View Presentation Video

Andreea Hertanu¹, Quentin Uhl¹, Tommaso Pavan¹, Christophe M. Lamy², and Ileana O. Jelescu^1
1Dept. of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland, ²Division of Anatomy, Faculty of Medicine, University of Geneva, Geneva, Switzerland

Keywords: Microstructure, Modelling, Diffusion

In this work, we characterized microstructure properties of cortical gray matter and hippocampus using diffusion MRI, on two samples of postmortem fixed healthy human brain. The weak-to-absent diffusivity time-dependence and marked kurtosis time-dependence supported the suitability of the Neurite Exchange Imaging (NEXI) model to probe postmortem human gray matter microstructure. NEXI parametric estimations revealed region-specific values, calling for further validation using histology and further clarifying the discrepancy between compartment diffusivities estimated here vs. the literature. This study offers an important window on human gray matter microstructure at a spatial resolution unachievable in vivo.

View Presentation Video

Nathan Hu Williamson¹, Rea Ravin^1,2, Teddy Xuke Cai^1,3, and Peter Joel Basser^1
1NICHD, NIH, Potomac, MD, United States, ²Celoptics, Rockville, MD, United States, ³Wellcome Centre for Integrative Neuroimaging, Oxford, Oxford, United Kingdom

Keywords: Diffusion/other diffusion imaging techniques, Neuroscience, Microstructure

Diffusion-weighted imaging (DWI) and intrinsic optical signal (IOS) are both used to measure neural tissue structure and function. Here we demonstrate with simultaneous real-time low-field, high-gradient MR and optical microscopy that DW signals and IOS share a similar contrast mechanism, most likely the ratio between intracellular and extracellular volume. Signals monitor how cells are affected and respond to adverse conditions, providing novel insight into pathological mechanisms and links between structure and function.

View Presentation Video

Rhea Carlson¹, Courtney Comrie¹, Justina Bonaventura², Kellys Morara¹, Noelle Daigle², Elizabeth Hutchinson¹, and Travis W. Sawyer^1,2
1Biomedical Engineering, University of Arizona, Tucson, AZ, United States, ²Wyant College of Optical Sciences, University of Arizona, Tucson, AZ, United States

Keywords: Data Acquisition, Multimodal, Polarized Light Imaging, Optics, Ferret

This study uses complete polarimetry to capture diattenuation and retardance in post-mortem ferret optic chiasm (OC) chosen for its well understood fiber structure. These methods are novel due to the limited analysis of diattenuation metrics on tissue. Our results suggest that retardance measurements are sensitive to microscale features rather than to macroscale geometry when compared to fractional anisotropy (FA) and propagator anisotropy (PA). In addition, we have shown fiber orientation distributions (FODs) created through direct optical measurement of the tissue on a 2D plane are comparable to diffusion FODs.

View Presentation Video

Kristofor Pas¹, Kadharbatcha Saleem¹, Peter J Basser¹, and Alexandru V Avram^1,2,3
1Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States, ²Center for Neuroscience and Regenerative Medicine, Bethesda, MD, United States, ³Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD, United States

Keywords: Microstructure, Gray Matter, MAP-MRI, cortical parcellation, cortical layers

We investigate the feasibility of using advanced diffusion MRI, specifically MAP-MRI, to automatically segment microstructural domains based on subject-specific intrinsic cortical cytoarchitectonic features. Our preliminary results suggest that MAP-derived cytoarchitectonic domains delineate boundaries between cortical areas and layers in good agreement with histology. Segmentation methods that leverage the sensitivity of high-resolution MAP parameters to cortical cytoarchitecture have the potential to augment and refine current techniques for automatic cortical parcellation that rely on atlas registration.

