Leonie E. Hunger¹, Alexander German¹, Felix Glang², Katrin M. Khakzar¹, Nam Dang¹, Angelika Mennecke¹, Andreas Maier³, Frederik Laun⁴, and Moritz Zaiss^1,2
1Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, ²High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ³Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany, ⁴Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany

The deepCEST approach enables to perform CEST experiments at a lower magnetic field strength and predict the contrasts of a higher field strength. This is possible through the application of a neural network, which was trained with low and high B1 Z-spectra acquired at 3T as input data, and as target data 5-pool-Lorentzian fitted amplitudes obtained from 7T spectra were used. The network included an uncertainty quantification to verify the reliability of the predicted images.

Moritz Simon Fabian¹, Felix Glang², Katrin Michaela Khakzar¹, Angelika Barbara Mennecke¹, Alexander German¹, Manuel Schmidt³, Burkhard Kasper⁴, Arnd Dörfler¹, Frederik B. Laun¹, and Moritz Zaiss^1
1Department of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany, ²High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübungen, Germany, ³Department of Neuroradiology, University Hospital Erlangen, Erlangen, Germany, ⁴Department of Neurology, Epilepsy Center, University Hospital Erlangen, Erlangen, Germany

Measurement and evaluation of multi-parametric CEST protocols requires complex and time consuming processing for correction of field inhomogeneities and contrast generation. In this work, we expand the linear projection approach for mapping motion corrected 7T CEST data directly to Lorentzian target parameters by L1-regularisation. This translates to subsampling in the frequency offset domain, resulting in reduced acquisition time. The method generalizes from healthy subject training data to unseen healthy test data and a tumor patient dataset. The L1-regularized linear projection approach integrates shortcutting of B0 and B1 correction, denoising, and Lorentzian fitting. It enforces sparsity of required frequency offsets.

Sebastian Mueller¹, Kai Herz¹, Klaus Scheffler^1,2, and Moritz Zaiss^1,3
1High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, ²Department of Biomedical Magnetic Resonance, Eberhard Karls University Tuebingen, Tuebingen, Germany, ³Department of Neuroradiology, University Hospital Erlangen, Erlangen, Germany

CEST MRI becomes a frequently applied tool, however, a lot of method development is still done on pre-clinical scanners. Here we propose an approach that allows a fully automatic combination of existing MRI readouts for Bruker systems with open source pulseq-files for definition of CEST pre-saturation, without additional sequence programming. We believe that our work facilitates both basic research on CEST MRI and straightforward implementation of sophisticated, precisely defined CEST experiments on Bruker systems. Additionally, the use of Pulseq provides a universal, sharable standard to run the exact same pre-saturation in simulations and on clinical devises at a later stage.

Felix Glang¹, Moritz Fabian², Alex German², Katrin Khakzar², Angelika Mennecke², Frederik Laun³, Burkhard Kasper⁴, Manuel Schmidt², Arnd Doerfler², Klaus Scheffler^1,5, and Moritz Zaiss^1,2
1High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ²Department of Neuroradiology, University Hospital Erlangen, Erlangen, Germany, ³Institute of Radiology, University Hospital Erlangen, Erlangen, Germany, ⁴Neurology, Epilepsy Center, University Clinic of Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany, ⁵Department of Biomedical Magnetic Resonance, Eberhard Karls University Tübingen, Tübingen, Germany

Evaluation of multi-parametric in vivo CEST MRI often requires complex computational processing for both field inhomogeneity correction and contrast generation. In this work, linear regression was used to obtain coefficient vectors that directly map uncorrected 7T spectra to corrected Lorentzian target parameters by simple linear projection. The method generalizes from healthy subject training data to unseen test data of both healthy subjects and tumor patients. The linear projection approach thus integrates correction of both B₀ and B₁ inhomogeneity as well as contrast generation in a single fast and interpretable computation step.

Or Perlman¹, Bo Zhu^1,2, Moritz Zaiss^3,4, Naoyuki Shono⁵, Hiroshi Nakashima⁵, E. Antonio Chiocca⁵, Matthew S. Rosen^1,2, and Christian T. Farrar^1
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, ²Department of Physics, Harvard University, Cambridge, MA, United States, ³Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ⁴Department of Neuroradiology, University Clinic Erlangen, Erlangen, Germany, ⁵Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States

The long acquisition-time and the semi-quantitative nature of the typical CEST-MRI experiment constitute a major obstacle for its clinical adoption. Recently, a machine-learning approach termed AutoCEST was developed, for the automatic design of the optimal acquisition schedule and the reconstruction of quantitative 2-pool CEST maps. Here, we expand this approach for in-vivo scenarios, by incorporating the semisolid-pool into the underlying computational-graph and allowing 3 pools. AutoCEST was evaluated for quantitative rNOE mapping using a GBM mouse model, resulting in a total acquisition and reconstruction times of 49.15s. The tumor rNOE volume-fraction was significantly decreased, in agreement with previous human studies.

