on T1-weighted images. Here, an imaging sequence is used that employs a parallel acquisition technique for the interleaved acquisition of an inversion-prepared T1-weighted image and a T1/T2*-mixed-weighted image for determination of the AIF. The sequence was applied in six patients with prostate cancer. A method is presented for quantifying the AIF derived from the signal intensity-time courses of both the T1/T2*-mixed-weighted and the T1-weighted image. Furthermore, in some patients the signal intensity-time course of the T1-weighted image exhibits flow-induced signal modulations. To reduce the effect of this flow-related signal enhancement the corresponding phase information was used. The sequence presented here has the potential to improve the quantification of the AIF at all time points and pharmacokinetic modeling of the CM dynamics of the prostate.

Algorithms↗