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Jingwen Yao¹, Jing Liu¹, Brian Burns², Roland Henry³, and Peder Larson^1,4
1Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²Applied Sciences Lab, GE Healthcare, Menlo Park, CA, United States, ³Department of Neurology, University of California, San Francisco, San Francisco, CA, United States, ⁴UCSF/UCB Graduate Program in Bioengineering, University of California, San Francisco, San Francisco, CA, United States

Keywords: Quantitative Imaging, Quantitative Imaging, MP2RAGE, multi-echo

In this study, we evaluated the use of interleaved undersampling and joint-contrast reconstruction to accelerate multi-echo MP2RAGE. We compared three sampling patterns (GRAPPA, interleaved GRAPPA, and CIRCUS) and five reconstruction algorithms (GRAPPA, ESPIRIT, LORAKS, Joint-GRAPPA, and Joint-LORAKS) using retrospective undersampling experiments. The results demonstrated better performance achieved using joint-contrast compared to single-contrast reconstruction, and CIRCUS sampling compared to GRAPPA. With the combination of CIRCUS undersampling and Joint-LORAKS reconstruction, we obtained quantitative measurements of T₁, R₂*, QSM, and volumes at R=6.8 highly consistent with the fully sampled data, demonstrating the potential of using the proposed strategy to accelerate ME-MP2RAGE acquisition.

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Rüdiger Stirnberg¹, Yannik Völzke¹, Daniel Löwen¹, Eberhard Daniel Pracht¹, Vincent Gras², Nicolas Boulant², Siya Sherif³, Difei Wang¹, Mónica Ferreira¹, Jennifer Faber^1,4, and Tony Stöcker^1,5
1German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, ²Commissariat à l’Energie Atomique, CNRS, NeuroSpin, Baobab, Université Paris-Saclay, Gif sur Yvette, France, ³GIGA - Cyclotron Research Centre - In Vivo Imaging, University of Liège, Liège, Belgium, ⁴Department of Neurology, University Hospital Bonn, Bonn, Germany, ⁵Department of Physics and Astronomy, University of Bonn, Bonn, Germany

Keywords: Quantitative Imaging, High-Field MRI, MPM, QSM, 3D-EPI

We present a versatile high-resolution whole-brain multiparametric/susceptibility mapping protocol at 7T, introducing interleaved fly-back skipped-CAIPI 3D-EPI. To overcome the impeding limitations of B₁⁺ inhomogeneity, universal pTX pulses for excitation and magnetization transfer saturation are employed. Within 17 minutes scan time, 0.6mm isotropic whole-brain MT-/PD-/T1-weighted magnitude and phase images at four echo times and corresponding quantitative parameter maps are obtained. Supplementary output, like SWI and MPRAGE-like images can be generated as well. Scan efficiency is high and geometric distortions are negligible. Optionally, the interleaved fly-back acquisition allows a separate analysis of two monopolar readout images.

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Edwin Versteeg¹, Hongyan Liu¹, Oscar van der Heide¹, Miha Fuderer¹, Cornelis AT van der Berg¹, and Alessandro Sbrizzi^1
1Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, UMC Utrecht, Utrecht, Netherlands

Keywords: Quantitative Imaging, Quantitative Imaging

MR-STAT is a framework that enables the estimation of multi-parametric quantitative MR-maps from a single short scan. Quantitative imaging at 7T can be used to probe the brain’s microstructure at high resolution. We show the first results of MR-STAT at 7T and show that SAR-limitations and B₁⁺-inhomogeneities can be successfully addressed by designing a low-SAR flip angle train and using a B₁⁺-prior during reconstruction. In addition, we use the increased SNR at 7T to achieve two-fold acceleration of the MR-STAT acquisition and show that high quality parameters can be obtained both on a gel-phantom and in-vivo (full-brain) in 3 minutes.