Pei Han^1,2, Karandeep Cheema^1,2, Hsu-Lei Lee¹, Zhengwei Zhou¹, Tianle Cao^1,2, Sen Ma¹, Nan Wang¹, Anthony G. Christodoulou^1,2, and Debiao Li^1,2
1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ²Department of Bioengineering, UCLA, Los Angeles, CA, United States

We propose a fast 3D steady-state CEST (ss-CEST) method at 3T using MR Multitasking. By exploiting the correlation among images throughout the spatial, time, and offset frequency dimensions, the low-rank tensor framework shows a possibility for at least 2x acceleration of ss- CEST. High-quality quantitative maps can be generated from ss-CEST images. The Z-spectrum acquisition with whole-brain coverage can be done within 5.5min.

Shu Zhang¹, Xinzeng Wang², F. William Schuler¹, R. Marc Lebel³, Mitsuharu Miyoshi⁴, Ersin Bayram², Elena Vinogradov⁵, Jason Michael Johnson⁶, Jingfei Ma⁷, and Mark David Pagel^1,7
1Cancer Systems Imaging, MD Anderson Cancer Center, Houston, TX, United States, ²Global MR Applications & Workflow, GE Healthcare, Houston, TX, United States, ³Global MR Applications & Workflow, GE Healthcare, Calgary, AB, Canada, ⁴Global MR Applications & Workflow, GE Healthcare Japan, Tokyo, Japan, ⁵Radiology, UT Southwestern Medical Center, Dallas, TX, United States, ⁶Neuroradiology, MD Anderson Cancer Center, Houston, TX, United States, ⁷Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States

Chemical exchange saturation transfer (CEST) measurements can be compromised by a low signal-to-noise ratio (SNR) due to the small CEST contrast in vivo. Deep learning-based image reconstruction (DL Recon) can enhance image SNR without losing image resolution or altering the image contrast, hence has the potential to improve quantitative CEST measurements. In this study, we investigated the improvement to CEST quantitation by DL Recon in glioma patients. We found that DL Recon substantially reduced the noise in the MTRasym maps and improved the lesion conspicuity.

Dushyant Kumar¹, Ryan Armbruster¹, Neil Wilson², Ravi Prakash Reddy Nanga¹, and Ravinder Reddy^1
1Radiology, University of Pennsylvania, Philadelphia, PA, United States, ²Siemens Medical Solutions USA Inc, Malvern, PA, United States

Intracellular acidosis, mainly due to lactic acid accumulation, has been regarded as the major contributor of skeletal muscle fatigue and may be a contributing factor across many musculoskeletal disorders, such as peripheral arterial disease (PAD), Duchenne dystrophy and Becker dystrophy, primary mitochondrial disorders, diabetes mellitus, and cardiovascular disease. Hence, an imaging biomarker capable of inferring the underlying acidification during varying exercise conditions could be valuable in assessing the efficacy of potential therapy options. Here, we demonstrate the feasibility of indirect detection of acidification in exercised skeletal muscle using creatine CEST.

Kerstin Heinecke¹, Henrik Narvaez¹, Christoph Kolbitsch¹, and Patrick Schuenke^1
1Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany

One of the bottlenecks in Chemical Exchange Saturation Transfer (CEST) MRI is its susceptibility to magnetic field inhomogeneities and dependency on T₁ relaxation times. To enable efficient correction for these parameters, we propose a new method for simultaneous quantitative mapping of B₀, B₁ and T₁ using a simple CEST sequence with a modified preparation block. For the analysis, we developed a neural network that provides an additional uncertainty estimation for each parameter. First results on phantom simulations demonstrate the feasibility of this approach as well as its applicability for the correction of CEST-MRI data.

