MR/PET is the first hybrid imaging modality with a true potential to exploit synergies from the modalities that it integrates such that it is possible to improve the quality of the results that could otherwise be obtained by using each modality in a completely independent fashion. The diagnosis and therapeutic monitoring of many pathologies could benefit greatly from this observation. Primary brain tumors are difficult to diagnose and manage due to their infiltrative nature and high heterogeneity. In fact, most of the conventional MRI techniques in use today are not capable to provide reliable quantitative information about key characteristics of the tumor microenvironment such as oxygenation, proliferative activity and cell density. Positron emission tomography (PET) is well known for its high sensitivity (nano-molar vs milli-molar) relative to MRI. In addition, PET tracers could be developed to target specific tumoral processes that could be used to improve diagnosis as well as actionable physiological information for guiding therapy. Several traces have been developed previously that have applications in neurooncology. The 18F tracer FMISO has been proposed as a means to assess tumor tissue oxygenation and, therefore, aid with radiation planning. Likewise, Fluorothymidine (FLT) is considered to be a marker of DNA synthesis and, as such, represents an attractive probe for the determination of proliferative activity. Each one of these tracers presents their own set of challenges for both acquisition and interpretation of the underlying images. Consequently, the data acquisition must be designed to take advantage of the synergy between MRI and PET and being able to remove as many of the potential uncertainties as possible.

Opportunities for improvements, relative to the use of PET alone are:

1.- Pharmacokinetic modeling of dynamically acquired images, including MR-based determination of the arterial input function (1).

2.- Reduction of partial voluming effects during PET image reconstruction (2-5).

3.- Reduction of motion blur during PET data acquisition (6-9).

Pharmacokinetic modeling of dynamically acquired images, in particular, permits extraction of physiological and functional information useful for grading brain tumors. Tracer kinetics can be calculated with the known (arterial) input as a function of time (AIF) that can be obtained either from arterial blood sampling, which is invasive, time-consuming, and clinically impractical, or as an image derived input function (IDIF) from a region of interest (ROI). To first order, the dynamics of the first phase distribution within the vasculature is expected to be similar for Gadolinium (Gd) and commonly used PET tracers, such as 18F-FDG, because they are low-molecular weight compounds. Therefore, high-resolution MR data could, in principle, be used to overcome the lower spatial resolution of the PET images, thereby reducing the partial voluming bias during the estimation IDIF and calculation of the tissue’s tracer kinetics constants. In this presentation we will, therefore, elaborate on the role of MRI/PET for integrating and improving the use of PET tracers during the diagnosis and treatment of primary brain tumors together with the methodological challenges involved and their potential solutions.

The overall outline of the presentation is as follows:

1.- Overview of the MR/PET platform.

2.- Data acquisition considerations.

3.- Tracers and their specific needs.

4.- Workflow considerations.

5.- Sequences for AIF determination

6.- Sequences or motion correction.

7.- Putting it all together.

8.- Potential interpretation confounds.

9.- Examples.

After completion of this course the attendees should be able to:

1.- Identify the conditions that must be met to successfully implement data acquisition techniques for concurrent MR/PET protocols targeting brain tumors.

2.- Identify the techniques that can be deployed to estimate the arterial input function from MRI images and the potential pitfalls associated with their implementation.

3.- Recognize the importance of the acquisition order when designing concurrent MR/PET data acquisition protocols.

4.- Identify the algorithms available for decreasing partial voluming effects in PET images and their advantages and limitations.

5.- Identify the methodologies available for reducing motion blur in PET images using MRI-based information and the requisites for their implementation.

6.- Recognize the limitations and potential interpretation confounds concurrently acquired and reconstructed MR and PET images.

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