Vasily L. Yarnykh^1
1Radiology, University of Washington, Seattle, WA, United States

Correction of B₁ field non-uniformity is critical for quantitative MRI methods including fast macromolecular proton fraction (MPF) and variable flip angle T₁ mapping. However, B₁ mapping sequences increase the examination time and are not commonly available in clinics. A new algorithm is presented to enable simultaneous B₁ correction in R₁=1/T₁ and MPF mapping without acquisition of B₁ maps. The principle of the algorithm is based on different mathematical dependences of B₁-related errors in R₁ and MPF allowing extraction of a surrogate B₁ map from uncorrected R₁ and MPF maps. The method demonstrated excellent agreement with actual B₁ mapping at 3T.

Jochen Keupp¹, Doneva Mariya¹, Jakob Meineke¹, and Peter Forthmann^1
1Philips Research, Hamburg, Germany

T2w-MRI plays an important role in prostate cancer providing information on the location/grade in diagnosis or surveillance. T2-mapping may provide objective characterization but is hampered by long acquisition time, which has been addressed by dedicated acceleration techniques (e.g. kt-T2 mapping). We investigate further acceleration of T2-mapping by prospective variable sub-sampling in the echo time domain, comparing regular or irregular patterns in combination with compressed sensing using low rank and sparsity constraints, towards a routine clinical T2 mapping protocol with increased volume coverage. Prostate and phantom T2-maps with 24 slices (1×1×3mm3 voxel) were acquired in 5½ minutes with promising map quality.

Ziyu Meng^1,2, Yudu Li^2,3, Rong Guo^2,3, Yibo Zhao^2,3, Tianyao Wang⁴, Fanyang Yu^2,5, Brad Sutton^2,5, Yao Li¹, and Zhi-Pei Liang^2,3
1Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ²Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ³Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁴Department of Radiology, The Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China, ⁵Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States

We propose a new method to learn the multi-TE image priors for accelerated T2 mapping. The proposed method has the following key features: a) fully leveraging the Human Connectome Project (HCP) database to learn T2-weighted image priors for a single TE, b) transferring the learned single-TE T2-weighted image priors to multi-TE via deep histogram mapping, c) reducing the learning complexity using a tissue-based training strategy, and d) recovering subject-dependent novel features using sparse modeling. The proposed method has been validated using experimental data, producing very encouraging results.

Xiaozhi Cao^1,2,3, Congyu Liao^2,3, Zijing Zhang^2,4, Siddharth Srinivasan Iyer^2,5, Hongjian He¹, Kawin Setsompop^2,3,6, Jianhui Zhong¹, and Berkin Bilgic^2,3,6
1Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China, ²Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, charlestown, MA, United States, ³Department of Radiology, Harvard Medical School, charlestown, MA, United States, ⁴State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China, ⁵Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁶Harvard-MIT Department of Health Sciences and Technology, Cambridge, MA, United States

We propose to combine the gSlider acquisition and blip-up/down acquisition (BUDA) to achieve high-resolution and distortion-free T₂ mapping. Firstly, we incorporate Hankel structured low-rank constraint into BUDA reconstruction to recover distortion-free images from blip-up/down shots without navigation. To utilize the similarity among RF-encodings and TEs, we introduce a model-based shuffling-gSlider joint reconstruction to recover high-resolution thin-slice images by gradually eliminating the weak coefficient components during the iterative reconstruction. Finally, the reconstructed images are used to obtain quantitative T₂ maps. The proposed method enables distortion-free high-quality whole-brain T₂ mapping with 1 mm isotropic resolution within ~1 minute.

Gitanjali Chhetri¹, Kelly C McPhee¹, and Alan H Wilman^1
1Biomedical Engineering, University of Alberta, Edmonton, AB, Canada

Differences in pulse sequences between vendors can result in variation in T2 mapping, if not accounted for.  We show that Bloch simulation based Indirect and Stimulated Echo Compensation minimizes these differences in T2 maps across different scanners.  In contrast, standard exponential fitting results in highly variable T2 values across MR systems even if echo and repetition times are identical.  By overcoming errors in T2 quantification through sequence modelling, T2 mapping can be applied in studies across multiple sites and vendors.

