Ingo Hermann^1,2, Jorge Chacon-Caldera¹, Irène Brumer¹, Sebastian Weingärtner², Lothar R. Schad¹, and Frank G. Zöllner^1
1Computer Assisted Clinical Medicine, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany, ²Magnetic Resonance Systems Lab, Department of Imaging Physics, Delft University of Technology, Delft, Netherlands

We implemented and validated a MRF sequence for simultaneous T₁ and T₂* quantification in the kidneys covering 4 slices within one breath-hold. Therefore, we used an echo-planar-imaging readout with fully sampled k-space and 35 measuremets for the matching process. We achieved promising results in phantom and in 8 healthy volunteers compared with conventional methods as MOLLI and GRE and with reference scans. Additionally, we performed smoothing on the baseline images to further improve the image qualitiy of the MRF parametric maps.

Cristobal Arrieta^1,2, Olivier Jaubert³, Gastao Cruz³, Sergio Uribe^1,2,4, Rene M Botnar³, Claudia Prieto³, and Carlos Sing-Long^2,5,6
1Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile, ²Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile, ³School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom, ⁴Radiology Department, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile, ⁵Instituto de Ingeniería Matemática y Computacional, Pontificia Universidad Catolica de Chile, Santiago, Chile, ⁶Millennium Nucleus Center for the Discovery of Structures in Complex Data, Santiago, Chile

In this work we validated a liver MR Fingerprinting technique which allows to simultaneously estimate T1, T2, Proton Density Fat Fraction (PDFF) and T2*. This technique is based on a novel water and fat separation optimisation scheme, which includes l2-norm of the fieldmap gradient, TV regularisation on T2* and l1-norm denoising of the water and fat concentrations. We presented results on T1/T2 and water/fat phantoms and in 11 volunteers. This approach showed to be robust and it is ready to be applied on more clinical challenging cases.

Tian Li¹, Di Cui², Edward S. Hui², and Jing Cai^1
1The Hong Kong Polytechnic University, Hong Kong, Hong Kong, ²The University of Hong Kong, Hong Kong, Hong Kong

Tumor motion imaging is of vital importance in managing mobile cancers in radiation therapy. However, current 4D-MRI techniques are inefficient and ineffective, potentially leading to suboptimal and inaccurate results. To solve this problem, we propose a novel four-dimensional magnetic resonance fingerprinting (4D-MRF) technique for radiation therapy applications. Our proposed method has been validated through simulations and in-vivo volunteer experiment.

Nikita Sushentsev¹, Joshua D Kaggie¹, Guido Buonincontri^2,3, Rolf Schulte⁴, Vincent J Gnanapragasam^5,6,7, Martin J Graves¹, and Tristan Barrett^1,8
1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, ²IRCCS Stella Maris, Piza, Italy, ³Imago7 Foundation, Piza, Italy, ⁴GE Healthcare, Munich, Germany, ⁵6) Cambridge Urology Translational Research and Clinical Trials Office, University of Cambridge, Cambridge, United Kingdom, ⁶Academic Urology Group, Department of Surgery & Oncology, University of Cambridge, Cambridge, United Kingdom, ⁷Department of Urology, University of Cambridge, Cambridge, United Kingdom, ⁸2) CamPARI Prostate Cancer Group, Addenbrooke's Hospital, Cambridge, United Kingdom

This study investigates the effect of hormone therapy for prostate cancer on T1 mapping values obtained from MR Fingerprinting. No differences were observed between tumour T1 values before and after treatment.  However, lower T1 MRF values were noted in prostate lesions compared to normal peripheral and transition zones, which is consistent with current literature. Moreover, a significant decrease in T1 values was observed in normal transition zone (TZ) following treatment, which may justify the need of using T1 mapping in contrast-enhanced MRI studies aimed at calculating quantitative TZ-derived parameters.

Xueying Zhao¹, Ying-Hua Chu², Qianfeng Wang¹, and He Wang^1,3
1Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China, ²MR Collaboration, Siemens Healthcare Ltd., Shanghai, China, ³Human Phenome Institute, Fudan University, Shanghai, China

Precise quantification of the contrast agent uptake in DCE-MRI is still challenging. Here, we redesigned the reconstruction scheme of MR fingerprinting by introducing a sliding window into the process of dictionary matching, which allows dynamic quantification of T1 and T2* in DCE-MRI with high temporal resolution. The performance of this proposed dynamic MRF method is simulated and tested on MATLAB. The time-varying trajectories of T1 and T2* have been successfully captured with a temporal resolution of 4.5 seconds. This method may open the door of utilizing MR fingerprinting to quantify time-varying variable with adjustable temporal resolution.

Joely Smith^1,2, Ben Statton³, Sarah Cardona¹, Mary Elizabeth Finnegan^1,2, Rebecca Abigail Quest^1,2, and Matthew Grech-Sollars^1,4
1Department of Imaging, Imperial College Healthcare NHS Trust, London, United Kingdom, ²Department of Bioengineering, Imperial College London, London, United Kingdom, ³MRC London Institute of Medical Sciences, Imperial College London, London, United Kingdom, ⁴Department of Surgery and Cancer, Imperial College London, London, United Kingdom

Obtaining quantitative measurements in a 7-minute acquisition could improve the sensitivity of MR diagnosis. We investigated the validity and reproducibility of magnetic resonance fingerprinting (MRF) relaxometry in 12 tissue compartments in the human brain through comparison to standard mapping techniques: variable flip angle for T1 and multi-echo spin echo for T2. Statistically significant strong and moderate correlations were found between the MRF and standard mapping methods for T1 and T2, respectively. The MRF results were shown to be highly reproducible and in agreement with values found within the literature. However, a bias was found between MRF and standard relaxometry methods.

Enlin Qian¹, Amaresh Shridhar Konar², Pavan Poojar¹, Maggie Fung³, and Sairam Geethanath^1
1Columbia Magnetic Resonance Research Center, New York, NY, United States, ²Memorial Sloan Kettering Cancer Center, New York, NY, United States, ³GE Healthcare Applied Sciences Laboratory East, New York, NY, United States

This work evaluates repeatability of T₁ and T₂ estimation of  the TMRF method compared to MRF and the gold standard measurements at two sites. In this work, we acquired data for 10 days on ISMRM/NIST phantom using the three methods at the two sites with the same vendor and field strength. The data was reconstructed and matched with an EPG simulated dictionary. ROI analysis was performed to extract T₁ and T₂ estimation for each sphere. The results and statistical analysis are presented here.

Ben Statton^1,2, Joely Smith^3,4, Mary E Finnegan^3,4, Rebecca A Quest^3,4, and Matthew Grech-Sollars^3,5
1Imperial College London, London, United Kingdom, ²Medical Research Council, London Institute of Medical Sciences, London, United Kingdom, ³Department of Imaging, Imperial College Healthcare NHS Trust, London, United Kingdom, ⁴Department of Bioengineering, Imperial College London, London, United Kingdom, ⁵Department of Surgery and Cancer, Imperial College London, London, United Kingdom

Magnetic Resonance Fingerprinting (MRF) is a technique which produces multiple parametric maps during a single fast acquisition. Before MRF can be adopted clinically, quantitative values derived from these maps must be proven accurate and reproducible over a range of T1 and T2 values and temperatures. The aim of this study was to investigate the accuracy and reproducibility of T1and T2 values derived from two different methods of MRF compared to conventional quantitative maps using the ISMRM/NIST system phantom.

