TY - JOUR A1 - Gómez Damián, Pedro A. A1 - Sperl, Jonathan I. A1 - Janich, Martin A. A1 - Khegai, Oleksandr A1 - Wiesinger, Florian A1 - Glaser, Steffen J. A1 - Haase, Axel A1 - Schwaiger, Markus A1 - Schulte, Rolf F. A1 - Menzel, Marion Irene T1 - Multisite Kinetic Modeling of 13C Metabolic MR Using [1-13C]Pyruvate JF - Radiology Research and Practice N2 - Hyperpolarized13C imaging allows real-timein vivomeasurements of metabolite levels. Quantification of metabolite conversion between [1-13C]pyruvate and downstream metabolites [1-13C]alanine, [1-13C]lactate, and [13C]bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multisite, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multisite model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multisite model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues. UR - https://doi.org/10.1155/2014/871619 Y1 - 2014 UR - https://doi.org/10.1155/2014/871619 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-41646 SN - 2090-195X VL - 2014 PB - Hindawi CY - New York ER - TY - JOUR A1 - Liu, Xin A1 - Gómez, Pedro A. A1 - Solana, Ana Beatriz A1 - Wiesinger, Florian A1 - Menzel, Marion Irene A1 - Menze, Bjoern H. T1 - Silent 3D MR sequence for quantitative and multicontrast T1 and proton density imaging JF - Physics in Medicine & Biology N2 - This study aims to develop a silent, fast and 3D method for T1 and proton density (PD) mapping, while generating time series of T1-weighted (T1w) images with bias-field correction. Undersampled T1w images at different effective inversion times (TIs) were acquired using the inversion recovery prepared RUFIS sequence with an interleaved k-space trajectory. Unaliased images were reconstructed by constraining the signal evolution to a temporal subspace which was learned from the signal model. Parameter maps were obtained by fitting the data to the signal model, and bias-field correction was conducted on T1w images. Accuracy and repeatability of the method was accessed in repeated experiments with phantom and volunteers. For the phantom study, T1 values obtained by the proposed method were highly consistent with values from the gold standard method, R2 = 0.9976. Coefficients of variation (CVs) ranged from 0.09% to 0.83%. For the volunteer study, T1 values from gray and white matter regions were consistent with literature values, and peaks of gray and white matter can be clearly delineated on whole-brain T1 histograms. CVs ranged from 0.01% to 2.30%. The acoustic noise measured at the scanner isocenter was 2.6 dBA higher compared to the in-bore background. Rapid and with low acoustic noise, the proposed method is shown to produce accurate T1 and PD maps with high repeatability by reconstructing sparsely sampled T1w images at different TIs using temporal subspace. Our approach can greatly enhance patient comfort during examination and therefore increase the acceptance of the procedure. UR - https://doi.org/10.1088/1361-6560/aba5e8 KW - T1 mapping KW - proton density KW - silent MRI KW - inversion recovery KW - temporal subspace Y1 - 2020 UR - https://doi.org/10.1088/1361-6560/aba5e8 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-18793 SN - 1361-6560 SN - 0031-9155 VL - 65 IS - 18 PB - IOP Publishing CY - Bristol ER - TY - INPR A1 - Kaushik, Sandeep A1 - Bylund, Mikael A1 - Cozzini, Cristina A1 - Shanbhag, Dattesh A1 - Petit, Steven F. A1 - Wyatt, Jonathan J. A1 - Menzel, Marion Irene A1 - Pirkl, Carolin A1 - Mehta, Bhairav A1 - Chauhan, Vikas A1 - Chandrasekharan, Kesavadas A1 - Jonsson, Joakim A1 - Nyholm, Tufve A1 - Wiesinger, Florian A1 - Menze, Bjoern H. T1 - Region of Interest focused MRI to Synthetic CT Translation using Regression and Classification Multi-task Network UR - https://doi.org/10.48550/arXiv.2203.16288 KW - MRI Radiation Therapy KW - Synthetic CT KW - Multi-task Network KW - image translation KW - PET/MR Y1 - 2022 UR - https://doi.org/10.48550/arXiv.2203.16288 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Kaushik, Sandeep A1 - Bylund, Mikael A1 - Cozzini, Cristina A1 - Shanbhag, Dattesh A1 - Petit, Steven F. A1 - Wyatt, Jonathan J. A1 - Menzel, Marion Irene A1 - Pirkl, Carolin A1 - Mehta, Bhairav A1 - Chauhan, Vikas A1 - Chandrasekharan, Kesavadas A1 - Jonsson, Joakim A1 - Nyholm, Tufve A1 - Wiesinger, Florian A1 - Menze, Bjoern H. T1 - Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network JF - Physics in Medicine & Biology UR - https://doi.org/10.1088/1361-6560/acefa3 Y1 - 2023 UR - https://doi.org/10.1088/1361-6560/acefa3 SN - 0031-9155 SN - 1361-6560 VL - 68 IS - 19 PB - IOP Publishing CY - Bristol ER - TY - JOUR A1 - Durst, Markus A1 - Koellisch, Ulrich A1 - Frank, Annette A1 - Rancan, Giaime A1 - Gringeri, Concetta V. A1 - Karas, Vincent A1 - Wiesinger, Florian A1 - Menzel, Marion Irene A1 - Schwaiger, Markus A1 - Haase, Axel A1 - Schulte, Rolf F. T1 - Comparison of acquisition schemes for hyperpolarised 13C imaging JF - NMR in Biomedicine UR - https://doi.org/10.1002/nbm.3301 Y1 - 2015 UR - https://doi.org/10.1002/nbm.3301 SN - 1099-1492 SN - 0952-3480 VL - 28 IS - 6 SP - 715 EP - 725 PB - Wiley CY - New York ER -