Phillip Zhe Sun^1
1Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States

CEST MRI omega plot quantifies the labile proton fraction ratio (fr) and exchange rate (ksw), yet it assumes long RF saturation time (Ts) and relaxation delay (Td). Our study aimed to test if a quasi-steady-state (QUASS) CEST analysis that accounts for the effect of finite Ts and Td could improve the accuracy of CEST MRI quantification. Both simulation and CEST MRI experiments confirmed that the QUASS solution enabled robust quantification of ksw and fr, superior over the omega plot analysis based on the conventional apparent CEST MRI measurements.

Bárbara Schmitz Abecassis¹, Elena Vinogradov Vinogradov^2,3, Jannie P. Wijnen⁴, Thijs van Harten¹, Evita C. Wiegers⁴, Hans J.M. Hoogduin⁴, Matthias J.P. van Osch ¹, and Ece Ercan^1
1Department of Radiology, Leiden University Medical Center, Leiden, Netherlands, ²Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States, ³Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States, ⁴Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands

Variable-delay multi-pulse (VDMP) is a chemical exchange saturation transfer (CEST) editing technique relying on the exchange rate as a filter to separate the CEST- effect from different solute pools. We investigated this method to evaluate CEST-effects from metabolites and proteins in in vivo human brain at 7T. We removed the pronounced magnetization transfer contrast present in vivo via Lorentzian-fittings, and evaluated the effect of B₁ on saturation build-up curves of the different CEST-pools. MTC-removed VDMP-curves from the human brain are reported for the first time, where the effect of slow and fast exchanging protons allows distinguishing different CEST-pools. 

Sugil Kim¹, Seong-Gi Kim^2,3, and Suhyung Park^4,5
1Siemens Healthineers, Seoul, Korea, Republic of, ²Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Korea, Republic of, ³Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of, ⁴Department of Computer Engineering, Chonnam National University, Gwangju, Korea, Republic of, ⁵Department of ICT Convergence System Engineering, Chonnam National University, Gwangju, Korea, Republic of

We propose highly accelerated 3D CEST MRI using CAIPI sampling based 3D segmented EPI with spectral random walk, potentially enabling 1mm-isotropic whole-brain CEST imaging within 5min at 7T.

Philip S Boyd¹, Johannes Breitling¹, Stephanie Laier², Karin Mueller-Decker², Andrey Glinka³, Mark E Ladd¹, Peter Bachert¹, and Steffen Goerke^1
1Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ²Center for Preclinial Research, Core Facility Tumor Models, German Cancer Research Center (DKFZ), Heidelberg, Germany, ³Division of Molecular Embryology, German Cancer Research Center (DKFZ), Heidelberg, Germany

In this study, we present a method for mapping intracellular pH values based on amide and guanidyl CEST-MRI which simultaneously compensates for concentration changes, the semi-solid magnetization transfer, and spillover dilution. Compensation of the concomitant effects and calculation of reliable pH maps in the range of pH 6.5-7.5 was verified experimentally in porcine brain lysates. Applicability in vivo was demonstrated in the lesions of three tumor-bearing mice showing an average intracellular pH of approximately 7. Consequently, endogenous amide and guanidyl signal-based mapping of the intracellular pH is now applicable for tumor imaging which was previously prevented by the concomitant effects.

Angelika Mennecke¹, Katrin Khakzar¹, Kai Herz², Moritz Fabian¹, Alexander German¹, Andrzej Liebert³, Ingmar Blümcke⁴, Burkhard Kasper⁵, Manuel Schmidt¹, Arnd Dörfler¹, Armin Nagel³, Frederik Laun³, and Moritz Zaiß^1
1Department of Neuroradiology, University Hospital of Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany, ²High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ³Institute of Radiology, University Hospital of Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany, ⁴Institute of Neuropathology, University Hospital of Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany, ⁵Department of Neurology, Epilepsy Centre, University Hospital of Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany

With the help of the presented post-processing procedure, it is possible to obtain an increased reproducibility. For the amide contrast, the CoV decreased from 4% to less than 1.2 %.

Kai Herz^1,2, Sebastian Mueller¹, Maxim Zaitsev³, Linda Knutsson^4,5, Jinyuan Zhou⁵, Phillip Zhe Sun⁶, Peter van Zijl^5,7, Klaus Scheffler^1,2, and Moritz Zaiss^1,8
1Magnetic Resonance Center, MPI for Biological Cybernetics, Tuebingen, Germany, ²Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany, ³Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria, ⁴Medical Radiation Physics, Lund University, Lund, Sweden, ⁵Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁶Yerkes Imaging Center, Emory University, Atlanta, GA, United States, ⁷F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, ⁸Neuroradiology, Friedrich‐Alexander Universität Erlangen‐Nuernberg, Erlangen, Germany

The design of the preparation period is crucial for a CEST experiment, thus, a common, easy-to-use and vendor-independent file format to share exact preparation parameters is desirable. Here, we propose the use of Pulseq to define CEST parameters in an open source and human-readable file format. By providing a protocol database, a pulseq-compatible Bloch-McConnell simulation and a hybrid sequence using Pulseq for CEST preparation, we present a straightforward approach to standardize, share, simulate and measure different CEST preparation schemes, which are inherently completely defined.