Varut Vardhanabhuti¹, Ho Ting Au², Jie Ding¹, Elaine Y Lee¹, Peng Cao¹, and Edward S Hui^1
1Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, ²The University of Hong Kong, Hong Kong, Hong Kong

The purpose of this study is to assess the repeatability of the magnetic resonance fingerprinting (MRF) sequence in a Philips 3T scanner with reference to the ISMRM/NIST MRI system phantom. The results showed a strong correlation between the T₁ and T₂ estimated from MRF versus the reference values (R² = 0.999, and R² = 0.981). A high level of repeatability was achieved over the 15 scanning sessions, although the T₁ estimated from MRF has a significantly higher degree of repeatability than T₂.

Gastao Cruz¹, Olivier Jaubert¹, Aurelien Bustin¹, Torben Schneider², Peter Koken³, Mariya Doneva³, René M. Botnar¹, and Claudia Prieto^1
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ²Philips Healthcare, Guildford, United Kingdom, ³Philips Research Hamburg, Hamburg, Germany

2D Cardiac Magnetic Resonance Fingerprinting (cMRF) has been previously proposed to provide co-registered T1/T2 maps from a single breath-hold scan. Gradient Spoiled gradient echo (GRE) readout is conventionally employed for 2D cMRF. RF-spoiled readouts (FLASH) have reduced signal-to-noise ratio but are less sensitive to field inhomogeneities that may bias the parametric maps (if not encoded in the MRF sequence). Here we compare the performance of FLASH and GRE readouts for simultaneous T1/T2 mapping in 2D cMRF. Phantom and in-vivo results showed that both sequences produce comparable maps and reproducible values, however GRE-cMRF presented larger underestimations for T1 and T2. 

Gastao Cruz¹, Thomas Kuestner¹, Ilkay Oksuz¹, Olivier Jaubert¹, Niccolo Fuin¹, Andy P. King¹, Julia A. Schnabel¹, René M. Botnar¹, and Claudia Prieto^1
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom

Conventional Magnetic Resonance Fingerprinting (MRF) relies on pixelwise dictionary matching of highly undersampled time-series images. However, remaining aliasing artefacts in these images can compromise the matching step and thus affect the accuracy of the parametric maps. Dictionary-based compression has been proposed to exploit redundancies in the signal evolution dimension, however these approaches do not exploit tissue redundancies within the images. Here we propose to leverage redundant information between similar tissues and the MRF dictionary to suppress residual artefacts along time, using long short-term memory (LSTM) networks. Preliminary results indicate that proposed MRF-LSTMs can suppress aliasing in highly undersampled scenarios.

Ryoichi Sasaki¹ and Yasuhiko Terada^1
1Institute of Applied Physics, University of Tsukuba, Tsukuba, Japan

Ideally, MRF can quantify multiple parameters at a single scan. In some cases, however, these parameters are not separable and additional scans for inseparable parameters are required, which reduces the advantage of the short scan time of MRF. This is remarkable when the large number of parameters are involved in the signal evolution process. Here, we used a pattern matching using a deep neural network called DRONE, and verified the separability of four parameters of T1, T2, B1, and ADC from MRF-FISP signals acquired at a single scan.

Yiling Xu¹, Elisabeth Hoppe¹, Peter Speier², Thomas Kluge², Mathias Nittka², Gregor Körzdörfer², and Andreas Maier^1
1Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, ²Magnetic Resonance, Siemens Healthcare, Erlangen, Germany

Various deep learning approaches have been recently introduced to enable a fast MRF reconstruction compared to dictionary matching. Artefacts resulting from the strong undersampling during the acquisition often impair the reconstruction results. In this work, we introduce a deep learning artefact reduction method in order to provide clean fingerprints for the subsequent regression network. Our results achieve a decreased relative error by over 50% using our artefact reduction method compared to previously proposed deep learning regression model without prior artefact reduction.

Fabien Boux^1,2, Florence Forbes², Julyan Arbel², Aurélien Delphin¹, Thomas Christen¹, and Emmanuel L. Barbier^1
1Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, GIN, 38000, Grenoble, France, ²Univ. Grenoble Alpes, Inria, CNRS, G-INP, 38000, Grenoble, France

In MR Fingerprinting, the exhaustive search in the dictionary may be bypassed by learning a mapping between fingerprints and parameter spaces. In general, the relationship between these spaces is particularly non-linear, which implies the use of advanced regression methods: deep learning frameworks but also methods based on statistical models have been proposed. In this study, we compare reconstruction time, accuracy and noise robustness of the conventional dictionary-matching method and two methods that handle the modelling of the non-linear relashionship with a neural network and a statistical inverse regression model.

Pavan Poojar^1,2, Enlin Qian¹, Maggie Fung³, and Sairam Geethanath^1,2
1Columbia University Magnetic Resonance Research Center, Columbia University in the City of New York, New York, NY, United States, ²Dayananda Sagar College of Engineering, Bangalore, India, ³GE Healthcare Applied Sciences Laboratory East, New York, New York, NY, United States

Tailored MRF (TMRF) provides scheme to acquire non-synthetic, multi contrast images simultaneously in one sequence by tailoring the acquisition scheme derived in MRF. Natural contrast obtained from TMRF overcomes artifacts observed in MRF such as flow and errors in tissue parameter quantitation. We acquired TMRF and MRF data on the ISMRM/NIST phantom along with gold standard relaxometry data. We also acquired MRF and TMRF data for 5 volunteers and compared the natural and synthetic contrasts; and the relaxometric maps. The TMRF natural contrasts are similar to control experiments and do not contain flow artifacts found in synthetic contrasts.

Qing Li¹, Xiaoyue Zhou¹, and Yi Sun^1
1MR Collaborations, Siemens Healthcare Ltd., Shanghai, China

A dictionary-based reconstruction method was applied to estimate T1 mapping from a series of highly undersampled images acquired with an inversion recovery–prepared FISP sequence and a radial readout. Motion robustness improved using interleaved slice acquisition and data rejection in T1 estimation. The measurement time was 4 s/slice. Phantom and in vivo knee results show an up to 50% data rejection results in less than 10% of quantification accuracy loss, compared to the T1 map reconstructed with the full dataset.