View Presentation Video

Silei Zhu¹, Istvan N. Huszar¹, Nicole Eichert¹, Michiel Cottaar¹, Greg Daubney², Alexandre Khrapitchev³, Rogier B. Mars^1,4, Jeroen Mollink¹, Connor Scott⁵, Adele Smart^1,5, Jerome Sallet², Saad Jbabdi¹, Karla Miller*¹, and Amy Howard*^1
1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, ²Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, University of Oxford, Oxford, United Kingdom, ³Department of Oncology, University of Oxford, Oxford, United Kingdom, ⁴Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands, ⁵Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

Keywords: Tractography & Fibre Modelling, Multimodal, diffusion MRI, microscopy

We present data fusion combining precisely co-registered dMRI and microscopy to reconstruct 3D fibre orientation with micron-scale spatial resolution. We then perform hybrid dMRI-microscopy tractography to investigate two known challenges in tractography: the gyral bias and bottleneck problems. Our results using hybrid tractography suggest that the gyral bias can be overcome by increased spatial resolution, and that microstructure-informed fibre orientations can overcome the bottleneck problem, irrespective of spatial resolution. These observations can be used to inform tractography analyses in vivo. This approach builds on the complementary strengths of microscopy (high spatial resolution) and dMRI (3D whole-brain coverage).

View Presentation Video

Sara Bosticardo^1,2, Matteo Battocchio^1,3, Simona Schiavi⁴, Cristina Granziera^2,5,6, and Alessandro Daducci^1
1Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy, ²Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, University of Basel, Basel, Switzerland, ³Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d’Informatique, Université de Sherbrooke, Sherbrooke, QC, Canada, ⁴Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy, ⁵Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University of Basel, Basel, Switzerland, ⁶Department of Neurology, MS Center, University Hospital Basel, Basel, Switzerland

Keywords: Diffusion/other diffusion imaging techniques, Brain Connectivity

The white matter is the complex system of neuronal fibers in the brain. Any disruption to this circuitry may lead to a wide range of neurological diseases and, thus, it is fundamental to be able of detecting pathological conditions at early stages. State-of-the-art methods for studying brain connectivity assume constant properties along the fibers, but this assumption is not valid in pathological conditions that locally affect the tissue, e.g. multiple sclerosis. Here, we present a model for “multi-compartment connectomes” to explicitly consider the presence of focal lesions during the estimation of connectivity and show its effectiveness using realistic numerical simulations.

View Presentation Video

Ying Liao¹, Santiago Coelho¹, Jenny Chen¹, Dmitry S. Novikov¹, and Els Fieremans^1
1Radiology, NYU School of Medicine, NEW YORK, NY, United States

Keywords: Diffusion/other diffusion imaging techniques, Diffusion/other diffusion imaging techniques

Multiple sclerosis (MS) is a neurodegenerative and inflammatory disease characterized by focal lesions and damages to normal appearing white matter (NAWM). Diffusion MRI (dMRI) is known for its sensitivity to the microstructural changes in white matter. In this work, we study the sensitivity of dMRI metrics to MS pathology in NAWM by distinguishing MS patients from healthy controls. We found that beyond-spherical-mean rotational invariants of high-b shells contribute mostly to the classification, indicating nontrivial information content of high-b diffusion signal beyond DTI.

View Presentation Video

Mustapha Bouhrara¹, Alexandru V Avram², Matthew Kiely¹, Aparna Trivedi¹, and Dan Benjamini^1
1National Institute on Aging, Baltimore, MD, United States, ²National Institute of Child Health and Human Development, Bethesda, MD, United States

Keywords: Diffusion/other diffusion imaging techniques, Aging

The relationship between brain microstructure and aging has been the subject of intense study. We used the mean apparent propagator (MAP) MRI framework, which is suitable to characterize diffusion in complex microstructure, to investigate age-related differences in a cohort of cognitively unimpaired participants, spanning a wide age range. In white matter, we established an opposing pattern of higher non-Gaussianity (NG) alongside lower propagator anisotropy (PA) among older adults. In gray matter, these two indices were consistent with one another, and exhibited regional pattern heterogeneity compared to other microstructural parameters. These results suggest that MAP-MRI provides otherwise inaccessible regional microstructural information.

