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Jiaren Zou^1,2, Yuchi Liu³, Jesse Hamilton^2,3, Yun Jiang^2,3, Nicole Seiberlich^2,3, and Yue Cao^1,2,3
1Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, United States, ²Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, ³Department of Radiology, University of Michigan, Ann Arbor, MI, United States

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting

Iterative image reconstruction of highly undersampled high-resolution 3D MR fingerprinting (MRF) is time-consuming and has high memory requirements. In this work, we propose to use stochastic gradient descent to accelerate the reconstruction and reduce the memory footprint. In addition, a conditional invertible neural network is used as a fast and flexible tool for estimating the posterior distribution of tissue properties from MRF. In a simulation study, we achieved an 11-fold and 45.5GB reduction in reconstruction time and memory requirement, respectively, compared with a conventional iterative method. Uncertainty maps of tissue properties derived from the estimated posterior distributions correlate well with reconstruction errors.

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Miha Fuderer¹, Hongyan Liu¹, Oscar van der Heide¹, Cornelis A.T. van den Berg¹, and Alessandro Sbrizzi^1
1Division Imaging and Oncology, University Medical Center Utrecht, Utrecht, Netherlands

Keywords: MR Fingerprinting/Synthetic MR, Relaxometry

We applied optimized phase modulation to the RF sequence in MR-STAT. We observe that applying optimized phase is beneficial towards the accuracy of T1 and T2 maps, particularly under constrained conditions. In particular, when comparing sequences with and without an initial inversion pulse we observe that the difference vanishes when applying optimized RF phase modulation. Thus optimized phase modulation allows to omit the initial inversion pulse. We hypothesize that the same holds for other multi-parametric qMRI techniques such as MRF.

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Yat Lam Wong¹, Tian Li¹, Chenyang Liu¹, Victor Ho Fun Lee², Lai Yin Andy Cheung³, Peng Cao⁴, Edward Sai Kam Hui⁵, and Jing Cai^1
1Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong, ²Department of Clinical Oncology, The University of Hong Kong, Hong Kong, Hong Kong, ³Department of Clinical Oncology, Queen Mary Hospital, Hong Kong, Hong Kong, ⁴Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, ⁵The Chinese University of Hong Kong, Hong Kong, Hong Kong

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting

Time-resolved magnetic resonance fingerprinting (MRF), or 4D-MRF, has demonstrated its feasibility in motion management in radiotherapy (RT). However, the prohibitive long acquisition time is one of challenges of the clinical implementation of 4D-MRF. The shortening of acquisition time may compromise the accuracies of the predicted tissues’ properties. Here, we propose a novel technique to enhance the accuracies of 4D-MRF with shortened acquisition by optimizing T1 and T2 sensitivities through inter-phase data sharing.

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Yoo Jin Lee¹, Peter Koken¹, Kristina Sonnabend^2,3,4, Grischa Bratke^3,4, Annerieke Heuvelink-Marck⁵, and Mariya Doneva^1
1Philips Research, Hamburg, Germany, ²Philips GmbH Market DACH, Hamburg, Germany, ³Faculty of Medicine, University of Cologne, Cologne, Germany, ⁴Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany, ⁵Philips Research, Eindhoven, Netherlands

Keywords: MR Fingerprinting/Synthetic MR, Body, Respiratory motion

MR fingerprinting (MRF) in the abdomen is challenging due to respiratory motion. In this study, as an alternative to a series of extended breath-holds which could be challenging especially for patients, visual and auditive in-bore breathing guidance was used during the MRF scans for better patient comfort. MRF sequences were designed based on predefined breathing patterns such that data are acquired only during exhale holds. The corresponding MRF dictionaries were calculated beforehand to enable real-time matching of quantitative maps. We demonstrate that MRF scans with guided breathing provide comparable abdominal T1 and T2 maps as those with breath-holds.   

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

Keywords: MR Fingerprinting/Synthetic MR, Prostate

Magnetic Resonance Fingerprinting (MRF) enables fast quantitative MR imaging, and represents an opportunity to improve upon the current standard of multi-parametric MRI (mp-MRI). In this work we demonstrate how the MRF pulse sequence can be adapted to include different saturation techniques, whilst retaining accurate T1 and T2 quantification. Extended Phase Graphs (EPGs) of the sequence illustrate the effective spoiling of chemical elements, such as fat, and spatial saturation. Phantom imaging shows that T1 quantification is not significantly affected and T2 quantification remains accurate up to 100ms. As an example, the framework is tested in-vivo in the context of prostate imaging.