Shohei Fujita^1,2, Akifumi Hagiwara¹, Naoyuki Takei³, Ken-Pin Hwang⁴, Issei Fukunaga¹, Shimpei Kato^1,2, Masaaki Hori⁵, Ryusuke Irie^1,2, Christina Andica¹, Toshiaki Akashi¹, Koji Kamagata¹, Ukihide Tateishi⁶, Osamu Abe², and Shigeki Aoki^1
1Department of Radiology, Juntendo University, Tokyo, Japan, ²Department of Radiology, The University of Tokyo, Tokyo, Japan, ³MR Applications and Workflow, GE Healthcare, Tokyo, Japan, ⁴Department of Radiology, MD Anderson Cancer Center, Houston, TX, United States, ⁵Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan, ⁶Department of Radiology, Tokyo Medical and Dental University, Tokyo, Japan

Simultaneous relaxometry of T1, T2, and proton density by 3D-QALAS still requires relatively lengthy acquisition times and further acceleration is desired in clinical practice. Here, we applied compressed sensing combined with parallel imaging to 3D-QALAS to accelerate scan time. Quantitative values and tissue segmentation performance were compared with and without acceleration in phantom, healthy volunteers, and patients. With accelerated 3D-QALAS acquisition, whole brain 1 mm isotropic volume data with multiple parametric maps and co-registered tissue segmentation maps were obtained in less than 6 minutes, with comparable quality to 3D-QALAS without acceleration.

Nina Pötsch¹, Marcus Raudner^1,2, Tom Hilbert^3,4,5, Tobias Kober^3,4,5, Elisabeth Weiland⁶, Panagiotis Kapetas¹, and Pascal Baltzer^1
1Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ²High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ³Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland, ⁴Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵LTS5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁶Siemens Healthcare GmbH, Erlangen, Germany

Contrast-enhanced breast MRI is the most sensitive tool for the detection of breast cancer. Contrast enhancement is however not specific to cancer: incidental benign findings regularly require further workup including ultimately avoidable follow-up scans and biopsies. Quantitative T1 and T2 measurements could be used as discriminative imaging markers to assist clinical decision-making. This feasibility study illustrates the potential clinical benefits of quantitative imaging for breast MRI by combining two fast and robust mapping techniques for high-resolution parameter mapping in a clinically feasible scan time of 7:32 min using prototype compressed sensing MP2RAGE and GRAPPATINI sequences with a harmonized protocol.

Nan Wang^1,2, Anthony G Christodoulou¹, Yibin Xie¹, Fei Han³, Xiaodong Zhong³, Sen Ma^1,2, Xiaoming Bi³, Vibhas Deshpande⁴, and Debiao Li^1
1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ²Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, ³Siemens Healthcare, Los Angeles, CA, United States, ⁴Siemens Healthcare, Austin, TX, United States

Quantitative MRI has been playing a key role in the assessment and characterization of liver. However, current applications are still facing technical challenges. In this work, we proposed a novel technique based on MR Multitasking, which enables simultaneous T1, R2*, and FF quantification in one scan with free-breathing acquisition, 3D whole-liver coverage, and sufficient spatial resolution. The feasibility of the proposed method were demonstrated on the volunteer study (N = 8), showing that the T1, R2*, and FF quantification was repeatable in vivo and consistent with the results from the reference methods. 

Radovan Jiřík¹, Lucie Krátká¹, Jiří Kratochvíla¹, Ondřej Macíček¹, Ye Tian², Peter Scheer³, Jana Hložková³, Edward DiBella², and Zenon Starčuk, jr.^1
1Institute of Scientific Instruments of the CAS, Brno, Czech Republic, ²Utah Center for Advanced Imaging and Research, University of Utah, Salt Lake City, UT, United States, ³University of Veterinary and Pharmaceutical Sciences Brno, Brno, Czech Republic

The main challenge of using DCE-MRI in stroke in combination with advanced pharmacokinetic models is the need for high temporal resolution, whole-brain coverage and a low SNR (especially in small-animal MRI) of the DCE signal (compared to DSC, due to the BBB and low fractional blood volume in brain). In this pilot study we test if compressed sensing could help solve these challenges.

Jian Wu¹, Xiaoyin Wang², Hongjian He², Lingceng Ma¹, Shuhui Cai¹, Congbo Cai¹, and Jianhui Zhong^3
1Department of Electronic Science, Xiamen University, Xiamen, China, ²The Center for Brain Imaging Science and Technology, Zhejiang University, Zhejiang, China, ³Department of Imaging Sciences, University of Rochester, Rochester, NY, United States

Simultaneously quantifying T₂ and T₂* properties can provide great sensitivity and specificity to diseases. However, most of the existing methods are time-consuming. Here, we develop an overlapping-echo method for simultaneously achieving reliable T₂ and T₂* maps in a single shot. This method is robust to motion and the inhomogeneity of B₀. Experimental results demonstrate that the resulting T₂ and T₂* values are in good agreement with those obtained with reference methods.

Michaela A U Hoesl¹, Lothar R Schad¹, and Stanislas Rapacchi^2
1Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, ²Aix-Marseille University, CRMBM, CNRS, Marseille, France

Multi-quantum sodium imaging offers additional insights compared to standard single-quantum (SQ) images with information beyond tissue sodium concentration (TSC). Simulation including B0 inhomogeneity and stimulated echo signals of multi-quantum signals and spectra of phase cycle choices facilitated robust sequence development. The characteristic temporal evolution of the SQ and triple quantum (TQ) sodium is of interest and a multi echo sequence for SQ and TQ signal acquisition was developed, which was evaluated in phantom and 5 healthy volunteers in the brain.

Davide Cicolari¹, Domenico Lizio², Patrizia Pedrotti³, Monica Teresa Moioli², Alessandro Lascialfari¹, Manuel Mariani¹, and Alberto Torresin^2,4
1Department of Physics, Università degli Studi di 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, Università degli Studi di Milano, Milan, Italy

Relaxation times measurement standardization, a great issue in clinical inter-centre and inter-scanner applications, is studied by comparing relaxation times maps of a MnCl₂ phantom, scanned with two different MRI imagers, with reference values measured with an NMR laboratory spectrometer. For this study standard sequences were used: NMR reference T₁ and T₂ values were obtained from IR (Inversion-Recovery) and CPMG (Carr-Purcell-Meiboom-Gill) sequences respectively; MRI maps were generated from clinical IR and SE (Spin-Echo) sequences. The MRI and NMR results agreement within the experimental error limits (5%) suggests that the estimation of the relaxation times is independent from the spectrometer/scanner utilized.

Tokunori Kimura¹, Kousuke Yamashita¹, and Kouta Fukatsu^1
1Department of Radiological Science, Shizuoka College of Medicare Science, Hamamatsu-Shi, Japan

We proposed a modified T2-based water suppression synthetic-MRI technique without loss of tissue SNR, which was introduced by subtraction of heavy-T2W image from standard acquired images. Our water suppression was achieved by subtracting only water portions except for tissue portions. We demonstrated both effects that CSF-PVE artifacts were dramatically suppressed and the tissue SNR was kept to before subtraction in our water suppressed quantitative maps; and thus water suppressed synthetic images of FLAIR and SE provided better gray-white matter contrasts than those for subtracting uniformly.