View Presentation Video

Noam Shemesh¹, Rita Alves², Jonas Olesen^3,4, Andrada Ianus¹, and Sune Nørhøj Jespersen^3,4
1Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal, ²Champalimaud Foundation, Lisbon, Portugal, ³Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark, ⁴Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark

Keywords: Contrast Mechanisms, Microstructure

Membrane permeability plays an important role in numerous physiological processes ranging from cell volume regulation to neural activity. Until now, diffusion MRI measurements mainly provided information on exchange rates; however, to map permeability, information on the surface-to-volume (S/V) ratio is needed. Here, we apply ultrahigh frequency OGSE to infer on S/V from the associated power law dependence (1/ω^1/2,) and the Standard Model with Exchange (SMEX) model for extracting the neurite -> extracellular space exchange rates in stroked rat brains. Combined, we present quantitative measurements of permeability which show plausible values and striking contrast in stroke.

View Presentation Video

Emily Hoffmann¹, Mirjam Gerwing¹, Stephan Niland², Rolf Niehoff¹, Max Masthoff¹, Enrica Wilken¹, Philipp Berger³, Thomas Vogl³, Johannes A. Eble², Bastian Maus¹, Anne Helfen¹, Moritz Wildgruber^1,4, and Cornelius Faber^1
1Clinic of Radiology, University of Münster, Münster, Germany, ²Institute of Physiological Chemistry and Pathobiochemistry, University of Münster, Münster, Germany, ³Institute of Immunology, University of Münster, Münster, Germany, ⁴Department of Radiology, LMU Munich, Munich, Germany

Keywords: Cancer, Tumor, T-cells, macrophages, immunotherapy

Immune cells are major players of the tumor microenvironment (TME), having profound effects on tumor development and metastatic progression. We present oscillating-gradient diffusion-weighted MRI (OGSE-DWI) as non-invasive imaging approach to monitor the intratumoral immune cell infiltrate, relying on size differences between cancer cells, T-cells and macrophages. By applying the Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion (IMPULSED) model to sine-shaped OGSE-DWI, changes within the TME and its specific immune cell composition were monitored and compared in syngeneic murine breast cancer models with different degrees of malignancy during tumor progression, clodronate liposome-mediated depletion of macrophages and immune checkpoint inhibitor treatment.

Junting Guo¹, Lu Zhang¹, Shuo Li¹, Ding Li¹, Zhichang Fan¹, Meining Chen², Guoqiang Yang³, Yan Li³, Bin Wang³, Le Wang³, and Xiaochun Wang^3
1College of Medical Imaging, Shanxi Medical University, Taiyuan, China, ²MR Scientific Marketing, Siemens Healthcare, Shanghai, China, ³Department of Radiology, The First Hospital of Shanxi Medical University, Taiyuan, China

Keywords: Diffusion/other diffusion imaging techniques, Cancer

Accurate assessment of the presence or absence of muscle invasiveness in bladder cancer is essential for selecting the best treatment options. In this study, we used 6 diffusion models including mono-exponential model (Mono), continuous-time random-walk (CTRW), incoherent motion within the voxel (IVIM), stretched exponential model (SEM), diffusion kurtosis imaging (DKI) and fractional-order calculus (FROC) model to assess muscle invasiveness in bladder cancer. The study showed that Mono,CTRW,IVIM,SEM and DKI could provide biomarkers for muscle invasion and distinguish non-muscle-invasive and muscle-invasive bladder cancer, and the combination of CTRW and FROC could further improve  the classification accuracy.

View Presentation Video

Lukas Lundholm¹, Mikael Montelius¹, Oscar Jalnefjord^1,2, Eva Forssell-Aronsson^1,2, and Maria Ljungberg^1,2
1Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, ²Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden

Keywords: Diffusion/other diffusion imaging techniques, Cancer, VERDICT, preclinical, histology

Characterization of tumor tissue may aid in grading and assessment of cancer treatment. Time-dependent diffusion MRI can provide non-invasive estimates of parameters relating to tissue microstructure in vivo. In this study, a cluster analysis was performed to group parameters estimated by the time-dependent diffusion MRI model VERDICT. Parameter cluster maps were compared with maps derived from classification of histological images. The results showed good agreement between VERDICT cluster maps and histology maps, indicating that the method shows potential in identifying tumor subregions of distinct morphological features.