Jie Liu¹, Hui Liu², Qi Liu², Jian Xu², Hairong Zheng¹, and Yin Wu^1
1Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, ²United Imaging Healthcare America, Houston, TX, United States

Optimization of acquisition strategies plays a key role in CEST-MRF imaging. However, an effective method to assess the performance of acquisition strategies in CEST quantification is lacking. In this study, we proposed a Cramer-Rao bound (CRB) based metric to measure the accuracy of CEST-MRF in pH quantification under various acquisition schemes. The results of both simulation and phantom experiments showed that the CRB-based index outperformed the conventionally used dictionary similarity metrics that are measured with dot products and Euclidean distance, implying that the proposed algorithm has great potential in optimizing CEST-MRF imaging for improved pH measurement. 

Ying Liu^1,2, Botao Zhao^1,2, and Xiao-Yong Zhang^1,2
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, ²Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China

CEST-MRI has emerged as a noninvasive pH imaging technique based on the pH-dependence of the prototropic exchange rates. In this work, we compared several recently published CEST pH imaging methods and proton exchange rate value in rat glioma models at 11.7T. All of these pH-weighted contrasts show a pH correlation and have significantly different signal intensities between the tumor region and the surrounding normal tissue. Our results demonstrated that pH enhanced method and APT imaging are not concentration-independent while the sensitivity of AACID is affected by the weak amine signals at 2.7ppm.

Ran Sui^1,2,3, Lin Chen^1,2, Yuguo Li^1,2, Jianpan Huang⁴, Kannie W.Y Chan^2,4, Xiang Xu⁵, Peter C.M.van Zijl^1,2, and Jiadi Xu^1,2
1F.M. Kirby Research Center for Functional Brain Imagin, Kennedy Krieger Institute, Baltimore, MD, United States, ²Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ³Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States, ⁴Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China, ⁵BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States

We aim to develop an acquisition and processing pipeline for amideCEST mapping on human brain at 3T. This includes steady-state radial CEST (starCEST) using PROPELLOR-based sampling to acquire Z-spectra that are robust to brain motions and one multi-linear singular value decomposition (MLSVD) post-processing for enhancing the CEST SNR. Finally, the amideCEST peak was quantified using the polynomial and Lorentzian line-shape fitting (PLOF) approach.The amideCEST contrast extracted by the PLOF method trended towards a stronger gray matter (GM) signal (1.33% ± 0.34%) than white matter (WM) (0.92% ± 0.09%; p=0.06, n=4).

Leedan Murray¹, Wilfred W. Lam¹, and Greg J. Stanisz^1,2
1Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, ²University of Toronto, Toronto, ON, Canada

MT and CEST characteristics of DU145 prostate tumour xenografts with known responses to radiation treatment were investigated to determine characteristics that may predict treatment response. After excision for histology, tumours were categorized according to their response to treatment (responder, partial responder and non-responder). Average MTR, qMT parameters, and CEST and rNOE contributions were calculated for each category. Significant changes were mostly observed in the necrotic/apoptotic regions of the tumour and were most evident in the qMT parameters. It may be possible to determine efficacy early on in the course of treatment based on the studied MR characteristics.

Helen Sporkin¹, Toral Patel², Christopher Schumann², Christopher Kramer^2,3, and Craig Meyer^1,3
1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, ²Cardiovascular Medicine, University of Virginia, Charlottesville, VA, United States, ³Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, United States

Patients with peripheral arterial disease (PAD) have been shown to have a delayed phosphocreatine recovery due to chronic ischemia. Creatine chemical exchange saturation transfer (CrCEST) is an MRI technique that allows for creatine concentrations to be monitored at high spatial resolution.  Combining ASL and CrCEST in the same protocol allows for spatial visualization of metabolism and perfusion. The goal of this study is to use this combination to assess changes after revascularization in patients undergoing both endovascular and surgical procedures and evaluate the recovery of both perfusion and metabolism in their muscle tissue.