Ronja Berg¹, Tobias Leutritz², Stephan Kaczmarz¹, Claus Zimmer¹, Nikolaus Weiskopf², and Christine Preibisch^1
1School of Medicine, Department of Neuroradiology, Technical University of Munich, Munich, Germany, ²Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurophysics, Leipzig, Germany

Measuring physical parameters quantitatively by magnetic resonance imaging (MRI) has a high value for diagnostic applications as it allows the detection of disease related systemic changes. However, quantitative MRI mapping methods increase the scan time significantly compared to conventional imaging. Therefore, we investigated the applicability of Compressed SENSE (CS) acceleration in a multi-parametric mapping protocol for R1, R2*, PD, and MTsat imaging. Our results demonstrate that absolute parameter values remained constant in all evaluated regions-of-interest when applying CS. Thus, CS can be used to almost halve the scan for R1, R2*, PD, and MTsat mapping without loss of fidelity.

Raïssa Yebga Hot^1,2, Alexandros Popov^1,2, Justine Beaujoin¹, Gaël Perez^1,3, Fabrice Poupon^1,2, Igor Lima Maldonado⁴, Jean-François Mangin^1,2, Christophe Destrieux⁴, and Cyril Poupon^1,2
1CEA - NeuroSpin, Gif-sur-Yvette, France, ²Université Paris-Saclay, Orsay, France, ³CentraleSupélec, Gif-sur-Yvette, France, ⁴Imaging and Brain laboratory (iBrain), Université de Tours - INSERM, Tours, France

The investigation of the human cerebral cortex at the mesoscopic scale remains challenging but promising to better understand brain pathologies associated with cortex damage. In this ex vivo study, samples of occipital cortex from both hemispheres of an unique subject have been delineated using their microstructural and myeloarchitectural information inferred from ultra-high field anatomical, quantitative and diffusion MRI. The high-resolved UHF-MRI dataset enabled to perform an automatic segmentation of the cortical layers within the primary and secondary visual cortices. The segmentations highlighted their commonalities and differences between the two hemispheres.

Aritrick Chatterjee¹, Grace Lee², Deb Dietz², Aytekin Oto¹, and Gregory Karczmar^1
1Department of Radiology, University of Chicago, Chicago, IL, United States, ²Ingalls Memorial Hospital, Flossmoor, IL, United States

This study evaluates the consistency of HM-MRI for non-invasive measurement of prostate tissue composition on scanners from two MRI vendors. HM-MRI was performed on Philips Achieva 3T (with endorectal coil) and Siemens Skyra 3T (without endorectal coil) MRI scanners. HM-MRI metrics measured for cancerous and benign prostatic tissue using Philips and Siemens were similar, with slight variation due to different patients in each cohort. Diagnostic accuracy for detecting PCa using HM-MRI was similar for both MR vendors: Philips (AUC = 0.94-0.99, p<0.05) and Siemens (AUC = 0.83-0.98, p<0.05).

Ka-Loh Li¹, Daniel Lewis², Sha Zhao¹, Alan Jackson¹, and Xiaoping Zhu^1
1Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, United Kingdom, ²Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester, United Kingdom

Accurate, high-spatial resolution whole-brain pharmacokinetic maps are highly desirable in clinical neuro-oncology practice. A new dual-temporal resolution based kinetic mapping technique for this purpose, termed LEGATOS, was recently described and tested with in-vivo patient data. In this study, quantitative assessment of the accuracy of parameter estimates derived using the LEGATOS analysis procedure was evaluated through computer simulation. Structural similarity and percentage deviation of the “measured” values from the known “true” values were used for evaluation and demonstrated that the LEGATOS technique offered superior accuracy compared to the use of unreconstructed composite HT and HS curves alone. 

Qianfeng Wang¹, Hong Xiao², He Wang¹, Xuchen Yu¹, and Fuhua Yan^2
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, ²Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

In this study, spin-lock and 2D UTE pulse sequences were developed to quantify T_1ρ and T₂* of 32 rat livers with iron overload at 11.7T MR system. Moreover, T₂ was also acquired to compare with T_1ρ and T₂*. Pearson correlation analyses (two-tailed) illustrated that T_1ρ were significantly associated with T₂ (all p ≤ 0.002), but insignificantly related with T₂* (all p > 0.05). No significant association was found between T₂ and T₂*.

Nathan Tibbitts Roberts^1,2, Diego Hernando^1,2,3,4, Timothy Colgan¹, Daiki Tamada¹, and Scott B Reeder^1,3,4,5,6
1Radiology, University of Wisconsin - Madison, Madison, WI, United States, ²Electrical and Computer Engineering, University of Wisconsin - Madison, Madison, WI, United States, ³Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, ⁴Biomedical Engineering, University of Wisconsin - Madison, Madison, WI, United States, ⁵Medicine, University of Wisconsin - Madison, Madison, WI, United States, ⁶Emergency Medicine, University of Wisconsin - Madison, Madison, WI, United States

Spatially varying B1 inhomogeneities and tissue fat are known confounders of quantitative T1 mapping methods that use variable flip angle techniques. Separately acquired B1 calibration maps can be used to correct flip angle errors caused by B1 inhomogeneities, but this requires an additional acquisition. In this work we propose a novel approach for simultaneous estimation of B1, T1, proton density fat-fraction and R2* using dual orthogonal RF pulses and multiple flip angles. The feasibility and noise performance of this proposed acquisition and fitting strategy are evaluated using Cramer-Rao Lower Bound analysis, simulations, and preliminary phantom experiments.

Andreia S Gaspar ¹, Andreia C Freitas¹, and Rita G Nunes^1
1ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico – Universidade de Lisboa, Lisbon, Portugal

Modified Look-Locker  inversion recovery (MOLLI) with a balance Steady State Free Precession (bSSFP) readout is widely applied in the clinical setting but it is known to be sensitive to fat partial volume effects (PVE), as well as static B₀ field inhomogeneities (ΔB₀). As an alternative, the FLASH readout,  more robust to ΔB₀, can be applied for T₁ mapping. In this work we studied the robustness of FLASH-MOLLI to fat PVE, and propose a new bi-component model to improve the accuracy of water T₁ estimates in both bSSFP and FLASH MOLLI.

Lena Trinh¹, Pernilla Peterson^1,2, Håkan Brorson³, and Sven Månsson^1,4
1Medical Radiation Physics, Department of Translational Medicine, Lund University, Malmö, Sweden, ²Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden, ³Department of Plastic and Reconstructive Surgery, Skåne University Hospital, Malmö, Sweden, ⁴Radiation Physics, Skåne University Hospital, Malmö, Sweden

Non-invasive estimation of the fatty acid composition of adipose tissue using MRI or MRS may be valuable in a number of disease scenarios. However, in vivo validation against an independent gold standard is still needed. In this work, we find that especially MRI estimation of the fraction of saturated fatty acids is strongly associated to gas chromatography analysis in the adipose tissue of lymphedema patients. The reliability of the estimated mono- and polyunsaturated fractions are reliant on the used signal model. Also MRS provided results which are associated to GC analysis, but with a lower agreement compared to MRI.