View Presentation Video

Ezequiel L. Saidman¹, Analia Zwick ^1,2,3, Stefano Tambalo ⁴, Thorsten Feiweier⁵, Jorge Jovicich⁴, and Gonzalo A. Alvarez^1,2,3
1Instituto Balseiro, CNEA, Universidad Nacional de Cuyo, S. C. de Bariloche, Argentina, ²Centro Atómico Bariloche, CONICET, CNEA, S. C. de Bariloche, Argentina, ³Instituto de Nanociencia y Nanotecnologia, CNEA, CONICET, S. C. de Bariloche, Argentina, ⁴Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy, ⁵Siemens Healthcare GmbH, Erlangen, Germany

Keywords: Diffusion/other diffusion imaging techniques, Microstructure

Magnetic resonance imaging is one of the most widely used methods for non-invasive medical imaging. Gradient modulation sequences can selectively extract quantitative information at micrometer and sub-micrometer scales that might be relevant for clinical applications. We approach this topic using white matter phantoms by observing the contrast generated by Non-uniform Oscillating Gradient Spin Echo (NOGSE) sequences to selectively filter the signal of molecules confined in compartments of specific sizes. The NOGSE contrast is determined by subtracting different OGSE acquisitions on a clinical scanner. Our results demonstrate a microscopic tortuosity mechanism that provides microstructural information at short time scales.

View Presentation Video

Daan Christiaens^1,2, J-Donald Tournier³, Stefan Sunaert^2,4, and Frederik Maes^1,2
1Dept. of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium, ²Medical Imaging Research Center, UZ Leuven, Leuven, Belgium, ³Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ⁴Department of Imaging & Pathology, Translational MRI, KU Leuven, Leuven, Belgium

Keywords: Microstructure, Diffusion/other diffusion imaging techniques

Microstructure imaging with diffusion MRI relies on non-linear fitting of a biophysical tissue model to the data, often at low signal-to-noise ratio. In this work, we derive a new rotation-invariant feature set for microstructure mapping based on a rank-1 decomposition of the multi-shell diffusion MRI signal in spherical harmonics. Simulations show that using this feature set avoids non-central-χ bias that is present at low SNR in parameter estimation based on conventional rotation-invariants. Results in human brain imaging data acquired with free waveform diffusion encoding show robust parameter estimates across white matter.

View Presentation Video

Santiago Coelho¹, Els Fieremans¹, and Dmitry S. Novikov^1
1Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, United States

Keywords: Diffusion/other diffusion imaging techniques, Data Acquisition

In brain dMRI, microstructure parameters of fiber fascicles, such as compartment fractions, exchange, diffusivities, relaxation rates, and structural disorder, are highly sought after. They can be accessed by sampling multiple diffusion weightings, b-tensor shapes, diffusion and/or echo times. Yet most scan time is spent oversampling the fiber orientation distribution function – because factoring it out nominally requires rotational invariants like the spherical mean. We show how to measure multiple inequivalent combinations of $$$(b,\,\Delta)$$$, while spending single gradient directions per unique combination. We recover signal’s rotational invariants for each one and use them for biophysical modeling of white and gray matter.

View Presentation Video

Jelle Veraart¹, Erika P. Raven¹, Derek K. Jones², and Marco Palombo^2,3
1Center for Biomedical Imaging, Dept. Radiology, NYU Grossman School of Medicine, New York, NY, United States, ²Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom, ³School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom

Keywords: Diffusion/other diffusion imaging techniques, Microstructure, Modeling, Axon Diameter Mapping

The specificity of strongly diffusion-weighted MRI to intra-axonal signal contributions to neuronal processes has always been presumed. Here we demonstrate empirically that strongly diffusion-weighted MRI data is also sensitive to a distinct isotropic compartment that may bias axon diameter estimates.  We hypothesize that such a compartment represents isotropically-distributed glial processes.  We use in vivo human data and Monte Carlo simulations to support our hypothesis and evaluate a novel strategy to suppress signal arising from glial cell bodies and processes to promote more accurate axon diameter mapping.

