TY - JOUR A1 - Pirkl, Carolin A1 - Nunez-Gonzalez, Laura A1 - Kofler, Florian A1 - Endt, Sebastian A1 - Grundl, Lioba A1 - Golbabaee, Mohammad A1 - Gómez, Pedro A. A1 - Cencini, Matteo A1 - Buonincontri, Guido A1 - Schulte, Rolf F. A1 - Smits, Marion A1 - Wiestler, Benedikt A1 - Menze, Bjoern H. A1 - Menzel, Marion Irene A1 - Hernandez-Tamames, Juan A. T1 - Accelerated 3D whole-brain T1, T2, and proton density mapping BT - feasibility for clinical glioma MR imaging JF - Neuroradiology N2 - Purpose: Advanced MRI-based biomarkers offer comprehensive and quantitative information for the evaluation and characterization of brain tumors. In this study, we report initial clinical experience in routine glioma imaging with a novel, fully 3D multiparametric quantitative transient-state imaging (QTI) method for tissue characterization based on T1 and T2 values. Methods: To demonstrate the viability of the proposed 3D QTI technique, nine glioma patients (grade II–IV), with a variety of disease states and treatment histories, were included in this study. First, we investigated the feasibility of 3D QTI (6:25 min scan time) for its use in clinical routine imaging, focusing on image reconstruction, parameter estimation, and contrast-weighted image synthesis. Second, for an initial assessment of 3D QTI-based quantitative MR biomarkers, we performed a ROI-based analysis to characterize T1 and T2 components in tumor and peritumoral tissue. Results: The 3D acquisition combined with a compressed sensing reconstruction and neural network-based parameter inference produced parametric maps with high isotropic resolution (1.125 × 1.125 × 1.125 mm3 voxel size) and whole-brain coverage (22.5 × 22.5 × 22.5 cm3 FOV), enabling the synthesis of clinically relevant T1-weighted, T2-weighted, and FLAIR contrasts without any extra scan time. Our study revealed increased T1 and T2 values in tumor and peritumoral regions compared to contralateral white matter, good agreement with healthy volunteer data, and high inter-subject consistency. Conclusion: 3D QTI demonstrated comprehensive tissue assessment of tumor substructures captured in T1 and T2 parameters. Aiming for fast acquisition of quantitative MR biomarkers, 3D QTI has potential to improve disease characterization in brain tumor patients under tight clinical time-constraints. UR - https://doi.org/10.1007/s00234-021-02703-0 KW - MRI KW - Image-based biomarkers KW - Multiparametric imaging KW - Glioma imaging KW - Neural networks Y1 - 2021 UR - https://doi.org/10.1007/s00234-021-02703-0 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13885 VL - 63 IS - 11 SP - 1831 EP - 1851 PB - Springer CY - Berlin ER - TY - CHAP A1 - Hoppe, Frederik A1 - Verdun, Claudio Mayrink A1 - Laus, Hannah A1 - Endt, Sebastian A1 - Menzel, Marion Irene A1 - Krahmer, Felix A1 - Rauhut, Holger ED - Leonardis, Aleš ED - Ricci, Elisa ED - Roth, Stefan ED - Russakovsky, Olga ED - Sattler, Torsten ED - Varol, Gül T1 - Imaging with Confidence: Uncertainty Quantification for High-Dimensional Undersampled MR Images T2 - Computer Vision – ECCV 2024: 18th European Conference, Proceedings, Part LXXVIII UR - https://doi.org/10.1007/978-3-031-73229-4_25 Y1 - 2024 UR - https://doi.org/10.1007/978-3-031-73229-4_25 SN - 978-3-031-73229-4 SP - 432 EP - 450 PB - Springer CY - Cham ER - TY - CHAP A1 - Hoppe, Frederik A1 - Krahmer, Felix A1 - Verdun, Claudio Mayrink A1 - Menzel, Marion Irene A1 - Rauhut, Holger T1 - High-Dimensional Confidence Regions in Sparse MRI T2 - Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) UR - https://doi.org/10.1109/ICASSP49357.2023.10096320 KW - debiased LASSO KW - compressed sensing KW - confidence regions KW - MRI Y1 - 2023 UR - https://doi.org/10.1109/ICASSP49357.2023.10096320 SN - 978-1-7281-6327-7 PB - IEEE CY - Piscataway ER - TY - INPR A1 - Endt, Sebastian A1 - Engel, Maria A1 - Naldi, Emanuele A1 - Assereto, Rodolfo A1 - Molendowska, Malwina A1 - Mueller, Lars A1 - Verdun, Claudio Mayrink A1 - Pirkl, Carolin A1 - Palombo, Marco A1 - Jones, Derek K. A1 - Menzel, Marion Irene T1 - In-vivo myelin water quantification using diffusion-relaxation correlation MRI: a comparison of 1D and 2D methods T2 - Research Square N2 - Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion-recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. While 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion. UR - https://doi.org/10.21203/rs.3.rs-3069146/v1 Y1 - 2023 UR - https://doi.org/10.21203/rs.3.rs-3069146/v1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-46448 SN - 2693-5015 PB - Research Square CY - Durham ER - TY - JOUR A1 - Endt, Sebastian A1 - Engel, Maria A1 - Naldi, Emanuele A1 - Assereto, Rodolfo A1 - Molendowska, Malwina A1 - Mueller, Lars A1 - Verdun, Claudio Mayrink A1 - Pirkl, Carolin A1 - Palombo, Marco A1 - Jones, Derek K. A1 - Menzel, Marion Irene T1 - In Vivo Myelin Water Quantification Using Diffusion–Relaxation Correlation MRI: A Comparison of 1D and 2D Methods JF - Applied Magnetic Resonance N2 - Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion–relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion. UR - https://doi.org/10.1007/s00723-023-01584-1 KW - MWF mapping KW - Microstructure KW - Relaxometry KW - Diffusometry KW - Multi-component KW - Multidimensional KW - Multi-exponential KW - Multiparametric KW - Correlation imaging Y1 - 2023 UR - https://doi.org/10.1007/s00723-023-01584-1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-40317 SN - 0937-9347 SN - 1613-7507 VL - 54 IS - 11-12 SP - 1571 EP - 1588 PB - Springer CY - Wien ER - TY - CHAP A1 - Endt, Sebastian A1 - Pirkl, Carolin A1 - Verdun, Claudio Mayrink A1 - Menze, Bjoern H. A1 - Menzel, Marion Irene ED - Romero, Eduardo ED - Costa, Eduardo Tavares ED - Brieva, Jorge ED - Rittner, Leticia ED - Linguraru, Marius George ED - Lepore, Natasha T1 - Unmixing tissue compartments via deep learning T1-T2-relaxation correlation imaging T2 - 17th International Symposium on Medical Information Processing and Analysis UR - https://doi.org/10.1117/12.2604737 Y1 - 2021 UR - https://doi.org/10.1117/12.2604737 SN - 978-1-5106-5053-4 SN - 978-1-5106-5052-7 PB - SPIE CY - Bellingham ER - TY - JOUR A1 - Sperl, Jonathan I. A1 - Sprenger, Tim A1 - Tan, Ek Tsoon A1 - Menzel, Marion Irene A1 - Hardy, Christopher J. A1 - Marinelli, Luca T1 - Model‐based denoising in diffusion‐weighted imaging using generalized spherical deconvolution JF - Magnetic Resonance in Medicine UR - https://doi.org/10.1002/mrm.26626 Y1 - 2017 UR - https://doi.org/10.1002/mrm.26626 SN - 1522-2594 VL - 78 IS - 6 SP - 2428 EP - 2438 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Feuerecker, Benedikt A1 - Durst, Markus A1 - Michalik, Michael A1 - Schneider, Günter A1 - Saur, Dieter A1 - Menzel, Marion Irene A1 - Schwaiger, Markus A1 - Schilling, Franz T1 - Hyperpolarized 13C Diffusion MRS of Co-Polarized Pyruvate and Fumarate to Measure Lactate Export and Necrosis JF - Journal of Cancer N2 - Background: Non-invasive tumor characterization and monitoring are among the key goals of medical imaging. Using hyperpolarized 13C-labelled metabolic probes fast metabolic pathways can be probed in real-time, providing new opportunities for tumor characterization. In this in vitro study, we investigated whether measurement of apparent diffusion coefficient (ADC) measurements and magnetic resonance spectroscopy (MRS) of co-polarized 13C-labeled pyruvic acid and fumaric acid can non-invasively detect both necrosis and changes in lactate export, which are parameters indicative of tumor aggressiveness. Methods: 13C-labeled pyruvic acid and fumaric acid were co-polarized in a preclinical hyperpolarizer and the dissolved compounds were added to prepared samples of 8932 pancreatic cancer and MCF-7 breast carcinoma cells. Extracellular lactate concentrations and cell viability were measured in separate assays. Results: The mean ratios of the ADC values of lactate and pyruvate (ADClac/ADCpyr) between MCF-7 (0.533 ± 0.015, n = 3) and 8932 pancreatic cancer cells (0.744 ± 0.064, n = 3) showed a statistically significant difference (p = 0.048). 8932 cells had higher extracellular lactate concentrations in the extracellular medium (22.97 ± 2.53 ng/µl) compared with MCF-7 cells (7.52 ± 0.59 ng/µl; p < 0.001). Fumarate-to-malate conversion was only detectable in necrotic cells, thereby allowing clear differentiation between necrotic and viable cells. Conclusion: We provide evidence that MRS of hyperpolarized 13C-labelled pyruvic acid and fumaric acid, with their respective conversions to lactate and malate, are useful for characterization of necrosis and lactate efflux in tumor cells. UR - https://doi.org/10.7150/jca.20250 Y1 - 2017 UR - https://doi.org/10.7150/jca.20250 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-41636 SN - 1837-9664 VL - 8 IS - 15 SP - 3078 EP - 3085 PB - Ivyspring International Publisher CY - Sydney ER - 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 - INPR A1 - Hoppe, Frederik A1 - Krahmer, Felix A1 - Verdun, Claudio Mayrink A1 - Menzel, Marion Irene A1 - Rauhut, Holger T1 - Uncertainty quantification for sparse Fourier recovery UR - https://doi.org/10.48550/arXiv.2212.14864 Y1 - 2022 UR - https://doi.org/10.48550/arXiv.2212.14864 PB - arXiv CY - Ithaca ER -