Alison Roth¹, Yongsheng Chen², Jun Li^2,3, and Richard D. Dortch^1,4,5
1Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States, ²Department of Neurology, Wayne State University, Detroit, MI, United States, ³Department of Neurology, Vanderbilt University, Nashville, TN, United States, ⁴Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States, ⁵Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States

Magnetization transfer (MT) can be quantified as the MT ratio (MTR), MT saturation (MTsat), and quantitative MT (qMT) pool-size-ratio (PSR). MTR is a promising peripheral nerve imaging biomarker in inherited neuropathies but has lower pathological specificity compared to MTsat and PSR. Here, MTR and MTsat metrics are compared to PSR. Eighteen subjects received 16 qMT scans, five T₁-weighted scans, and the B₀ and B₁ fields were measured. Mean MTR, MTsat, and PSR were extracted from the sciatic nerve. MTR had the highest SNR (median>15.76) and scan-rescan repeatability (ICC=0.93, CV=4.6%), whereas MTsat had the strongest correlation to PSR (r=0.94, p<0.001).

Hendrik Mattern¹, Frank Angenstein², Christian Mawrin³, and Valentina Perosa^2,4,5
1Biomedical Magnetic Resonance, Otto von Guericke University, Magdeburg, Germany, ²German Center for Neurodegenerative Disease, Magdeburg, Germany, ³Institute of Neuropathology, Medical Faculty at the Otto von Guericke University, Magdeburg, Germany, ⁴J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, United States, ⁵Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany

In this proof-of-principle study, an image acquisition and processing pipeline was developed to assess the cortical vasculature and its surrounding tissue. To that end, a block of human brain, which included cortex and juxtacortical white matter, was scanned post-mortem at high resolution with a multi-echo GRE sequence at 9.4T. Subsequently, R2* and vessel distance maps (VDM) were computed and their layer-specific patterns analyzed.

MungSoo Kang^1,2, Yan Wen³, Michael Carl³, Gerald G. Behr⁴, Ricardo Otazo^1,4, and Youngwook Kee^1
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ²Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Korea, Republic of, ³GE Healthcare, Waukesha, WI, United States, ⁴Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States

Respiratory motion is one of the major factors hindering accurate R₂^* mapping for hepatic iron quantification. In this work, motion-resolved 3D multi-echo UTE cones MRI with pseudo-random view ordering was implemented for motion-robust and free-breathing R₂^* mapping of hepatic iron. Compared to conventional gridding reconstruction, motion-resolved reconstruction reduced the overestimation of R₂^* induced by respiratory motion artifacts, enabling an accurate measurement of R₂^*. 3D multi-echo UTE cones MRI with motion-resolved reconstruction demonstrated the feasibility of accurate free-breathing R₂^* mapping for hepatic iron quantification. 

Aniket Tolpadi^1,2, Francesco Calivà¹, Misung Han¹, Valentina Pedoia¹, and Sharmila Majumdar^1
1Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States, ²Bioengineering, University of California, Berkeley, Berkeley, CA, United States

Compositional MRI (cMRI) offers sensitivity to biochemical changes that can precede morphological changes in tissues and offer quantitative assessments of musculoskeletal tissue health but suffer from long scan times. We present a recurrent encoder-decoder architecture that predicts ground truth T₂ maps from spatially undersampled echo images. Reconstructed maps showed strong fidelity to ground truth in lumbar spine IVDs and knee and hip knee cartilage. Reconstruction errors were below clinically significant T₂ changes through R=12 in the knee and lumbar spine and R=8 in the hip. This work marks progress towards a clinical pipeline that reduces cMRI acquisition time.

Andreia S Gaspar¹, Nuno A Silva², and Rita G Nunes^1
1Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal, ²Hospital da Luz Learning Health, Luz Saúde, Lisbon, Portugal

Clinical myocardial T1 mapping protocols typically acquire three 2D slices, each obtained in a separate breath-hold; this is only feasible in patients able to do sequential breath-holds. We propose SMS-ProMyoT1 which integrates simultaneous multi-slice (SMS) with open-source ProMyoT1, previously implemented with Pulseq, to obtain all slices in a fast single shot. SMS-ProMyoT1 differs from previous implementations by combining blip-bSSFP with VERSE-multiband for RF modulation, and auto-calibrated blip patterns for a fast self-contained sequence. The method was successfully applied both in a reference phantom and in-vivo.