Stephan A.R. Kannengiesser¹, Cathy Cazin², Michel Lapp², Khalid Ambarki³, Berthold Kiefer¹, and Valérie Laurent^2,4
1MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany, ²Department of Radiology, CHRU Nancy, Brabois Adults Hospital, Vandoeuvre-lès-Nancy, France, ³Siemens Healthcare SAS, Saint Denis, France, ⁴IADI, U1254, INSERM, Université de Lorraine, CHRU de Nancy Brabois, Vandoeuvre-lès-Nancy, France

A simple prototype inline mean stiffness evaluation approach for MR Elastography based on anatomical liver segmentation and the confidence map was evaluated in 25 hemochromatosis patients, and compared with manual evaluation by two readers according to QIBA guidelines. Pairwise comparisons were found to be of similar statistics: mean±std relative difference -3.40±5.10% and -0.69±6.72% for reader1 vs. reader2 and manual (average of readers)  vs. inline. The presented approach is promising given the particular patient cohort and limited stiffness range, but further evaluation is needed.

Andreas Ehrmann¹, Beata Bachrata^1,2, Korbinian Eckstein¹, David Bancelin¹, Pedro Lima Cardoso¹, Charles Joseph Guthrie¹, Siegfried Trattnig^1,2, and Simon Daniel Robinson^1,3,4
1High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ²Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria, ³Department of Neurology, Medical University of Graz, Graz, Austria, ⁴Centre for Advanced Imaging, University of Queensland, Queensland, Australia

2D EPI-based Quantitative Susceptibility Mapping offers a means to localise brainstem structures very quickly. However, this comes at the price of limited achievable slice thickness, restricting the precision of the localisation. In this work, we develop a fast super-resolution reconstruction method for complex MRI data, allowing the reconstruction of high resolution magnitude and phase images, and hence also high resolution susceptibility maps. We demonstrate that the reconstructed super-resolution 2D EPI images significantly improve the visibility of small structures allowing for improved localisation of the brainstem and other small structures such as veins in the generated susceptibility maps.

Gisela E Hagberg^1,2, Korbinian Eckstein³, Enrique Cuna⁴, Simon Robinson^3,5, and Klaus Scheffler^1,2
1Biomedical Magnetic Resonance, University Hospital Tübingen, Tübingen, Germany, ²High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ³High Field MR Centre, Medical University of Vienna, Vienna, Austria, ⁴Centro Uruguayo de Imagenología Molecular (CUDIM), Montevideo, Uruguay, ⁵Centre for Advanced Imaging, University of Queensland, Brisbane, Australia

Strong background signals leading to multiple phase wraps may hamper accurate quantification of magnetic tissue susceptibility (QSM) especially at high field strengths using long echo times to achieve a high spatial sampling. Here we show how different coil-combination, automated tissue masking and background removal techniques can be used to improve QSM quality. Performance was evaluated with regard to iron quantification in subcortical and cortical areas in the same subjects. We found a substantial improvement in accuracy and precision of QSM in high-field applications at long echo times through the use of ASPIRE and removal of areas with excessive phase evolution.

Ya-Fang Chen¹, Sung-Chun Tang², and Wen-Chau Wu^3,4
1Department of Medical Imaging, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan, ²Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan, ³Institute of Medical Device and Imaging, National Taiwan University, Taipei, Taiwan, ⁴Graduate Institute of Clinical Medicine, National Taiwan University, Taipei, Taiwan

With arterial spin labeling (ASL) MRI, the delay time between labeling and image acquisition is a critical imaging parameter for accurate flow quantification. Multi-delay ASL has been proposed to tackle the problem of unknown arterial transit time (ATT). However, it is not fully understood how the range of delay times affects the derived CBF. The present study aimed to investigate this potential issue. Results show that the CBF derived from multi-PLD ASL varies with the choice of PLD (overestimated when the PLD range does not cover ATT) as well as SNR (overestimated along with greater variability when SNR is low).

Dinil Sasi S¹, Rakesh K Gupta², Indrajit Saha³, Anandh K Ramaniharan³, and Anup Singh^4,5
1Indian Institute of Technology Delhi, New Delhi, India, ²Fortis Memorial Research Institute, Gurugram, India, ³Philips India Limited, Gurugram, India, ⁴Indian Institute of Technology Delhi, Hauz Khas, India, ⁵All India Institute of Medical Science, New Delhi, India

T1-perfusion derived parameters have been utilized for brain tumor quantification and grading. In this study, we have analyzed the potential of Compressed SENSE (CSENSE) acceleration technique on high resolution T1-perfusion MRI for quantitative analysis of brain tumor(glioma) and compared its performance and accuracy with conventional acquisition protocol in terms of concentration-time curve, perfusion parameters and glioma grading. A prospective analysis was also carried on healthy subjects to analyze the spatial error propagation at different acceleration factors(R). All derived perfusion parameters were able to quantify and differentiate different tumor classes with improved concentration-time curve(High grade and low grade glioma).

Yaël Balbastre¹, Nadège Corbin¹, and Martina F Callaghan^1
1Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom

The longitudinal relaxation rate is a useful myelin proxy that can be estimated by combining multiple acquisitions with different nominal flip angles. Inter-scan motion can introduce large biases that can be efficiently corrected if reference data with a relatively ‘flat’ sensitivity profile, e.g. a body coil, is available. This is generally not the case at ultra-high field where highly inhomogeneous localised transmit-receive coils are used. Therefore, we propose a new method for estimating and removing the net coil sensitivity that does not require a body coil, needs only coil-wise magnitude images, yet reduces motion-induced bias in R1.

Fan Yang¹, Jun Xie², Guobin Li², Meng Jiang³, and Chenxi Hu^4
1College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China, ²United Imaging Healthcare Co., Ltd, Shanghai, China, ³Department of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China, ⁴Institute of Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China

Three-dimensional variable-flip-angle(VFA) T1-mapping is a rapid T1 quantification method with important clinical applications. However, the requirement of acquiring multiple 3D images greatly increases the scan time. We propose a novel application of SUPER—a recently developed framework for parametric mapping acceleration—to reduce scan time and/or improve spatial resolution of 3D VFA T1-mapping. In healthy subjects, we demonstrate that SUPER(R=2) and SUPER-SENSE(R=4 combining SUPER and parallel imaging) achieved similar accuracy, reasonable noise amplification, and similar reconstruction time compared with the non-acceleration gold standard. The whole upper-brain T1-mapping scan time was reduced from 5.33 minutes to 1.33 by employment of SUPER-SENSE.

Agah Karakuzu^1,2, Mathieu Boudreau^1,2, Julien Cohen-Adad^1,3, and Nikola Stikov^1,2
1NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada, ²Montreal Heart Institute, Montreal, QC, Canada, ³Unité de Neuroimagerie Fonctionnelle (UNF), Centre de recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, QC, Canada

Quantitative MRI is pointless if we cannot peak inside the black box that generates the numbers. This is the main motivation behind our concept for a fully transparent qMRI pipelines starting at the scanner console and extending all the way to a journal publication. In this work, we developed a simple application to demonstrate this for variable flip angle (VFA) T₁ mapping. This application exemplifies the feasibility of a vendor-neutral qMRI sequence that is publicly shared under version control (https://github.com/qMRLab/pulse_sequences). Our approach opens a way towards community-driven development and improvement of qMRI applications without the need for specialized programming skills.

