OUTLINE:

•Why MRF and how it is used in epilepsy

•Some technical aspects of MRF

•Other clinical use of MRF 

•Further tech development

•Challenges and future of clinical MRF

Clinical 7T MRI is a relatively new tool for the evaluation of medically refractory epilepsy.   Offering improved signal to noise ratio and spatial resolution over MRI at 1.5 and 3.0 Tesla field strengths, 7T MRI can potentially identify very subtle epileptogenic lesions such as cortical dysplasias in patients that have previously been classified as "MRI negative".  Additional epileptogenic pathologies better demonstrated with 7T MRI include mesial temporal sclerosis, tuberous sclerosis, and cavernomas.  7T fMRI may improve mapping of eloquent cortex in preparation for epilepsy surgery.   Ongoing challenges with this technique include B1 inhomogeneity artifacts and safety concerns regarding metallic implants .

In this talk the quantum mechanics of a single spin 1/2 particle are discussed. The density operator formalism, which is a method to treat an ensemble of spins is then introduced. The effects of free precession and RF pulses are then demonstrated, and it is shown how the density operator relates to the classical Bloch vector model.  A brief overview of how to deal with spin > 1/2 particles or coupled spins which are necessary to describe spectroscopy experiments is discussed.

This talk is aimed at physicists and engineers who want to understand the different approaches used to simulate MR signals. It will cover steady-state closed form expressions, isochromat simulations, and the extended phase graph method.

Extracellular agents are distributed within the extracellular interstitial space. Gadolinium chelates, which are formed by the chelation of gadolinium to organic ligands such as diethylenetriaminepentaacetic acid, constitute a class of extra-cellular agents. Although several formulations are available with different ligands, their pharmacologic characteristics and imaging considerations are essentially identical. There are multiple indications for the use of extracellular contrast agents in MR imaging of the liver. These include lesion detection, lesion characterization, and liver vasculature assessment. In this lecture, I will talk about “representative pearls and pitfalls” of the GD-EOB-DTPA Liver MRI, comparing ECA enhanced liver MRI. 

- Understand the strengths and weaknesses of MRS

-Let the clinical/research question drive the methodology

- Be rigorous with quantitative methods

Noise is the eminent adversary when studying brain function. First, it incurs sensitivity loss for our small effects of interest by drowning them in un(cor)related fluctuations. Second, noise may correlate with effects, reducing specificity or increasing false positives by conflating them with fluctuations of non-neuronal origin. Here, we revisit how both the scanner and the subject generate noise in fMRI time series through different pathways, namely as thermal noise, encoding noise (magnetic field), and physiological noise of different origin.

We structure different approaches to noise mitigation following the recycling waste hierarchy, which also applies to sustainable science: avoid, reduce, reuse.

·       Dual-tuned coils provide metabolic information (x-nuclei module) and co-registered anatomical images and B0 shim settings (1H module) without repositioning the subject or coil

·       X-nuclei signal strength is typically less than 1/1,000× that of 1H (1). Therefore it is important to maximize x-nuclei receive sensitivity while simultaneously providing adequate 1H sensitivity

·       We will discuss prevalent dual-tuning techniques and considerations for performance characterization and interfacing dual-tuned coils

In this talk, we will discuss the basics of machine learning: a supervised learning framework and neural networks. In particular, we will cover the following topics, focussing on the intuition behind them:

(1) Types of machine learning

(2) Neural networks, from perceptron, MLP to deep neural networks

(3) Training, overfitting and regularization

(4) Practical considerations for applying ML

(5) Challenges of deep learning.

This talk reviews a few popular RF pulse design applications: inner volume imaging, simultaneous multislice, $$$B_{1}$$$ shimming, and parallel transmission. 

Late gadolinium enhancement imaging of “scar” and fibrosis is a vital tool in the assessment of a broad spectrum of cardiovascular diseases.  In particular, late gadolinium enhancement characterization of myocardial infarction and cardiomyopathy has demonstrated its utility in predicting future adverse cardiovascular events.  This presentation reviews the basics of late gadolinium enhancement imaging, touching upon technical challenges and simple solutions that may mitigate image artifact.  Additionally, examples of the common clinical applications are discussed.

Fiber tracking is the only tool that can delineate specific fiber bundles within the brain in-vivo, enabling region-specific investigation of MRI parameters and helping neurosurgeons to plan delicate neurosurgery. Fiber tracking has also claimed a central role in the field of ‘connectomics’, the study of the complex network of connections within the brain. Despite these unique abilities and exciting applications, fiber tracking is not without controversy, in particular when it comes to its interpretation. In light of this controversy, this course will provide an overview of the concepts, technical considerations, algorithms, mistakes and challenges of fiber tracking.

In recent years, there is increasing interest to move MRI toward higher static field strengths. The motivation for higher field strengths lies in the promise of higher signal-to-noise ratio (SNR), however, higher field (e.g., 7 Tesla [T]) human MRI remains challenging due to several difficulties including the inhomogeneity of the transmitted radio frequency (RF) field, which leads to two phenomena.

1. (1)     Non-uniform excitation (B1+) and therefore non-uniform image intensity;
2. (2)     Non-uniform electric fields and therefore locally increased tissue heating.

This talk will focus on RF modeling methods to predict B1+ and SAR distributions in the human body.