Davide Cicolari¹, Domenico Lizio², Patrizia Pedrotti³, Monica Teresa Moioli², Alessandro Lascialfari¹, Manuel Mariani¹, and Alberto Torresin^2,4
1Department of Physics, University of Pavia, Pavia, Italy, ²Department of Medical Physics, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy, ³Department of Cardiology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy, ⁴Department of Physics, University of Milan, Milan, Italy

In this work we tested the feasibility of MRI relaxation time maps recalibration by employing an in-scan reference system. This ‘belt phantom’ was characterized through NMR standard spectroscopic technique. Scan-dependent recalibrations of the relaxation time maps could be performed relying on the ground-truth NMR values of the phantom, aiming to clinical intra- and inter-center harmonization. The in-scan reference phantom allowed also, together with the analysis of the standard deviation maps (measured as the 68% confidence bound of the fitted relaxation time value), to evaluate the reliability of the maps and the applicability of the recalibration.

Maik Rothe¹, Andreas Deistung¹, Richard Brill¹, Walter Alexander Wohlgemuth¹, and Alexander Gussew^1
1University clinic and policlinic for Radiology, University Hospital Halle (Saale), Halle (Saale), Germany

In this study we present a 3D high resolution method for fast in vivo T₁ and T₂^* mapping of fast relaxating tissues of the knee. All experiments were performed using a prototypical 3D spoiled gradient echo ultrashort echo time sequence with stack of spirals readout. T₁ and T₂^* values of the mapping technique were validated by reference methods and literature values and showed good agreement for fast T₁ and T₂^* values. The mapping technique enables T₁ and T₂^* quantitation of fast relaxating tissues in a clinically appropriate measurement time of 9 minutes with a submillimeter spatial resolution (0.8mmx0.8mmx0.8mm).

Pierre-Yves Baudin^1,2, Ericky Caldas de Almeida Araujo^1,2, Harmen Reyngoudt^1,2, and Benjamin Marty^1,2
1NMR Laboratory, Institute of Myology, Neuromuscular Investigation Center, Paris, France, ²NMR Laboratory, CEA, DRF, IBFJ, MIRCen, Paris, France

In order to improve the reliability of the muscle T2 as a clinical outcome in clinical studies of neuromuscular disorders, we investigate the accuracy of the fat signal modeling in transverse relaxometry from multi-spin echo imaging. A new approach for muscle T2/fat-fraction mapping is proposed, combining a water signal dictionary with water T2/B1-dependent entries created from EPG simulations, and a hybrid Gaussian Locally Linear Mapping (hGLLiM) to provide B1-dependent fat signals. Preliminary results on a dataset of healthy controls, DMD and IBM patients are consistent with common knowledge, but interesting divergences are found when compared to another recent approach.

Yi-Chun Wang^1,2, Faezeh Sanaei-Nezhad¹, Joao Peixoto¹, Carolina Fernandes¹, Alex Smith¹, Matthew Robson¹, and Rajarshi Banerjee^1
1Perspectum Ltd., Oxford, United Kingdom, ²University of Oxford, Oxford, United Kingdom

Pineapple juice (PJ) is used in Magnetic Resonance Cholangiopancreatography to suppress gastrointestinal tract signals. To explore how PJ affects multiparametric liver MRI, 30 participants underwent scans before and after ingesting PJ. Image data were analysed with LiverMultiScan (yielding iron corrected T1 (cT1), iron, and PDFF) and statistically compared. The changes post PJ administration were statistically significant for cT1 at both 1.5T and 3T but not for iron and PDFF. However, the repeatability analysis indicates the post PJ administration cT1 changes were smaller than the repeatability limits of agreement, suggesting that PJ has neglect-able clinical effect on multiparametric liver MRI.

Yong Chen¹, Rasim Boyacioglu¹, Gamage Sugandima Nishadi Weragoda², Michael Martens², Chaitra Badve^1,3, and Mark Griswold^1
1Radiology, Case Western Reserve University, Cleveland, OH, United States, ²Physics, Case Western Reserve University, Cleveland, OH, United States, ³Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, United States

In this study, we introduced a new deep learning method to take advantage of both radiologists’ expertise and multi-parametric MR Fingerprinting data to improve annotation accuracy in MRI dataset. A U-Net based convolutional neural network was adopted and each dataset was evaluated multiple times using different combinations of training dataset. Our initial results obtained from a brain tumor dataset demonstrates that the developed method could effectively identify mislabeled tissues and improve annotation accuracy.