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Simran Kukran^1,2, Iulius Dragonu³, Ben Statton^1,4, Jack Allen⁵, Pete Lally^1,6, Rebecca Quest^1,7, Neal Bangerter¹, Dow-Mu Koh², Matthew Orton², and Matthew Grech-Sollars^8
1Imperial College London, London, United Kingdom, ²Institute of Cancer Research, London, United Kingdom, ³Siemens Healthcare Ltd, Frimley, United Kingdom, ⁴London Institute of Medical Sciences, Medical Research Council, London, United Kingdom, ⁵Independent Researcher, Norwich, United Kingdom, ⁶UK Dementia Research Institute Centre for Care Research and Technology, London, United Kingdom, ⁷Imperial College Healthcare NHS Trust, London, United Kingdom, ⁸University College London, London, United Kingdom

Keywords: MR Fingerprinting/Synthetic MR, Magnetization transfer

A fingerprinting sequence was developed with and without off resonance pulses before every TR to investigate MT effects on T1 and T2 values. Off-resonance pulses suppress MT effects by saturating signal from free protons that exchange with bound protons. Observed T2 values increased with off resonance pulses as expected. Observed T1 values decreased, this was an opposite effect to what was observed previously with a different pulse sequence.

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Constantin Slioussarenko¹, Pierre-Yves Baudin¹, and Benjamin Marty^1
1NMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting

We introduce an optimization framework using the longitudinal steady-state equilibrium for FLASH MRF sequences, and taking into account signal noise by using a Monte Carlo method. We use this framework to optimize echo times, flip angles, timings and recovery time for T1_H2O and FF mapping while shortening our original MRF T1-FF sequence. The resulting Fast MRF T1-FF sequence yields comparable estimation results to the original sequence with an almost twice reduced acquisition time.

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Andrew Dupuis¹, Yong Chen¹, Michael Hansen², Kelvin Chow³, Dan Ma¹, Mark Griswold¹, and Rasim Boyacioglu^1
1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ²Microsoft Research, Redmond, WA, United States, ³Siemens Medical Solutions USA, Inc., Chicago, IL, United States

Keywords: MR Fingerprinting/Synthetic MR, Quantitative Imaging, Reproducibility, MNI, Automated, Gadgetron, FIRE

We evaluate the reproducibility of 3D-MRF versus clinical-standard MPRAGE and TSE acquisitions for ten subjects across three acquisition sets on two scanner via a fully-automated registration and regional analysis framework. T1 and T2 quantitative maps from 3D-MRF were found to be highly reproducible (T1+/-4.6%, T2+/-6.3%) across scanners and sessions, with no significant difference between repeating a scan immediately on the same scanner, repeating a scan after repositioning the subject and reshimming, and repeating a scan on a different scanner entirely. The same is not true for MPRAGE (+/-12.4%) or TSE (+/-28.8%) acquisitions.

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Ouri Cohen¹ and Ricardo Otazo^1
1Medical Physics, Memorial Sloan Kettering, New York, NY, United States

Keywords: MR Fingerprinting/Synthetic MR, CEST & MT

CEST MR fingerprinting (CEST-MRF) enables fast quantitative relaxation and exchange mapping. The CEST-MRF signal depends on multiple acquisition and tissue parameters which makes optimization of the acquisition schedule challenging. The goal of this work is to develop a deep learning approach that uses a quantification network and a surrogate network to optimize the acquisition schedule for in vivo scans. Numerical simulations are used to characterize the optimized schedule and the benefits of optimization are demonstrated in vivo in a healthy subject. The optimized schedule can reduce scan time by 12% and provide better image quality than a randomly generated schedule.  

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Sophie Schauman^1,2, Siddharth Iyer^3,4, Xiaozhi Cao^1,2, Quan Chen^1,2, Mahmut Yurt^1,2, Natthanan Ruengchaijatuporn⁵, Congyu Liao^1,2, Greg Zaharchuk¹, and Kawin Setsompop^1,2
1Department of Radiology, Stanford University, Stanford, CA, United States, ²Department of Electrical Engineering, Stanford University, Stanford, CA, United States, ³Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ⁴Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, United States, ⁵Center of Excellence in Computational Molecular Biology, Chulalongkorn University, Bangkok, Thailand

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting

Clinical contrasts can be generated from a 1 min 1 mm isotropic whole brain MRF scan and B0 correction improves it further. We tested this method in healthy volunteers as well as clinical populations.