Xiaochuan Wu^1,2, Zheyuan Yi^1,2,3, Yilong Liu^1,2, Fei Chen³, Yanqiu Feng⁴, and Ed X. Wu^1,2
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China, ²Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, ³Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China, ⁴School of Biomedical Engineering, Southern Medical University, Guangzhou, China

T2* mapping in abdominal imaging is challenging due to respiration motions that can result in severe artifacts and affect the accuracy of T2* quantification. Traditional simultaneous autocalibrating and k-space estimation (SAKE) provides a calibrationless parallel imaging approach to reduce the image acquisition time. However, SAKE does not utilize the highly sharable image contents and coil sensitivities among multi-slice multi-echo data. In this study, we proposed a joint calibrationless reconstruction of multi-slice multi-echo images from undersampled MR data for abdominal imaging. Results demonstrated that the resulting T2* maps were in excellent agreement with those from the fully sampled data.

Omer Faruk Gulban¹, Benedikt Poser¹, Martin Havlicek¹, Federico De Martino¹, and Dimo Ivanov^1
1Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands

Spatial misencoding of the vascular signal due to flow is an imaging artifact that presents a significant challenge for in vivo MRI at high resolutions (≤0.5mm). Here we propose a method for mitigating this artifact in multi-echo gradient recalled echo (ME-GRE) images at 350μm isotropic resolution by applying 90° rotations to their phase-encoding direction. After applying our method, we demonstrate clearly visible stria of Gennari, intracortical veins, and pial vessels while mitigating the flow artifact. In addition, we report T₂^* estimates of several human brain tissues (artery, vein, gray/white matter, CSF) in-vivo which are valuable for future hemodynamic signal modeling.

Qinqin Yang¹, Jian Wu¹, Wei Wang¹, Jiyang Dong¹, Shuhui Cai¹, and Congbo Cai^1
1Department of Electronics Science, Xiamen University, Xiamen, Fujian, China

Quantitative MRI is of great value to both clinical diagnosis and scientific research. In this study, a novel T₂* mapping method, gradient-echo multiple overlapping-echo detachment acquisition (GRE-MOLED) sequence with deep learning-based reconstruction algorithm was proposed. The method is capable of acquiring reliable T₂*, M₀ and B₀ maps simultaneously in a single shot and is robust to B₀-inhomogeneities. As a rapid T₂* quantitative tool, GRE-MOLED reduces the scan time of T₂* mapping to less than 75 ms per slice and has great potential in clinical real-time applications.

Fardad Michael Serry¹, Sen Ma^1,2, Debiao Li^1,2, and Anthony G Christodoulou^1
1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ²Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States

T1 mapping is important for many diseases, from cancer [1] to cardiovascular disease [2], and more. Many fast T1 mapping protocols rely on an IR-FLASH sequence, especially in the heart. However, the accuracy and repeatability of T1 mapping with IR-FLASH are compromised by B1+ inhomogeneity. Here we present a simple dual-flip-angle (DFA) modification of the IR-FLASH pulse sequence to provide  B1+-robust T1 mapping that obviates the need for a separate B1+ scan . We show the improved agreement of DFA-IR-FLASH to IR-TSE in a phantom study as well as its feasibility for in vivo cardiac T1 mapping with MR Multitasking.

Cheng-Chieh Cheng¹, Pei-Hsin Wu¹, Michael C. Langham¹, and Felix W. Wehrli^1
1University of Pennsylvania, Philadelphia, PA, United States

A T₂-based oximetry method for quantifying whole-organ metabolic rate of oxygen (MRO₂): A velocity-encoded acquisition module with golden-angle radial sampling was inserted into a background-suppressed T₂-prepared sequence specifically for blood water T₂ quantification. Parallel imaging and compressed-sensing techniques were applied to the reconstruction of the sparsely-sampled velocity-encoded k-space data to generate velocity maps. Whole-organ oxygen metabolic rate was estimated by converting T₂ to blood oxygenation level via a calibration curve. A pilot study in the superior sagittal sinus showed the method’s ability to estimate whole-brain CMRO₂ (136±23 μmol/minute/100g, mean±S.D.) in a single pass.