Gian Franco Piredda^1,2,3, Peipeng Liang⁴, Tom Hilbert^1,2,3, Karl Egger⁵, Shan Yang⁵, Jean-Philippe Thiran^2,3, Bénédicte Maréchal^1,2,3, Yi Sun⁶, Kuncheng Li^7,8, and Tobias Kober^1,2,3
1Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, ²Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ³LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁴School of Psychology, Capital Normal University, Beijing Key Laboratory of Learning and Cognition, Beijing, China, ⁵Faculty of Medicine, University of Freiburg, Freiburg, Germany, ⁶MR Collaboration, Siemens Healthcare Ltd., Shanghai, China, ⁷Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China, ⁸Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China

Understanding the normal evolution of T₁ values across the life span allows to disentangle ageing from degenerative pathologies. Following previous studies reporting brain anatomical and functional differences between Western and Chinese cohorts, this work investigates whether differences in the evolution of T₁ values across the life span exist between these two populations using two datasets with 200 healthy subjects each. Derived trends were found to differ between the two populations in some brain structures, especially in grey matter tissues. The observed differences may indicate that norms derived from one population may not be directly applied to another without recalibration.

Nam Gyun Lee¹, Zhibo Zhu², and Krishna S. Nayak^2
1Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, ²Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States

Quantitative DCE requires accurate and precise pre-contrast M₀/T₁ maps.  Variable flip angle (VFA) T1 mapping has good precision but has accuracy issues. Magnetization transfer (MT)  effects is one of the major reasons for differences between VFA and reference IR-FSE T1 measurements. Here, we apply the recent framework for MT-balanced RF pulse design to high-resolution whole-brain T1 mapping.

Ruoxun Zi¹, Dan Zhu^1,2, Wenbo Li^2,3, and Qin Qin^2,3
1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ³F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States

We presented a T2 prepared stack-of-spiral gradient echo (GRE) pulse sequence with or without CSF nulling for T2 mapping of brain. T2 maps were iteratively optimized by data consistency, model consistency and spatial sparsity regularization using projected-gradients approach, which was evaluated by in vivo experiments and compared with SENSE, CS SENSE and model-based methods. The proposed reconstruction method provided better performance with  normalized root mean square error (nRMSE) of the whole brain T2 estimation equal to 8.2±0.5% with an acceleration factor of 5. The T2 estimation with and without CSF nulling were consistent.

Seonyeong Shin¹, Riwaj Byanju², Seong Dae Yun¹, Stefan Klein², Dirk H. J. Poot², and N. Jon Shah^1,3,4,5
1Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany, ²Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands, ³Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Jülich, Germany, ⁴JARA - BRAIN - Translational Medicine, Aachen, Germany, ⁵Department of Neurology, RWTH Aachen University, Aachen, Germany

Quantification of T2* is relatively time-efficient. However, still the scan times might be too long for the desired resolution. In this work, we demonstrated the ability to accelerate the acquisition by joint reconstruction and parameter estimation for T2* quantification. From retrospectively highly subsampled k-spaces, images and T2* maps were reconstructed directly. It was shown that an acceleration factor of 16 is feasible for T2* mapping.

John Morgan¹ and Yi Wang^1
1Cornell University, New York, NY, United States

Current methods for perfusion characterization are difficult to quantify absolutely and provide only relative and qualitative information.  Perfusion-phantoms that enable quantitative analysis of transport phenomena are needed to test theoretical models against experimental data.  The initial design and deployment of a 3D-printed phantom with pump-driven perfusion of multi-level microvascular structure encapsulated in hydrogel is presented.  It simulates vascularized tissue and enables experimental validation.  A new quantitative analytical method , using voxelized constitutive convection-diffusion equations, is applied to DCE data and compared to traditional Kety’s methods.  The largely qualitative and unmeasurable Kety global AIF assumption is replaced with measurable and reproducible data.

Maria Aristova¹, Jianing Pang², Liliana Ma¹, Michael Markl¹, and Susanne Schnell^1
1Radiology, Northwestern University, Chicago, IL, United States, ²Siemens Healthcare, Chicago, IL, United States

Dual-venc 4D flow MRI has previously been reported to achieve wide velocity dynamic range while maintaining a high velocity-to-noise ratio, which is particularly relevant for neurovascular applications. To increase flexibility in spatiotemporal resolution, we present a prototype implementation of a interleaved 8-point dual-venc 4D Flow acquisition with independently prescribed (prospectively undersampled) spatial resolution of the high venc acquisition, i.e. Variable Spatial Resolution Dual Venc (VSRDV). This allowed anti-aliasing error rates less than 15% error for a high venc spatial resolution of 70-80%. This represents 10-15% reduction of scan time.  

Chengyue Wu¹, Ty Easley², Victor Eijkhout³, David A. Hormuth⁴, Federico Pineda⁵, Gregory S. Karczmar⁵, and Thomas Yankeelov^1,4,6,7
1Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, United States, ²Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States, ³HPC Software Tools Group, Texas Advanced Computing Center, Austin, TX, United States, ⁴Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX, United States, ⁵Department of Radiology, University of Chicago, Chicago, IL, United States, ⁶Department of Diagnostic Medicine, University of Texas at Austin, Austin, TX, United States, ⁷Department of Oncology, University of Texas at Austin, Austin, TX, United States

We have recently developed novel image processing and computational methods to characterize both the morphology and hemodynamics of tumor-associated vessels to assist in the diagnosis of suspicious breast lesions. In this contribution, we employ a dynamic digital phantom of contrast agent perfusion and extravasation to systematically evaluate the sensitivity of our methods to spatial resolution, temporal resolution, and signal-to-noise ratio (SNR). The immediate goal is to use the phantom to determine an acquisition-reconstruction protocol that can implemented in the routine clinical setting, thereby enabling quantitative hemodynamic analysis to be widely available for the characterization of cancer.

Dong-Hoon Lee¹, Do-Wan Lee², Chul-Woong Woo³, Hwon Heo⁴, Jae-Im Kwon³, Yeon Ji Chae⁴, Su Jung Ham⁵, Jeong Kon Kim², Kyung Won Kim^2,5, and Dong-Cheol Woo^3,4
1Faculty of Health Sciences and Brain & Mind Centre, The University of Sydney, Sydney, Australia, ²Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea, ³Convergence Medicine Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea, ⁴Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea, ⁵Asan Image Research, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea

We evaluated the effects of a reference image and keyhole factor selections for high-frequency substitution on a keyhole imaging technique for application in glutamate CEST (GluCEST) imaging to reduce data acquisition time. The calculated GluCEST signals and visually inspected results from the reconstructed GluCEST maps indicated that a combination of unsaturated image as a reference image and >50% of keyhole factors showed consistent signals and image quality as opposed to the fully-sampled CEST data. Combining the keyhole imaging technique with GluCEST imaging enables stable image reconstruction and quantitative evaluation, and this approach is potentially implemented in various CEST imaging applications.

