Brendan L. Eck¹, Jeehun Kim², Mingrui Yang², Dan Ma³, Mark A. Griswold^3,4, and Xiaojuan Li^2,3
1Imaging Institute, Cleveland Clinic, Cleveland, OH, United States, ²Biomedical Engineering, Cleveland Clinic, Cleveland, OH, United States, ³Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ⁴Department of Radiology, Case Western Reserve University, Cleveland, OH, United States

Magnetic resonance fingerprinting offers a promising framework by which to rapidly quantify T_1rho relaxation alongside other tissue properties such as T₁ and T₂. However, T_1rho-MRF has only recently been reported and sequence optimization remains under-explored, particularly for 3D sequences. Using a digital phantom constructed from real knee tissue property maps, we investigate sequence parameters for a 3D Cartesian T_1rho-MRF sequence including preparation pulse scheduling and timing, flip angles, number of readouts, and acceleration factor. T₁, T₂, and T_1rho quantification errors in cartilage and skeletal muscle were evaluated.

Giovanni Vito Spinelli¹, Leonardo Brizi^1,2, Marco Barbieri³, Fabiana Zama⁴, Germana Landi⁴, Villiam Bortolotti⁵, Daniel Remondini^1,2, and Claudia Testa^1,2
1Department of Physics and Astronomy "Augusto Righi", University of Bologna, Bologna, Italy, ²INFN, Istituto Nazionale di Fisica Nucleare, Sezione di Bologna, Bologna, Italy, ³Department of Radiology, Stanford University, Stanford, CA, United States, ⁴Department of Mathematics, University of Bologna, Bologna, Italy, ⁵Department of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, Bologna, Italy

A novel application of Magnetic Resonance Fingerprinting (MRF) on low-field NMR is presented. To successfully implement MRF, the correlation between the static and the radio-frequency fields has to be measured, because the evolution of the signal cannot be analyzed without accounting for magnetic fields inhomogeneities. Experimental results have been validated by simulations and compared using the RMSE. This preparatory evaluation allows the use of MRF for NMR parameters quantification. Then, an artificial intelligence approach for parameters reconstruction has been used to overcome the limitation of the standard dictionary approaches when several parameters have to be estimated.

Thomas Coudert¹, Aurélien Delphin¹, Jan M Warnking¹, Benjamin Lemasson^1,2, Emmanuel Luc Barbier¹, and Thomas Christen^1
1Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, GIN, Grenoble, France, ²MoGlimaging Network, HTE Program of the French Cancer Plan, Toulouse, France

We propose to use numerical simulations and Monte Carlo approaches to test 40 MR fingerprinting sequences for their ability to quantify the BOLD effect and provide maps of baseline blood oxygen saturation without the need for contrast agent injection. Our results suggest that several sequences can produce SO2 maps with less that 3% error on average even in the presence of B1 and B0 inhomogeneities. T2 and blood vessel radius could also be estimated with the same acquisitions.

Aurélien Delphin¹, Fabien Boux^1,2, Clément Brossard^1,3, Jan M Warnking¹, Benjamin Lemasson^1,3, Emmanuel Luc Barbier¹, and Thomas Christen^1
1Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, GIN, 38000, Grenoble, France, ²Univ. Grenoble Alpes, Inria, CNRS, G-INP, 38000, Grenoble, France, ³MoGlimaging Network, HTE Program of the French Cancer Plan, Toulouse, France

MR vascular fingerprinting aims at mapping cerebral vascular properties such as blood volume and blood oxygenation. We propose to improve the technique by generating dictionaries based on 3D vascular networks segmented from whole brain high-resolution (3 µm isotropic) microscopy datasets. In order to compensate for the limited number of available data and long computing times, we used a machine-learning reconstruction process to generalize our results and tested our approach in healthy, stroke and tumor animal models. Our results show high quality maps with expected contrast and baseline values in healthy animals as well as expected trends in pathological tissues.

Manuel Baumann¹, Jochen Keupp¹, Peter Mazurkewitz¹, Peter Koken¹, Kay Nehrke¹, Jakob Meineke¹, Thomas Amthor¹, and Mariya Doneva^1
1Philips Research Europe, Hamburg, Germany

We present an efficient MR Fingerprinting (MRF) protocol for prostate imaging at 3T. Full prostate coverage is achieved in 04:20 min with no considerable reconstruction latency. Dixon-MRF has been implemented in the scanner software and combined with a B₁⁺ DREAM scan in a fully-integrated B1-corrected MRF reconstruction. Furthermore, flow compensation is included to suppress artifacts caused by blood flow in large vessels. The proposed prostate MRF protocol has been evaluated in six healthy volunteers.

Christopher George Trimble¹, Kaia Sørland¹, Elise Sandsmark², Mattijs Elschot^1,2, Tone F. Bathen^1,2, and Martijn A. Cloos^3
1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway, ²Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, Norway, ³Centre for Advanced Imaging, University of Queensland, Brisbane, Australia

Magnetic Resonance Fingerprinting (MRF) enables fast quantitative MR imaging, which is appealing in prostate cancer diagnostics. In pelvic MR Fingerprinting, blood flow in the femoral vessels causes strong streak-like artefacts when a radial sampling strategy is used. Here we develop a strategy to incorporate saturation bands into MRF sequences. Our phantom study shows quantification of areas outside the saturation band are not significantly affected. Meanwhile, qualitative analysis of in vivo experiments indicates a marked reduction in streak intensity when saturation is applied.

