Yang Zhou¹, Peter van Zijl^2,3, Jiadi Xu^2,3, and Nirbhay N. Yadav^2,3
1Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen, China, ²The Russell H. Morgan Department of Radiology, The 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

A three-pool relayed NOE (rNOE) model and its theoretical solution is formulated to describe the rNOE-based signal in CEST experiments and the analytical solution for rNOE transfer presented. We show that experimental data for glycogen solutions in D₂O and H₂O could be analyzed successfully using this analytical theory, which was further validated using numerical simulations with the Bloch equations. The study increases the understanding of the aliphatic components of Z-spectra of sugar polymers as well as of other macromolecules such as proteins and lipids. 

Tianzhe Li¹, Aikaterini Kotrotsou¹, Shu Zhang¹, Kyle Jones¹, and Mark Pagel^1
1Cancer Systems Imaging, UT MD Anderson Cancer Center, Houston, TX, United States

With the expansion of clinical CEST MRI, the analysis methods for Z-spectra need further validation and optimization. Fitting CEST spectra with the modified Bloch-McConnell equations provides the gold standard for chemical exchange rate (k_ex) quantification, but the current direct-fitting process requires fitting eight parameters. In this study, we have optimized the Bloch-fitting process and incorporated experimentally measured information. We tested the performance of the optimized algorithm using iopamidol phantoms of various pH levels and discovered that including experimentally determined T₁, T₂ and B₀ information can increase the accuracy of the k_ex fitting results.

Maria Gusseva^1,2, Daniel Alexander Castellanos³, Mohamed Abdelghafar Hussein^4,5, Joshua Greer ⁴, Gerald Greil⁴, Surendranath Veeram Reddy⁴, Dominique Chapelle^1,2, Tarique Hussain⁴, and Radomir Chabiniok^1,2,4,6
1Inria, Palaiseau, France, ²LMS, Ecole Polytechnique, Palaiseau, France, ³Department of Cardiology, Boston Children’s Hospital, Boston, MA, United States, ⁴Division of Pediatric Cardiology, UT Southwestern Medical Center Dallas, Dallas, TX, United States, ⁵Pediatric department, Kafrelsheikh University, Kafr Elsheikh, Egypt, ⁶Department of Mathematics, Czech Technical University in Prague, Faculty of Nuclear Sciences and Physical Engineering, Prague, Czech Republic

Time resynchronization of data is often needed when the analysis is based on combining several cardiovascular MRI (CMR) sequences and/or when CMR is combined with a different modality such as pressure catheter during interventional CMR (iCMR). In the present work we propose using patient-specific biophysical model to resynchronize the intraventricular pressure and volume data. The model-driven resynchronization strategy generates pressure-volume (P-V) loops, which can be then used for clinical interpretation. Moreover, the patient-specific model provides additional mechanical indicators of patient's physiology. This framework has the perspective to contribute to planning of complex surgical interventions.

Jan N Rose¹, Ignasi Alemany¹, Andrew D Scott^2,3, and Denis J Doorly^1
1Department of Aeronautics, Imperial College London, London, United Kingdom, ²Cardiovascular Magnetic Resonance unit, Royal Brompton Hospital, London, United Kingdom, ³National Heart and Lung Institute, Imperial College London, London, United Kingdom

Computational simulations and specifically random walks provide a unique opportunity to investigate how several confounding factors might affect the diffusion tensor cardiovascular magnetic resonance (DT-CMR) parameters. We investigate the effect of membrane permeability and diffusion time on the fractional anisotropy (FA) and mean diffusivity in a realistic histology-based 3D substrate considering two common sequence types. Comparing the results from permeable with that from impermeable membranes helps to considerably reduce FA towards levels expected from in-vivo DT-CMR. We further reveal that FA is unaffected by changes in diffusion times above 500ms. A similar, albeit weaker effect is observed regarding MD.