Christopher D Rowley^1,2, Ilana R. Leppert¹, Jennifer S.W. Campbell¹, Mark C. Nelson¹, G Bruce Pike³, and Christine L Tardif^1,2,4
1McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada, ²Neurology and Neurosurgery, McGill University, Montreal, QC, Canada, ³Hotchkiss Brain Institute and Departments of Radiology and Clinical Neuroscience, University of Calgary, Calgary, AB, Canada, ⁴Biomedical Engineering, McGill University, Montreal, QC, Canada

In this study we investigate the use of MP2RAGE derived M₀ and T₁ maps for use in MT_sat imaging. These values are compared against maps calculated from the traditional VFA approach. Additionally, the MP2RAGE approach is evaluated with and without sparse sampling and compressed sensing reconstruction. We show that VFA produces elevated T₁ values, and consequently lower MT_sat compared to MP2RAGE approaches. A model-based ΔB₁⁺ correction was able to remove the dependence of MT_sat on ΔB₁⁺. The sparse MP2RAGE provided high quality maps, leading to a full MT_sat protocol that was 32% faster than the traditional approach.

Ting Gong¹, Merlin J. Fair², Kawin Setsompop^2,3, and Hui Zhang^1
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, ²Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA, United States, ³Department of Electrical Engineering, Stanford University, Stanford, CA, United States

Inspired by recent developments in combined relaxometry-diffusion imaging and growing interests in T2* imaging, this study achieves simultaneous compartmental T2 and T2* mapping for the first time. We take advantage of the recently developed diffusion-PEPTIDE imaging technique, which allows for efficient acquisition of diffusion datasets with varying T2/T2* contrast. A relaxometry-diffusion combined microstructure model and a robust multi-stage fitting approach are developed to enable compartmental T2 and T2* mapping. This technique could be a new tool for future neuroimaging studies benefiting from quantification of T2-T2*-diffusion, such as studying iron content related development and pathology.

Hongyan Liu¹, Oscar van den Heide¹, Miha Fuderer¹, Cornelis A.T. van den Berg¹, and Alessandro Sbrizzi^1
1Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, UMC Utrecht, Utrecht, Netherlands

MR-STAT is a framework for simultaneous mapping of quantitative MR parameters from single short scans. In this work, we extend the current 2D Cartesian MR-STAT sequence to 3D acquisitions, in order to achieve higher SNR and isotropic resolution with a scan lasting few minutes. In particular, we implement a prototype 3D MR-STAT sequence for whole brain coverage with  isotropic resolution, and test it on gel phantom and in-vivo brain data. Acceleration strategy of the 3D sequence is proposed, and the corresponding retrospective undersampling of the measured in-vivo data is reconstructed.

Gabriele Bonanno^1,2,3, José P. Marques⁴, Tobias Kober^5,6,7, and Tom Hilbert^5,6,7
1Siemens Healthcare AG, Bern, Switzerland, ²Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland, ³Translational Imaging Center, sitem-insel, Bern, Switzerland, ⁴Donders Institute for Brain Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, ⁵Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, ⁶Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, ⁷LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

T₁ and T₂ relaxometry provide important quantitative information and can serve as imaging biomarkers thanks to their sensitivity to pathology. However, quantitative imaging requires long scan times for high-resolution whole-brain coverage. Magnetization-prepared approaches combined with fast sequences allow for high isotropic resolution, but they are often biased due to other relaxation mechanisms than the one being probed. To account for this effect, we introduce QuantoRAGE: a new method that uses a T₂-prepared inversion within an accelerated MP2RAGE sequence for simultaneous T₁ and T₂ mapping. Preliminary tests demonstrate the feasibility to obtain high-resolution simultaneous T₁ and T₂ relaxometry at 3T.

Vincenzo Anania^1,2, Ben Jeurissen^1,3, Jan Morez¹, Annemieke E. Buikema¹, Thibo Billiet², Jan Sijbers^1,3, and Arnold J. den Dekker^1,3
1imec-Vision Lab, Dept. of Physics, University of Antwerp, Antwerp, Belgium, ²icometrix, Leuven, Belgium, ³µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium

Fitting the diffusion kurtosis imaging free water elimination model (DKI-FWE) to diffusion MRI data represents an ill-conditioned problem. Fortunately, the conditioning of the model fitting can be improved by explicitly modeling the T2 relaxation dependency of the signal. As a benefit, diffusion and kurtosis metrics robust to partial volume effects can be estimated with conventional techniques. In this work, we use Cramér-Rao lower bound (CRLB) theory to identify optimal acquisition settings that maximize the precision of the model parameter estimates.