Yang Qizhi¹, Wenhua Geng¹, Hongjian He², Jianhui Zhong^2,3, Congbo Cai¹, Zhong Chen¹, and Shuhui Cai^1
1Xiamen University, Xiamen, China, ²Zhejiang University, Hangzhou, China, ³University of Rochester, Rochester, NY, United States

Keywords: Quantitative Imaging, Quantitative Imaging, multiple overlapping-echo detachment imaging

A multi-shot acquisition strategy is adapted to multiple overlapping-echo detachment imaging (MOLED), implementing T₂ mapping with the spatial resolution of submillimeter. Compared with ssh-MOLED (ssh- for single-shot), msh-MOLED (msh- for multi-shot) are more resistant to B₀ inhomogeneity, leading to quantitative results with less distortion. Besides, msh-MOLED fulfills a high acquisition efficiency. Accuracy of msh-MOLED was validated on phantoms with a 7T zoological scanner and a 3T whole-body scanner. Higher spatial resolution also alleviates partial volume effect and results in a better structure delineation of msh-MOLED, which was corroborated with in vivo experiments.

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Suryava Bhattacharya¹, Anthony Price^1,2,3, Alena Uus^1,3, Helena S. Sousa¹, Massimo Marenzana^2,3, Kathleen Colford^2,3, Peter Murkin^2,3, Maggie Lee^2,3, Lucilio Cordero-Grande^3,4, Rui Pedro Azeredo Gomes Teixeira^1,3, Shaihan J. Malik^1,3, and Maria Deprez^1,3
1Department of Biomedical Engineering, King's College London, London, United Kingdom, ²Guy's and St Thomas Trust, London, United Kingdom, ³Centre for the Developing Brain, King's College London, London, United Kingdom, ⁴Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, Madrid, Spain

Keywords: Quantitative Imaging, Fetus

Fetal brains go through rapid development, resulting in significant changes in tissue observable by MRI, during gestation. This work presents a quantitative MR imaging pipeline that aims to measure T2 relaxation in fetal brains from clinically acquired single-shot TSE sequences, reconstructed using slice to volume registration (SVR). Images with different echo times (TE) were acquired using a 1.5T MR system; we explored both a simple exponential decay model and more complex simulation-based dictionary for T2 estimation. Measured T2 values are greater than estimates from neonates and developmentally important regions such as the subplate are visible with significantly longer T2s.

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Samuele Caneschi^1,2,3, Tom Hilbert^1,2,3, Gabriele Bonanno^4,5,6, Robert Hoepner⁷, Roland Wiest^5,8, Piotr Radojewski^5,8, Bénédicte Maréchal^1,2,3, Jean-Philippe Thiran^2,3, Tobias Kober^1,2,3, and Gian Franco Piredda^1,9,10
1Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland, ²Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ³LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁴Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Bern, Switzerland, ⁵Translational Imaging Center (TIC), Swiss institute for Translational and Entrepreneurial Medicine, Bern, Switzerland, ⁶Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland, ⁷Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland, ⁸Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland, ⁹Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland, ¹⁰CIBM-AIT, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

Keywords: Quantitative Imaging, Data Processing, Brain cortex

Quantitative MRI allows establishing normative atlases of relaxometry parameters which enable single-subject comparisons for anomaly detection. The large anatomical inter-subject variability of the brain cortex and its convoluted shape, however, complicate such comparison in this region. In this study, a method to align inter-subject brain cortices is proposed and a voxel-wise normative T₁ atlas in the cortex is built from a cohort of 133 healthy subjects scanned at 7T. The atlas is used to detect and characterize T₁ alterations in two multiple sclerosis patients on a single-subject basis.

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Fahad Hannan¹, Michael T. Jurkiewicz², Jonathan Thiessen^1,2,3, and Susan Shih-Han Huang^1,4,5
1Medical Biophysics, University of Western Ontario, London, ON, Canada, ²Medical Imaging, University of Western University, London, ON, Canada, ³Lawson Health Research Institute, London, ON, Canada, ⁴Medicine, Schulich School of Medicine & Dentistry, London, ON, Canada, ⁵The Lilibeth Caberto Kidney Clinical Research Unit, London, ON, Canada

Keywords: Quantitative Imaging, Neurodegeneration, Cognitive decline, neuroinflammation, myelin water fraction

Despite being in remission, patients with immune-mediated thrombotic thrombocytopenic purpura (iTTP) experience a variety of cognitive health problems. Quantitative MRI was used to verify the health of white matter in 19 patients. Patients had increased T1 in the cingulate cortex and increased T2 in the frontal, parietal, and temporal lobes. These regions correlate with decreased cognitive scores and depression tests taken by patients alongside the MRI scan. Increased T1 and T2 could suggest a variety of tissue pathologies but require further investigation to determine exactly what condition is affecting white matter health.