Jan N Rose¹, Andrew D Scott^2,3, and Denis J Doorly^1
1Department of Aeronautics, Imperial College London, London, United Kingdom, ²Cardiovascular Magnetic Resonance unit, Royal Brompton Hospital, London, United Kingdom, ³National Heart and Lung Institute, Imperial College London, London, United Kingdom

In order to facilitate parameter studies of diffusion tensor cardiovascular magnetic resonance through simulations, there is a need to synthesise realistic microstructural substrates. We developed an algorithm to pack arbitrary shapes (polygons) into an arbitrarily shaped target region. We pack cardiomyocytes into the myocardial cell groupings known as sheetlets. In turn, these sheetlets are packed into a voxel. Our method produces a substrate that is comparable to histology in both extra-cellular volume fraction and distribution of extra-cellular space. Future work aims to expand capabilities and extend packing from 2D to 3D.

Anita Monteverdi^1,2, Giuseppe Gagliano², Stefano Casali², Fulvia Palesi^1,2, Claudia AM Gandini Wheeler-Kingshott ^1,2,3, Lisa Mapelli², and Egidio D'Angelo^1,2
1Brain Connectivity Center Research Department, IRCCS Mondino Foundation, Pavia, Italy, ²Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, ³Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom

Neuroimaging studies in humans showed different patterns of BOLD responses in cerebellar vermis and cortical regions when performing tasks at different grip forces. In this study we investigated the basis of different cerebellar fMRI responses ex-vivo. Capillary dilation and neuronal activity were recorded in the vermis and hemisphere of mouse cerebellar slices, highlighting a region and frequency dependency of neurovascular responses in the granular layer. The correlation between neuronal activity and vessel diameter changes was explored through a computational model, which supported a central role played by the NMDAR-NO pathway in shaping the vasodilation time course.

Joerg Peter Pfannmoeller¹, Grant Addison Hartung¹, Xiaojun Cheng², Avery Berman¹, David Boas², and Jonathan Rizzo Polimeni^1
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ²Neurophotonics Center, Boston University, Boston, MA, United States

The stimulus duration depended nonlinearity of the BOLD response is difficult to model, as it often requires stimulus-specific parameter values. Here we have extended an existing framework of BOLD response modeling based on biophysical simulations of realistic microvascular anatomy and dynamics to incorporate viscoelastic properties of individual blood vessels and tissue. We then applied this model to examine BOLD response nonlinearities to long-duration stimuli. We find that this model largely captures the differences in BOLD responses observed to short- and long-duration stimuli.

Luo Bao fa¹, Huang Yi long¹, Yang Kai wen¹, Nie Li sha², and He Bo^1
1The First Affiliated Hospital of Kunming Medical University, kunming, China, ²GE Healthcare, MR Research China, Beijing, Beijing, China

In this study, a discogenic low back pain (DLBP) model was established by puncture of rat  intervertebral disc under the guidance of X-ray, and functional magnetic resonance imaging (fMRI) was performed on paravertebral muscles of DLBP rats to explore the feasibility of the DLBP model and the changes of T2 value and R2*value of paravertebral muscles in the early stage of DLBP. The conclusion is that it is feasible to construct DLBP rat model by X-ray guided puncture of intervertebral disc, and the T2 value changes earlier than R2*in the early stage of DLBP.

Atena Akbari¹, Saskia Bollmann¹, and Markus Barth^1,2,3
1Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia, ²School of Information Technology and Electrical Engineering, Brisbane, Australia, ³ARC Training Centre for Innovation in Biomedical Imaging Technology, Brisbane, Australia

Depth-dependent high resolution fMRI studies in animals and humans hold promise to reveal the input-output and feedforward-feedback connections across cortical layers. However, our understanding of the underling physiology is limited. In this work, using a cortical vascular model we simulated BOLD and VASO signal changes in human primary motor cortex.

Yuan Le¹, Andrew J. Fagan¹, Jun Chen¹, Eric G. Stinson², Joel P. Felmlee¹, Matthew C. Murphy¹, Kevin J. Glaser¹, Arvin Arani¹, Phillip J. Rossman¹, Stephan Kannengiesser³, Bradley D. Bolster, Jr.², John Huston, III¹, and Richard L. Ehman^1
1Radiology, Mayo Clinic, Rochester, MN, United States, ²Siemens Medical Solutions USA, Inc., Malvern, PA, United States, ³Siemens Healthcare GmbH, Erlangen, Germany

This study aimed to compare MRE image quality and stiffness measurements performed at 3T and 7T. It was found that in PVC phantom images the estimated stiffness values were very close between images acquired at 7T and 3T; the signal-to-noise ratio (SNR) at 7T was much higher than that at 3T, and the octahedral shear strain based SNR more than doubled at 7T. These results indicate potential of obtaining high resolution MRE images without affecting the stiffness measurement at 7T.