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Jakob Meineke¹, Christian Wülker¹, Jean Tkach², Usha Nagaraj², Mariya Doneva¹, and Tim Nielsen^1
1Philips Reseach, Hamburg, Germany, ²Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting

A neural network for the estimation and removal of colored noise in non-Cartesian MRI is trained and subsequently applied for denoising coefficient images in MR Fingerprinting. It is shown that the neural network does not introduce bias in the quantitative parameter maps and improves their precision. Invivo T1- and T2-maps are demonstrated to be visually improved.

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Constantin Slioussarenko¹ and Benjamin Marty^1
1NMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France

Keywords: MR Fingerprinting/Synthetic MR, Sparse & Low-Rank Models

We propose an iterative algorithm to remove remaining artefacts of Magnetic Resonance Fingerprinting maps, using projected gradient descent with exact line search and spatial regularization.  We use this framework to denoise 3D MRF T1-FF acquisitions undersampled in the partition direction and show that this allows to reduce undersampling artefacts for the T1_H2O and FF maps after a few iterations.

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Miha Fuderer¹, Oscar van der Heide¹, C.A.T. van den Berg¹, and Alessandro Sbrizzi^1
1Division Imaging and Oncology, University Medical Center Utrecht, Utrecht, Netherlands

Keywords: MR Fingerprinting/Synthetic MR, Relaxometry

In MRF, it has been established – but often ignored – that the presence of diffusion causes bias in the estimated T2. We measure this effect in MR-STAT. Thereby we confirm the theoretical model that the bias is proportional to the square of T2. We also find that the bias level strongly depends on the RF sequence used. This opens the prospect of optimizing sequences on minimal diffusion-induced bias in T2.

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Brendan Eck^1,2, Jeehun Kim^2,3, Mingrui Yang², and Xiaojuan Li^2
1Imaging Institute, Cleveland Clinic, Cleveland, OH, United States, ²Department of Biomedical Engineering, Program of Advanced Musculoskeletal Imaging (PAMI), Cleveland Clinic, Cleveland, OH, United States, ³Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH, United States

Keywords: MR Fingerprinting/Synthetic MR, Quantitative Imaging, T1rho Dispersion

T_1ρ dispersion is a potential biomarker that can characterize chemical exchange or diffusive exchange, complementary to other MR relaxometry parameters (e.g. T₁, T₂). However, T_1ρ dispersion conventionally involves quantification of T_1ρ at multiple spin-lock frequencies, which can require prohibitively long scan times and high radiofrequency pulse energy deposition. MR Fingerprinting (MRF) has been reported for quantification of T_1ρ at a single spin-lock frequency. We propose a framework to enable T_1ρ dispersion MRF data acquisition and reconstruction. We report initial simulation and real-world phantom results that demonstrate the feasibility of this MRF-based T_1ρ dispersion characterization method.

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Raffaella Fiamma Cabini^1,2, Davide Cicolari^2,3, Leonardo Barzaghi^1,4, Paolo Arosio^5,6, Stefano Carrazza^5,6, Silvia Figini^2,7, Marta Filibian^2,8, Marco Peviani⁹, Anna Pichiecchio^4,10, and Alessandro Lascialfari^2,3
1Mathematics, University of Pavia, Pavia, Italy, ²INFN, Istituto Nazionale di Fisica Nucleare, Pavia, Italy, ³Physics, University of Pavia, Pavia, Italy, ⁴Advanced Imaging and Radiomics, Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy, ⁵Physics, University of Milano, Milano, Italy, ⁶INFN, Istituto Nazionale di Fisica Nucleare, Milano, Italy, ⁷Department of Social and Political Science, University of Pavia, Pavia, Italy, ⁸Centro Grandi Strumenti, University of Pavia, Pavia, Italy, ⁹University of Pavia, Pavia, Italy, ¹⁰Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy

Keywords: MR Fingerprinting/Synthetic MR, Data Processing

We proposed a DL method and an automatic hyperparameters optimization strategy to reconstruct T₁ and T₂ maps acquired with two Magnetic Resonance Fingerprinting (MRF) sequences. The model was trained and validated on a preclinical MRF dataset and tested on an independent test set. Through a lower number of MRF images and a lower k-space sampling percentage than the standard post-processing, the DL-based method and the automatic hyperparameters optimization strategy deliver parametric maps with similar accuracy as the dictionary-based methodology. 