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Xiaonan Zhang¹, Guohua Zhao¹, Huiting Zhang², Eryuan Er Gao¹, and Jingliang Cheng^1
1The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, ²MR Scientific Marketing, Siemens Healthineers Ltd., Wuhan, China

Keywords: Quantitative Imaging, Brain

The hippocampal microstructural alterations by using routine magnetic resonance imaging presents a challenge. This study aimed to evaluate the performance of the NODDI  and MAP models in temporal lobe epilepsy (TLE) patients with hippocampal sclerosis (HS). Our results found that all NODDI and MAP parameters had significant differences between ipsilateral HS and contralateral HS/HC, and had MAP models better diagnostic performance than NODDI. In addition, combined MAP model had significant better diagnostic performance than all the single parameters. In conclusion, MAP is superior to NODDI in diagnosing TLE with HS.

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Junqi Xu¹, Yaru Sheng², Hao Li¹, Qianfeng Wang¹, Zidong Yang¹, Yan Ren², and He Wang^1,3
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, ²Radiology Department, Hua Shan Hospital, Fudan University, Shanghai, China, ³Human Phenome Institute, Fudan University, Shanghai, China

Keywords: Quantitative Imaging, Brain, Diffusion, Multi-exponential spectroscopy

We present a multi-exponential diffusivity spectroscopy model to measure the diffusivity distribution of individual voxels in gliomas, which enables the comparison of the spectral fraction components between brain tumors and normal tissues. A neural network algorithm was used to speed up and improve the stability of the decomposition of multi-exponential decay data with a lower signal-to-noise ratio. The results show that diffusivity fractions of some spectral components were significantly different between IDH-mutant and -wild gliomas in grades 2 and 3.

Ana Jorge Gonçalves¹, Julian Matthews², Hamied Haroon², Laura M. Parkes², Marie-Claude Asselin¹, and Stephen Williams^1
1Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom, ²Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom

Keywords: Quantitative Imaging, Spectroscopy, Brain

Variations in six neuro-metabolite (N-acetylaspartate, creatine, myo-inositol, glutamate, glutamine and glycerophosphorylcholine) signals from MR spectroscopy (MRS) data across eleven brain regions were tested for regional differences and for dependence on the spectroscopic volume tissue composition (fractional grey matter (GM)), using a linear mixed-effect model. We found significant positive correlations of N-acetylaspartate, creatine and glutamate concentrations with fractional GM across all eleven regions and a significant regional effect for all six metabolites. This provides clear evidence that brain metabolite measurements are dependent on both the region and fractional GM, demonstrating the importance of knowing tissue fractions when interpreting MRS measurements.

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Nuwan D. Nanayakkara¹, Liesel-Ann Meusel¹, Nicole D. Anderson^1,2, and J. Jean Chen^1,3,4
1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, ²Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada, ³Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, ⁴Department of Biomedical Engineering, University of Toronto, Toronto, ON, Canada

Keywords: Quantitative Imaging, Diabetes, Cerebrovascular reactivity, CVR

Differences in CVR amplitude and time delay were assessed among patients with hypertension (HT), hypertension-plus-type-2 diabetes (HT+DM), and age-matched controls (CTL) using a pipeline for adaptive capturing of the BH response directly from BOLD data, ensuring greater robustness. The lowest CVR amplitude and the longest delay were found in the HT+DM group. CTL had the highest CVR amplitude, and the HT group had the shortest time delays. CVR delay was more sensitive to group differences than amplitude.