View Presentation Video

Hong-Hsi Lee^1,2, Qiyuan Tian^1,2, Ricardo Coronado-Leija³, Els Fieremans³, Dmitry S Novikov³, and Susie Y Huang^1,2
1Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ²Radiology, Harvard Medical School, Boston, MA, United States, ³Center for Advanced Imaging Innovation and Research, New York University School of Medicine, New York, NY, United States

Keywords: Validation, Microstructure

To disentangle the effect of complex features on axon diameter mapping, we segmented myelinated axons in a human brain electron microscopy data and use these to create artificial cylinders with undulations and caliber variations that can be tuned to varying degrees. Diffusion simulations in segmented real axons and artificial axons showed that undulations and beadings lead to overestimation and underestimation of the axon diameter, respectively.

View Presentation Video

Anders Dyhr Sandgaard¹, Valerij G. Kiselev², Noam Shemesh³, and Sune Nørhøj Jespersen^1,4
1Center for functionally integrative neuroscience, department of clinical medicine, Aarhus University, Aarhus, Denmark, ²Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany, ³Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, ⁴Department of Phsysics and Astronomy, Aarhus University, Aarhus, Denmark

Keywords: Microstructure, Diffusion/other diffusion imaging techniques

Estimating parameters of the Standard Model (SM) of white matter (WM) is an ill-posed problem (WM). To overcome this degeneracy, models extensions have been proposed adding echo-time dependent information. Here we investigate the feasibility of incorporating our analytical solution for the frequency shift from white matter axons accounting for magneto-structural anisotropy along with an empirical orientation dependence of relaxation into SM parameter estimation. This may also help achieving rotation-free mapping of susceptibility-related parameters using diffusion MRI instead of the impractical sample rotation in the scanner.

View Presentation Video

Naoki Ohno¹, Tosiaki Miyati¹, Genki Nambu¹, Daichi Tanaka¹, Yuki Makino¹, Noam Alperin², Yu Ueda³, Marc Van Cauteren³, Toshifumi Gabata¹, and Satoshi Kobayashi^1
1Kanazawa University, Kanazawa, Japan, ²University of Miami, Miami, FL, United States, ³Philips Japan, Tokyo, Japan

Keywords: Diffusion/other diffusion imaging techniques, Diffusion/other diffusion imaging techniques

Diffusion imaging with phase-contrast (DIP) can quantitatively evaluate regional cerebral blood flow (rCBF), in which total CBF (tCBF) from phase-contrast magnetic resonance imaging (PC-MRI) converts the brain’s perfusion-related diffusion parameters into rCBF values. However, it is sensitive to bulk motion (i.e., brain pulsation), potentially causing an overestimation of DIP-derived rCBF values. To overcome this issue, we propose a motion-compensated DIP (MC-DIP) that incorporates motion-compensated diffusion gradients. DIP with second-order motion-compensated diffusion gradients (2nd-MC-DIP) improved the fitting accuracy of the biexponential analysis and showed the ability to quantitatively evaluate rCBF in gray and white matter.
 

View Presentation Video

Emmanuel Caruyer^1
1IRISA UMR 6074, Empenn ERL 1228, Univ Rennes, CNRS, Inria, Inserm, Rennes, France

Keywords: Diffusion/other diffusion imaging techniques, Data Acquisition

Diffusion-encoding gradient waveforms are a key parameter of experimental design in diffusion magnetic resonance imaging. Their optimization is important for e.g. maximizing the efficiency in B-tensor encoding, or improving the sensitivity and specificity to microstructure parameters of biophysical models. The main challenge in optimizing gradient waveforms and trajectories is the large dimension of the search space and the constraints associated with physical and physiological limitations. Here we propose an original piecewise polynomial representation, which natively enforces the linear constraints that arise from refocusing and regularity. We illustrate the basis on B-tensor encoding and Monte-Carlo simulation of the diffusion signal.