Jian Hou¹, Vincent Wong², Baiyan Jiang¹, Yixiang Wang¹, Anthony Chan³, Winnie Chu¹, and Weitian Chen^1
1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, Hong Kong, ²Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong, ³Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Hong Kong, Hong Kong

Macromolecular Proton Fraction (MPF) is the relative amount of protons associated with macromolecules involved in magnetization transfer with free water protons. MPF is typically measured by quantitative magnetization transfer methods. In this work, we reported that MPF can also be measured based on spin-lock. Compared to the existing MPF methods, our method requires fewer parameter maps. We demonstrated our method using simulation, phantom, and in vivo experiments.
 

Mark Bydder¹, Vahid K Ghodrati¹, Yu Gao¹, Matthew D Robson², Yingli Yang¹, and Peng Hu^1
1UCLA, Los Angeles, CA, United States, ²Perspectum Diagnostics, Oxford, United Kingdom

The study evaluates four physically motivated constraints in the estimation of the proton density fat fraction (PDFF) based on the physics of magnetic resonance imaging. These were smooth fieldmap, smooth initial phase, nonnegative proton density and moderate $$$R2*$$$  values. Results show that constraints are effective at reducing standard deviation and bias.

Riwaj Byanju¹, Stefan Klein¹, and Dirk H. J. Poot^1
1Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, Netherlands

Myelin water fractions (MWF) can provide biomarkers for many brain disorders. Multiple-spin-echo (MSE) is considered as gold standard for obtaining MWF. However, its clinical application is limited by its long acquisition time. Efficient undersampling and exploiting the redundancy in the contrast images of MSE can decrease the acquisition time. We propose a subspace based image reconstruction technique designed for reconstructing contrast images from highly undersampled MSE acquisition, so that it can be used for MWF mapping. We evaluate it for different signal-to-noise ratios for up to  acceleration factor of 16 and show its feasibility for accelerating acquisition beyond parallel imaging.

Fei Han¹, Mahesh Bharath Keerthivasan², and Vibhas Deshpande^3
1MR R&D and Collaboration, Siemens Healthineers, Los Angeles, CA, United States, ²MR R&D and Collaboration, Siemens Healthineers, Tucson, AZ, United States, ³MR R&D and Collaboration, Siemens Healthineers, Austin, TX, United States

Quantitative imaging is the key to developing reliable and reproducible imaging methods for standardized diagnostic exams. Most practical T2 mapping solutions are based on the CPMG concept, using the SEMC or TSE sequence. However, several confounding variables, such as, but not limited to the B1, RF profile, refocusing flip-angle, choice of TEs, and the imaging noise/artifacts, can lead to distorted signal and inaccurate T2 quantification. In this work, we investigated some of these confounders in CPMG-based T2 quantification and proposed a new model and fitting methods to improve the reliability, reproducibility of in-vivo T2 quantification.  

Manish Awasthi¹, Bansmita Kar¹, Neha Vats¹, Virendra Kumar Yadav¹, Dinil Sasi¹, Mamta Gupta², Rakesh Kumar Gupta², and Anup Singh^1,3
1Centre for Biomedical Engineering, Indian Institute of Technology, Delhi, New Delhi, India, ²Department of Radiology, Fortis Memorial Research Institute, Gurugram, India, ³Biomedical Engineering, All India Institute of Medical Science, Delhi, New Delhi, India

Presence of large blood vessels within tumor region can mislead interpretation on quantitative T1-perfusion MRI, particularly using automatic classification approaches.  Purpose of this study was to develop a methodology for automatic blood vessel removal from quantitative T1-perfusion maps, compare it with previously reported methodology and finally evaluating impact of blood-vessel removal on tumor grading. In the proposed approach, signal intensity time curves characteristics, particularly contrast wash-out rate and peak value provided accurate automatic removal of blood-vessel from tumor region. Significant differences between T1-perfusion maps with and without blood-vessel removal were observed and tumor grading were also influenced.

Richard G Spencer¹, Mustapha Bouhrara¹, Kenneth W Fishbein¹, and Joy You Zhuo^1
1National Institute on Aging, NIH, Baltimore, MD, United States

Analysis of multiexponential decay has remained a topic of active research for over 200 years, attesting to the difficulty in deriving the rate constants and component amplitudes of the underlying monoexponential decays. We have shown previously that parameter estimates from 2D relaxometry, with two distinct time variables, exhibit substantially greater accuracy and precision than those from analysis of 1D data, with a single time variable. We now present a statistical study of this remarkable phenomenon and indicate applications in 2D relaxometry and related experiments.  These results provide a potential means of circumventing conventional limits on multiexponential parameter estimation.
 

Elisa Moya-Sáez¹, Óscar Peña-Nogales¹, Santiago Sanz-Estébanez¹, Rodrigo de Luis-Garcia¹, and Carlos Alberola-López^1
1Laboratorio de Procesado de Imagen, Universidad de Valladolid, Valladolid, Spain

Parametric MR maps (T1, T2 and PD) not only play a key role in quantitative imaging but they also have the capability of synthesizing any modality. However, their direct acquisition is hardly used in practice due to the need of lengthy relaxometry protocols. Synthetic MRI is a surrogate; however, no approach has been described to synthesize these maps out of a small number of customary sequences. In this work we synthesize T1, T2 and PD maps out of a T1- and a T2-weighted image using a CNN trained only with synthetic data. Our approach yields realistic maps from real data.

Renee Cattell¹, Shenglan Chen¹, Jie Ding^1,2, and Chuan Huang^1,3,4
1Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States, ²Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong, ³Radiology, Stony Brook University, Stony Brook, NY, United States, ⁴Psychiatry, Stony Brook University, Stony Brook, NY, United States

Quantitative measurement of breast density is important for personalized risk assessment and frequent, longitudinal monitoring of breast density modifying drugs. Current standard of care for assessing breast density is qualitative assessment of mammogram, which involves ionizing radiation and breast compression. MRI-derived breast density (MagDensity) using fat-water decomposition has the potential to provide a sensitive and useful tool for clinicians. This study aims to prospectively determine the reliability and reproducibility of this measure across different vendors, scanner models and field strengths

Keita Nagawa¹, Suzuki Masashi¹, Masami Yoneyama², Kaiji Inoue¹, Eito Kozawa¹, and Mamoru Niitsu^1
1Saitama Medical University, Saitama, Japan, ²Philips Japan, Tokyo, Japan

For T1ρ quantification, a three-dimensional (3D) acquisition is desired to obtain high-resolution images. In order to achieve a rapid and robust acquisition of 3D T1 rho mapping data, we examined here the 3D sub-millimeter isotropic resolution sequences, applying them to the assessment of knee-joint. 3D isotropic resolution sequences can reduce partial-volume artifacts through the acquisition of thin continuous sections through joints. Furthermore, the isotropic source data can be used to create multiplanar reformations (MPRs). With the optimized voxel size (0.8mm³), we could obtain motion-robust high-quality isotropic images within the time constraints of a clinical exam (<10 minutes) .