Chiara Coletti¹, Sebastian Domsch¹, Frans Vos¹, and Sebastian Weingärtner^1
1Imaging Physics, TU Delft, Delft, Netherlands

Functional imaging based on detection of neuronal currents using spin-lock prepared MRI may overcome limitations inherent to haemodynamic fMRI with BOLD. However, in-vivo application is hindered by system imperfections. In this work, the effects of B₀ and B₁⁺  inhomogeneities and background noise on neuro-current MRI signals are quantified. Furthermore, a new statistical data-processing technique based on the analysis of signal variability, SVarM, is proposed for neuro-current MRI time series. SVarM achieves overall higher sensitivity than existing data-processing methods and is shown to be more robust in the presence of system imperfections.

Xiaowei Zou¹, Venkata V Chebrolu², and Nakul Gupta^3
1Siemens Medical Solutions USA Inc., Houston, TX, United States, ²Siemens Medical Solutions USA Inc., Rochester, MN, United States, ³Department of Radiology, Houston Methodist Research Institute, Houston, TX, United States

Fat-suppressed turbo-spin-echo (TSE) imaging is very important to visualize knee pathology such as cartilage defects in clinical routine. Ultra-high-field 7T magnetic resonance imaging (MRI) provides higher signal-to-noise-ratio (SNR) and contrast-to-noise-ratio (CNR) than 3T and 1.5T MRI, enabling better visualization of fine anatomical structures and physiological effects. However, imaging at 7T has higher receive and transmit non-uniformity that may degrade its clinical value. Recently, a UNIform COmbined RecoNstruction (UNICORN) algorithm was proposed for reducing the receive non-uniformity.  The purpose of this preliminary work is to quantitatively and qualitatively evaluate and optimize UNICORN performance for 7T clinical TSE with fat suppression.

Ludger Starke¹, Thoralf Niendorf¹, and Sonia Waiczies^1
1Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany

Labeling cells with ¹⁹F nanoparticles (NPs) continues to elicit interest for non-invasive localization of inflammation and monitoring immune cell therapy. Systematic overestimation in low SNR MRI of ¹⁹F-NPs has been previously described which needs to be corrected for valid quantitative conclusions. We develop a statistical model which successfully compensates this bias and demonstrate its efficacy for the correct estimation of signal intensities on neuroinflammation data acquired in a mouse model of multiple sclerosis. The correction only relies on the image data itself and promises to be a valuable contribution to the development of reliable quantitative ¹⁹F MRI.

Zhixin Li^1,2,3, Yue Wu^1,2,3, Dongbiao Sun^1,2,3, Jing An⁴, Qingle Kong⁵, Rong Xue^1,2,3, Yan Zhuo^1,2,3, and Zihao Zhang^1,2,3
1State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China, ²The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, China, ³University of Chinese Academy of Sciences, Beijing, China, ⁴Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, ⁵MR Collaboration, Siemens Healthcare Ltd, Beijing, China

Due to the possible interaction between cerebral small vessel disease (CSVD) and a variety of brain diseases or pathological changes, people's interest in small vessel pathology was growing. With the increased imaging resolution at ultra-high field MRI, imaging cerebral small vessels become feasible with TOF-MRA sequence. In this study, we introduced an automated vascular segmentation and tracing method based on deep learning, machine learning and multi filtering. Our method performed well for the multistage branching of cerebral vessels, and could quantitatively evaluate the vasculature. The technique was potentially useful for the clinical studies of CSVD.

