Ulrich Katscher¹, Bjoern Steinhorst¹, Jakob Meineke¹, and Jochen Keupp^1
1Philips Research, Hamburg, Germany

Double-echo steady-state (DESS) sequences are a promising candidate for diffusion weighted imaging (DWI) free of geometric distortions. The design of diffusion-weighted DESS (dwDESS) sequences allows waveform variations for the diffusion weighting gradient G_D. While dwDESS sequences were originally introduced with unipolar G_D, also bipolar or higher order G_D are possible. A balanced G_D (i.e., with nulling zeroth momentum) typically necessitates a spoiler gradient to suppress banding artefacts, which additionally increases the degrees of freedom in the design of dwDESS sequences. This study explores different dwDESS sequence variants according to predefined optimization criteria.

Elizabeth Huaroc Moquillaza¹, Manuel Baumann², Kilian Weiss³, Thomas Amthor², Peter Koken², Benedikt Schwaiger⁴, Markus R. Makowski¹, Mariya Doneva², and Dimitrios C. Karampinos^1
1Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany, ²Philips Research Lab, Hamburg, Germany, ³Philips Healthcare, Hamburg, Germany, ⁴Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany

Dixon Magnetic Resonance Fingerprinting (Dixon-MRF) is being increasingly used to measure multiple quantitative parameters with effective fat suppression across body tissues. Dixon-MRF processing is typically performed in two steps: water-fat separation and dictionary matching. The present work introduces a versatile formulation for chemical species separation in Dixon-MRF (CSS-MRF) which allows to process a multi-echo fingerprint in a single step obtaining a water fingerprint, a fat fingerprint, a B₀ value and a R₂* value as outputs. CSS-MRF allows an easy and flexible definition of the parameters to be estimated and enables the option of a varying fat spectrum across the MRF-dimension.

Thomas Kluge¹, Mathias Nittka¹, Stephan Kannengiesser¹, Gregor Koerzdoerfer¹, Christina Grund¹, Guido Buonincontri², Jianing Pang³, Rasim Boyacioglu⁴, Yong Chen⁴, and Mark Griswold^4
1Siemens Healthcare GmbH, Erlangen, Germany, ²Siemens Healthcare s.r.l, Milan, Italy, ³Siemens Medical Solutions USA Inc., Chicago, IL, United States, ⁴Department of Radiology, Case Western Reserve University, Cleveland, OH, United States

Magnetic Resonance Fingerprinting (MRF), as an approach for multi-parametric, quantitative imaging, imposes new paradigms for sequence design in terms of optimized signal encoding and dictionary matching. In this work, we present a novel comprehensive framework and tool chain for rapid and efficient MRF prototyping. Key concepts are modularization and abstraction of the MRF experiment related to spin-physics, spatial encoding, and scanner hardware.

Antoine Klauser^1,2, Bernhard Strasser³, Wolfgang Bogner³, Lukas Hingerl³, Claudiu Schirda⁴, Bijaya Thapa⁵, Daniel Cahill⁶, Tracy Batchelor⁷, Francois Lazeyras¹, and Ovidiu Andronesi^5
1University of Geneva, Geneva, Switzerland, ²CIBM Center for Biomedical Imaging, Geneva, Switzerland, ³Medical University of Vienna, Vienna, Austria, ⁴University of Pittsburgh Medical Center, Pittsburgh, PA, United States, ⁵Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, United States, ⁶Massachusetts General Hospital, Boston, MA, United States, ⁷Brigham and Women Hospital, Boston, Switzerland

MR spectroscopic imaging (MRSI) can map specific metabolic alterations of glioma brain tumors. Increasing structural details for spatial distribution of metabolites is needed to probe tumor margins and heterogeneity with higher sensitivity and specificity. Here we evaluate the performance of ECCENTRIC, a newly developed non-Cartesian compressed sense MRSI method, to realize fast and high-resolution metabolic imaging at 7T ultra-high field in glioma patients. This is expected to improve diagnosis, prognostication, planning, guidance, and response assessment of treatment in glioma patients and other brain diseases.

Antoine Klauser^1,2, Bernhard Strasser³, Wolfgang Bogner³, Bijaya Thapa⁴, Jorg Dietrich⁵, Erik Uhlmann⁵, Tracy Batchelor⁶, Daniel Cahill⁵, Francois Lazeyras^1,2, and Ovidiu Andronesi^4
1University of Geneva, Geneva, Switzerland, ²CIBM Center for Biomedical Imaging, Geneva, Switzerland, ³Medical University of Vienna, Vienna, Austria, ⁴Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, United States, ⁵Massachusetts General Hospital, Boston, MA, United States, ⁶Brigham and Women Hospital, Boston, MA, United States

Metabolic alterations specific to glioma can be imaged by MR spectroscopic imaging (MRSI). Adiabatic spin-echo (ASE) MRSI enables spectral editing for specific metabolites with uniform excitation over whole-brain but needs long TR at 7T due to specific absorption rate which results in long acquisition times for high spatial resolution. Acceleration of ASE can be obtained with non-cartesian compressed sense MRSI (ECCENTRIC) acquisition. Here we evaluate the performance of ASE-ECCENTRIC metabolic imaging in glioma patients. We expect that enhanced spectral sensitivity, specificity and high spatial resolution of ASE-ECCENTRIC will improve diagnosis, prognostication, and treatment response monitoring in glioma patients.

Michael van Rijssel¹, Cornelis van den Berg¹, Stan Noordman¹, and Astrid van Lier^1
1Radiotherapy, UMC Utrecht, Utrecht, Netherlands

Banding artifacts in balanced steady state free precession images can be resolved by applying radiofrequency phase cycling. Unfortunately, the scan time increases linearly with the amount of phase cycles acquired, hindering clinical adoption of this sequence. We aimed to reduce the amount of phase cycles that need to be acquired by employing a signal model in an iterative reconstruction. Preliminary validation of this algorithm was performed in-silico and in a phantom. Results show excellent agreement in-silico (relative mean absolute error, RMAE, 0.0045%) and in phantom tubes with T₁ and T₂ values in the physiological range (RMAE 3-4%).

Siyuan Hu¹, Debra McGivney¹, Mark Griswold², and Dan Ma^1
1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ²Radiology, Case Western Reserve University, Cleveland, OH, United States

The MRF framework has been recently investigated to estimate T1, T2 and apparent diffusion coefficient (ADC) from a single scan with b-tensor encoding schemes. However, the current human-designed experiment protocol for multi-dimensional MRF is still subject to limited measurement accuracy. Here we propose to adapt the Cramer-Rao Bounds to optimize multi-dimensional MRF scan for simultaneous quantification of relaxation and diffusion. The optimization framework explores all possible combinations of MRF sequence parameters, including flip angles, TRs, b-values, and preparation modules to seek the optimal tissue parameter encoding scheme. The optimized sequence simultaneously improves the measurement precision of T1, T2 and ADC.