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Di Cui¹, Xiaoxi Liu¹, Peder E.Z. Larson¹, and Duan Xu^1
1University of California, San Francisco, San Francisco, CA, United States

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting

A 2D EPI based MRF acquisition and reconstruction method was developed in this study. A shuffled acquisition order and pseudo-randomized sampling pattern was designed for 2D k-space and compressed time-resolved reconstruction was utilized for faster reconstruction. T₁ T₂ T₂* were simultaneously quantified, B₀, B₁+ and proton density maps are generated.

Yifan Guo¹, Lixian Zou², Congcong Liu², Fanshi Li², Yanjie Zhu², Xin Liu², Hairong Zheng², Dong Liang², and Haifeng Wang^2
1Research Center for Medical AI, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, ²Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Keywords: MR Fingerprinting/Synthetic MR, MR Fingerprinting

Spiral-based MR fingerprinting (MRF) is an efficient T1 and T2 quantification technique for simultaneous measurement of tissue properties. Affected by the artifacts caused by the B0 eddy currents effects at 5T, a system response eddy current correction strategy is proposed to mitigate the blurring and artifacts of the MRF Spiral. The results of in vivo experiments on the head and abdomen showed that our approach to correct the artifacts caused by the B0 eddy currents was effective.

Yawen Liu¹, Pengling Ren², Hongxia Yin³, Yi Zhu⁴, Rong Wei⁵, Tingting Zhang², Zuofeng Zheng⁶, and Zhenchang Wang^1,2
1School of Biological Science and Medical Engineering, Beihang University, Beijing, China, ²Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China, ³Department of Medical Engineering, Beijing Friendship Hospital, Capital Medical University, Beijing, China, ⁴Philips Healthcare, Beijing, China, ⁵Peking university Academy for Advanced Interdisciplinary Studies, Beijing, China, ⁶Beijing ChuiYangLiu Hospital, Beijing, China

Keywords: MR Fingerprinting/Synthetic MR, Image Reconstruction

Quantitative magnetic resonance imaging (qMRI) can reflect the inherent characteristics of human tissue of relaxation time and proton density, and has important value for clinical diagnostic. However, long scan times limit the use of qMRI. We propose a method to optimize fast qMRI using a super-resolution generative adversarial network, thereby reducing scan time and obtaining accurate quantitative values. The results showed that this method was able to improve the image quality of qMRI, and the quantitative values were not significantly different from those obtained in conventional acquisitions.

Luxi Yang¹, Wenhua Wang¹, Yunwen Chen¹, Miaoqi Zhang², Lisha Nie ², Xiao Zhang¹, and Zhihua Pan^1
1416 Hospital of Nuclear Industry, Chengdu, China, ²GE Healthcare, MR Research, Beijing, China

Keywords: Quantitative Imaging, Head & Neck/ENT

In this study, we aim to investigate the performance of quantitative measurements from synthetic MRI in predicting the disease activity of Graves’ ophthalmopathy (GO).  40 patients with different Clinical Activity Scores are investigated. We found a trend that the muscles’ T1, T2 and PD values increased with increasing CAS level, spatially for T2 values. Furthermore, fact that T2 escalation in ‘inactive’ CAS groups compared with healthy controls, indicate CAS staging may underestimate disease activity. We conclude that synthetic MRI have potential to predict clinical activity of GO, and T2 value has the highest diagnostic efficiency.

Hailei Gu¹, Weiqiang Dou², and Wenwei Tang^1
1Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China, ²GE Healthcare, MR Research China, Beijing, China

Keywords: Data Analysis, Cancer

This study aimed to investigate whether synthetic-MRI can diagnose endometrial carcinoma (EC). 116 patients were recruited, including submucous myomas(SM),endometrial hyperplasia and endometrial polyps(EH&EP) and EC. Synthetic MRI derived T1, T2 and proton density(PD) mapping were obtained for each patient. Significantly different T1 and T2 were shown between EC and SM, and the optimal diagnostic efficacy was for T1+T2 with AUC of 0.865 . T2 and PD were also different between EC and EH&EP. The corresponding optimal diagnostic efficacy was for T2+PD with AUC of 0.690. With these findings, synthetic-MRI may thus be effective in differentiating EC from other intrauterine diseases.