Joana Pinto¹, Nicholas P. Blockley², James W. Harkin³, and Daniel P. Bulte^1
1Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom, ²School of Life Sciences, University of Nottingham, Nottingham, United Kingdom, ³Respiratory Medicine Department, School of Medicine, University of Nottingham, Nottingham, United Kingdom

Despite most ASL cerebrovascular reactivity (CVR) studies being based on single-PLD approaches, it has been shown that the vascular spatiotemporal dynamics of cerebral blood flow (CBF)  are altered during hypercapnia. This ultimately leads to inaccuracies in some ASL modelling assumptions, compromising CVR assessment. In this work, we test several multiple-PLD ASL modelling strategies and assess their impact on CBF dynamics and CVR assessment. In particular, the individual and combined impact of estimating dispersion effects and the macrovascular signal are evaluated in terms of quantification of several haemodynamic parameters using multiple-PLD ASL data during two different conditions (resting-state and hypercapnia).

Anita Monteverdi^1,2, Fulvia Palesi^1,2, Claudia AM Gandini Wheeler-Kingshott ^1,2,3, and Egidio D'Angelo^1,2
1Brain Connectivity Center Research Department, IRCCS Mondino Foundation, Pavia, Italy, ²Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, ³NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, UCL, London, United Kingdom

The Virtual Brain (TVB) has been recently developed to simulate whole-brain dynamics in healthy and pathological conditions, including only cerebral nodes. However, it has been demonstrated that the integration of cerebro-cerebellar connections in TVB can improve its predictive power. Thus, in this study we integrated cerebro-cerebellar connectivity in TVB simulation exploring its impact on prediction of brain dynamics in three different conditions: healthy, Alzheimer’s disease and Frontotemporal Spectrum Disorder. Notably we demonstrated that cerebro-cerebellar circuits integration in the TVB further improve its predictive power, both in healthy and pathological states.

Grant Hartung¹, Joerg Pfannmoeller¹, Avery J. L. Berman¹, and Jonathan R. Polimeni^1
1Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, United States

Here we extend a recent approach employing biophysical simulations of realistic cortical microvascular anatomy and dynamics to test whether the topology of the microvasculature impact the BOLD response. We create 3D vascular anatomical networks with varying ratios of arteries to venules and simulated the effects on cerebral blood flow and volume responses. We observed a difference in the cerebral blood volume response after we varied the ratio of diving arteries to ascending veins.

Patricia Pais-Roldan¹, Seong Dae Yun¹, and Jon N Shah^1
1Forschungszentrum Juelich, Juelich, Germany

Due to their rapid acquisition and high contrast-to-noise-ratio, MRI sequences based on gradient-echo (GE) schemes, e.g., gradient-echo echo-planar-imaging (GE-EPI), are the most commonly used method in human functional MRI. However, their enhanced sensitivity to veins restricts their use in laminar fMRI due to poor signal localization, i.e., venous bias. Here, we investigated the spatial specificity of high-resolution GE signals, pre-processed with ten different approaches. Removal of motion parameters, physiological signals and non-GM tissue contributions, as well as regression of the pre-processed phase image from the magnitude image, significantly increased the spatial specificity of GE-fMRI in resting-state and task paradigms.

Nolan K Meyer¹, Daehun Kang², MyungHo In², John Huston², Yunhong Shu², Matt A Bernstein², and Joshua D Trzasko^2
1Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, United States, ²Radiology, Mayo Clinic, Rochester, MN, United States

Locally low-rank (LLR) regularization is extended to a multi-echo tensor framework for resting-state fMRI, building on previous generalizations of LLR frameworks. We demonstrate substantial increases in temporal SNR with improved robustness in mapping default mode, auditory, and sensorimotor resting-state connectivity networks in a preliminary seed-based analysis.

Stefan Winzeck^1,2, Maíra Siqueira Pinto³, Virginia F. J. Newcombe², Ben Glocker¹, David K. Menon², and Marta M. Correia^4
1BioMedIA, Department of Computing, Imperial College London, London, United Kingdom, ²Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, United Kingdom, ³Universitair Ziekenhuis Antwerpen, Antwerp, Belgium, ⁴MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom

This study compares the impact of voxel-wise versus region-wise harmonisation of diffusion-weighted imaging (DWI) signal via Z-scoring and ComBat. Both approaches and algorithms were shown equally effective in significantly reducing the variation in regionally observed FA and MD in a multi-acquisition DWI dataset.