Anne Adlung¹, Nadia K. Paschke¹, Alena-Kathrin Schnurr¹, Sherif Mohamed², Victor Saase², Melina Samartzi³, Marc Fatar³, Eva Neumaier-Probst², and Lothar R. Schad^1
1Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, ²Department of Neuroradiology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, ³Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

This study investigates the possibility to reduce 23Na MRI measurement time for stroke patients by applying CNNs and evaluates the resulting TSC accuracy in GM and WM. Three different CNN architectures were implemented and compared. The CNNs’ performance was evaluated by calculating the TSC quantification error and with a qualitative evaluation from neuroradiologists. The implementation of TSC quantification into the clinical routine might be greately facilitated by an acceleration factor of 4 for the 23Na MRI acquisition time while keeping its TSC accuracy in WM and GM.

Agah Karakuzu^1,2, Gilles Hollander^3,4, Stefan Appelhof⁵, Tibor Auer⁶, Mathieu Boudreau^1,2, Franklin Feingold⁷, Ali R. Khan⁸, Alberto Lazari⁹, Christophe Phillips¹⁰, Nikola Stikov^1,2, and Kirstie Whitaker^11,12
1NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada, ²Montreal Heart Institute, Montreal, QC, Canada, ³Laboratory for Social and Neural Systems Research (SNS Lab), Department of Economics, University of Zurich, Zürich, Switzerland, ⁴Spinoza Centre for Neuroimaging, Amsterdam, Netherlands, ⁵Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany, ⁶University of Surrey, Guildford, United Kingdom, ⁷Stanford University, Stanford, CA, United States, ⁸Department of Medical Biophysics, Robarts Research Institute, University of Western Ontario, London, ON, Canada, ⁹Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, ¹⁰GIGA Institute, University of Liège, Liège, Belgium, ¹¹Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom, ¹²The Alan Turing Institute, London, United Kingdom

The Brain Imaging Data Structure (BIDS) aims to develop a standard for organizing and describing neuroimaging data (https://bids.neuroimaging.io/). It has rapidly gained traction across neuroimaging disciplines through community-driven development of BIDS extension proposals (BEPs; http://bit.ly/bids_bep). Here were present such an extension proposal, that captures a wide range of structural MRI contrasts and parametric mapping protocols that are of interest to the broader ISMRM community (https:/bit.ly/bep001). This abstract reports the current state of the proposal and illustrates the developments made since the 2018 ISMRM virtual meeting Bringing BIDS closer to quantitative MRI.

Fábio Seiji Otsuka¹, Carlos Ernesto Garrido Salmon¹, Iman Ghodratitoostani^2,3, Zahrasadat Vazirikangolya^2,4, Renan Maatsuda⁵, Abhishek Datta⁶, and Chris Thomas^6
1Inbrain Lab, Department of Physics, Faculty of Phylosophy, Sciences and Letter of Ribeirão Preto (FFCLRP), University of São Paulo (USP), Ribeirão Preto, Brazil, ²Neurocognitive Engineering Laboratory (NEL), Institute of Mathematics and Computer Sciences, University of São Paulo (USP), São Carlos, Brazil, ³Reconfigurable Computing Laboratory, Institute of Mathematics and Computer Science, University of São Paulo (USP), São Carlos, Brazil, ⁴Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo (USP), Ribeirão Preto, Brazil, ⁵Biomag Lab, Department of Physics, Faculty of Phylosophy, Sciences and Letter of Ribeirão Preto (FFCLRP), University of São Paulo (USP), Ribeirão Preto, Brazil, ⁶Soterix Medical, New York, NY, United States

Two methods to map the magnetic field distributions generated by tDCS’s electric currents using MRI were evaluated in this work. First method Stimulus/Rest Difference and second GLM. Phase images were preprocessed using motion parameters calculated by SPM from the magnitude images. To evaluate the results, simulated magnetic field distribution was calculated using simulated data for the electric current distribution. The first method showed similarities with simulated data except for one case, while the second method showed magnetic field variations only at occipital region. These results points toward the possibility of mapping these very low intensity magnetic fields using MRI.

Ryoko Yamamori¹, Akihiro Kitanaka¹, Masatoshi Sakai¹, Shinsuke Oie¹, Naoki Ohno², Yuki Koshino², and Ayako Katagiri^3
1Department of Radiological technology, Ishikawa Prefectural Central Hospital, Kanazawa, Japan, ²Division of Health Sciences, Institute of Sciences, Kanazawa University, Kanazawa, Japan, ³Department of Radiology, Ishikawa Prefectural Central Hospital, Kanazawa, Japan

We evaluated native T1 and extracellular volume (ECV) of the breast using modified Look-Locker inversion recovery (MOLLI) sequence and compared those between invasive ductal carcinoma (IDC) and fibroglandular tissue. Moreover, we investigated the relationship between ECV and apparent diffusion coefficient (ADC) in IDC. Our results showed that ECV of IDC was significantly higher than fibroglandular tissue, whereas there was no significant difference in native T1 between both tissues. In addition, there was no significant correlation between ECV and ADC in IDC. ECV measurement using MOLLI may provide new and more detailed information in breast cancer.

Ying Chu¹ and Jürgen Finsterbusch^1
1Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

Cortico-spinal functional magnetic resonance imaging (fMRI) covering slices in the brain and cervical spinal cord usually involves specific geometry (field-of-view, voxel size) and timing parameters (bandwidth) for the two volumes. This requires a time-consuming and cumbersome retrospective reconstruction after the experiment because the standard program cannot handle the different parameter settings properly, e.g., for regridding of ramp-sampled data or correction of distortions induced by Maxwell terms. Here, a reconstruction program is presented that performs an optimized reconstruction on-the-fly including the correction of receive-coil inhomogeneities without the need of a retrospective reconstruction. It could help the applicability of cortico-spinal fMRI.

Linda Bianchini¹, João Santinha², Nuno Loução³, Mário Figueiredo⁴, Francesca Botta⁵, Daniela Origgi⁵, Marta Cremonesi⁵, Nickolas Papanikolaou², and Alessandro Lascialfari^1
1Università degli Studi di Milano, Milan, Italy, ²Champalimaud Center for the Unknown, Lisbon, Portugal, ³Philips Healthcare, Lisbon, Portugal, ⁴Instituto de Telecomunicações, Instituto Superior Técnico, Lisbon, Portugal, ⁵Istituto Europeo di Oncologia (IEO) IRCCS, Milan, Italy

The radiomic features stability when MR scanners of different vendors or magnetic fields are involved is not known and is needed to support clinical studies. A study on the radiomic features repeatability and reproducibility was carried out with a pelvis phantom designed for radiomic purposes on three MR scanners, two of same field but different vendors and two of same vendor but different fields. The crucial results include a consistent percentage loss of features repeatability after phantom repositioning, suggesting the need for a features selection in studies involving patient’s repositioning. The limited reproducibility demands attention when dealing with multicentric studies.