Nada Kamona^1,2, Brandon C. Jones^1,2, Hyunyeol Lee^1,3, Connor S. Wagner⁴, Makayla Clark¹, Advait Thaploo¹, Sandhya Konar¹, Carlos Mendez Cruz¹, Kevin Li¹, Bartlett P. Bartlett⁴, Chamith S. Rajapakse^1,5, Hee Kwon Song¹, and Felix W. Wehrli^1
1Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States, ²Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, ³School of Electronics Engineering, Kyungpook National University, Daegu, Korea, Republic of, ⁴Division of Plastic, Reconstructive, and Oral Surgery, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, United States, ⁵Department of Orthopaedic Surgery, University of Pennsylvania, Philadelphia, PA, United States

Keywords: Quantitative Imaging, Bone, Skull imaging

Risk of ionizing radiation from CT remains a concern for pediatric patients, such as craniosynostosis patients who may require multiple scans at a young age. We quantitatively compared three MRI methods for imaging the skull by scanning healthy adults using our solid-state bone-selective ultrashort echo subtraction sequence, along with zero echo time and gradient-echo sequences. We demonstrate the similarities among the 3D rendered bone segmentations in terms of Dice similarity coefficient and craniometric measurements across all imaging methods. Our UTE echo subtraction technique shows clear visualization of craniofacial structures near the bone-air boundaries and superior signal suppression of soft-tissues.

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Fahad Salman¹, Abhisri Ramesh¹, Thomas Jochmann^1,2, Mirjam Prayer¹, Niels Bergsland^1,3, Michael G. Dwyer^1,4, Dejan Jakimovski¹, Robert Zivadinov^1,4, and Ferdinand Schweser^1,4
1Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States, ²Department of Computer Science and Automation, Technische Universität Ilmenau, Ilmenau, Germany, ³IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy, ⁴Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, United States

Keywords: Quantitative Imaging, Quantitative Susceptibility mapping

Quantitative susceptibility mapping (QSM) calculates the tissue magnetic susceptibility from gradient-echo phase images. Tissue magnetic susceptibility is of high clinical interest because it reflects tissue iron, myelin, and calcium. However, the clinical significance of these findings remains unclear. In particular, it is unknown if algorithms differ in their ability to detect group differences and longitudinal changes in susceptibility.The present work compared a large number of published algorithms with respect to their ability to detect aging-related changes over time. 

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Zhenghao Li¹, Ruimin Feng¹, and Hongjiang Wei^1
1Shanghai Jiao Tong University, Shanghai, China

Keywords: Quantitative Imaging, Quantitative Susceptibility mapping

Conventional quantitative susceptibility mapping (QSM) reconstruction methods only provide voxel-averaged susceptibility value. We proposed a comprehensive complex signal model that describes the relationship between the 3D GRE signal and the contributions of opposing susceptibility to the frequency shift and $$$R_2^*$$$ relaxation. We used an iterative data fitting scheme to alternatively determine the sub-voxel susceptibilities and the voxel-wise proportionality coefficient between $$$R_2'$$$ and absolute susceptibility. Our experiments on in-vivo human brain data compared with histological staining images demonstrate that the proposed method provides more accurate results for quantifying brain iron and myelin than previous QSM separation methods.

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Hyungseok Jang¹, Sam Sedaghat¹, Soo Hyun Shin¹, Saeed Jerban¹, Yajun Ma¹, Eric Y Chang^1,2, and Jiang Du^1,2,3
1Department of Radiology, University of California, San Diego, San Diego, CA, United States, ²Radiology Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, United States, ³Department of Bioengineering, University of California, San Diego, San Diego, CA, United States

Keywords: Quantitative Imaging, Electromagnetic Tissue Properties

Electrical conductivity is an intrinsic tissue property. At the Larmor frequency of the MR system (i.e., ~128 MHz at 3T), the electrical conductivity reflects the tissue composition and ionic contents. Electrical conductivity mapping (ECM) has recently emerged as a promising MR-based biomarker. In this study, we show the feasibility of ECM using ultrashort echo time double echo steady state (UTE-DESS). In addition, three ECM methods, including forward Laplacian, parabolic fitting, and inverse Laplacian, are compared in computer simulation and ex vivo experiments with four cadaveric human brain specimens.