27th ISMRM Annual Meeting • 11-16 May 2019 • Montréal, QC, Canada

Weekend Educational Session
Diffusion & Microstructure: Fundamentals & Frontiers

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Diffusion & Microstructure: Fundamentals
Weekend Course

ORGANIZERS: Dmitry Novikov, Ivana Drobnjak

 
Saturday, 11 May 2019
Room 710B 08:00 - 11:30 Moderators:  Dmitry Novikov, Ivana Drobnjak, Alexander Leemans, Noam Shemesh, C-F Westin

Skill Level: Basic to Intermediate

Session Number: WE-05A

Overview
This course will discuss the foundations of diffusion physics and basic experimental design, followed by an overview of basic image artifacts, standard representations of diffusion signal, and simple models. This year’s educational session on diffusion has two distinct features: (1) It has been designed as a coherent course by all the teachers together from the outset; (2) it combines lectures with exercises. For the exercises, which will be given during the lectures and subsequently solved and discussed, please bring paper and pencil. This morning course serves as an introduction to the subsequent advanced course in the afternoon designed according to the same principles. 

Target Audience
Researchers and clinicians who are interested in understanding the basics of molecular diffusion, design diffusion experiments, gain familiarity with common artifacts and ways to correct them, perform basic parameter estimation of standard diffusion metrics (such as DTI and DKI), and understand the difference between biophysical models and signal representations. 

Educational Objectives
As a result of attending this course, participants should be able to:
- Explain the basic physics of diffusion;
- Describe basic diffusion MRI sequences;
- Identify common imaging artifacts and the associated biases in the measured parameters;
- Compare and contrast biophysical models (e.g., multi-exponential), and signal representations, such as DTI and DKI.
 

 

 
08:00
 
  Fundamentals of Diffusion
Marco Palombo, Chantal Tax
This lecture introduces key concepts behind the physics of diffusion MRI (dMRI) signal contrast, and motivate why these concepts are relevant in the context of quantifying tissue microstructure. Following this lecture, researchers and clinicians who are interested in understanding the basics of molecular diffusion, will gain intuition about the diffusion process as conceptualised by random-walks of particles, familiarise with representing the diffusion process by the diffusion propagator, understand the regimes in which the diffusion can and cannot be considered Gaussian and understand how these concepts are relevant in the context of tissue microstructure. Hands-on exercises will give intuition into the concepts discussed.

 
08:45
 
  Diffusion MRI Acquisition, Part I: From Propagator to Image
Jana Hutter, Filip Szczepankiewicz
Single-shot Pulsed Gradient Spin Echo echo planar imaging remains the most commonly used sequence for diffusion MRI. However, recent years have seen numerous extensions. This lecture will introduce both the basic modular elements and more experimental novel approaches including modified diffusion preparations, read-out accelerations and combinations with additional contrasts such as relaxometry.

 
09:30
 
  Break & Meet the Teachers
10:00
 
  Image Artifacts & Processing Pipelines, Part I
Rita Nunes, Jelle Veraart
Diffusion-weighted images (DWI) are corrupted by noise and various imaging artifacts such as Gibbs ringing, EPI and eddy current distortions, motion and other physiological artifacts. The correction of those artifacts is of utmost importance to improve the qualitative, quantitative and statistical inspection of the diffusion data. Here we will give an overview of the major image artifacts, explain how they might confound the DWI analysis, and how they can be corrected for or at least minimized at source or using image processing

 
10:45
 
  Diffusion MRI Models & Representations
Chantal Tax, Marco Palombo
The lecture provides researchers and clinicians who use or are planning to use dMRI to quantify the diffusion process and/or tissue microstructure with the basic tools to extract relevant features from the diffusion-weighted signal. The language of the dMRI community regarding signal modelling and representation is introduced. Examples of both signal representations going beyond the Gaussian diffusion regime, and model parameter estimation, are used to give intuition of how these concepts are relevant in the context of tissue microstructure. By solving exercises, the audience will gain intuition into the concepts discussed in the lecture.

 
11:30
 
  Lunch & Meet the Teachers
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Diffusion & Microstructure: Frontiers
Weekend Course

ORGANIZERS: Dmitry Novikov, Ivana Drobnjak

 
Saturday, 11 May 2019
Room 710B  13:30 - 17:00 Moderators:  Dmitry Novikov, Ivana Drobnjak, Alexander Leemans, Noam Shemesh, C-F Westin

Skill Level: Intermediate to Advanced

Session Number: WE-05B

Overview
Relying on the introductory material presented in the morning, this advanced course will discuss currently used microstructural models, their assumptions, and parameter estimation pitfalls; ways to combine correlations with T1 and T2 relaxation; multi-dimensional diffusion encodings; and advanced artifact correction methods and pipelines. Similar to the morning session, this session has two distinct features: (1) It has been designed as a coherent course by all the lecturers together from the outset; (2) it combines lectures with exercises. For the exercises, which will be given during the lectures and subsequently solved and discussed, please bring paper and pencil. 

Target Audience
Researchers and clinicians brave enough to explore the frontiers of modern tissue microstructure mapping and solve challenging exercises. 

Educational Objectives
As a result of attending this course, participants should be able to:
- Explain the concept of coarse-graining and the associated time-dependence of diffusion metrics;
- State the assumptions behind the Standard Model of diffusion in white matter, and understand the degeneracies in estimating its parameters; 
- Describe advanced diffusion MRI sequences employing T1, T2 contrasts and multi-dimensional diffusion encoding;
- Understand the ideas and benefits of denoising algorithms, Gibbs ringing removal, outlier detection, and other advanced image processing methods. 
 

 

 
13:30
 
  Microstructure Models, Part I
Valerij Kiselev, Sune Jespersen
We discuss the principles of accessing the tissue microstructure using diffusion MRI. This challenge is decomposed into the forward and inverse problems: the biophysical modeling of the diffusion-weighted MRI signal, and the model parameter estimation, respectively. We focus on the former and briefly discuss the latter. The central phenomenon for the biophysical modeling is the course-graning of the structural details by diffusion. It will be discussed for the regimes of short times (when diffusion reveals the interface surface per unit volume) to long times (when diffusion becomes sensitive to the overall structural organization of tissues). The case of impermeable compartments will be treated separately to clarify the sensitivity of diffusion measurements to the size of small cells

 
14:15
 
  Diffusion MRI Acquisition, Part II: Adding Dimensions
Filip Szczepankiewicz, Jana Hutter
This lecture explores how diffusion-weighted experiment can be expanded to include correlations with T1 and T2 relaxation and multidimensional diffusion encoding. The exercises will include calculations relevant to the T2-dependent diffusion encoding, and to the design of non-conventional gradient waveforms.

 
15:00
 
  Break & Meet the Teachers
15:45
 
  Microstructure Models, Part II
Sune Jespersen, Valerij Kiselev
We discuss tissue microstructure from the point of view of biophysical modeling, using the so-called Standard Model of diffusion in the brain as our primary example. We review its assumptions, potential regimes of validity, validation studies, and approaches for parameter estimation. Prominent among these are “orthogonal measurements”, where e.g. diffusion pulse sequences employing generalized q-space trajectories may play an important role.

 
16:30
 
  Image Artifacts & Processing Pipelines, Part II
Jelle Veraart, Rita Nunes
In the second part of this topic, we focus on more advanced image processing methods. We will give an overview of image denoising methods, Gibbs ringing removal, outlier detection, frequency stabilization, effects of gradient nonlinearity, and discuss challenges of pushing for higher spatial resolution.

 
17:15
 
  Adjournment & Meet the Teachers
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