Diffusion & Microstructure: Fundamentals
Weekend Course
ORGANIZERS: Dmitry Novikov, Ivana Drobnjak
Saturday, 11 May 2019
Room 710B 
08:00  11:30 
Moderators: Ivana Drobnjak, Dmitry Novikov 
Skill Level: Basic to Intermediate
Session Number: WE05A
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., multiexponential), 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 randomwalks 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. Handson exercises will give intuition into the concepts discussed.
Slides in PDF format
Problem sets + solutions

08:45


Diffusion MRI Acquisition, Part I: From Propagator to Image
Jana Hutter, Filip Szczepankiewicz
Singleshot 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, readout accelerations and combinations with additional contrasts such as relaxometry.
Slides in PDF format
Problem sets + solutions

09:30


Break & Meet the Teachers 
10:00


Image Artifacts & Processing Pipelines, Part I
Rita Nunes, Jelle Veraart
Diffusionweighted 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
Slides in PDF format
Problem sets + solutions

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 diffusionweighted 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.
Slides in PDF format
Problem sets + solutions

11:30


Lunch & Meet the Teachers 

Diffusion & Microstructure: Frontiers
Weekend Course
ORGANIZERS: Dmitry Novikov, Ivana Drobnjak
Saturday, 11 May 2019
Room 710B 
13:30  17:00 
Moderators: Dmitry Novikov, Noam Shemesh 
Skill Level: Intermediate to Advanced
Session Number: WE05B
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; multidimensional 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 coarsegraining and the associated timedependence 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 multidimensional diffusion encoding; and
 Identify 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 diffusionweighted 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 coursegraning 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
Slides in PDF format
Problem sets + solutions

14:15


Diffusion MRI Acquisition, Part II: Adding Dimensions
Filip Szczepankiewicz, Jana Hutter
This lecture explores how diffusionweighted experiment can be expanded to include correlations with T1 and T2 relaxation and multidimensional diffusion encoding. The exercises will include calculations relevant to the T2dependent diffusion encoding, and to the design of nonconventional gradient waveforms.
Slides in PDF format
Problem sets + solutions

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 socalled 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 qspace trajectories may play an important role.
Slides in PDF format
Problem sets + solutions

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.
Slides in PDF format
Problem sets + solutions

17:15


Adjournment & Meet the Teachers 