Rasim Boyacioglu¹, Sherry Huang², Debra McGivney², Yong Chen¹, and Mark A Griswold^1
1Radiology, Case Western Reserve University, Cleveland, OH, United States, ²Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States

This study presents an optimization tool to investigate and validate the effects of MR sequence modules on MR Fingerprinting. Dictionary variance across the tissue property dimension can predict the outcome of a given change in an MRF sequence. An MRF sequence variant is optimized by varying three typical MRF sequence blocks of FA pattern, RF phase and inversion pulses. The observations from the dictionary variance align with in vivo data results.

John T. Lundstrom^1,2, Megan E. Poorman³, Andrew Dienstfrey⁴, and Kathryn E. Keenan^3
1Department of Physics, University of Colorado, Boulder, CO, United States, ²Associate of the National Institute of Standards and Technology, Boulder, CO, United States, ³Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, CO, United States, ⁴Information Technology Laboratory, National Institute of Standards and Technology, Boulder, CO, United States

We investigate non-linear optimization to produce quantitative parameter maps in MR Fingerprinting. Our Monte Carlo analysis shows non-linear optimization to be robust with respect to noise. We also find non-linear optimization to yield consistent results when initialized by dictionary matching using either sparse or densely populated dictionaries. Our research outcomes suggest non-linear optimization is an effective enhancement to the MR Fingerprinting pipeline, allowing for smaller dictionary sizes and more accurate parameter retrieval. Future work will include enhancements to, and analysis of, the computational efficiency of non-linear optimization.

Gregory J. Wheeler¹, Quimby N. Lee², Mary Kate Manhard³, Berkin Bilgic⁴, and Audrey P. Fan^1,2
1Biomedical Engineering, University of California Davis, Davis, CA, United States, ²Neurology, University of California Davis, Davis, CA, United States, ³Radiology, Cincinnati Children's Hospital, Cincinnati, OH, United States, ⁴Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States

Vascular magnetic resonance fingerprinting (vMRF) using both magnitude and phase information can achieve reasonable vascular parameter maps of the brain without contrast agents. This approach combined with a rapid, multi-echo pulse sequence enables dynamic vascular function mapping of brain physiology. Here we begin to investigate the feasibility and tradeoffs of performing vMRF with only 5 echoes and a temporal resolution of 5 seconds. Initial findings indicate that reasonable fingerprint matching can be done with only 5 echoes and that the proposed sequence has adequate signal-to-noise ratio for reliable results.

Simran Kukran^1,2, Iulius Dragonu³, Ben Statton⁴, Jack Allen⁵, Pete Lally⁶, Rebecca Quest^7,8, Neal Bangerter⁷, Dow-Mu Koh^9,10, Matthew Orton^10,11, and Matthew Grech-Sollars^1,12
1Surgery and Cancer, Imperial College London, London, United Kingdom, ²Radiotherapy and Imaging, Institute of Cancer Research, LONDON, United Kingdom, ³Research and Collaborations GB&I, Siemens Healthcare Ltd, Frimley, United Kingdom, ⁴London Institute of Medical Sciences,Medical Research Council, Imperial College London, London, United Kingdom, ⁵National Heart and Lung Institute, Imperial College London, London, United Kingdom, ⁶Brain Sciences, Imperial College London, London, United Kingdom, ⁷Department of Bioengineering, Imperial College London, London, United Kingdom, ⁸Department of Imaging, Imperial College Healthcare NHS Trust, London, United Kingdom, ⁹Department of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom, ¹⁰Department of Radiology, Royal Marsden Hospital, London, United Kingdom, ¹¹Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom, ¹²Department of Medical Physics, Royal Surrey NHS Trust, London, United Kingdom

Previous work has shown an inherent bias in quantitative T1 values for current standard MRF techniques as compared to gold standard methods. In our study we show how magnetisation transfer effects are a component of this bias and that the introduction of off-resonance pulses within an MRF sequence may mitigate these effects.

Martijn Nagtegaal¹, Laura Nunez-Gonzalez², Dirk Poot², Jeroen de Bresser³, Thijs van Osch⁴, Juan Hernandez Tamames², and Frans Vos^1,2
1Imaging Physics, Delft University of Technology, Delft, Netherlands, ²Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands, ³Department of Radiology, Leiden University Medical Centre, Leiden, Netherlands, ⁴C.J. Gorter Center for High Field MRI, Radiology Department, Leiden University Medical Centre, Leiden, Netherlands

Multi-component MR Fingerprinting estimations with Sparsity Promoting Iterative Joint Non-negative least squares (SPIJN-MRF) provide the possibility to obtain partial volume tissue segmentations and myelin water maps. We evaluated the accuracy and repeatability of SPIJN-MRF estimations in simulations and 5 subjects, scanned 8 times. The obtained segmentations were compared to segmentations from SPM12 and FSL. In simulations, SPIJN-MRF showed the highest accuracy in total volume and voxel-wise measures. In vivo, higher variation was observed with SPIJN-MRF than with SPM12 and FSL, especially in WM and GM. In conclusion, SPIJN-MRF provides accurate and precise tissue relaxation parameter estimations with partial volume estimations.

Victoria Y Yu¹, Ouri Cohen¹, Can Wu¹, Ergys Subashi¹, Manuel Baumann², Peter Koken², Mariya Doneva², Michael Zelefsky³, Laura Cervino¹, and Ricardo Otazo^1
1Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ²Philips Research, Hamburg, Germany, ³Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States

The application of MR fingerprinting in the prostate is challenging due to the presence of image distortions produced by B0 inhomogeneities. This works presents the combination of radial sampling to minimize the effects of B0 inhomogeneity and temporal subspace reconstruction to accelerate the acquisition for fast distortionless T1 and T2 mapping in the prostate in less than 4 minutes.